release 1.2.2

Backport PR #3284 on branch 1.2.x (Changelog for 1.2.2)

.circleci/config.yml

@@ -0,0 +1,33 @@
+# Python CircleCI 2.0 configuration file
+# Updating CircleCI configuration from v1 to v2
+# Check https://circleci.com/docs/2.0/language-python/ for more details
+#
+version: 2
+jobs:
+  build:
+    machine: true
+    steps:
+      - checkout
+      - run:
+          name: build images
+          command: |
+            docker build -t jupyterhub/jupyterhub .
+            docker build -t jupyterhub/jupyterhub-onbuild onbuild
+            docker build -t jupyterhub/jupyterhub:alpine -f dockerfiles/Dockerfile.alpine .
+            docker build -t jupyterhub/singleuser singleuser
+      - run:
+          name: smoke test jupyterhub
+          command: |
+            docker run --rm -it jupyterhub/jupyterhub jupyterhub --help
+      - run:
+          name: verify static files
+          command: |
+            docker run --rm -it -v $PWD/dockerfiles:/io jupyterhub/jupyterhub python3 /io/test.py
+
+
+# Tell CircleCI to use this workflow when it builds the site
+workflows:
+  version: 2
+  default:
+    jobs:
+      - build

.flake8

@@ -3,9 +3,14 @@
 # E: style errors
 # W: style warnings
 # C: complexity
-# D: docstring warnings (unused pydocstyle extension)
+# F401: module imported but unused
+# F403: import *
+# F811: redefinition of unused `name` from line `N`
 # F841: local variable assigned but never used
-ignore = E, C, W, D, F841
+# E402: module level import not at top of file
+# I100: Import statements are in the wrong order
+# I101: Imported names are in the wrong order. Should be
+ignore = E, C, W, F401, F403, F811, F841, E402, I100, I101, D400
 builtins = c, get_config
 exclude =
     .cache,

.github/dependabot.yml

@@ -1,15 +0,0 @@
-# dependabot.yml reference: https://docs.github.com/en/code-security/dependabot/dependabot-version-updates/configuration-options-for-the-dependabot.yml-file
-#
-# Notes:
-# - Status and logs from dependabot are provided at
-#   https://github.com/jupyterhub/jupyterhub/network/updates.
-#
-version: 2
-updates:
-  # Maintain dependencies in our GitHub Workflows
-  - package-ecosystem: github-actions
-    directory: "/"
-    schedule:
-      interval: weekly
-      time: "05:00"
-      timezone: "Etc/UTC"

.github/workflows/release.yml

@@ -1,225 +0,0 @@
-# This is a GitHub workflow defining a set of jobs with a set of steps.
-# ref: https://docs.github.com/en/actions/learn-github-actions/workflow-syntax-for-github-actions
-#
-# Test build release artifacts (PyPI package, Docker images) and publish them on
-# pushed git tags.
-#
-name: Release
-
-on:
-  pull_request:
-    paths-ignore:
-      - "docs/**"
-      - "**.md"
-      - "**.rst"
-      - ".github/workflows/*"
-      - "!.github/workflows/release.yml"
-  push:
-    paths-ignore:
-      - "docs/**"
-      - "**.md"
-      - "**.rst"
-      - ".github/workflows/*"
-      - "!.github/workflows/release.yml"
-    branches-ignore:
-      - "dependabot/**"
-      - "pre-commit-ci-update-config"
-    tags:
-      - "**"
-  workflow_dispatch:
-
-jobs:
-  build-release:
-    runs-on: ubuntu-20.04
-    steps:
-      - uses: actions/checkout@v3
-      - uses: actions/setup-python@v4
-        with:
-          python-version: "3.9"
-
-      - uses: actions/setup-node@v3
-        with:
-          node-version: "14"
-
-      - name: install build requirements
-        run: |
-          npm install -g yarn
-          pip install --upgrade pip
-          pip install build
-          pip freeze
-
-      - name: build release
-        run: |
-          python -m build --sdist --wheel .
-          ls -l dist
-
-      - name: verify sdist
-        run: |
-          ./ci/check_sdist.py dist/jupyterhub-*.tar.gz
-
-      - name: verify data-files are installed where they are found
-        run: |
-          pip install dist/*.whl
-          ./ci/check_installed_data.py
-
-      - name: verify sdist can be installed without npm/yarn
-        run: |
-          docker run --rm -v $PWD/dist:/dist:ro docker.io/library/python:3.9-slim-bullseye bash -c 'pip install /dist/jupyterhub-*.tar.gz'
-
-      # ref: https://github.com/actions/upload-artifact#readme
-      - uses: actions/upload-artifact@v3
-        with:
-          name: jupyterhub-${{ github.sha }}
-          path: "dist/*"
-          if-no-files-found: error
-
-      - name: Publish to PyPI
-        if: startsWith(github.ref, 'refs/tags/')
-        env:
-          TWINE_USERNAME: __token__
-          TWINE_PASSWORD: ${{ secrets.PYPI_PASSWORD }}
-        run: |
-          pip install twine
-          twine upload --skip-existing dist/*
-
-  publish-docker:
-    runs-on: ubuntu-20.04
-
-    services:
-      # So that we can test this in PRs/branches
-      local-registry:
-        image: registry:2
-        ports:
-          - 5000:5000
-
-    steps:
-      - name: Should we push this image to a public registry?
-        run: |
-          if [ "${{ startsWith(github.ref, 'refs/tags/') || (github.ref == 'refs/heads/main') }}" = "true" ]; then
-              # Empty => Docker Hub
-              echo "REGISTRY=" >> $GITHUB_ENV
-          else
-              echo "REGISTRY=localhost:5000/" >> $GITHUB_ENV
-          fi
-
-      - uses: actions/checkout@v3
-
-      # Setup docker to build for multiple platforms, see:
-      # https://github.com/docker/build-push-action/tree/v2.4.0#usage
-      # https://github.com/docker/build-push-action/blob/v2.4.0/docs/advanced/multi-platform.md
-      - name: Set up QEMU (for docker buildx)
-        uses: docker/setup-qemu-action@e81a89b1732b9c48d79cd809d8d81d79c4647a18 # associated tag: v1.0.2
-
-      - name: Set up Docker Buildx (for multi-arch builds)
-        uses: docker/setup-buildx-action@8c0edbc76e98fa90f69d9a2c020dcb50019dc325
-        with:
-          # Allows pushing to registry on localhost:5000
-          driver-opts: network=host
-
-      - name: Setup push rights to Docker Hub
-        # This was setup by...
-        # 1. Creating a Docker Hub service account "jupyterhubbot"
-        # 2. Creating a access token for the service account specific to this
-        #    repository: https://hub.docker.com/settings/security
-        # 3. Making the account part of the "bots" team, and granting that team
-        #    permissions to push to the relevant images:
-        #    https://hub.docker.com/orgs/jupyterhub/teams/bots/permissions
-        # 4. Registering the username and token as a secret for this repo:
-        #    https://github.com/jupyterhub/jupyterhub/settings/secrets/actions
-        if: env.REGISTRY != 'localhost:5000/'
-        run: |
-          docker login -u "${{ secrets.DOCKERHUB_USERNAME }}" -p "${{ secrets.DOCKERHUB_TOKEN }}"
-
-      # image: jupyterhub/jupyterhub
-      #
-      # https://github.com/jupyterhub/action-major-minor-tag-calculator
-      # If this is a tagged build this will return additional parent tags.
-      # E.g. 1.2.3 is expanded to Docker tags
-      # [{prefix}:1.2.3, {prefix}:1.2, {prefix}:1, {prefix}:latest] unless
-      # this is a backported tag in which case the newer tags aren't updated.
-      # For branches this will return the branch name.
-      # If GITHUB_TOKEN isn't available (e.g. in PRs) returns no tags [].
-      - name: Get list of jupyterhub tags
-        id: jupyterhubtags
-        uses: jupyterhub/action-major-minor-tag-calculator@v2
-        with:
-          githubToken: ${{ secrets.GITHUB_TOKEN }}
-          prefix: "${{ env.REGISTRY }}jupyterhub/jupyterhub:"
-          defaultTag: "${{ env.REGISTRY }}jupyterhub/jupyterhub:noref"
-          branchRegex: ^\w[\w-.]*$
-
-      - name: Build and push jupyterhub
-        uses: docker/build-push-action@c56af957549030174b10d6867f20e78cfd7debc5
-        with:
-          context: .
-          platforms: linux/amd64,linux/arm64
-          push: true
-          # tags parameter must be a string input so convert `gettags` JSON
-          # array into a comma separated list of tags
-          tags: ${{ join(fromJson(steps.jupyterhubtags.outputs.tags)) }}
-
-      # image: jupyterhub/jupyterhub-onbuild
-      #
-      - name: Get list of jupyterhub-onbuild tags
-        id: onbuildtags
-        uses: jupyterhub/action-major-minor-tag-calculator@v2
-        with:
-          githubToken: ${{ secrets.GITHUB_TOKEN }}
-          prefix: "${{ env.REGISTRY }}jupyterhub/jupyterhub-onbuild:"
-          defaultTag: "${{ env.REGISTRY }}jupyterhub/jupyterhub-onbuild:noref"
-          branchRegex: ^\w[\w-.]*$
-
-      - name: Build and push jupyterhub-onbuild
-        uses: docker/build-push-action@c56af957549030174b10d6867f20e78cfd7debc5
-        with:
-          build-args: |
-            BASE_IMAGE=${{ fromJson(steps.jupyterhubtags.outputs.tags)[0] }}
-          context: onbuild
-          platforms: linux/amd64,linux/arm64
-          push: true
-          tags: ${{ join(fromJson(steps.onbuildtags.outputs.tags)) }}
-
-      # image: jupyterhub/jupyterhub-demo
-      #
-      - name: Get list of jupyterhub-demo tags
-        id: demotags
-        uses: jupyterhub/action-major-minor-tag-calculator@v2
-        with:
-          githubToken: ${{ secrets.GITHUB_TOKEN }}
-          prefix: "${{ env.REGISTRY }}jupyterhub/jupyterhub-demo:"
-          defaultTag: "${{ env.REGISTRY }}jupyterhub/jupyterhub-demo:noref"
-          branchRegex: ^\w[\w-.]*$
-
-      - name: Build and push jupyterhub-demo
-        uses: docker/build-push-action@c56af957549030174b10d6867f20e78cfd7debc5
-        with:
-          build-args: |
-            BASE_IMAGE=${{ fromJson(steps.onbuildtags.outputs.tags)[0] }}
-          context: demo-image
-          # linux/arm64 currently fails:
-          # ERROR: Could not build wheels for argon2-cffi which use PEP 517 and cannot be installed directly
-          # ERROR: executor failed running [/bin/sh -c python3 -m pip install notebook]: exit code: 1
-          platforms: linux/amd64
-          push: true
-          tags: ${{ join(fromJson(steps.demotags.outputs.tags)) }}
-
-      # image: jupyterhub/singleuser
-      #
-      - name: Get list of jupyterhub/singleuser tags
-        id: singleusertags
-        uses: jupyterhub/action-major-minor-tag-calculator@v2
-        with:
-          githubToken: ${{ secrets.GITHUB_TOKEN }}
-          prefix: "${{ env.REGISTRY }}jupyterhub/singleuser:"
-          defaultTag: "${{ env.REGISTRY }}jupyterhub/singleuser:noref"
-          branchRegex: ^\w[\w-.]*$
-
-      - name: Build and push jupyterhub/singleuser
-        uses: docker/build-push-action@c56af957549030174b10d6867f20e78cfd7debc5
-        with:
-          build-args: |
-            JUPYTERHUB_VERSION=${{ github.ref_type == 'tag' && github.ref_name || format('git:{0}', github.sha) }}
-          context: singleuser
-          platforms: linux/amd64,linux/arm64
-          push: true
-          tags: ${{ join(fromJson(steps.singleusertags.outputs.tags)) }}

.github/workflows/support-bot.yml

@@ -1,31 +0,0 @@
-# https://github.com/dessant/support-requests
-name: "Support Requests"
-
-on:
-  issues:
-    types: [labeled, unlabeled, reopened]
-
-permissions:
-  issues: write
-
-jobs:
-  action:
-    runs-on: ubuntu-latest
-    steps:
-      - uses: dessant/support-requests@v2
-        with:
-          github-token: ${{ github.token }}
-          support-label: "support"
-          issue-comment: |
-            Hi there @{issue-author} :wave:!
-
-            I closed this issue because it was labelled as a support question.
-
-            Please help us organize discussion by posting this on the http://discourse.jupyter.org/ forum.
-
-            Our goal is to sustain a positive experience for both users and developers. We use GitHub issues for specific discussions related to changing a repository's content, and let the forum be where we can more generally help and inspire each other.
-
-            Thanks you for being an active member of our community! :heart:
-          close-issue: true
-          lock-issue: false
-          issue-lock-reason: "off-topic"

.github/workflows/test-docs.yml

@@ -1,62 +0,0 @@
-# This is a GitHub workflow defining a set of jobs with a set of steps.
-# ref: https://docs.github.com/en/actions/learn-github-actions/workflow-syntax-for-github-actions
-#
-# This workflow validates the REST API definition and runs the pytest tests in
-# the docs/ folder. This workflow does not build the documentation. That is
-# instead tested via ReadTheDocs (https://readthedocs.org/projects/jupyterhub/).
-#
-name: Test docs
-
-# The tests defined in docs/ are currently influenced by changes to _version.py
-# and scopes.py.
-on:
-  pull_request:
-    paths:
-      - "docs/**"
-      - "jupyterhub/_version.py"
-      - "jupyterhub/scopes.py"
-      - ".github/workflows/test-docs.yml"
-  push:
-    paths:
-      - "docs/**"
-      - "jupyterhub/_version.py"
-      - "jupyterhub/scopes.py"
-      - ".github/workflows/test-docs.yml"
-    branches-ignore:
-      - "dependabot/**"
-      - "pre-commit-ci-update-config"
-    tags:
-      - "**"
-  workflow_dispatch:
-
-env:
-  # UTF-8 content may be interpreted as ascii and causes errors without this.
-  LANG: C.UTF-8
-  PYTEST_ADDOPTS: "--verbose --color=yes"
-
-jobs:
-  validate-rest-api-definition:
-    runs-on: ubuntu-20.04
-    steps:
-      - uses: actions/checkout@v3
-
-      - name: Validate REST API definition
-        uses: char0n/swagger-editor-validate@v1.3.2
-        with:
-          definition-file: docs/source/_static/rest-api.yml
-
-  test-docs:
-    runs-on: ubuntu-20.04
-    steps:
-      - uses: actions/checkout@v3
-      - uses: actions/setup-python@v4
-        with:
-          python-version: "3.9"
-
-      - name: Install requirements
-        run: |
-          pip install -r docs/requirements.txt pytest
-
-      - name: pytest docs/
-        run: |
-          pytest docs/

.github/workflows/test-jsx.yml

@@ -1,52 +0,0 @@
-# This is a GitHub workflow defining a set of jobs with a set of steps.
-# ref: https://docs.github.com/en/actions/learn-github-actions/workflow-syntax-for-github-actions
-#
-name: Test jsx (admin-react.js)
-
-on:
-  pull_request:
-    paths:
-      - "jsx/**"
-      - ".github/workflows/test-jsx.yml"
-  push:
-    paths:
-      - "jsx/**"
-      - ".github/workflows/test-jsx.yml"
-    branches-ignore:
-      - "dependabot/**"
-      - "pre-commit-ci-update-config"
-    tags:
-      - "**"
-  workflow_dispatch:
-
-permissions:
-  contents: read
-
-jobs:
-  # The ./jsx folder contains React based source code files that are to compile
-  # to share/jupyterhub/static/js/admin-react.js. The ./jsx folder includes
-  # tests also has tests that this job is meant to run with `yarn test`
-  # according to the documentation in jsx/README.md.
-  test-jsx-admin-react:
-    runs-on: ubuntu-20.04
-    timeout-minutes: 5
-
-    steps:
-      - uses: actions/checkout@v3
-      - uses: actions/setup-node@v3
-        with:
-          node-version: "14"
-
-      - name: Install yarn
-        run: |
-          npm install -g yarn
-
-      - name: yarn
-        run: |
-          cd jsx
-          yarn
-
-      - name: yarn test
-        run: |
-          cd jsx
-          yarn test

.github/workflows/test.yml

@@ -1,44 +1,60 @@
 # This is a GitHub workflow defining a set of jobs with a set of steps.
-# ref: https://docs.github.com/en/actions/learn-github-actions/workflow-syntax-for-github-actions
+# ref: https://docs.github.com/en/free-pro-team@latest/actions/reference/workflow-syntax-for-github-actions
 #
-name: Test
+name: Run tests
 
+# Trigger the workflow's on all PRs but only on pushed tags or commits to
+# main/master branch to avoid PRs developed in a GitHub fork's dedicated branch
+# to trigger.
 on:
   pull_request:
-    paths-ignore:
-      - "docs/**"
-      - "**.md"
-      - "**.rst"
-      - ".github/workflows/*"
-      - "!.github/workflows/test.yml"
   push:
-    paths-ignore:
-      - "docs/**"
-      - "**.md"
-      - "**.rst"
-      - ".github/workflows/*"
-      - "!.github/workflows/test.yml"
-    branches-ignore:
-      - "dependabot/**"
-      - "pre-commit-ci-update-config"
-    tags:
-      - "**"
-  workflow_dispatch:
+
+defaults:
+  run:
+    # Declare bash be used by default in this workflow's "run" steps.
+    #
+    # NOTE: bash will by default run with:
+    #   --noprofile: Ignore ~/.profile etc.
+    #   --norc:      Ignore ~/.bashrc etc.
+    #   -e:          Exit directly on errors
+    #   -o pipefail: Don't mask errors from a command piped into another command
+    shell: bash
 
 env:
   # UTF-8 content may be interpreted as ascii and causes errors without this.
   LANG: C.UTF-8
-  PYTEST_ADDOPTS: "--verbose --color=yes"
-  SQLALCHEMY_WARN_20: "1"
-
-permissions:
-  contents: read
 
 jobs:
+  # Run "pre-commit run --all-files"
+  pre-commit:
+    runs-on: ubuntu-20.04
+    timeout-minutes: 2
+
+    steps:
+      - uses: actions/checkout@v2
+      - uses: actions/setup-python@v2
+        with:
+          python-version: 3.8
+
+      # ref: https://github.com/pre-commit/action
+      - uses: pre-commit/action@v2.0.0
+      - name: Help message if pre-commit fail
+        if: ${{ failure() }}
+        run: |
+          echo "You can install pre-commit hooks to automatically run formatting"
+          echo "on each commit with:"
+          echo "    pre-commit install"
+          echo "or you can run by hand on staged files with"
+          echo "    pre-commit run"
+          echo "or after-the-fact on already committed files with"
+          echo "    pre-commit run --all-files"
+
+
   # Run "pytest jupyterhub/tests" in various configurations
   pytest:
     runs-on: ubuntu-20.04
-    timeout-minutes: 15
+    timeout-minutes: 10
 
     strategy:
       # Keep running even if one variation of the job fail
@@ -57,40 +73,27 @@ jobs:
         #   Tests everything when JupyterHub works against a dedicated mysql or
         #   postgresql server.
         #
-        # legacy_notebook:
+        # jupyter_server:
         #   Tests everything when the user instances are started with
-        #   the legacy notebook server instead of jupyter_server.
-        #
-        # ssl:
-        #   Tests everything using internal SSL connections instead of
-        #   unencrypted HTTP
+        #   jupyter_server instead of notebook.
         #
         # main_dependencies:
         #   Tests everything when the we use the latest available dependencies
-        #   from: traitlets.
+        #   from: ipytraitlets.
         #
         # NOTE: Since only the value of these parameters are presented in the
         #       GitHub UI when the workflow run, we avoid using true/false as
         #       values by instead duplicating the name to signal true.
-        # Python versions available at:
-        #   https://github.com/actions/python-versions/blob/HEAD/versions-manifest.json
         include:
-          - python: "3.7"
-            oldest_dependencies: oldest_dependencies
-            legacy_notebook: legacy_notebook
-          - python: "3.8"
-            legacy_notebook: legacy_notebook
-          - python: "3.9"
-            db: mysql
-          - python: "3.10"
-            db: postgres
-          - python: "3.11"
+          - python: "3.6"
             subdomain: subdomain
-          - python: "3.11"
-            ssl: ssl
-          - python: "3.11"
-            selenium: selenium
-          - python: "3.11"
+          - python: "3.7"
+            db: mysql
+          - python: "3.8"
+            db: postgres
+          - python: "3.8"
+            jupyter_server: jupyter_server
+          - python: "3.9"
             main_dependencies: main_dependencies
 
     steps:
@@ -106,9 +109,6 @@ jobs:
               echo "MYSQL_HOST=127.0.0.1" >> $GITHUB_ENV
               echo "JUPYTERHUB_TEST_DB_URL=mysql+mysqlconnector://root@127.0.0.1:3306/jupyterhub" >> $GITHUB_ENV
           fi
-          if [ "${{ matrix.ssl }}" == "ssl" ]; then
-              echo "SSL_ENABLED=1" >> $GITHUB_ENV
-          fi
           if [ "${{ matrix.db }}" == "postgres" ]; then
               echo "PGHOST=127.0.0.1" >> $GITHUB_ENV
               echo "PGUSER=test_user" >> $GITHUB_ENV
@@ -118,46 +118,37 @@ jobs:
           if [ "${{ matrix.jupyter_server }}" != "" ]; then
               echo "JUPYTERHUB_SINGLEUSER_APP=jupyterhub.tests.mockserverapp.MockServerApp" >> $GITHUB_ENV
           fi
-      - uses: actions/checkout@v3
-      # NOTE: actions/setup-node@v3 make use of a cache within the GitHub base
+      - uses: actions/checkout@v2
+
+      # NOTE: actions/setup-node@v1 make use of a cache within the GitHub base
       #       environment and setup in a fraction of a second.
       - name: Install Node v14
-        uses: actions/setup-node@v3
+        uses: actions/setup-node@v1
         with:
           node-version: "14"
-      - name: Install Javascript dependencies
+      - name: Install Node dependencies
         run: |
           npm install
-          npm install -g configurable-http-proxy yarn
+          npm install -g configurable-http-proxy
           npm list
 
-      # NOTE: actions/setup-python@v4 make use of a cache within the GitHub base
+      # NOTE: actions/setup-python@v2 make use of a cache within the GitHub base
       #       environment and setup in a fraction of a second.
       - name: Install Python ${{ matrix.python }}
-        uses: actions/setup-python@v4
+        uses: actions/setup-python@v2
         with:
-          python-version: "${{ matrix.python }}"
-
+          python-version: ${{ matrix.python }}
       - name: Install Python dependencies
         run: |
           pip install --upgrade pip
-          pip install -e ".[test]"
-
-          if [ "${{ matrix.oldest_dependencies }}" != "" ]; then
-            # take any dependencies in requirements.txt such as tornado>=5.0
-            # and transform them to tornado==5.0 so we can run tests with
-            # the earliest-supported versions
-            cat requirements.txt | grep '>=' | sed -e 's@>=@==@g' > oldest-requirements.txt
-            pip install -r oldest-requirements.txt
-          fi
+          pip install --upgrade . -r dev-requirements.txt
 
           if [ "${{ matrix.main_dependencies }}" != "" ]; then
               pip install git+https://github.com/ipython/traitlets#egg=traitlets --force
-              pip install --upgrade --pre sqlalchemy
           fi
-          if [ "${{ matrix.legacy_notebook }}" != "" ]; then
-              pip uninstall jupyter_server --yes
-              pip install 'notebook<7'
+          if [ "${{ matrix.jupyter_server }}" != "" ]; then
+              pip uninstall notebook --yes
+              pip install jupyter_server
           fi
           if [ "${{ matrix.db }}" == "mysql" ]; then
               pip install mysql-connector-python
@@ -193,59 +184,23 @@ jobs:
         if: ${{ matrix.db }}
         run: |
           if [ "${{ matrix.db }}" == "mysql" ]; then
-            if [[ -z "$(which mysql)" ]]; then
               sudo apt-get update
               sudo apt-get install -y mysql-client
-            fi
               DB=mysql bash ci/docker-db.sh
               DB=mysql bash ci/init-db.sh
           fi
           if [ "${{ matrix.db }}" == "postgres" ]; then
-            if [[ -z "$(which psql)" ]]; then
               sudo apt-get update
               sudo apt-get install -y postgresql-client
-            fi
               DB=postgres bash ci/docker-db.sh
               DB=postgres bash ci/init-db.sh
           fi
-      - name: Setup Firefox
-        if: matrix.selenium
-        uses: browser-actions/setup-firefox@latest
-        with:
-          firefox-version: latest
-
-      - name: Setup Geckodriver
-        if: matrix.selenium
-        uses: browser-actions/setup-geckodriver@latest
-
-      - name: Configure selenium tests
-        if: matrix.selenium
-        run: echo "PYTEST_ADDOPTS=$PYTEST_ADDOPTS -m selenium" >> "${GITHUB_ENV}"
 
       - name: Run pytest
+        # FIXME: --color=yes explicitly set because:
+        #        https://github.com/actions/runner/issues/241
         run: |
-          pytest --maxfail=2 --cov=jupyterhub jupyterhub/tests
-
-      - uses: codecov/codecov-action@v3
-
-  docker-build:
-    runs-on: ubuntu-20.04
-    timeout-minutes: 20
-
-    steps:
-      - uses: actions/checkout@v3
-
-      - name: build images
+          pytest -v --maxfail=2 --color=yes --cov=jupyterhub jupyterhub/tests
+      - name: Submit codecov report
         run: |
-          docker build -t jupyterhub/jupyterhub .
-          docker build -t jupyterhub/jupyterhub-onbuild onbuild
-          docker build -t jupyterhub/jupyterhub:alpine -f dockerfiles/Dockerfile.alpine .
-          docker build -t jupyterhub/singleuser singleuser
-
-      - name: smoke test jupyterhub
-        run: |
-          docker run --rm -t jupyterhub/jupyterhub jupyterhub --help
-
-      - name: verify static files
-        run: |
-          docker run --rm -t -v $PWD/dockerfiles:/io jupyterhub/jupyterhub python3 /io/test.py
+          codecov

.gitignore

@@ -8,9 +8,7 @@ dist
 docs/_build
 docs/build
 docs/source/_static/rest-api
-docs/source/rbac/scope-table.md
 .ipynb_checkpoints
-jsx/build/
 # ignore config file at the top-level of the repo
 # but not sub-dirs
 /jupyterhub_config.py
@@ -20,7 +18,6 @@ package-lock.json
 share/jupyterhub/static/components
 share/jupyterhub/static/css/style.min.css
 share/jupyterhub/static/css/style.min.css.map
-share/jupyterhub/static/js/admin-react.js*
 *.egg-info
 MANIFEST
 .coverage
@@ -31,6 +28,3 @@ htmlcov
 .pytest_cache
 pip-wheel-metadata
 docs/source/reference/metrics.rst
-oldest-requirements.txt
-jupyterhub-proxy.pid
-examples/server-api/service-token

.pre-commit-config.yaml

@@ -1,61 +1,19 @@
-# pre-commit is a tool to perform a predefined set of tasks manually and/or
-# automatically before git commits are made.
-#
-# Config reference: https://pre-commit.com/#pre-commit-configyaml---top-level
-#
-# Common tasks
-#
-# - Run on all files:   pre-commit run --all-files
-# - Register git hooks: pre-commit install --install-hooks
-#
 repos:
-  # Autoformat: Python code, syntax patterns are modernized
-  - repo: https://github.com/asottile/pyupgrade
-    rev: v3.2.2
-    hooks:
-      - id: pyupgrade
-        args:
-          - --py36-plus
-
-  # Autoformat: Python code
-  - repo: https://github.com/PyCQA/autoflake
-    rev: v2.0.0
-    hooks:
-      - id: autoflake
-        # args ref: https://github.com/PyCQA/autoflake#advanced-usage
-        args:
-          - --in-place
-
-  # Autoformat: Python code
-  - repo: https://github.com/pycqa/isort
-    rev: 5.10.1
-    hooks:
-      - id: isort
-
-  # Autoformat: Python code
-  - repo: https://github.com/psf/black
-    rev: 22.10.0
-    hooks:
-      - id: black
-
-  # Autoformat: markdown, yaml, javascript (see the file .prettierignore)
-  - repo: https://github.com/pre-commit/mirrors-prettier
-    rev: v3.0.0-alpha.4
-    hooks:
-      - id: prettier
-
-  # Autoformat and linting, misc. details
-  - repo: https://github.com/pre-commit/pre-commit-hooks
-    rev: v4.4.0
-    hooks:
-      - id: end-of-file-fixer
-        exclude: share/jupyterhub/static/js/admin-react.js
-      - id: requirements-txt-fixer
-      - id: check-case-conflict
-      - id: check-executables-have-shebangs
-
-  # Linting: Python code (see the file .flake8)
-  - repo: https://github.com/PyCQA/flake8
-    rev: "6.0.0"
-    hooks:
-      - id: flake8
+- repo: https://github.com/asottile/reorder_python_imports
+  rev: v1.9.0
+  hooks:
+  - id: reorder-python-imports
+- repo: https://github.com/psf/black
+  rev: 19.10b0
+  hooks:
+  - id: black
+- repo: https://github.com/pre-commit/pre-commit-hooks
+  rev: v2.4.0
+  hooks:
+  - id: end-of-file-fixer
+  - id: check-json
+  - id: check-yaml
+  - id: check-case-conflict
+  - id: check-executables-have-shebangs
+  - id: requirements-txt-fixer
+  - id: flake8

.prettierignore

@@ -1,2 +0,0 @@
-share/jupyterhub/templates/
-share/jupyterhub/static/js/admin-react.js

.readthedocs.yaml

@@ -1,25 +0,0 @@
-# Configuration on how ReadTheDocs (RTD) builds our documentation
-# ref: https://readthedocs.org/projects/jupyterhub/
-# ref: https://docs.readthedocs.io/en/stable/config-file/v2.html
-#
-version: 2
-
-sphinx:
-  configuration: docs/source/conf.py
-
-build:
-  os: ubuntu-20.04
-  tools:
-    nodejs: "16"
-    python: "3.9"
-
-python:
-  install:
-    - requirements: docs/requirements.txt
-
-formats:
-  # Adding htmlzip enables a Downloads section in the rendered website's RTD
-  # menu where the html build can be downloaded. This doesn't require any
-  # additional configuration in docs/source/conf.py.
-  #
-  - htmlzip

CHECKLIST-Release.md

@@ -0,0 +1,26 @@
+# Release checklist
+
+- [ ] Upgrade Docs prior to Release
+
+    - [ ] Change log
+    - [ ] New features documented
+    - [ ] Update the contributor list - thank you page
+
+- [ ] Upgrade and test Reference Deployments
+
+- [ ] Release software
+
+    - [ ] Make sure 0 issues in milestone
+    - [ ] Follow release process steps
+    - [ ] Send builds to PyPI (Warehouse) and Conda Forge
+
+- [ ] Blog post and/or release note
+
+- [ ] Notify users of release
+
+    - [ ] Email Jupyter and Jupyter In Education mailing lists
+    - [ ] Tweet (optional)
+
+- [ ] Increment the version number for the next release
+
+- [ ] Update roadmap

CODE_OF_CONDUCT.md

@@ -1 +1 @@
-Please refer to [Project Jupyter's Code of Conduct](https://github.com/jupyter/governance/blob/HEAD/conduct/code_of_conduct.md).
+Please refer to [Project Jupyter's Code of Conduct](https://github.com/jupyter/governance/blob/master/conduct/code_of_conduct.md).

CONTRIBUTING.md

@@ -1,14 +1,137 @@
 # Contributing to JupyterHub
 
 Welcome! As a [Jupyter](https://jupyter.org) project,
-you can follow the [Jupyter contributor guide](https://jupyter.readthedocs.io/en/latest/contributing/content-contributor.html).
+you can follow the [Jupyter contributor guide](https://jupyter.readthedocs.io/en/latest/contributor/content-contributor.html).
 
-Make sure to also follow [Project Jupyter's Code of Conduct](https://github.com/jupyter/governance/blob/HEAD/conduct/code_of_conduct.md)
+Make sure to also follow [Project Jupyter's Code of Conduct](https://github.com/jupyter/governance/blob/master/conduct/code_of_conduct.md)
 for a friendly and welcoming collaborative environment.
 
-Please see our documentation on
+## Setting up a development environment
 
-- [Setting up a development install](https://jupyterhub.readthedocs.io/en/latest/contributing/setup.html)
-- [Testing JupyterHub and linting code](https://jupyterhub.readthedocs.io/en/latest/contributing/tests.html)
+<!--
+https://jupyterhub.readthedocs.io/en/stable/contributing/setup.html
+contains a lot of the same information. Should we merge the docs and
+just have this page link to that one?
+-->
 
-If you need some help, feel free to ask on [Gitter](https://gitter.im/jupyterhub/jupyterhub) or [Discourse](https://discourse.jupyter.org/).
+JupyterHub requires Python >= 3.5 and nodejs.
+
+As a Python project, a development install of JupyterHub follows standard practices for the basics (steps 1-2).
+
+
+1. clone the repo
+    ```bash
+    git clone https://github.com/jupyterhub/jupyterhub
+    ```
+2. do a development install with pip
+
+    ```bash
+    cd jupyterhub
+    python3 -m pip install --editable .
+    ```
+3. install the development requirements,
+   which include things like testing tools
+
+    ```bash
+    python3 -m pip install -r dev-requirements.txt
+    ```
+4. install configurable-http-proxy with npm:
+
+    ```bash
+    npm install -g configurable-http-proxy
+    ```
+5. set up pre-commit hooks for automatic code formatting, etc.
+
+    ```bash
+    pre-commit install
+    ```
+
+    You can also invoke the pre-commit hook manually at any time with
+
+    ```bash
+    pre-commit run
+    ```
+
+## Contributing
+
+JupyterHub has adopted automatic code formatting so you shouldn't
+need to worry too much about your code style.
+As long as your code is valid,
+the pre-commit hook should take care of how it should look.
+You can invoke the pre-commit hook by hand at any time with:
+
+```bash
+pre-commit run
+```
+
+which should run any autoformatting on your code
+and tell you about any errors it couldn't fix automatically.
+You may also install [black integration](https://github.com/psf/black#editor-integration)
+into your text editor to format code automatically.
+
+If you have already committed files before setting up the pre-commit
+hook with `pre-commit install`, you can fix everything up using
+`pre-commit run --all-files`.  You need to make the fixing commit
+yourself after that.
+
+## Testing
+
+It's a good idea to write tests to exercise any new features,
+or that trigger any bugs that you have fixed to catch regressions.
+
+You can run the tests with:
+
+```bash
+pytest -v
+```
+
+in the repo directory. If you want to just run certain tests,
+check out the [pytest docs](https://pytest.readthedocs.io/en/latest/usage.html)
+for how pytest can be called.
+For instance, to test only spawner-related things in the REST API:
+
+```bash
+pytest -v -k spawn jupyterhub/tests/test_api.py
+```
+
+The tests live in `jupyterhub/tests` and are organized roughly into:
+
+1. `test_api.py` tests the REST API
+2. `test_pages.py` tests loading the HTML pages
+
+and other collections of tests for different components.
+When writing a new test, there should usually be a test of
+similar functionality already written and related tests should
+be added nearby.
+
+The fixtures live in `jupyterhub/tests/conftest.py`. There are
+fixtures that can be used for JupyterHub components, such as:
+
+- `app`: an instance of JupyterHub with mocked parts
+- `auth_state_enabled`: enables persisting auth_state (like authentication tokens)
+- `db`: a sqlite in-memory DB session
+- `io_loop`: a Tornado event loop
+- `event_loop`: a new asyncio event loop
+- `user`: creates a new temporary user
+- `admin_user`: creates a new temporary admin user
+- single user servers
+  - `cleanup_after`: allows cleanup of single user servers between tests
+- mocked service
+  - `MockServiceSpawner`: a spawner that mocks services for testing with a short poll interval
+  - `mockservice`: mocked service with no external service url
+  - `mockservice_url`: mocked service with a url to test external services
+
+And fixtures to add functionality or spawning behavior:
+
+- `admin_access`: grants admin access
+- `no_patience`: sets slow-spawning timeouts to zero
+- `slow_spawn`: enables the SlowSpawner (a spawner that takes a few seconds to start)
+- `never_spawn`: enables the NeverSpawner (a spawner that will never start)
+- `bad_spawn`: enables the BadSpawner (a spawner that fails immediately)
+- `slow_bad_spawn`: enables the SlowBadSpawner (a spawner that fails after a short delay)
+
+To read more about fixtures check out the
+[pytest docs](https://docs.pytest.org/en/latest/fixture.html)
+for how to use the existing fixtures, and how to create new ones.
+
+When in doubt, feel free to [ask](https://gitter.im/jupyterhub/jupyterhub).

COPYING.md

@@ -24,7 +24,7 @@ software without specific prior written permission.
 THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND
 ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
 WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
-DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE
+DISCLAIMED.  IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE
 FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL
 DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR
 SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
@@ -46,8 +46,8 @@ Jupyter uses a shared copyright model. Each contributor maintains copyright
 over their contributions to Jupyter. But, it is important to note that these
 contributions are typically only changes to the repositories. Thus, the Jupyter
 source code, in its entirety is not the copyright of any single person or
-institution. Instead, it is the collective copyright of the entire Jupyter
-Development Team. If individual contributors want to maintain a record of what
+institution.  Instead, it is the collective copyright of the entire Jupyter
+Development Team.  If individual contributors want to maintain a record of what
 changes/contributions they have specific copyright on, they should indicate
 their copyright in the commit message of the change, when they commit the
 change to one of the Jupyter repositories.

Dockerfile

@@ -21,7 +21,7 @@
 # your jupyterhub_config.py will be added automatically
 # from your docker directory.
 
-ARG BASE_IMAGE=ubuntu:22.04
+ARG BASE_IMAGE=ubuntu:focal-20200729@sha256:6f2fb2f9fb5582f8b587837afd6ea8f37d8d1d9e41168c90f410a6ef15fa8ce5
 FROM $BASE_IMAGE AS builder
 
 USER root
@@ -35,14 +35,12 @@ RUN apt-get update \
     python3-dev \
     python3-pip \
     python3-pycurl \
-    python3-venv \
     nodejs \
     npm \
  && apt-get clean \
  && rm -rf /var/lib/apt/lists/*
 
-RUN python3 -m pip install --upgrade setuptools pip build wheel
-RUN npm install --global yarn
+RUN python3 -m pip install --upgrade setuptools pip wheel
 
 # copy everything except whats in .dockerignore, its a
 # compromise between needing to rebuild and maintaining
@@ -52,7 +50,7 @@ WORKDIR /src/jupyterhub
 
 # Build client component packages (they will be copied into ./share and
 # packaged with the built wheel.)
-RUN python3 -m build --wheel
+RUN python3 setup.py bdist_wheel
 RUN python3 -m pip wheel --wheel-dir wheelhouse dist/*.whl
 
 

MANIFEST.in

@@ -8,7 +8,6 @@ include *requirements.txt
 include Dockerfile
 
 graft onbuild
-graft jsx
 graft jupyterhub
 graft scripts
 graft share
@@ -19,10 +18,6 @@ graft ci
 graft docs
 prune docs/node_modules
 
-# Intermediate javascript files
-prune jsx/node_modules
-prune jsx/build
-
 # prune some large unused files from components
 prune share/jupyterhub/static/components/bootstrap/dist/css
 exclude share/jupyterhub/static/components/bootstrap/dist/fonts/*.svg

README.md

@@ -6,37 +6,29 @@
 **[License](#license)** |
 **[Help and Resources](#help-and-resources)**
 
----
-
-Please note that this repository is participating in a study into the sustainability of open source projects. Data will be gathered about this repository for approximately the next 12 months, starting from 2021-06-11.
-
-Data collected will include the number of contributors, number of PRs, time taken to close/merge these PRs, and issues closed.
-
-For more information, please visit
-[our informational page](https://sustainable-open-science-and-software.github.io/) or download our [participant information sheet](https://sustainable-open-science-and-software.github.io/assets/PIS_sustainable_software.pdf).
-
----
 
 # [JupyterHub](https://github.com/jupyterhub/jupyterhub)
 
+
 [![Latest PyPI version](https://img.shields.io/pypi/v/jupyterhub?logo=pypi)](https://pypi.python.org/pypi/jupyterhub)
-[![Latest conda-forge version](https://img.shields.io/conda/vn/conda-forge/jupyterhub?logo=conda-forge)](https://anaconda.org/conda-forge/jupyterhub)
+[![Latest conda-forge version](https://img.shields.io/conda/vn/conda-forge/jupyterhub?logo=conda-forge)](https://www.npmjs.com/package/jupyterhub)
 [![Documentation build status](https://img.shields.io/readthedocs/jupyterhub?logo=read-the-docs)](https://jupyterhub.readthedocs.org/en/latest/)
-[![GitHub Workflow Status - Test](https://img.shields.io/github/workflow/status/jupyterhub/jupyterhub/Test?logo=github&label=tests)](https://github.com/jupyterhub/jupyterhub/actions)
+[![TravisCI build status](https://img.shields.io/travis/com/jupyterhub/jupyterhub?logo=travis)](https://travis-ci.com/jupyterhub/jupyterhub)
 [![DockerHub build status](https://img.shields.io/docker/build/jupyterhub/jupyterhub?logo=docker&label=build)](https://hub.docker.com/r/jupyterhub/jupyterhub/tags)
-[![Test coverage of code](https://codecov.io/gh/jupyterhub/jupyterhub/branch/main/graph/badge.svg)](https://codecov.io/gh/jupyterhub/jupyterhub)
+[![CircleCI build status](https://img.shields.io/circleci/build/github/jupyterhub/jupyterhub?logo=circleci)](https://circleci.com/gh/jupyterhub/jupyterhub)<!-- CircleCI Token: b5b65862eb2617b9a8d39e79340b0a6b816da8cc -->
+[![Test coverage of code](https://codecov.io/gh/jupyterhub/jupyterhub/branch/master/graph/badge.svg)](https://codecov.io/gh/jupyterhub/jupyterhub)
 [![GitHub](https://img.shields.io/badge/issue_tracking-github-blue?logo=github)](https://github.com/jupyterhub/jupyterhub/issues)
 [![Discourse](https://img.shields.io/badge/help_forum-discourse-blue?logo=discourse)](https://discourse.jupyter.org/c/jupyterhub)
 [![Gitter](https://img.shields.io/badge/social_chat-gitter-blue?logo=gitter)](https://gitter.im/jupyterhub/jupyterhub)
 
 With [JupyterHub](https://jupyterhub.readthedocs.io) you can create a
-**multi-user Hub** that spawns, manages, and proxies multiple instances of the
+**multi-user Hub** which spawns, manages, and proxies multiple instances of the
 single-user [Jupyter notebook](https://jupyter-notebook.readthedocs.io)
 server.
 
 [Project Jupyter](https://jupyter.org) created JupyterHub to support many
 users. The Hub can offer notebook servers to a class of students, a corporate
-data science workgroup, a scientific research project, or a high-performance
+data science workgroup, a scientific research project, or a high performance
 computing group.
 
 ## Technical overview
@@ -50,30 +42,37 @@ Three main actors make up JupyterHub:
 Basic principles for operation are:
 
 - Hub launches a proxy.
-- The Proxy forwards all requests to Hub by default.
-- Hub handles login and spawns single-user servers on demand.
-- Hub configures proxy to forward URL prefixes to the single-user notebook
+- Proxy forwards all requests to Hub by default.
+- Hub handles login, and spawns single-user servers on demand.
+- Hub configures proxy to forward url prefixes to the single-user notebook
   servers.
 
 JupyterHub also provides a
-[REST API][]
+[REST API](http://petstore.swagger.io/?url=https://raw.githubusercontent.com/jupyter/jupyterhub/master/docs/rest-api.yml#/default)
 for administration of the Hub and its users.
 
-[rest api]: https://jupyterhub.readthedocs.io/en/latest/reference/rest-api.html
-
 ## Installation
 
+
 ### Check prerequisites
 
 - A Linux/Unix based system
-- [Python](https://www.python.org/downloads/) 3.6 or greater
+- [Python](https://www.python.org/downloads/) 3.5 or greater
 - [nodejs/npm](https://www.npmjs.com/)
 
-  - If you are using **`conda`**, the nodejs and npm dependencies will be installed for
+  * If you are using **`conda`**, the nodejs and npm dependencies will be installed for
     you by conda.
 
-  - If you are using **`pip`**, install a recent version (at least 12.0) of
+  * If you are using **`pip`**, install a recent version of
     [nodejs/npm](https://docs.npmjs.com/getting-started/installing-node).
+    For example, install it on Linux (Debian/Ubuntu) using:
+
+    ```
+    sudo apt-get install npm nodejs-legacy
+    ```
+
+    The `nodejs-legacy` package installs the `node` executable and is currently
+    required for npm to work on Debian/Ubuntu.
 
 - If using the default PAM Authenticator, a [pluggable authentication module (PAM)](https://en.wikipedia.org/wiki/Pluggable_authentication_module).
 - TLS certificate and key for HTTPS communication
@@ -89,11 +88,12 @@ To install JupyterHub along with its dependencies including nodejs/npm:
 conda install -c conda-forge jupyterhub
 ```
 
-If you plan to run notebook servers locally, install JupyterLab or Jupyter notebook:
+If you plan to run notebook servers locally, install the Jupyter notebook
+or JupyterLab:
 
 ```bash
-conda install jupyterlab
 conda install notebook
+conda install jupyterlab
 ```
 
 #### Using `pip`
@@ -105,10 +105,10 @@ npm install -g configurable-http-proxy
 python3 -m pip install jupyterhub    
 ```
 
-If you plan to run notebook servers locally, you will need to install
-[JupyterLab or Jupyter notebook](https://jupyter.readthedocs.io/en/latest/install.html):
+If you plan to run notebook servers locally, you will need to install the
+[Jupyter notebook](https://jupyter.readthedocs.io/en/latest/install.html)
+package:
 
-    python3 -m pip install --upgrade jupyterlab
     python3 -m pip install --upgrade notebook
 
 ### Run the Hub server
@@ -117,12 +117,13 @@ To start the Hub server, run the command:
 
     jupyterhub
 
-Visit `http://localhost:8000` in your browser, and sign in with your system username and password.
+Visit `https://localhost:8000` in your browser, and sign in with your unix
+PAM credentials.
 
-_Note_: To allow multiple users to sign in to the server, you will need to
-run the `jupyterhub` command as a _privileged user_, such as root.
+*Note*: To allow multiple users to sign into the server, you will need to
+run the `jupyterhub` command as a *privileged user*, such as root.
 The [wiki](https://github.com/jupyterhub/jupyterhub/wiki/Using-sudo-to-run-JupyterHub-without-root-privileges)
-describes how to run the server as a _less privileged user_, which requires
+describes how to run the server as a *less privileged user*, which requires
 more configuration of the system.
 
 ## Configuration
@@ -141,7 +142,7 @@ To generate a default config file with settings and descriptions:
 
 ### Start the Hub
 
-To start the Hub on a specific url and port `10.0.1.2:443` with **https**:
+To start the Hub on a specific url and port ``10.0.1.2:443`` with **https**:
 
     jupyterhub --ip 10.0.1.2 --port 443 --ssl-key my_ssl.key --ssl-cert my_ssl.cert
 
@@ -190,7 +191,7 @@ this a good choice for **testing JupyterHub on your desktop or laptop**.
 
 If you want to run docker on a computer that has a public IP then you should
 (as in MUST) **secure it with ssl** by adding ssl options to your docker
-configuration or by using an ssl enabled proxy.
+configuration or by using a ssl enabled proxy.
 
 [Mounting volumes](https://docs.docker.com/engine/admin/volumes/volumes/) will
 allow you to **store data outside the docker image (host system) so it will be persistent**, even when you start
@@ -203,7 +204,7 @@ These accounts will be used for authentication in JupyterHub's default configura
 ## Contributing
 
 If you would like to contribute to the project, please read our
-[contributor documentation](https://jupyter.readthedocs.io/en/latest/contributing/content-contributor.html)
+[contributor documentation](http://jupyter.readthedocs.io/en/latest/contributor/content-contributor.html)
 and the [`CONTRIBUTING.md`](CONTRIBUTING.md). The `CONTRIBUTING.md` file
 explains how to set up a development installation, how to run the test suite,
 and how to contribute to documentation.
@@ -230,17 +231,18 @@ docker container or Linux VM.
 We use a shared copyright model that enables all contributors to maintain the
 copyright on their contributions.
 
-All code is licensed under the terms of the [revised BSD license](./COPYING.md).
+All code is licensed under the terms of the revised BSD license.
 
 ## Help and resources
 
-We encourage you to ask questions and share ideas on the [Jupyter community forum](https://discourse.jupyter.org/).
-You can also talk with us on our JupyterHub [Gitter](https://gitter.im/jupyterhub/jupyterhub) channel.
+We encourage you to ask questions on the [Jupyter mailing list](https://groups.google.com/forum/#!forum/jupyter).
+To participate in development discussions or get help, talk with us on
+our JupyterHub [Gitter](https://gitter.im/jupyterhub/jupyterhub) channel.
 
 - [Reporting Issues](https://github.com/jupyterhub/jupyterhub/issues)
 - [JupyterHub tutorial](https://github.com/jupyterhub/jupyterhub-tutorial)
 - [Documentation for JupyterHub](https://jupyterhub.readthedocs.io/en/latest/) | [PDF (latest)](https://media.readthedocs.org/pdf/jupyterhub/latest/jupyterhub.pdf) | [PDF (stable)](https://media.readthedocs.org/pdf/jupyterhub/stable/jupyterhub.pdf)
-- [Documentation for JupyterHub's REST API][rest api]
+- [Documentation for JupyterHub's REST API](http://petstore.swagger.io/?url=https://raw.githubusercontent.com/jupyter/jupyterhub/master/docs/rest-api.yml#/default)
 - [Documentation for Project Jupyter](http://jupyter.readthedocs.io/en/latest/index.html) | [PDF](https://media.readthedocs.org/pdf/jupyter/latest/jupyter.pdf)
 - [Project Jupyter website](https://jupyter.org)
 - [Project Jupyter community](https://jupyter.org/community)

RELEASE.md

@@ -1,55 +0,0 @@
-# How to make a release
-
-`jupyterhub` is a package available on [PyPI][] and [conda-forge][].
-These are instructions on how to make a release.
-
-## Pre-requisites
-
-- Push rights to [jupyterhub/jupyterhub][]
-- Push rights to [conda-forge/jupyterhub-feedstock][]
-
-## Steps to make a release
-
-1. Create a PR updating `docs/source/changelog.md` with [github-activity][] and
-   continue only when its merged.
-
-   ```shell
-   pip install github-activity
-
-   github-activity --heading-level=3 jupyterhub/jupyterhub
-   ```
-
-1. Checkout main and make sure it is up to date.
-
-   ```shell
-   git checkout main
-   git fetch origin main
-   git reset --hard origin/main
-   ```
-
-1. Update the version, make commits, and push a git tag with `tbump`.
-
-   ```shell
-   pip install tbump
-   tbump --dry-run ${VERSION}
-
-   tbump ${VERSION}
-   ```
-
-   Following this, the [CI system][] will build and publish a release.
-
-1. Reset the version back to dev, e.g. `2.1.0.dev` after releasing `2.0.0`
-
-   ```shell
-   tbump --no-tag ${NEXT_VERSION}.dev
-   ```
-
-1. Following the release to PyPI, an automated PR should arrive to
-   [conda-forge/jupyterhub-feedstock][] with instructions.
-
-[pypi]: https://pypi.org/project/jupyterhub/
-[conda-forge]: https://anaconda.org/conda-forge/jupyterhub
-[jupyterhub/jupyterhub]: https://github.com/jupyterhub/jupyterhub
-[conda-forge/jupyterhub-feedstock]: https://github.com/conda-forge/jupyterhub-feedstock
-[github-activity]: https://github.com/executablebooks/github-activity
-[ci system]: https://github.com/jupyterhub/jupyterhub/actions/workflows/release.yml

SECURITY.md

@@ -1,5 +0,0 @@
-# Reporting a Vulnerability
-
-If you believe you’ve found a security vulnerability in a Jupyter
-project, please report it to security@ipython.org. If you prefer to
-encrypt your security reports, you can use [this PGP public key](https://jupyter-notebook.readthedocs.io/en/stable/_downloads/1d303a645f2505a8fd283826fafc9908/ipython_security.asc).

bower-lite

@@ -29,5 +29,5 @@ dependencies = package_json['dependencies']
 for dep in dependencies:
     src = join(node_modules, dep)
     dest = join(components, dep)
-    print(f"{src} -> {dest}")
+    print("%s -> %s" % (src, dest))
     shutil.copytree(src, dest)

ci/check_installed_data.py

@@ -1,35 +0,0 @@
-#!/usr/bin/env python
-# Check that installed package contains everything we expect
-
-
-from pathlib import Path
-
-import jupyterhub
-from jupyterhub._data import DATA_FILES_PATH
-
-print("Checking jupyterhub._data", end=" ")
-print(f"DATA_FILES_PATH={DATA_FILES_PATH}", end=" ")
-DATA_FILES_PATH = Path(DATA_FILES_PATH)
-assert DATA_FILES_PATH.is_dir(), DATA_FILES_PATH
-for subpath in (
-    "templates/page.html",
-    "static/css/style.min.css",
-    "static/components/jquery/dist/jquery.js",
-    "static/js/admin-react.js",
-):
-    path = DATA_FILES_PATH / subpath
-    assert path.is_file(), path
-
-print("OK")
-
-print("Checking package_data", end=" ")
-jupyterhub_path = Path(jupyterhub.__file__).parent.resolve()
-for subpath in (
-    "alembic.ini",
-    "alembic/versions/833da8570507_rbac.py",
-    "event-schemas/server-actions/v1.yaml",
-):
-    path = jupyterhub_path / subpath
-    assert path.is_file(), path
-
-print("OK")

ci/check_sdist.py

@@ -1,27 +0,0 @@
-#!/usr/bin/env python
-# Check that sdist contains everything we expect
-
-import sys
-import tarfile
-
-expected_files = [
-    "docs/requirements.txt",
-    "jsx/package.json",
-    "package.json",
-    "README.md",
-]
-
-assert len(sys.argv) == 2, "Expected one file"
-print(f"Checking {sys.argv[1]}")
-
-tar = tarfile.open(name=sys.argv[1], mode="r:gz")
-try:
-    # Remove leading jupyterhub-VERSION/
-    filelist = {f.partition('/')[2] for f in tar.getnames()}
-finally:
-    tar.close()
-
-for e in expected_files:
-    assert e in filelist, f"{e} not found"
-
-print("OK")

ci/docker-db.sh

@@ -22,7 +22,7 @@ if [[ "$DB" == "mysql" ]]; then
     # ref server: https://hub.docker.com/_/mysql/
     # ref client: https://dev.mysql.com/doc/refman/5.7/en/setting-environment-variables.html
     #
-    DOCKER_RUN_ARGS="-p 3306:3306 --env MYSQL_ALLOW_EMPTY_PASSWORD=1 mysql:8.0"
+    DOCKER_RUN_ARGS="-p 3306:3306 --env MYSQL_ALLOW_EMPTY_PASSWORD=1 mysql:5.7"
     READINESS_CHECK="mysql --user root --execute \q"
 elif [[ "$DB" == "postgres" ]]; then
     # Environment variables can influence both the postgresql server in the
@@ -36,7 +36,7 @@ elif [[ "$DB" == "postgres" ]]; then
     # used by the postgresql client psql, so we configure the user based on how
     # we want to connect.
     #
-    DOCKER_RUN_ARGS="-p 5432:5432 --env "POSTGRES_USER=${PGUSER}" --env "POSTGRES_PASSWORD=${PGPASSWORD}" postgres:15.1"
+    DOCKER_RUN_ARGS="-p 5432:5432 --env "POSTGRES_USER=${PGUSER}" --env "POSTGRES_PASSWORD=${PGPASSWORD}" postgres:9.5"
     READINESS_CHECK="psql --command \q"
 else
     echo '$DB must be mysql or postgres'

ci/init-db.sh

@@ -19,9 +19,8 @@ else
 fi
 
 # Configure a set of databases in the database server for upgrade tests
-# this list must be in sync with versions in test_db.py:test_upgrade
 set -x
-for SUFFIX in '' _upgrade_110 _upgrade_122 _upgrade_130 _upgrade_150 _upgrade_211; do
+for SUFFIX in '' _upgrade_072 _upgrade_081 _upgrade_094; do
     $SQL_CLIENT "DROP DATABASE jupyterhub${SUFFIX};" 2>/dev/null || true
     $SQL_CLIENT "CREATE DATABASE jupyterhub${SUFFIX} ${EXTRA_CREATE_DATABASE_ARGS:-};"
 done

demo-image/README.md

@@ -15,7 +15,6 @@ This should only be used for demo or testing purposes!
 It shouldn't be used as a base image to build on.
 
 ### Try it
-
 1. `cd` to the root of your jupyterhub repo.
 
 2. Build the demo image with `docker build -t jupyterhub-demo demo-image`. 

dev-requirements.txt

@@ -0,0 +1,20 @@
+-r requirements.txt
+# temporary pin of attrs for jsonschema 0.3.0a1
+# seems to be a pip bug
+attrs>=17.4.0
+beautifulsoup4
+codecov
+coverage
+cryptography
+html5lib  # needed for beautifulsoup
+mock
+notebook
+pre-commit
+pytest-asyncio
+pytest-cov
+pytest>=3.3
+requests-mock
+# blacklist urllib3 releases affected by https://github.com/urllib3/urllib3/issues/1683
+# I *think* this should only affect testing, not production
+urllib3!=1.25.4,!=1.25.5
+virtualenv

dockerfiles/Dockerfile.alpine

@@ -1,14 +1,9 @@
-FROM alpine:3.13
-ENV LANG=en_US.UTF-8
-RUN apk add --no-cache \
-        python3 \
-        py3-pip \
-        py3-ruamel.yaml \
-        py3-cryptography \
-        py3-sqlalchemy
+FROM python:3.6.3-alpine3.6
+
+ARG JUPYTERHUB_VERSION=0.8.1
 
-ARG JUPYTERHUB_VERSION=1.3.0
 RUN pip3 install --no-cache jupyterhub==${JUPYTERHUB_VERSION}
+ENV LANG=en_US.UTF-8
 
 USER nobody
 CMD ["jupyterhub"]

dockerfiles/README.md

@@ -1,22 +1,20 @@
 ## What is Dockerfile.alpine
-
-Dockerfile.alpine contains the base image for jupyterhub. It does not work independently, but only as part of a full jupyterhub cluster
+Dockerfile.alpine  contains base image for jupyterhub. It does not work independently, but only as part of a full jupyterhub cluster
 
 ## How to use it?
 
-You will need:
-
 1. A running configurable-http-proxy, whose API is accessible. 
 2. A jupyterhub_config file.
 3. Authentication and other libraries required by the specific jupyterhub_config file.
 
+
 ## Steps to test it outside a cluster
 
-- start configurable-http-proxy in another container
-- specify CONFIGPROXY_AUTH_TOKEN env in both containers
-- put both containers on the same network (e.g. docker network create jupyterhub; docker run ... --net jupyterhub)
-- tell jupyterhub where CHP is (e.g. c.ConfigurableHTTPProxy.api_url = 'http://chp:8001')
-- tell jupyterhub not to start the proxy itself (c.ConfigurableHTTPProxy.should_start = False)
-- Use a dummy authenticator for ease of testing. Update following in jupyterhub_config file
-  - c.JupyterHub.authenticator_class = 'dummyauthenticator.DummyAuthenticator'
-  - c.DummyAuthenticator.password = "your strong password"
+* start configurable-http-proxy in another container
+* specify CONFIGPROXY_AUTH_TOKEN env in both containers
+* put both containers on the same network (e.g. docker network create jupyterhub; docker run ... --net jupyterhub)
+* tell jupyterhub where CHP is (e.g. c.ConfigurableHTTPProxy.api_url = 'http://chp:8001')
+* tell jupyterhub not to start the proxy itself (c.ConfigurableHTTPProxy.should_start = False)
+* Use dummy authenticator for ease of testing. Update following in jupyterhub_config file
+    - c.JupyterHub.authenticator_class = 'dummyauthenticator.DummyAuthenticator'
+    - c.DummyAuthenticator.password = "your strong password"

dockerfiles/test.py

@@ -4,11 +4,6 @@ from jupyterhub._data import DATA_FILES_PATH
 
 print(f"DATA_FILES_PATH={DATA_FILES_PATH}")
 
-for sub_path in (
-    "templates",
-    "static/components",
-    "static/css/style.min.css",
-    "static/js/admin-react.js",
-):
+for sub_path in ("templates", "static/components", "static/css/style.min.css"):
     path = os.path.join(DATA_FILES_PATH, sub_path)
     assert os.path.exists(path), path

docs/Makefile

@@ -53,20 +53,20 @@ help:
 clean:
 	rm -rf $(BUILDDIR)/*
 
+node_modules: package.json
+	npm install && touch node_modules
+
+rest-api: source/_static/rest-api/index.html
+
+source/_static/rest-api/index.html: rest-api.yml node_modules
+	npm run rest-api
+
 metrics: source/reference/metrics.rst
 
 source/reference/metrics.rst: generate-metrics.py
 	python3 generate-metrics.py
 
-scopes: source/rbac/scope-table.md
-
-source/rbac/scope-table.md: source/rbac/generate-scope-table.py
-	python3 source/rbac/generate-scope-table.py
-
-# If the pre-requisites for the html target is updated, also update the Read The
-# Docs section in docs/source/conf.py.
-#
-html: metrics scopes
+html: rest-api metrics
 	$(SPHINXBUILD) -b html $(ALLSPHINXOPTS) $(BUILDDIR)/html
 	@echo
 	@echo "Build finished. The HTML pages are in $(BUILDDIR)/html."

docs/generate-metrics.py

@@ -1,4 +1,5 @@
 import os
+from os.path import join
 
 from pytablewriter import RstSimpleTableWriter
 from pytablewriter.style import Style

docs/package.json

@@ -0,0 +1,14 @@
+{
+  "name": "jupyterhub-docs-build",
+  "version": "0.8.0",
+  "description": "build JupyterHub swagger docs",
+  "scripts": {
+    "rest-api": "bootprint openapi ./rest-api.yml source/_static/rest-api"
+  },
+  "author": "",
+  "license": "BSD-3-Clause",
+  "devDependencies": {
+    "bootprint": "^1.0.0",
+    "bootprint-openapi": "^1.0.0"
+  }
+}

docs/requirements.txt

@@ -1,21 +1,12 @@
-# We install the jupyterhub package to help autodoc-traits inspect it and
-# generate documentation.
-#
-# FIXME: If there is a way for this requirements.txt file to pass a flag that
-#        the build system can intercept to not build the javascript artifacts,
-#        then do so so. That would mean that installing the documentation can
-#        avoid needing node/npm installed.
-#
---editable .
+-r ../requirements.txt
 
-autodoc-traits
-myst-parser
-pre-commit
+alabaster_jupyterhub
+# Temporary fix of #3021. Revert back to released autodoc-traits when
+# 0.1.0 released.
+https://github.com/jupyterhub/autodoc-traits/archive/75885ee24636efbfebfceed1043459715049cd84.zip
 pydata-sphinx-theme
 pytablewriter>=0.56
-ruamel.yaml
-sphinx>=4
+recommonmark>=0.6
 sphinx-copybutton
 sphinx-jsonschema
-sphinxext-opengraph
-sphinxext-rediraffe
+sphinx>=1.7

docs/rest-api.yml

@@ -0,0 +1,881 @@
+# see me at: http://petstore.swagger.io/?url=https://raw.githubusercontent.com/jupyterhub/jupyterhub/master/docs/rest-api.yml#/default
+swagger: '2.0'
+info:
+  title: JupyterHub
+  description: The REST API for JupyterHub
+  version: 1.2.0dev
+  license:
+    name: BSD-3-Clause
+schemes:
+  [http, https]
+securityDefinitions:
+  token:
+    type: apiKey
+    name: Authorization
+    in: header
+security:
+  - token: []
+basePath: /hub/api
+produces:
+  - application/json
+consumes:
+  - application/json
+paths:
+  /:
+    get:
+      summary: Get JupyterHub version
+      description: |
+        This endpoint is not authenticated for the purpose of clients and user
+        to identify the JupyterHub version before setting up authentication.
+      responses:
+        '200':
+          description: The JupyterHub version
+          schema:
+            type: object
+            properties:
+              version:
+                type: string
+                description: The version of JupyterHub itself
+  /info:
+    get:
+      summary: Get detailed info about JupyterHub
+      description: |
+        Detailed JupyterHub information, including Python version,
+        JupyterHub's version and executable path,
+        and which Authenticator and Spawner are active.
+      responses:
+        '200':
+          description: Detailed JupyterHub info
+          schema:
+            type: object
+            properties:
+              version:
+                type: string
+                description: The version of JupyterHub itself
+              python:
+                type: string
+                description: The Python version, as returned by sys.version
+              sys_executable:
+                type: string
+                description: The path to sys.executable running JupyterHub
+              authenticator:
+                type: object
+                properties:
+                  class:
+                    type: string
+                    description: The Python class currently active for JupyterHub Authentication
+                  version:
+                    type: string
+                    description: The version of the currently active Authenticator
+              spawner:
+                type: object
+                properties:
+                  class:
+                    type: string
+                    description: The Python class currently active for spawning single-user notebook servers
+                  version:
+                    type: string
+                    description: The version of the currently active Spawner
+  /users:
+    get:
+      summary: List users
+      responses:
+        '200':
+          description: The Hub's user list
+          schema:
+            type: array
+            items:
+              $ref: '#/definitions/User'
+    post:
+      summary: Create multiple users
+      parameters:
+        - name: body
+          in: body
+          required: true
+          schema:
+            type: object
+            properties:
+              usernames:
+                type: array
+                description: list of usernames to create on the Hub
+                items:
+                  type: string
+              admin:
+                description: whether the created users should be admins
+                type: boolean
+      responses:
+        '201':
+          description: The users have been created
+          schema:
+            type: array
+            description: The created users
+            items:
+              $ref: '#/definitions/User'
+  /users/{name}:
+    get:
+      summary: Get a user by name
+      parameters:
+        - name: name
+          description: username
+          in: path
+          required: true
+          type: string
+      responses:
+        '200':
+          description: The User model
+          schema:
+            $ref: '#/definitions/User'
+    post:
+      summary: Create a single user
+      parameters:
+        - name: name
+          description: username
+          in: path
+          required: true
+          type: string
+      responses:
+        '201':
+          description: The user has been created
+          schema:
+            $ref: '#/definitions/User'
+    patch:
+      summary: Modify a user
+      description: Change a user's name or admin status
+      parameters:
+        - name: name
+          description: username
+          in: path
+          required: true
+          type: string
+        - name: body
+          in: body
+          required: true
+          description: Updated user info. At least one key to be updated (name or admin) is required.
+          schema:
+            type: object
+            properties:
+              name:
+                type: string
+                description: the new name (optional, if another key is updated i.e. admin)
+              admin:
+                type: boolean
+                description: update admin (optional, if another key is updated i.e. name)
+      responses:
+        '200':
+          description: The updated user info
+          schema:
+            $ref: '#/definitions/User'
+    delete:
+      summary: Delete a user
+      parameters:
+        - name: name
+          description: username
+          in: path
+          required: true
+          type: string
+      responses:
+        '204':
+          description: The user has been deleted
+  /users/{name}/activity:
+    post:
+      summary:
+        Notify Hub of activity for a given user.
+      description:
+        Notify the Hub of activity by the user,
+        e.g. accessing a service or (more likely)
+        actively using a server.
+      parameters:
+        - name: name
+          description: username
+          in: path
+          required: true
+          type: string
+        - name: body
+          in: body
+          schema:
+            type: object
+            properties:
+              last_activity:
+                type: string
+                format: date-time
+                description: |
+                  Timestamp of last-seen activity for this user.
+                  Only needed if this is not activity associated
+                  with using a given server.
+              servers:
+                description: |
+                  Register activity for specific servers by name.
+                  The keys of this dict are the names of servers.
+                  The default server has an empty name ('').
+                type: object
+                properties:
+                  '<server name>':
+                    description: |
+                      Activity for a single server.
+                    type: object
+                    required:
+                      - last_activity
+                    properties:
+                      last_activity:
+                        type: string
+                        format: date-time
+                        description: |
+                          Timestamp of last-seen activity on this server.
+            example:
+              last_activity: '2019-02-06T12:54:14Z'
+              servers:
+                '':
+                  last_activity: '2019-02-06T12:54:14Z'
+                gpu:
+                  last_activity: '2019-02-06T12:54:14Z'
+      responses:
+        '401':
+          $ref: '#/responses/Unauthorized'
+        '404':
+          description: No such user
+  /users/{name}/server:
+    post:
+      summary: Start a user's single-user notebook server
+      parameters:
+        - name: name
+          description: username
+          in: path
+          required: true
+          type: string
+        - name: options
+          description: |
+            Spawn options can be passed as a JSON body
+            when spawning via the API instead of spawn form.
+            The structure of the options
+            will depend on the Spawner's configuration.
+            The body itself will be available as `user_options` for the
+            Spawner.
+          in: body
+          required: false
+          schema:
+            type: object
+
+      responses:
+        '201':
+          description: The user's notebook server has started
+        '202':
+          description: The user's notebook server has not yet started, but has been requested
+    delete:
+      summary: Stop a user's server
+      parameters:
+        - name: name
+          description: username
+          in: path
+          required: true
+          type: string
+      responses:
+        '204':
+          description: The user's notebook server has stopped
+        '202':
+          description: The user's notebook server has not yet stopped as it is taking a while to stop
+  /users/{name}/servers/{server_name}:
+    post:
+      summary: Start a user's single-user named-server notebook server
+      parameters:
+        - name: name
+          description: username
+          in: path
+          required: true
+          type: string
+        - name: server_name
+          description: |
+            name given to a named-server. 
+            
+            Note that depending on your JupyterHub infrastructure there are chracterter size limitation to `server_name`. Default spawner with K8s pod will not allow Jupyter Notebooks to be spawned with a name that contains more than 253 characters (keep in mind that the pod will be spawned with extra characters to identify the user and hub).
+          in: path
+          required: true
+          type: string
+        - name: options
+          description: |
+            Spawn options can be passed as a JSON body
+            when spawning via the API instead of spawn form.
+            The structure of the options
+            will depend on the Spawner's configuration.
+          in: body
+          required: false
+          schema:
+            type: object
+      responses:
+        '201':
+          description: The user's notebook named-server has started
+        '202':
+          description: The user's notebook named-server has not yet started, but has been requested
+    delete:
+      summary: Stop a user's named-server
+      parameters:
+        - name: name
+          description: username
+          in: path
+          required: true
+          type: string
+        - name: server_name
+          description: name given to a named-server
+          in: path
+          required: true
+          type: string
+        - name: body
+          in: body
+          required: false
+          schema:
+            type: object
+            properties:
+              remove:
+                type: boolean
+                description: |
+                  Whether to fully remove the server, rather than just stop it.
+                  Removing a server deletes things like the state of the stopped server.
+                  Default: false.
+      responses:
+        '204':
+          description: The user's notebook named-server has stopped
+        '202':
+          description: The user's notebook named-server has not yet stopped as it is taking a while to stop
+  /users/{name}/tokens:
+    parameters:
+      - name: name
+        description: username
+        in: path
+        required: true
+        type: string
+    get:
+      summary: List tokens for the user
+      responses:
+        '200':
+          description: The list of tokens
+          schema:
+            type: array
+            items:
+              $ref: '#/definitions/Token'
+        '401':
+          $ref: '#/responses/Unauthorized'
+        '404':
+          description: No such user
+    post:
+      summary: Create a new token for the user
+      parameters:
+        - name: token_params
+          in: body
+          required: false
+          schema:
+            type: object
+            properties:
+              expires_in:
+                type: number
+                description: lifetime (in seconds) after which the requested token will expire.
+              note:
+                type: string
+                description: A note attached to the token for future bookkeeping
+      responses:
+        '201':
+          description: The newly created token
+          schema:
+            $ref: '#/definitions/Token'
+        '400':
+          description: Body must be a JSON dict or empty
+  /users/{name}/tokens/{token_id}:
+    parameters:
+      - name: name
+        description: username
+        in: path
+        required: true
+        type: string
+      - name: token_id
+        in: path
+        required: true
+        type: string
+    get:
+      summary: Get the model for a token by id
+      responses:
+        '200':
+          description: The info for the new token
+          schema:
+            $ref: '#/definitions/Token'
+    delete:
+      summary: Delete (revoke) a token by id
+      responses:
+        '204':
+          description: The token has been deleted
+  /user:
+    get:
+      summary: Return authenticated user's model
+      responses:
+        '200':
+          description: The authenticated user's model is returned.
+          schema:
+            $ref: '#/definitions/User'
+  /groups:
+    get:
+      summary: List groups
+      responses:
+        '200':
+          description: The list of groups
+          schema:
+            type: array
+            items:
+              $ref: '#/definitions/Group'
+  /groups/{name}:
+    get:
+      summary: Get a group by name
+      parameters:
+        - name: name
+          description: group name
+          in: path
+          required: true
+          type: string
+      responses:
+        '200':
+          description: The group model
+          schema:
+            $ref: '#/definitions/Group'
+    post:
+      summary: Create a group
+      parameters:
+        - name: name
+          description: group name
+          in: path
+          required: true
+          type: string
+      responses:
+        '201':
+          description: The group has been created
+          schema:
+            $ref: '#/definitions/Group'
+    delete:
+      summary: Delete a group
+      parameters:
+        - name: name
+          description: group name
+          in: path
+          required: true
+          type: string
+      responses:
+        '204':
+          description: The group has been deleted
+  /groups/{name}/users:
+    post:
+      summary: Add users to a group
+      parameters:
+        - name: name
+          description: group name
+          in: path
+          required: true
+          type: string
+        - name: body
+          in: body
+          required: true
+          description: The users to add to the group
+          schema:
+            type: object
+            properties:
+              users:
+                type: array
+                description: List of usernames to add to the group
+                items:
+                  type: string
+      responses:
+        '200':
+          description: The users have been added to the group
+          schema:
+            $ref: '#/definitions/Group'
+    delete:
+      summary: Remove users from a group
+      parameters:
+        - name: name
+          description: group name
+          in: path
+          required: true
+          type: string
+        - name: body
+          in: body
+          required: true
+          description: The users to remove from the group
+          schema:
+            type: object
+            properties:
+              users:
+                type: array
+                description: List of usernames to remove from the group
+                items:
+                  type: string
+      responses:
+        '200':
+          description: The users have been removed from the group
+  /services:
+    get:
+      summary: List services
+      responses:
+        '200':
+          description: The service list
+          schema:
+            type: array
+            items:
+              $ref: '#/definitions/Service'
+  /services/{name}:
+    get:
+      summary: Get a service by name
+      parameters:
+        - name: name
+          description: service name
+          in: path
+          required: true
+          type: string
+      responses:
+        '200':
+          description: The Service model
+          schema:
+            $ref: '#/definitions/Service'
+  /proxy:
+    get:
+      summary: Get the proxy's routing table
+      description: A convenience alias for getting the routing table directly from the proxy
+      responses:
+        '200':
+          description: Routing table
+          schema:
+            type: object
+            description: configurable-http-proxy routing table (see configurable-http-proxy docs for details)
+    post:
+      summary: Force the Hub to sync with the proxy
+      responses:
+        '200':
+          description: Success
+    patch:
+      summary: Notify the Hub about a new proxy
+      description: Notifies the Hub of a new proxy to use.
+      parameters:
+        - name: body
+          in: body
+          required: true
+          description: Any values that have changed for the new proxy. All keys are optional.
+          schema:
+            type: object
+            properties:
+              ip:
+                type: string
+                description: IP address of the new proxy
+              port:
+                type: string
+                description: Port of the new proxy
+              protocol:
+                type: string
+                description: Protocol of new proxy, if changed
+              auth_token:
+                type: string
+                description: CONFIGPROXY_AUTH_TOKEN for the new proxy
+      responses:
+        '200':
+          description: Success
+  /authorizations/token:
+    post:
+      summary: Request a new API token
+      description: |
+        Request a new API token to use with the JupyterHub REST API.
+        If not already authenticated, username and password can be sent
+        in the JSON request body.
+        Logging in via this method is only available when the active Authenticator
+        accepts passwords (e.g. not OAuth).
+      parameters:
+        - name: credentials
+          in: body
+          schema:
+            type: object
+            properties:
+              username:
+                type: string
+              password:
+                type: string
+      responses:
+        '200':
+          description: The new API token
+          schema:
+            type: object
+            properties:
+              token:
+                type: string
+                description: The new API token.
+        '403':
+          description: The user can not be authenticated.
+  /authorizations/token/{token}:
+    get:
+      summary: Identify a user or service from an API token
+      parameters:
+        - name: token
+          in: path
+          required: true
+          type: string
+      responses:
+        '200':
+          description: The user or service identified by the API token
+        '404':
+          description: A user or service is not found.
+  /authorizations/cookie/{cookie_name}/{cookie_value}:
+    get:
+      summary: Identify a user from a cookie
+      description: Used by single-user notebook servers to hand off cookie authentication to the Hub
+      parameters:
+        - name: cookie_name
+          in: path
+          required: true
+          type: string
+        - name: cookie_value
+          in: path
+          required: true
+          type: string
+      responses:
+        '200':
+          description: The user identified by the cookie
+          schema:
+            $ref: '#/definitions/User'
+        '404':
+          description: A user is not found.
+  /oauth2/authorize:
+    get:
+      summary: 'OAuth 2.0 authorize endpoint'
+      description: |
+        Redirect users to this URL to begin the OAuth process.
+        It is not an API endpoint.
+      parameters:
+        - name: client_id
+          description: The client id
+          in: query
+          required: true
+          type: string
+        - name: response_type
+          description: The response type (always 'code')
+          in: query
+          required: true
+          type: string
+        - name: state
+          description: A state string
+          in: query
+          required: false
+          type: string
+        - name: redirect_uri
+          description: The redirect url
+          in: query
+          required: true
+          type: string
+      responses:
+        '200':
+          description: Success
+        '400':
+          description: OAuth2Error
+  /oauth2/token:
+    post:
+      summary: Request an OAuth2 token
+      description: |
+        Request an OAuth2 token from an authorization code.
+        This request completes the OAuth process.
+      consumes:
+        - application/x-www-form-urlencoded
+      parameters:
+        - name: client_id
+          description: The client id
+          in: formData
+          required: true
+          type: string
+        - name: client_secret
+          description: The client secret
+          in: formData
+          required: true
+          type: string
+        - name: grant_type
+          description: The grant type (always 'authorization_code')
+          in: formData
+          required: true
+          type: string
+        - name: code
+          description: The code provided by the authorization redirect
+          in: formData
+          required: true
+          type: string
+        - name: redirect_uri
+          description: The redirect url
+          in: formData
+          required: true
+          type: string
+      responses:
+        '200':
+          description: JSON response including the token
+          schema:
+            type: object
+            properties:
+              access_token:
+                type: string
+                description: The new API token for the user
+              token_type:
+                type: string
+                description: Will always be 'Bearer'
+  /shutdown:
+    post:
+      summary: Shutdown the Hub
+      parameters:
+        - name: body
+          in: body
+          schema:
+            type: object
+            properties:
+              proxy:
+                type: boolean
+                description: Whether the proxy should be shutdown as well (default from Hub config)
+              servers:
+                type: boolean
+                description: Whether users' notebook servers should be shutdown as well (default from Hub config)
+      responses:
+        '202':
+          description: Shutdown successful
+        '400':
+          description: Unexpeced value for proxy or servers
+# Descriptions of common responses
+responses:
+  NotFound:
+    description: The specified resource was not found
+  Unauthorized:
+    description: Authentication/Authorization error
+definitions:
+  User:
+    type: object
+    properties:
+      name:
+        type: string
+        description: The user's name
+      admin:
+        type: boolean
+        description: Whether the user is an admin
+      groups:
+        type: array
+        description: The names of groups where this user is a member
+        items:
+          type: string
+      server:
+        type: string
+        description: The user's notebook server's base URL, if running; null if not.
+      pending:
+        type: string
+        enum: ["spawn", "stop", null]
+        description: The currently pending action, if any
+      last_activity:
+        type: string
+        format: date-time
+        description: Timestamp of last-seen activity from the user
+      servers:
+        type: array
+        description: The active servers for this user.
+        items:
+          $ref: '#/definitions/Server'
+  Server:
+    type: object
+    properties:
+      name:
+        type: string
+        description: The server's name. The user's default server has an empty name ('')
+      ready:
+        type: boolean
+        description: |
+          Whether the server is ready for traffic.
+          Will always be false when any transition is pending.
+      pending:
+        type: string
+        enum: ["spawn", "stop", null]
+        description: |
+          The currently pending action, if any.
+          A server is not ready if an action is pending.
+      url:
+        type: string
+        description: |
+          The URL where the server can be accessed
+          (typically /user/:name/:server.name/).
+      progress_url:
+        type: string
+        description: |
+          The URL for an event-stream to retrieve events during a spawn.
+      started:
+        type: string
+        format: date-time
+        description: UTC timestamp when the server was last started.
+      last_activity:
+        type: string
+        format: date-time
+        description: UTC timestamp last-seen activity on this server.
+      state:
+        type: object
+        description: Arbitrary internal state from this server's spawner.  Only available on the hub's users list or get-user-by-name method, and only if a hub admin.  None otherwise.
+      user_options:
+        type: object
+        description: User specified options for the user's spawned instance of a single-user server.
+  Group:
+    type: object
+    properties:
+      name:
+        type: string
+        description: The group's name
+      users:
+        type: array
+        description: The names of users who are members of this group
+        items:
+          type: string
+  Service:
+    type: object
+    properties:
+      name:
+        type: string
+        description: The service's name
+      admin:
+        type: boolean
+        description: Whether the service is an admin
+      url:
+        type: string
+        description: The internal url where the service is running
+      prefix:
+        type: string
+        description: The proxied URL prefix to the service's url
+      pid:
+        type: number
+        description: The PID of the service process (if managed)
+      command:
+        type: array
+        description: The command used to start the service (if managed)
+        items:
+          type: string
+      info:
+        type: object
+        description: |
+          Additional information a deployment can attach to a service.
+          JupyterHub does not use this field.
+  Token:
+    type: object
+    properties:
+      token:
+        type: string
+        description: The token itself. Only present in responses to requests for a new token.
+      id:
+        type: string
+        description: The id of the API token. Used for modifying or deleting the token.
+      user:
+        type: string
+        description: The user that owns a token (undefined if owned by a service)
+      service:
+        type: string
+        description: The service that owns the token (undefined of owned by a user)
+      note:
+        type: string
+        description: A note about the token, typically describing what it was created for.
+      created:
+        type: string
+        format: date-time
+        description: Timestamp when this token was created
+      expires_at:
+        type: string
+        format: date-time
+        description: Timestamp when this token expires. Null if there is no expiry.
+      last_activity:
+        type: string
+        format: date-time
+        description: |
+          Timestamp of last-seen activity using this token.
+          Can be null if token has never been used.

docs/source/_static/custom.css

@@ -2,9 +2,3 @@
 .navbar-brand {
   height: 4rem !important;
 }
-
-/* hide redundant funky-formatted swagger-ui version */
-
-.swagger-ui .info .title small {
-  display: none !important;
-}

docs/source/admin/capacity-planning.md

@@ -1,308 +0,0 @@
-# Capacity planning
-
-General capacity planning advice for JupyterHub is hard to give,
-because it depends almost entirely on what your users are doing,
-and what JupyterHub users do varies _wildly_ in terms of resource consumption.
-
-**There is no single answer to "I have X users, what resources do I need?" or "How many users can I support with this machine?"**
-
-Here are three _typical_ Jupyter use patterns that require vastly different resources:
-
-- **Learning**: negligible resources because computation is mostly idle,
-  e.g. students learning programming for the first time
-- **Production code**: very intense, sustained load, e.g. training machine learning models
-- **Bursting**: _mostly_ idle, but needs a lot of resources for short periods of time
-  (interactive research often looks like this)
-
-But just because there's no single answer doesn't mean we can't help.
-So we have gathered here some useful information to help you make your decisions
-about what resources you need based on how your users work,
-including the relative invariants in terms of resources that JupyterHub itself needs.
-
-## JupyterHub infrastructure
-
-JupyterHub consists of a few components that are always running.
-These take up very little resources,
-especially relative to the resources consumed by users when you have more than a few.
-
-As an example, an instance of mybinder.org (running JupyterHub 1.5.0),
-running with typically ~100-150 users has:
-
-| Component | CPU (mean/peak) | Memory (mean/peak) |
-| --------- | --------------- | ------------------ |
-| Hub       | 4% / 13%        | (230 MB / 260 MB)  |
-| Proxy     | 6% / 13%        | (47 MB / 65 MB)    |
-
-So it would be pretty generous to allocate ~25% of one CPU core
-and ~500MB of RAM to overall JupyterHub infrastructure.
-
-The rest is going to be up to your users.
-Per-user overhead from JupyterHub is typically negligible
-up to at least a few hundred concurrent active users.
-
-```[figure} ../images/mybinder-hub-components-cpu-memory.png
-JupyterHub component resource usage for mybinder.org.
-```
-
-## Factors to consider
-
-### Static vs elastic resources
-
-A big factor in planning resources is:
-**how much does it cost to change your mind?**
-If you are using a single shared machine with local storage,
-migrating to a new one because it turns out your users don't fit might be very costly.
-You will have to get a new machine, set it up, and maybe even migrate user data.
-
-On the other hand, if you are using ephemeral resources,
-such as node pools in Kubernetes,
-changing resource types costs close to nothing
-because nodes can automatically be added or removed as needed.
-
-Take that cost into account when you are picking how much memory or cpu to allocate to users.
-
-Static resources (like [the-littlest-jupyterhub][]) provide for more **stable, predictable costs**,
-but elastic resources (like [zero-to-jupyterhub][]) tend to provide **lower overall costs**
-(especially when deployed with monitoring allowing cost optimizations over time),
-but which are **less predictable**.
-
-[the-littlest-jupyterhub]: https://the-littlest-jupyterhub.readthedocs.io
-
-[zero-to-jupyterhub]: https://zero-to-jupyterhub.readthedocs.io
-
-(limits-requests)=
-
-### Limit vs Request for resources
-
-Many scheduling tools like Kubernetes have two separate ways of allocating resources to users.
-A **Request** or **Reservation** describes how much resources are _set aside_ for each user.
-Often, this doesn't have any practical effect other than deciding when a given machine is considered 'full'.
-If you are using expandable resources like an autoscaling Kubernetes cluster,
-a new node must be launched and added to the pool if you 'request' more resources than fit on currently running nodes (a cluster **scale-up event**).
-If you are running on a single VM, this describes how many users you can run at the same time, full stop.
-
-A **Limit**, on the other hand, enforces a limit to how much resources any given user can consume.
-For more information on what happens when users try to exceed their limits, see [](oversubscription).
-
-In the strictest, safest case, you can have these two numbers be the same.
-That means that each user is _limited_ to fit within the resources allocated to it.
-This avoids **[oversubscription](oversubscription)** of resources (allowing use of more than you have available),
-at the expense (in a literal, this-costs-money sense) of reserving lots of usually-idle capacity.
-
-However, you often find that a small fraction of users use more resources than others.
-In this case you may give users limits that _go beyond the amount of resources requested_.
-This is called **oversubscribing** the resources available to users.
-
-Having a gap between the request and the limit means you can fit a number of _typical_ users on a node (based on the request),
-but still limit how much a runaway user can gobble up for themselves.
-
-(oversubscription)=
-
-### Oversubscribed CPU is okay, running out of memory is bad
-
-An important consideration when assigning resources to users is: **What happens when users need more than I've given them?**
-
-A good summary to keep in mind:
-
-> When tasks don't get enough CPU, things are slow.
-> When they don't get enough memory, things are broken.
-
-This means it's **very important that users have enough memory**,
-but much less important that they always have exclusive access to all the CPU they can use.
-
-This relates to [Limits and Requests](limits-requests),
-because these are the consequences of your limits and/or requests not matching what users actually try to use.
-
-A table of mismatched resource allocation situations and their consequences:
-
-| issue                                                    | consequence                                                                           |
-| -------------------------------------------------------- | ------------------------------------------------------------------------------------- |
-| Requests too high                                        | Unnecessarily high cost and/or low capacity.                                          |
-| CPU limit too low                                        | Poor performance experienced by users                                                 |
-| CPU oversubscribed (too-low request + too-high limit)    | Poor performance across the system; may crash, if severe                              |
-| Memory limit too low                                     | Servers killed by Out-of-Memory Killer (OOM); lost work for users                     |
-| Memory oversubscribed (too-low request + too-high limit) | System memory exhaustion - all kinds of hangs and crashes and weird errors. Very bad. |
-
-Note that the 'oversubscribed' problem case is where the request is lower than _typical_ usage,
-meaning that the total reserved resources isn't enough for the total _actual_ consumption.
-This doesn't mean that _all_ your users exceed the request,
-just that the _limit_ gives enough room for the _average_ user to exceed the request.
-
-All of these considerations are important _per node_.
-Larger nodes means more users per node, and therefore more users to average over.
-It also means more chances for multiple outliers on the same node.
-
-### Example case for oversubscribing memory
-
-Take for example, this system and sampling of user behavior:
-
-- System memory = 8G
-- memory request = 1G, limit = 3G
-- typical 'heavy' user: 2G
-- typical 'light' user: 0.5G
-
-This will assign 8 users to those 8G of RAM (remember: only requests are used for deciding when a machine is 'full').
-As long as the total of 8 users _actual_ usage is under 8G, everything is fine.
-But the _limit_ allows a total of 24G to be used,
-which would be a mess if everyone used their full limit.
-But _not_ everyone uses the full limit, which is the point!
-
-This pattern is fine if 1/8 of your users are 'heavy' because _typical_ usage will be ~0.7G,
-and your total usage will be ~5G (`1 × 2 + 7 × 0.5 = 5.5`).
-
-But if _50%_ of your users are 'heavy' you have a problem because that means your users will be trying to use 10G (`4 × 2 + 4 × 0.5 = 10`),
-which you don't have.
-
-You can make guesses at these numbers, but the only _real_ way to get them is to measure (see [](measuring)).
-
-### CPU:memory ratio
-
-Most of the time, you'll find that only one resource is the limiting factor for your users.
-Most often it's memory, but for certain tasks, it could be CPU (or even GPUs).
-
-Many cloud deployments have just one or a few fixed ratios of cpu to memory
-(e.g. 'general purpose', 'high memory', and 'high cpu').
-Setting your secondary resource allocation according to this ratio
-after selecting the more important limit results in a balanced resource allocation.
-
-For instance, some of Google Cloud's ratios are:
-
-| node type   | GB RAM / CPU core |
-| ----------- | ----------------- |
-| n2-highmem  | 8                 |
-| n2-standard | 4                 |
-| n2-highcpu  | 1                 |
-
-(idleness)=
-
-### Idleness
-
-Jupyter being an interactive tool means people tend to spend a lot more time reading and thinking than actually running resource-intensive code.
-This significantly affects how much _cpu_ resources a typical active user needs,
-but often does not significantly affect the _memory_.
-
-Ways to think about this:
-
-- More idle users means unused CPU.
-  This generally means setting your CPU _limit_ higher than your CPU _request_.
-- What do your users do when they _are_ running code?
-  Is it typically single-threaded local computation in a notebook?
-  If so, there's little reason to set a limit higher than 1 CPU core.
-- Do typical computations take a long time, or just a few seconds?
-  Longer typical computations means it's more likely for users to be trying to use the CPU at the same moment,
-  suggesting a higher _request_.
-- Even with idle users, parallel computation adds up quickly - one user fully loading 4 cores and 3 using almost nothing still averages to more than a full CPU core per user.
-- Long-running intense computations suggest higher requests.
-
-Again, using mybinder.org as an example—we run around 100 users on 8-core nodes,
-and still see fairly _low_ overall CPU usage on each user node.
-The limit here is actually Kubernetes' pods per node, not memory _or_ CPU.
-This is likely a extreme case, as many Binder users come from clicking links on webpages
-without any actual intention of running code.
-
-```[figure} ../images/mybinder-load5.png
-mybinder.org node CPU usage is low with 50-150 users sharing just 8 cores
-```
-
-### Concurrent users and culling idle servers
-
-Related to [][idleness], all of these resource consumptions and limits are calculated based on **concurrently active users**,
-not total users.
-You might have 10,000 users of your JupyterHub deployment, but only 100 of them running at any given time.
-That 100 is the main number you need to use for your capacity planning.
-JupyterHub costs scale very little based on the number of _total_ users,
-up to a point.
-
-There are two important definitions for **active user**:
-
-- Are they _actually_ there (i.e. a human interacting with Jupyter, or running code that might be )
-- Is their server running (this is where resource reservations and limits are actually applied)
-
-Connecting those two definitions (how long are servers running if their humans aren't using them) is an important area of deployment configuration, usually implemented via the [JupyterHub idle culler service][idle-culler].
-
-[idle-culler]: https://github.com/jupyterhub/jupyterhub-idle-culler
-
-There are a lot of considerations when it comes to culling idle users that will depend:
-
-- How much does it save me to shut down user servers? (e.g. keeping an elastic cluster small, or keeping a fixed-size deployment available to active users)
-- How much does it cost my users to have their servers shut down? (e.g. lost work if shutdown prematurely)
-- How easy do I want it to be for users to keep their servers running? (e.g. Do they want to run unattended simulations overnight? Do you want them to?)
-
-Like many other things in this guide, there are many correct answers leading to different configuration choices.
-For more detail on culling configuration and considerations, consult the [JupyterHub idle culler documentation][idle-culler].
-
-## More tips
-
-### Start strict and generous, then measure
-
-A good tip, in general, is to give your users as much resources as you can afford that you think they _might_ use.
-Then, use resource usage metrics like prometheus to analyze what your users _actually_ need,
-and tune accordingly.
-Remember: **Limits affect your user experience and stability. Requests mostly affect your costs**.
-
-For example, a sensible starting point (lacking any other information) might be:
-
-```yaml
-request:
-  cpu: 0.5
-  mem: 2G
-limit:
-  cpu: 1
-  mem: 2G
-```
-
-(more memory if significant computations are likely - machine learning models, data analysis, etc.)
-
-Some actions
-
-- If you see out-of-memory killer events, increase the limit (or talk to your users!)
-- If you see typical memory well below your limit, reduce the request (but not the limit)
-- If _nobody_ uses that much memory, reduce your limit
-- If CPU is your limiting scheduling factor and your CPUs are mostly idle,
-  reduce the cpu request (maybe even to 0!).
-- If CPU usage continues to be low, increase the limit to 2 or 4 to allow bursts of parallel execution.
-
-(measuring)=
-
-### Measuring user resource consumption
-
-It is _highly_ recommended to deploy monitoring services such as [Prometheus][]
-and [Grafana][] to get a view of your users' resource usage.
-This is the only way to truly know what your users need.
-
-JupyterHub has some experimental [grafana dashboards][] you can use as a starting point,
-to keep an eye on your resource usage.
-Here are some sample charts from (again from mybinder.org),
-showing >90% of users using less than 10% CPU and 200MB,
-but a few outliers near the limit of 1 CPU and 2GB of RAM.
-This is the kind of information you can use to tune your requests and limits.
-
-![Snapshot from JupyterHub's Grafana dashboards on mybinder.org](../images/mybinder-user-resources.png)
-
-[prometheus]: https://prometheus.io
-[grafana]: https://grafana.com
-[grafana dashboards]: https://github.com/jupyterhub/grafana-dashboards
-
-### Measuring costs
-
-Measuring costs may be as important as measuring your users activity.
-If you are using a cloud provider, you can often use cost thresholds and quotas to instruct them to notify you if your costs are too high,
-e.g. "Have AWS send me an email if I hit X spending trajectory on week 3 of the month."
-You can then use this information to tune your resources based on what you can afford.
-You can mix this information with user resource consumption to figure out if you have a problem,
-e.g. "my users really do need X resources, but I can only afford to give them 80% of X."
-This information may prove useful when asking your budget-approving folks for more funds.
-
-### Additional resources
-
-There are lots of other resources for cost and capacity planning that may be specific to JupyterHub and/or your cloud provider.
-
-Here are some useful links to other resources
-
-- [Zero to JupyterHub](https://zero-to-jupyterhub.readthedocs.io) documentation on
-  - [projecting costs](https://zero-to-jupyterhub.readthedocs.io/en/latest/administrator/cost.html)
-  - [configuring user resources](https://zero-to-jupyterhub.readthedocs.io/en/latest/jupyterhub/customizing/user-resources.html)
-- Cloud platform cost calculators:
-  - [Google Cloud](https://cloud.google.com/products/calculator/)
-  - [Amazon AWS](https://calculator.s3.amazonaws.com)
-  - [Microsoft Azure](https://azure.microsoft.com/en-us/pricing/calculator/)

docs/source/admin/log-messages.md

@@ -1,72 +0,0 @@
-# Interpreting common log messages
-
-When debugging errors and outages, looking at the logs emitted by
-JupyterHub is very helpful. This document intends to describe some common
-log messages, what they mean and what are the most common causes that generated them, as well as some possible ways to fix them.
-
-## Failing suspected API request to not-running server
-
-### Example
-
-Your logs might be littered with lines that look scary
-
-```
-[W 2022-03-10 17:25:19.774 JupyterHub base:1349] Failing suspected API request to not-running server: /hub/user/<user-name>/api/metrics/v1
-```
-
-### Cause
-
-This likely means that the user's server has stopped running but they
-still have a browser tab open. For example, you might have 3 tabs open and you shut
-the server down via one.
-Another possible reason could be that you closed your laptop and the server was culled for inactivity, then reopened the laptop!
-However, the client-side code (JupyterLab, Classic Notebook, etc) doesn't interpret the shut-down server and continues to make some API requests.
-
-JupyterHub's architecture means that the proxy routes all requests that
-don't go to a running user server to the hub process itself. The hub
-process then explicitly returns a failure response, so the client knows
-that the server is not running anymore. This is used by JupyterLab to
-inform the user that the server is not running anymore, and provide an option
-to restart it.
-
-Most commonly, you'll see this in reference to the `/api/metrics/v1`
-URL, used by [jupyter-resource-usage](https://github.com/jupyter-server/jupyter-resource-usage).
-
-### Actions you can take
-
-This log message is benign, and there is usually no action for you to take.
-
-## JupyterHub Singleuser Version mismatch
-
-### Example
-
-```
- jupyterhub version 1.5.0 != jupyterhub-singleuser version 1.3.0. This could cause failure to authenticate and result in redirect loops!
-```
-
-### Cause
-
-JupyterHub requires the `jupyterhub` python package installed inside the image or
-environment, the user server starts in. This message indicates that the version of
-the `jupyterhub` package installed inside the user image or environment is not
-the same as the JupyterHub server's version itself. This is not necessarily always a
-problem - some version drift is mostly acceptable, and the only two known cases of
-breakage are across the 0.7 and 2.0 version releases. In those cases, issues pop
-up immediately after upgrading your version of JupyterHub, so **always check the JupyterHub
-changelog before upgrading!**. The primary problems this _could_ cause are:
-
-1. Infinite redirect loops after the user server starts
-2. Missing expected environment variables in the user server once it starts
-3. Failure for the started user server to authenticate with the JupyterHub server -
-   note that this is _not_ the same as _user authentication_ failing!
-
-However, for the most part, unless you are seeing these specific issues, the log
-message should be counted as a warning to get the `jupyterhub` package versions
-aligned, rather than as an indicator of an existing problem.
-
-### Actions you can take
-
-Upgrade the version of the `jupyterhub` package in your user environment or image
-so that it matches the version of JupyterHub running your JupyterHub server! If you
-are using the [zero-to-jupyterhub](https://z2jh.jupyter.org) helm chart, you can find the appropriate
-version of the `jupyterhub` package to install in your user image [here](https://jupyterhub.github.io/helm-chart/)

docs/source/admin/upgrading.rst

@@ -1,3 +1,5 @@
+.. _admin/upgrading:
+
 ====================
 Upgrading JupyterHub
 ====================
@@ -6,34 +8,34 @@ JupyterHub offers easy upgrade pathways between minor versions. This
 document describes how to do these upgrades.
 
 If you are using :ref:`a JupyterHub distribution <index/distributions>`, you
-should consult the distribution's documentation on how to upgrade. This documentation is 
-for those who have set up their JupyterHub without using a distribution.
+should consult the distribution's documentation on how to upgrade. This
+document is if you have set up your own JupyterHub without using a
+distribution.
 
-This documentation is lengthy because it is quite detailed. Most likely, upgrading
+It is long because is pretty detailed! Most likely, upgrading
 JupyterHub is painless, quick and with minimal user interruption.
 
-The steps are discussed in detail, so if you get stuck at any step you can always refer to this guide. 
-
 Read the Changelog
 ==================
 
-The `changelog <../changelog.md>`_ contains information on what has
-changed with the new JupyterHub release and any deprecation warnings.
+The `changelog <../changelog.html>`_ contains information on what has
+changed with the new JupyterHub release, and any deprecation warnings.
 Read these notes to familiarize yourself with the coming changes. There
-might be new releases of the authenticators & spawners you use, so
+might be new releases of authenticators & spawners you are using, so
 read the changelogs for those too!
 
 Notify your users
 =================
 
-If you use the default configuration where ``configurable-http-proxy``
+If you are using the default configuration where ``configurable-http-proxy``
 is managed by JupyterHub, your users will see service disruption during
 the upgrade process. You should notify them, and pick a time to do the
 upgrade where they will be least disrupted.
 
-If you use a different proxy or run ``configurable-http-proxy``
+If you are using a different proxy, or running ``configurable-http-proxy``
 independent of JupyterHub, your users will be able to continue using notebook
-servers they had already launched, but will not be able to launch new servers or sign in.
+servers they had already launched, but will not be able to launch new servers
+nor sign in.
 
 
 Backup database & config
@@ -41,37 +43,37 @@ Backup database & config
 
 Before doing an upgrade, it is critical to back up:
 
-#. Your JupyterHub database (SQLite by default, or MySQL / Postgres if you used those). 
-   If you use SQLite (the default), you should backup the ``jupyterhub.sqlite`` file.
-
+#. Your JupyterHub database (sqlite by default, or MySQL / Postgres
+   if you used those). If you are using sqlite (the default), you
+   should backup the ``jupyterhub.sqlite`` file.
 #. Your ``jupyterhub_config.py`` file.
-
-#. Your users' home directories. This is unlikely to be affected directly by
-   a JupyterHub upgrade, but we recommend a backup since user data is critical.
+#. Your user's home directories. This is unlikely to be affected directly by
+   a JupyterHub upgrade, but we recommend a backup since user data is very
+   critical.
 
 
-Shut down JupyterHub
-====================
+Shutdown JupyterHub
+===================
 
-Shut down the JupyterHub process. This would vary depending on how you
-have set up JupyterHub to run. It is most likely using a process
+Shutdown the JupyterHub process. This would vary depending on how you
+have set up JupyterHub to run. Most likely, it is using a process
 supervisor of some sort (``systemd`` or ``supervisord`` or even ``docker``).
-Use the supervisor-specific command to stop the JupyterHub process.
+Use the supervisor specific command to stop the JupyterHub process.
 
 Upgrade JupyterHub packages
 ===========================
 
 There are two environments where the ``jupyterhub`` package is installed:
 
-#. The *hub environment*: where the JupyterHub server process
+#. The *hub environment*, which is where the JupyterHub server process
    runs. This is started with the ``jupyterhub`` command, and is what
    people generally think of as JupyterHub.
 
-#. The *notebook user environments*: where the user notebook
+#. The *notebook user environments*. This is where the user notebook
    servers are launched from, and is probably custom to your own
    installation. This could be just one environment (different from the
    hub environment) that is shared by all users, one environment
-   per user, or the same environment as the hub environment. The hub
+   per user, or same environment as the hub environment. The hub
    launched the ``jupyterhub-singleuser`` command in this environment,
    which in turn starts the notebook server.
 
@@ -92,8 +94,10 @@ with:
 
    conda install -c conda-forge jupyterhub==<version>
 
+Where ``<version>`` is the version of JupyterHub you are upgrading to.
+
 You should also check for new releases of the authenticator & spawner you
-are using. You might wish to upgrade those packages, too, along with JupyterHub
+are using. You might wish to upgrade those packages too along with JupyterHub,
 or upgrade them separately.
 
 Upgrade JupyterHub database
@@ -107,7 +111,7 @@ database. From the hub environment, in the same directory as your
 
    jupyterhub upgrade-db
 
-This should find the location of your database, and run the necessary upgrades
+This should find the location of your database, and run necessary upgrades
 for it.
 
 SQLite database disadvantages
@@ -116,11 +120,11 @@ SQLite database disadvantages
 SQLite has some disadvantages when it comes to upgrading JupyterHub. These
 are:
 
--  ``upgrade-db`` may not work, and you may need to delete your database
+-  ``upgrade-db`` may not work, and you may need delete your database
    and start with a fresh one.
 -  ``downgrade-db`` **will not** work if you want to rollback to an
    earlier version, so backup the ``jupyterhub.sqlite`` file before
-   upgrading.
+   upgrading
 
 What happens if I delete my database?
 -------------------------------------
@@ -135,10 +139,10 @@ resides only in the Hub database includes:
 If the following conditions are true, you should be fine clearing the
 Hub database and starting over:
 
--  users specified in the config file, or login using an external
+-  users specified in config file, or login using an external
    authentication provider (Google, GitHub, LDAP, etc)
--  user servers are stopped during the upgrade
--  don't mind causing users to log in again after the upgrade
+-  user servers are stopped during upgrade
+-  don't mind causing users to login again after upgrade
 
 Start JupyterHub
 ================
@@ -146,7 +150,7 @@ Start JupyterHub
 Once the database upgrade is completed, start the ``jupyterhub``
 process again.
 
-#. Log in and start the server to make sure things work as
+#. Log-in and start the server to make sure things work as
    expected.
 #. Check the logs for any errors or deprecation warnings. You
    might have to update your ``jupyterhub_config.py`` file to

docs/source/api/index.rst

@@ -17,6 +17,11 @@ information on:
 - making an API request programmatically using the requests library
 - learning more about JupyterHub's API
 
+The same JupyterHub API spec, as found here, is available in an interactive form
+`here (on swagger's petstore) <http://petstore.swagger.io/?url=https://raw.githubusercontent.com/jupyterhub/jupyterhub/master/docs/rest-api.yml#!/default>`__.
+The `OpenAPI Initiative`_ (fka Swagger™) is a project used to describe
+and document RESTful APIs.
+
 JupyterHub API Reference:
 
 .. toctree::

docs/source/conf.py

@@ -1,70 +1,71 @@
-# Configuration file for Sphinx to build our documentation to HTML.
+# -*- coding: utf-8 -*-
 #
-# Configuration reference: https://www.sphinx-doc.org/en/master/usage/configuration.html
-#
-import contextlib
-import datetime
-import io
 import os
-import subprocess
+import sys
 
-from docutils import nodes
-from sphinx.directives.other import SphinxDirective
+# Set paths
+sys.path.insert(0, os.path.abspath('.'))
+
+# -- General configuration ------------------------------------------------
+
+# Minimal Sphinx version
+needs_sphinx = '1.4'
+
+# Sphinx extension modules
+extensions = [
+    'sphinx.ext.autodoc',
+    'sphinx.ext.intersphinx',
+    'sphinx.ext.napoleon',
+    'autodoc_traits',
+    'sphinx_copybutton',
+    'sphinx-jsonschema',
+    'recommonmark',
+]
+
+# The master toctree document.
+master_doc = 'index'
+
+# General information about the project.
+project = u'JupyterHub'
+copyright = u'2016, Project Jupyter team'
+author = u'Project Jupyter team'
+
+# Autopopulate version
+from os.path import dirname
+
+docs = dirname(dirname(__file__))
+root = dirname(docs)
+sys.path.insert(0, root)
 
 import jupyterhub
-from jupyterhub.app import JupyterHub
 
-# -- Project information -----------------------------------------------------
-# ref: https://www.sphinx-doc.org/en/master/usage/configuration.html#project-information
-#
-project = "JupyterHub"
-author = "Project Jupyter Contributors"
-copyright = f"{datetime.date.today().year}, {author}"
-version = "%i.%i" % jupyterhub.version_info[:2]
+# The short X.Y version.
+version = '%i.%i' % jupyterhub.version_info[:2]
+# The full version, including alpha/beta/rc tags.
 release = jupyterhub.__version__
 
+language = None
+exclude_patterns = []
+pygments_style = 'sphinx'
+todo_include_todos = False
 
-# -- General Sphinx configuration --------------------------------------------
-# ref: https://www.sphinx-doc.org/en/master/usage/configuration.html#general-configuration
-#
-extensions = [
-    "sphinx.ext.autodoc",
-    "sphinx.ext.intersphinx",
-    "sphinx.ext.napoleon",
-    "autodoc_traits",
-    "sphinx_copybutton",
-    "sphinx-jsonschema",
-    "sphinxext.opengraph",
-    "sphinxext.rediraffe",
-    "myst_parser",
-]
-root_doc = "index"
-source_suffix = [".md", ".rst"]
-# default_role let's use use `foo` instead of ``foo`` in rST
-default_role = "literal"
+# Set the default role so we can use `foo` instead of ``foo``
+default_role = 'literal'
 
+# -- Source -------------------------------------------------------------
 
-# -- MyST configuration ------------------------------------------------------
-# ref: https://myst-parser.readthedocs.io/en/latest/configuration.html
-#
-myst_heading_anchors = 2
-myst_enable_extensions = [
-    "colon_fence",
-    "deflist",
-]
+import recommonmark
+from recommonmark.transform import AutoStructify
 
+# -- Config -------------------------------------------------------------
+from jupyterhub.app import JupyterHub
+from docutils import nodes
+from sphinx.directives.other import SphinxDirective
+from contextlib import redirect_stdout
+from io import StringIO
 
-# -- Custom directives to generate documentation -----------------------------
-# ref: https://myst-parser.readthedocs.io/en/latest/syntax/roles-and-directives.html
-#
-# We define custom directives to help us generate documentation using Python on
-# demand when referenced from our documentation files.
-#
-
-# Create a temp instance of JupyterHub for use by two separate directive classes
-# to get the output from using the "--generate-config" and "--help-all" CLI
-# flags respectively.
-#
+# create a temp instance of JupyterHub just to get the output of the generate-config
+# and help --all commands.
 jupyterhub_app = JupyterHub()
 
 
@@ -81,8 +82,8 @@ class ConfigDirective(SphinxDirective):
         # The generated configuration file for this version
         generated_config = jupyterhub_app.generate_config_file()
         # post-process output
-        home_dir = os.environ["HOME"]
-        generated_config = generated_config.replace(home_dir, "$HOME", 1)
+        home_dir = os.environ['HOME']
+        generated_config = generated_config.replace(home_dir, '$HOME', 1)
         par = nodes.literal_block(text=generated_config)
         return [par]
 
@@ -98,118 +99,135 @@ class HelpAllDirective(SphinxDirective):
 
     def run(self):
         # The output of the help command for this version
-        buffer = io.StringIO()
-        with contextlib.redirect_stdout(buffer):
-            jupyterhub_app.print_help("--help-all")
+        buffer = StringIO()
+        with redirect_stdout(buffer):
+            jupyterhub_app.print_help('--help-all')
         all_help = buffer.getvalue()
         # post-process output
-        home_dir = os.environ["HOME"]
-        all_help = all_help.replace(home_dir, "$HOME", 1)
+        home_dir = os.environ['HOME']
+        all_help = all_help.replace(home_dir, '$HOME', 1)
         par = nodes.literal_block(text=all_help)
         return [par]
 
 
 def setup(app):
-    app.add_css_file("custom.css")
-    app.add_directive("jupyterhub-generate-config", ConfigDirective)
-    app.add_directive("jupyterhub-help-all", HelpAllDirective)
+    app.add_config_value('recommonmark_config', {'enable_eval_rst': True}, True)
+    app.add_css_file('custom.css')
+    app.add_transform(AutoStructify)
+    app.add_directive('jupyterhub-generate-config', ConfigDirective)
+    app.add_directive('jupyterhub-help-all', HelpAllDirective)
 
 
-# -- Read The Docs -----------------------------------------------------------
-#
-# Since RTD runs sphinx-build directly without running "make html", we run the
-# pre-requisite steps for "make html" from here if needed.
-#
-if os.environ.get("READTHEDOCS"):
-    docs = os.path.dirname(os.path.dirname(__file__))
-    subprocess.check_call(["make", "metrics", "scopes"], cwd=docs)
+source_suffix = ['.rst', '.md']
+# source_encoding = 'utf-8-sig'
+
+# -- Options for HTML output ----------------------------------------------
+
+# The theme to use for HTML and HTML Help pages.
+html_theme = 'pydata_sphinx_theme'
+
+html_logo = '_static/images/logo/logo.png'
+html_favicon = '_static/images/logo/favicon.ico'
+
+# Paths that contain custom static files (such as style sheets)
+html_static_path = ['_static']
+
+htmlhelp_basename = 'JupyterHubdoc'
+
+# -- Options for LaTeX output ---------------------------------------------
+
+latex_elements = {
+    # 'papersize': 'letterpaper',
+    # 'pointsize': '10pt',
+    # 'preamble': '',
+    # 'figure_align': 'htbp',
+}
+
+# Grouping the document tree into LaTeX files. List of tuples
+# (source start file, target name, title,
+#  author, documentclass [howto, manual, or own class]).
+latex_documents = [
+    (
+        master_doc,
+        'JupyterHub.tex',
+        u'JupyterHub Documentation',
+        u'Project Jupyter team',
+        'manual',
+    )
+]
+
+# latex_logo = None
+# latex_use_parts = False
+# latex_show_pagerefs = False
+# latex_show_urls = False
+# latex_appendices = []
+# latex_domain_indices = True
 
 
-# -- Spell checking ----------------------------------------------------------
-# ref: https://sphinxcontrib-spelling.readthedocs.io/en/latest/customize.html#configuration-options
-#
-# The "sphinxcontrib.spelling" extension is optionally enabled if its available.
-#
+# -- manual page output -------------------------------------------------
+
+# One entry per manual page. List of tuples
+# (source start file, name, description, authors, manual section).
+man_pages = [(master_doc, 'jupyterhub', u'JupyterHub Documentation', [author], 1)]
+
+# man_show_urls = False
+
+
+# -- Texinfo output -----------------------------------------------------
+
+# Grouping the document tree into Texinfo files. List of tuples
+# (source start file, target name, title, author,
+#  dir menu entry, description, category)
+texinfo_documents = [
+    (
+        master_doc,
+        'JupyterHub',
+        u'JupyterHub Documentation',
+        author,
+        'JupyterHub',
+        'One line description of project.',
+        'Miscellaneous',
+    )
+]
+
+# texinfo_appendices = []
+# texinfo_domain_indices = True
+# texinfo_show_urls = 'footnote'
+# texinfo_no_detailmenu = False
+
+
+# -- Epub output --------------------------------------------------------
+
+# Bibliographic Dublin Core info.
+epub_title = project
+epub_author = author
+epub_publisher = author
+epub_copyright = copyright
+
+# A list of files that should not be packed into the epub file.
+epub_exclude_files = ['search.html']
+
+# -- Intersphinx ----------------------------------------------------------
+
+intersphinx_mapping = {'https://docs.python.org/3/': None}
+
+# -- Read The Docs --------------------------------------------------------
+
+on_rtd = os.environ.get('READTHEDOCS', None) == 'True'
+if on_rtd:
+    # readthedocs.org uses their theme by default, so no need to specify it
+    # build both metrics and rest-api, since RTD doesn't run make
+    from subprocess import check_call as sh
+
+    sh(['make', 'metrics', 'rest-api'], cwd=docs)
+
+# -- Spell checking -------------------------------------------------------
+
 try:
-    import sphinxcontrib.spelling  # noqa
+    import sphinxcontrib.spelling
 except ImportError:
     pass
 else:
     extensions.append("sphinxcontrib.spelling")
-spelling_word_list_filename = "spelling_wordlist.txt"
 
-
-# -- Options for HTML output -------------------------------------------------
-# ref: https://www.sphinx-doc.org/en/master/usage/configuration.html#options-for-html-output
-#
-html_logo = "_static/images/logo/logo.png"
-html_favicon = "_static/images/logo/favicon.ico"
-html_static_path = ["_static"]
-
-html_theme = "pydata_sphinx_theme"
-html_theme_options = {
-    "icon_links": [
-        {
-            "name": "GitHub",
-            "url": "https://github.com/jupyterhub/jupyterhub",
-            "icon": "fab fa-github-square",
-        },
-        {
-            "name": "Discourse",
-            "url": "https://discourse.jupyter.org/c/jupyterhub/10",
-            "icon": "fab fa-discourse",
-        },
-    ],
-    "use_edit_page_button": True,
-    "navbar_align": "left",
-}
-html_context = {
-    "github_user": "jupyterhub",
-    "github_repo": "jupyterhub",
-    "github_version": "main",
-    "doc_path": "docs/source",
-}
-
-
-# -- Options for linkcheck builder -------------------------------------------
-# ref: https://www.sphinx-doc.org/en/master/usage/configuration.html#options-for-the-linkcheck-builder
-#
-linkcheck_ignore = [
-    r"(.*)github\.com(.*)#",  # javascript based anchors
-    r"(.*)/#%21(.*)/(.*)",  # /#!forum/jupyter - encoded anchor edge case
-    r"https://github.com/[^/]*$",  # too many github usernames / searches in changelog
-    "https://github.com/jupyterhub/jupyterhub/pull/",  # too many PRs in changelog
-    "https://github.com/jupyterhub/jupyterhub/compare/",  # too many comparisons in changelog
-]
-linkcheck_anchors_ignore = [
-    "/#!",
-    "/#%21",
-]
-
-
-# -- Intersphinx -------------------------------------------------------------
-# ref: https://www.sphinx-doc.org/en/master/usage/extensions/intersphinx.html#configuration
-#
-intersphinx_mapping = {
-    "python": ("https://docs.python.org/3/", None),
-    "tornado": ("https://www.tornadoweb.org/en/stable/", None),
-}
-# -- Options for the opengraph extension -------------------------------------
-# ref: https://github.com/wpilibsuite/sphinxext-opengraph#options
-#
-# ogp_site_url is set automatically by RTD
-ogp_image = "_static/logo.png"
-ogp_use_first_image = True
-
-
-# -- Options for the rediraffe extension -------------------------------------
-# ref: https://github.com/wpilibsuite/sphinxext-rediraffe#readme
-#
-# This extensions help us relocated content without breaking links. If a
-# document is moved internally, a redirect like should be configured below to
-# help us not break links.
-#
-rediraffe_branch = "main"
-rediraffe_redirects = {
-    # "old-file": "new-folder/new-file-name",
-}
+spelling_word_list_filename = 'spelling_wordlist.txt'

docs/source/contributing/community.md

@@ -1,27 +0,0 @@
-# Community communication channels
-
-We use different channels of communication for different purposes. Whichever one you use will depend on what kind of communication you want to engage in.
-
-## Discourse (recommended)
-
-We use [Discourse](https://discourse.jupyter.org) for online discussions and support questions.
-You can ask questions here if you are a first-time contributor to the JupyterHub project.
-Everyone in the Jupyter community is welcome to bring ideas and questions there.
-
-We recommend that you first use our Discourse as all past and current discussions on it are archived and searchable. Thus, all discussions remain useful and accessible to the whole community.
-
-## Gitter
-
-We use [our Gitter channel](https://gitter.im/jupyterhub/jupyterhub) for online, real-time text chat; a place for more ephemeral discussions. When you're not on Discourse, you can stop here to have other discussions on the fly.
-
-## Github Issues
-
-[Github issues](https://docs.github.com/en/issues/tracking-your-work-with-issues/about-issues) are used for most long-form project discussions, bug reports and feature requests.
-
-- Issues related to a specific authenticator or spawner should be opened in the appropriate repository for the authenticator or spawner.
-- If you are using a specific JupyterHub distribution (such as [Zero to JupyterHub on Kubernetes](http://github.com/jupyterhub/zero-to-jupyterhub-k8s) or [The Littlest JupyterHub](http://github.com/jupyterhub/the-littlest-jupyterhub/)), you should open issues directly in their repository.
-- If you cannot find a repository to open your issue in, do not worry! Open the issue in the [main JupyterHub repository](https://github.com/jupyterhub/jupyterhub/) and our community will help you figure it out.
-
-```{note}
-Our community is distributed across the world in various timezones, so please be patient if you do not get a response immediately!
-```

docs/source/contributing/community.rst

@@ -0,0 +1,30 @@
+.. _contributing/community:
+
+================================
+Community communication channels
+================================
+
+We use `Discourse <https://discourse.jupyter.org>` for online discussion.
+Everyone in the Jupyter community is welcome to bring ideas and questions there.
+In addition, we use `Gitter <https://gitter.im>`_ for online, real-time text chat,
+a place for more ephemeral discussions.
+The primary Gitter channel for JupyterHub is `jupyterhub/jupyterhub <https://gitter.im/jupyterhub/jupyterhub>`_.
+Gitter isn't archived or searchable, so we recommend going to discourse first
+to make sure that discussions are most useful and accessible to the community.
+Remember that our community is distributed across the world in various
+timezones, so be patient if you do not get an answer immediately!
+
+GitHub issues are used for most long-form project discussions, bug reports
+and feature requests. Issues related to a specific authenticator or
+spawner should be directed to the appropriate repository for the
+authenticator or spawner. If you are using a specific JupyterHub
+distribution (such as `Zero to JupyterHub on Kubernetes <http://github.com/jupyterhub/zero-to-jupyterhub-k8s>`_
+or `The Littlest JupyterHub <http://github.com/jupyterhub/the-littlest-jupyterhub/>`_),
+you should open issues directly in their repository. If you can not
+find a repository to open your issue in, do not worry! Create it in the `main
+JupyterHub repository <https://github.com/jupyterhub/jupyterhub/>`_ and our
+community will help you figure it out.
+
+A `mailing list <https://groups.google.com/forum/#!forum/jupyter>`_ for all
+of Project Jupyter exists, along with one for `teaching with Jupyter
+<https://groups.google.com/forum/#!forum/jupyter-education>`_. 

docs/source/contributing/docs.rst

@@ -5,7 +5,7 @@ Contributing Documentation
 ==========================
 
 Documentation is often more important than code. This page helps
-you get set up on how to contribute to JupyterHub's documentation.
+you get set up on how to contribute documentation to JupyterHub.
 
 Building documentation locally
 ==============================
@@ -13,12 +13,12 @@ Building documentation locally
 We use `sphinx <http://sphinx-doc.org>`_ to build our documentation. It takes
 our documentation source files (written in `markdown
 <https://daringfireball.net/projects/markdown/>`_ or `reStructuredText
-<https://www.sphinx-doc.org/en/master/usage/restructuredtext/basics.html>`_ &
+<http://www.sphinx-doc.org/en/master/usage/restructuredtext/basics.html>`_ &
 stored under the ``docs/source`` directory) and converts it into various
 formats for people to read. To make sure the documentation you write or
 change renders correctly, it is good practice to test it locally.
 
-#. Make sure you have successfully completed :ref:`contributing/setup`.
+#. Make sure you have successfuly completed :ref:`contributing/setup`.
 
 #. Install the packages required to build the docs.
 
@@ -27,7 +27,7 @@ change renders correctly, it is good practice to test it locally.
       python3 -m pip install -r docs/requirements.txt
 
 #. Build the html version of the docs. This is the most commonly used
-   output format, so verifying it renders correctly is usually good
+   output format, so verifying it renders as you should is usually good
    enough.
 
    .. code-block:: bash
@@ -44,14 +44,8 @@ change renders correctly, it is good practice to test it locally.
 
    .. tip::
 
-      **On Windows**, you can open a file from the terminal with ``start <path-to-file>``.
-      
-      **On macOS**, you can do the same with ``open <path-to-file>``.
-      
-      **On Linux**, you can do the same with ``xdg-open <path-to-file>``.
-
-      After opening index.html in your browser you can just refresh the page whenever
-      you rebuild the docs via ``make html``
+      On macOS, you can open a file from the terminal with ``open <path-to-file>``.
+      On Linux, you can do the same with ``xdg-open <path-to-file>``.
 
 
 .. _contributing/docs/conventions:

docs/source/contributing/index.rst

@@ -6,8 +6,8 @@ We want you to contribute to JupyterHub in ways that are most exciting
 & useful to you. We value documentation, testing, bug reporting & code equally,
 and are glad to have your contributions in whatever form you wish :)
 
-Our `Code of Conduct <https://github.com/jupyter/governance/blob/HEAD/conduct/code_of_conduct.md>`_
-(`reporting guidelines <https://github.com/jupyter/governance/blob/HEAD/conduct/reporting_online.md>`_)
+Our `Code of Conduct <https://github.com/jupyter/governance/blob/master/conduct/code_of_conduct.md>`_
+(`reporting guidelines <https://github.com/jupyter/governance/blob/master/conduct/reporting_online.md>`_)
 helps keep our community welcoming to as many people as possible.
 
 .. toctree::

docs/source/contributing/roadmap.md

@@ -4,10 +4,10 @@ This roadmap collects "next steps" for JupyterHub. It is about creating a
 shared understanding of the project's vision and direction amongst
 the community of users, contributors, and maintainers.
 The goal is to communicate priorities and upcoming release plans.
-It is not aimed at limiting contributions to what is listed here.
+It is not a aimed at limiting contributions to what is listed here.
+
 
 ## Using the roadmap
-
 ### Sharing Feedback on the Roadmap
 
 All of the community is encouraged to provide feedback as well as share new
@@ -22,17 +22,17 @@ maintainers will help identify what a good next step is for the issue.
 When submitting an issue, think about what "next step" category best describes
 your issue:
 
-- **now**, concrete/actionable step that is ready for someone to start work on.
-  These might be items that have a link to an issue or more abstract like
-  "decrease typos and dead links in the documentation"
-- **soon**, less concrete/actionable step that is going to happen soon,
-  discussions around the topic are coming close to an end at which point it can
-  move into the "now" category
-- **later**, abstract ideas or tasks, need a lot of discussion or
-  experimentation to shape the idea so that it can be executed. Can also
-  contain concrete/actionable steps that have been postponed on purpose
-  (these are steps that could be in "now" but the decision was taken to work on
-  them later)
+* **now**, concrete/actionable step that is ready for someone to start work on.
+These might be items that have a link to an issue or more abstract like
+"decrease typos and dead links in the documentation"
+* **soon**, less concrete/actionable step that is going to happen soon,
+discussions around the topic are coming close to an end at which point it can
+move into the "now" category
+* **later**, abstract ideas or tasks, need a lot of discussion or
+experimentation to shape the idea so that it can be executed. Can also
+contain concrete/actionable steps that have been postponed on purpose
+(these are steps that could be in "now" but the decision was taken to work on
+them later)
 
 ### Reviewing and Updating the Roadmap
 
@@ -47,8 +47,8 @@ For those please create a
 The roadmap should give the reader an idea of what is happening next, what needs
 input and discussion before it can happen and what has been postponed.
 
-## The roadmap proper
 
+## The roadmap proper
 ### Project vision
 
 JupyterHub is a dependable tool used by humans that reduces the complexity of
@@ -58,19 +58,20 @@ creating the environment in which a piece of software can be executed.
 
 These "Now" items are considered active areas of focus for the project:
 
-- HubShare - a sharing service for use with JupyterHub.
-  - Users should be able to:
-    - Push a project to other users.
-    - Get a checkout of a project from other users.
-    - Push updates to a published project.
-    - Pull updates from a published project.
-    - Manage conflicts/merges by simply picking a version (our/theirs)
-    - Get a checkout of a project from the internet. These steps are completely different from saving notebooks/files.
-    - Have directories that are managed by git completely separately from our stuff.
-    - Look at pushed content that they have access to without an explicit pull.
-    - Define and manage teams of users.
-      - Adding/removing a user to/from a team gives/removes them access to all projects that team has access to.
-    - Build other services, such as static HTML publishing and dashboarding on top of these things.
+* HubShare - a sharing service for use with JupyterHub.
+    * Users should be able to:
+        - Push a project to other users.
+        - Get a checkout of a project from other users.
+        - Push updates to a published project.
+        - Pull updates from a published project.
+        - Manage conflicts/merges by simply picking a version (our/theirs)
+        - Get a checkout of a project from the internet. These steps are completely different from saving notebooks/files.
+        - Have directories that are managed by git completely separately from our stuff.
+        - Look at pushed content that they have access to without an explicit pull.
+        - Define and manage teams of users.
+            - Adding/removing a user to/from a team gives/removes them access to all projects that team has access to.
+        - Build other services, such as static HTML publishing and dashboarding on top of these things.
+
 
 ### Soon
 
@@ -78,10 +79,11 @@ These "Soon" items are under discussion. Once an item reaches the point of an
 actionable plan, the item will be moved to the "Now" section. Typically,
 these will be moved at a future review of the roadmap.
 
-- resource monitoring and management:
-  - (prometheus?) API for resource monitoring
-  - tracking activity on single-user servers instead of the proxy
-  - notes and activity tracking per API token
+* resource monitoring and management:
+    - (prometheus?) API for resource monitoring
+    - tracking activity on single-user servers instead of the proxy
+    - notes and activity tracking per API token
+
 
 ### Later
 
@@ -90,6 +92,6 @@ time there is no active plan for an item. The project would like to find the
 resources and time to discuss these ideas.
 
 - real-time collaboration
-  - Enter into real-time collaboration mode for a project that starts a shared execution context.
-  - Once the single-user notebook package supports realtime collaboration,
-    implement sharing mechanism integrated into the Hub.
+    - Enter into real-time collaboration mode for a project that starts a shared execution context.
+    - Once the single-user notebook package supports realtime collaboration,
+      implement sharing mechanism integrated into the Hub.

docs/source/contributing/setup.rst

@@ -7,7 +7,7 @@ Setting up a development install
 System requirements
 ===================
 
-JupyterHub can only run on macOS or Linux operating systems. If you are
+JupyterHub can only run on MacOS or Linux operating systems. If you are
 using Windows, we recommend using `VirtualBox <https://virtualbox.org>`_
 or a similar system to run `Ubuntu Linux <https://ubuntu.com>`_ for
 development.
@@ -15,27 +15,25 @@ development.
 Install Python
 --------------
 
-JupyterHub is written in the `Python <https://python.org>`_ programming language and
-requires you have at least version 3.6 installed locally. If you haven’t
+JupyterHub is written in the `Python <https://python.org>`_ programming language, and
+requires you have at least version 3.5 installed locally. If you haven’t
 installed Python before, the recommended way to install it is to use
-`Miniconda <https://conda.io/miniconda.html>`_. Remember to get the ‘Python 3’ version,
+`miniconda <https://conda.io/miniconda.html>`_. Remember to get the ‘Python 3’ version,
 and **not** the ‘Python 2’ version!
 
 Install nodejs
 --------------
 
-`NodeJS 12+ <https://nodejs.org/en/>`_ is required for building some JavaScript components.
-``configurable-http-proxy``, the default proxy implementation for JupyterHub, is written in Javascript.
-If you have not installed NodeJS before, we recommend installing it in the ``miniconda`` environment you set up for Python.
-You can do so with ``conda install nodejs``.
-
-Many in the Jupyter community use [``nvm``](https://github.com/nvm-sh/nvm) to
-managing node dependencies.
+``configurable-http-proxy``, the default proxy implementation for
+JupyterHub, is written in Javascript to run on `NodeJS
+<https://nodejs.org/en/>`_. If you have not installed nodejs before, we
+recommend installing it in the ``miniconda`` environment you set up for
+Python. You can do so with ``conda install nodejs``.
 
 Install git
 -----------
 
-JupyterHub uses `Git <https://git-scm.com>`_ & `GitHub <https://github.com>`_
+JupyterHub uses `git <https://git-scm.com>`_ & `GitHub <https://github.com>`_
 for development & collaboration. You need to `install git
 <https://git-scm.com/book/en/v2/Getting-Started-Installing-Git>`_ to work on
 JupyterHub. We also recommend getting a free account on GitHub.com.
@@ -43,11 +41,13 @@ JupyterHub. We also recommend getting a free account on GitHub.com.
 Setting up a development install
 ================================
 
-When developing JupyterHub, you would need to make changes and be able to instantly view the results of the changes. To achieve that, a developer install is required.
+When developing JupyterHub, you need to make changes to the code & see
+their effects quickly. You need to do a developer install to make that
+happen.
 
 .. note:: This guide does not attempt to dictate *how* development
-   environments should be isolated since that is a personal preference and can
-   be achieved in many ways, for example, `tox`, `conda`, `docker`, etc. See this
+   environements should be isolated since that is a personal preference and can
+   be achieved in many ways, for example `tox`, `conda`, `docker`, etc. See this
    `forum thread <https://discourse.jupyter.org/t/thoughts-on-using-tox/3497>`_ for
    a more detailed discussion.
 
@@ -66,7 +66,7 @@ When developing JupyterHub, you would need to make changes and be able to instan
 
       python -V
 
-   This should return a version number greater than or equal to 3.6.
+   This should return a version number greater than or equal to 3.5.
 
    .. code:: bash
 
@@ -74,51 +74,53 @@ When developing JupyterHub, you would need to make changes and be able to instan
 
    This should return a version number greater than or equal to 5.0.
 
-3. Install ``configurable-http-proxy`` (required to run and test the default JupyterHub configuration) and ``yarn`` (required to build some components):
+3. Install ``configurable-http-proxy``. This is required to run
+   JupyterHub.
 
    .. code:: bash
 
-      npm install -g configurable-http-proxy yarn
+      npm install -g configurable-http-proxy
 
-   If you get an error that says ``Error: EACCES: permission denied``, you might need to prefix the command with ``sudo``.
-   ``sudo`` may be required to perform a system-wide install.
-   If you do not have access to sudo, you may instead run the following commands:
+   If you get an error that says ``Error: EACCES: permission denied``,
+   you might need to prefix the command with ``sudo``. If you do not
+   have access to sudo, you may instead run the following commands:
 
    .. code:: bash
 
-      npm install configurable-http-proxy yarn
+      npm install configurable-http-proxy
       export PATH=$PATH:$(pwd)/node_modules/.bin
 
    The second line needs to be run every time you open a new terminal.
 
-   If you are using conda you can instead run:
+4. Install the python packages required for JupyterHub development.
 
    .. code:: bash
 
-      conda install configurable-http-proxy yarn
+      python3 -m pip install -r dev-requirements.txt
+      python3 -m pip install -r requirements.txt
 
-4. Install an editable version of JupyterHub and its requirements for
-   development and testing. This lets you edit JupyterHub code in a text editor
-   & restart the JupyterHub process to see your code changes immediately.
-
-   .. code:: bash
-
-      python3 -m pip install --editable ".[test]"
-
-5. Set up a database.
+5. Setup a database.
 
    The default database engine is ``sqlite`` so if you are just trying
    to get up and running quickly for local development that should be
-   available via `Python <https://docs.python.org/3.5/library/sqlite3.html>`__.
+   available via `python <https://docs.python.org/3.5/library/sqlite3.html>`__.
    See :doc:`/reference/database` for details on other supported databases.
 
-6. You are now ready to start JupyterHub!
+6. Install the development version of JupyterHub. This lets you edit
+   JupyterHub code in a text editor & restart the JupyterHub process to
+   see your code changes immediately.
+
+   .. code:: bash
+
+      python3 -m pip install --editable .
+
+7. You are now ready to start JupyterHub!
 
    .. code:: bash
 
       jupyterhub
 
-7. You can access JupyterHub from your browser at
+8. You can access JupyterHub from your browser at
    ``http://localhost:8000`` now.
 
 Happy developing!
@@ -126,12 +128,12 @@ Happy developing!
 Using DummyAuthenticator & SimpleLocalProcessSpawner
 ====================================================
 
-To simplify testing of JupyterHub, it is helpful to use
+To simplify testing of JupyterHub, it’s helpful to use
 :class:`~jupyterhub.auth.DummyAuthenticator` instead of the default JupyterHub
 authenticator and SimpleLocalProcessSpawner instead of the default spawner.
 
 There is a sample configuration file that does this in
-``testing/jupyterhub_config.py``. To launch JupyterHub with this
+``testing/jupyterhub_config.py``. To launch jupyterhub with this
 configuration:
 
 .. code:: bash
@@ -147,14 +149,14 @@ JupyterHub as.
 
 DummyAuthenticator allows you to log in with any username & password,
 while SimpleLocalProcessSpawner allows you to start servers without having to
-create a Unix user for each JupyterHub user. Together, these make it
+create a unix user for each JupyterHub user. Together, these make it
 much easier to test JupyterHub.
 
 Tip: If you are working on parts of JupyterHub that are common to all
 authenticators & spawners, we recommend using both DummyAuthenticator &
-SimpleLocalProcessSpawner. If you are working on just authenticator-related
+SimpleLocalProcessSpawner. If you are working on just authenticator related
 parts, use only SimpleLocalProcessSpawner. Similarly, if you are working on
-just spawner-related parts, use only DummyAuthenticator.
+just spawner related parts, use only DummyAuthenticator.
 
 Troubleshooting
 ===============
@@ -184,4 +186,3 @@ development updates, with:
 
    python3 setup.py js    # fetch updated client-side js
    python3 setup.py css   # recompile CSS from LESS sources
-   python3 setup.py jsx   # build React admin app

docs/source/contributing/tests.rst

@@ -1,22 +1,23 @@
 .. _contributing/tests:
 
-===================================
-Testing JupyterHub and linting code
-===================================
+==================
+Testing JupyterHub
+==================
 
-Unit testing helps to validate that JupyterHub works the way we think it does,
+Unit test help validate that JupyterHub works the way we think it does,
 and continues to do so when changes occur. They also help communicate
 precisely what we expect our code to do. 
 
-JupyterHub uses `pytest <https://pytest.org>`_ for all the tests. You
-can find them under the `jupyterhub/tests <https://github.com/jupyterhub/jupyterhub/tree/main/jupyterhub/tests>`_ directory in the git repository.
+JupyterHub uses `pytest <https://pytest.org>`_ for all our tests. You
+can find them under ``jupyterhub/tests`` directory in the git repository.
 
 Running the tests
 ==================
 
-#. Make sure you have completed :ref:`contributing/setup`.
-   Once you are done, you would be able to run ``jupyterhub`` from the command line and access it from your web browser.
-   This ensures that the dev environment is properly set up for tests to run.
+#. Make sure you have completed :ref:`contributing/setup`. You should be able
+   to start ``jupyterhub`` from the commandline & access it from your
+   web browser. This ensures that the dev environment is properly set
+   up for tests to run.
 
 #. You can run all tests in JupyterHub 
 
@@ -56,48 +57,6 @@ Running the tests
       
       pytest -v jupyterhub/tests/test_api.py::test_shutdown
 
-   For more details, refer to the `pytest usage documentation <https://pytest.readthedocs.io/en/latest/usage.html>`_.
-
-Test organisation
-=================
-
-The tests live in ``jupyterhub/tests`` and are organized roughly into:
-
-#. ``test_api.py`` tests the REST API
-#. ``test_pages.py`` tests loading the HTML pages
-
-and other collections of tests for different components.
-When writing a new test, there should usually be a test of
-similar functionality already written and related tests should
-be added nearby.
-
-The fixtures live in ``jupyterhub/tests/conftest.py``. There are
-fixtures that can be used for JupyterHub components, such as:
-
-- ``app``: an instance of JupyterHub with mocked parts
-- ``auth_state_enabled``: enables persisting auth_state (like authentication tokens)
-- ``db``: a sqlite in-memory DB session
-- ``io_loop```: a Tornado event loop
-- ``event_loop``: a new asyncio event loop
-- ``user``: creates a new temporary user
-- ``admin_user``: creates a new temporary admin user
-- single user servers
-  - ``cleanup_after``: allows cleanup of single user servers between tests
-- mocked service
-  - ``MockServiceSpawner``: a spawner that mocks services for testing with a short poll interval
-  - ``mockservice```: mocked service with no external service url
-  - ``mockservice_url``: mocked service with a url to test external services
-
-And fixtures to add functionality or spawning behavior:
-
-- ``admin_access``: grants admin access
-- ``no_patience```: sets slow-spawning timeouts to zero
-- ``slow_spawn``: enables the SlowSpawner (a spawner that takes a few seconds to start)
-- ``never_spawn``: enables the NeverSpawner (a spawner that will never start)
-- ``bad_spawn``: enables the BadSpawner (a spawner that fails immediately)
-- ``slow_bad_spawn``: enables the SlowBadSpawner (a spawner that fails after a short delay)
-
-Refer to the `pytest fixtures documentation <https://pytest.readthedocs.io/en/latest/fixture.html>`_  to learn how to use fixtures that exists already and to create new ones.
 
 Troubleshooting Test Failures
 =============================
@@ -105,34 +64,5 @@ Troubleshooting Test Failures
 All the tests are failing
 -------------------------
 
-Make sure you have completed all the steps in :ref:`contributing/setup` successfully, and are able to access JupyterHub from your browser at http://localhost:8000 after starting ``jupyterhub`` in your command line.
-
-
-Code formatting and linting
-===========================
-
-JupyterHub automatically enforces code formatting. This means that pull requests
-with changes breaking this formatting will receive a commit from pre-commit.ci
-automatically.
-
-To automatically format code locally, you can install pre-commit and register a
-*git hook* to automatically check with pre-commit before you make a commit if
-the formatting is okay.
-
-.. code:: bash
-
-   pip install pre-commit
-   pre-commit install --install-hooks
-
-To run pre-commit manually you would do:
-
-.. code:: bash
-
-   # check for changes to code not yet committed
-   pre-commit run
-
-   # check for changes also in already committed code
-   pre-commit run --all-files
-
-You may also install `black integration <https://github.com/psf/black#editor-integration>`_
-into your text editor to format code automatically.
+Make sure you have completed all the steps in :ref:`contributing/setup` successfully, and
+can launch ``jupyterhub`` from the terminal.

docs/source/contributor-list.md

@@ -120,4 +120,3 @@ contribution on JupyterHub:
 - yuvipanda
 - zoltan-fedor
 - zonca
-- Neeraj Natu

docs/source/events/index.rst

@@ -1,7 +1,10 @@
-Event logging and telemetry
-===========================
+Eventlogging and Telemetry
+==========================
+
+JupyterHub can be configured to record structured events from a running server using Jupyter's `Telemetry System`_. The types of events that JupyterHub emits are defined by `JSON schemas`_ listed below_
+
+ emitted as JSON data, defined and validated by the JSON schemas listed below.
 
-JupyterHub can be configured to record structured events from a running server using Jupyter's `Telemetry System`_. The types of events that JupyterHub emits are defined by `JSON schemas`_ listed at the bottom of this page_.
 
 .. _logging: https://docs.python.org/3/library/logging.html
 .. _`Telemetry System`: https://github.com/jupyter/telemetry
@@ -15,7 +18,7 @@ Event logging is handled by its ``Eventlog`` object. This leverages Python's sta
 
 To begin recording events, you'll need to set two configurations:
 
-    1. ``handlers``: tells the EventLog *where* to route your events. This trait is a list of Python logging handlers that route events to the event log file.  
+    1. ``handlers``: tells the EventLog *where* to route your events. This trait is a list of Python logging handlers that route events to 
     2. ``allows_schemas``: tells the EventLog *which* events should be recorded. No events are emitted by default; all recorded events must be listed here.
 
 Here's a basic example:
@@ -35,12 +38,13 @@ Here's a basic example:
 The output is a file, ``"event.log"``, with events recorded as JSON data.
 
 
-.. _page:
+
+.. _below:
 
 Event schemas
 -------------
 
 .. toctree::
-    :maxdepth: 2
+   :maxdepth: 2
 
-    server-actions.rst
+   server-actions.rst

docs/source/gallery-jhub-deployments.md

@@ -8,29 +8,27 @@ high performance computing.
 
 Please submit pull requests to update information or to add new institutions or uses.
 
+
 ## Academic Institutions, Research Labs, and Supercomputer Centers
 
 ### University of California Berkeley
 
 - [BIDS - Berkeley Institute for Data Science](https://bids.berkeley.edu/)
-
-  - [Teaching with Jupyter notebooks and JupyterHub](https://bids.berkeley.edu/resources/videos/teaching-ipythonjupyter-notebooks-and-jupyterhub)
+    - [Teaching with Jupyter notebooks and JupyterHub](https://bids.berkeley.edu/resources/videos/teaching-ipythonjupyter-notebooks-and-jupyterhub)
 
 - [Data 8](http://data8.org/)
-
-  - [GitHub organization](https://github.com/data-8)
+    - [GitHub organization](https://github.com/data-8)
 
 - [NERSC](http://www.nersc.gov/)
-
-  - [Press release on Jupyter and Cori](http://www.nersc.gov/news-publications/nersc-news/nersc-center-news/2016/jupyter-notebooks-will-open-up-new-possibilities-on-nerscs-cori-supercomputer/)
-  - [Moving and sharing data](https://www.nersc.gov/assets/Uploads/03-MovingAndSharingData-Cholia.pdf)
+    - [Press release on Jupyter and Cori](http://www.nersc.gov/news-publications/nersc-news/nersc-center-news/2016/jupyter-notebooks-will-open-up-new-possibilities-on-nerscs-cori-supercomputer/)
+    - [Moving and sharing data](https://www.nersc.gov/assets/Uploads/03-MovingAndSharingData-Cholia.pdf)
 
 - [Research IT](http://research-it.berkeley.edu)
-  - [JupyterHub server supports campus research computation](http://research-it.berkeley.edu/blog/17/01/24/free-fully-loaded-jupyterhub-server-supports-campus-research-computation)
+    - [JupyterHub server supports campus research computation](http://research-it.berkeley.edu/blog/17/01/24/free-fully-loaded-jupyterhub-server-supports-campus-research-computation)
 
 ### University of California Davis
 
-- [Spinning up multiple Jupyter Notebooks on AWS for a tutorial](https://github.com/mblmicdiv/course2017/blob/HEAD/exercises/sourmash-setup.md)
+- [Spinning up multiple Jupyter Notebooks on AWS for a tutorial](https://github.com/mblmicdiv/course2017/blob/master/exercises/sourmash-setup.md)
 
 Although not technically a JupyterHub deployment, this tutorial setup
 may be helpful to others in the Jupyter community.
@@ -61,31 +59,23 @@ easy to do with RStudio too.
 
 - [jupyterhub-deploy-teaching](https://github.com/jupyterhub/jupyterhub-deploy-teaching) based on work by Brian Granger for Cal Poly's Data Science 301 Course
 
-### Chameleon
-
-[Chameleon](https://www.chameleoncloud.org) is a NSF-funded configurable experimental environment for large-scale computer science systems research with [bare metal reconfigurability](https://chameleoncloud.readthedocs.io/en/latest/technical/baremetal.html). Chameleon users utilize JupyterHub to document and reproduce their complex CISE and networking experiments.
-
-- [Shared JupyterHub](https://jupyter.chameleoncloud.org): provides a common "workbench" environment for any Chameleon user.
-- [Trovi](https://www.chameleoncloud.org/experiment/share): a sharing portal of experiments, tutorials, and examples, which users can launch as a dedicated isolated environments on Chameleon's JupyterHub.
-
 ### Clemson University
 
 - Advanced Computing
-  - [Palmetto cluster and JupyterHub](http://citi.sites.clemson.edu/2016/08/18/JupyterHub-for-Palmetto-Cluster.html)
+    - [Palmetto cluster and JupyterHub](http://citi.sites.clemson.edu/2016/08/18/JupyterHub-for-Palmetto-Cluster.html)
 
 ### University of Colorado Boulder
 
 - (CU Research Computing) CURC
-
-  - [JupyterHub User Guide](https://www.rc.colorado.edu/support/user-guide/jupyterhub.html)
-    - Slurm job dispatched on Crestone compute cluster
-    - log troubleshooting
-    - Profiles in IPython Clusters tab
-  - [Parallel Processing with JupyterHub tutorial](https://www.rc.colorado.edu/support/examples-and-tutorials/parallel-processing-with-jupyterhub.html)
-  - [Parallel Programming with JupyterHub document](https://www.rc.colorado.edu/book/export/html/833)
+    - [JupyterHub User Guide](https://www.rc.colorado.edu/support/user-guide/jupyterhub.html)
+        - Slurm job dispatched on Crestone compute cluster
+        - log troubleshooting
+        - Profiles in IPython Clusters tab
+    - [Parallel Processing with JupyterHub tutorial](https://www.rc.colorado.edu/support/examples-and-tutorials/parallel-processing-with-jupyterhub.html)
+    - [Parallel Programming with JupyterHub document](https://www.rc.colorado.edu/book/export/html/833)
 
 - Earth Lab at CU
-  - [Tutorial on Parallel R on JupyterHub](https://earthdatascience.org/tutorials/parallel-r-on-jupyterhub/)
+    - [Tutorial on Parallel R on JupyterHub](https://earthdatascience.org/tutorials/parallel-r-on-jupyterhub/)
 
 ### George Washington University
 
@@ -97,7 +87,7 @@ easy to do with RStudio too.
 
 ### University of Illinois
 
-- https://datascience.business.illinois.edu (currently down; checked 10/26/22)
+- https://datascience.business.illinois.edu (currently down; checked 04/26/19)
 
 ### IllustrisTNG Simulation Project
 
@@ -122,11 +112,11 @@ easy to do with RStudio too.
 ### Paderborn University
 
 - [Data Science (DICE) group](https://dice.cs.uni-paderborn.de/)
-  - [nbgraderutils](https://github.com/dice-group/nbgraderutils): Use JupyterHub + nbgrader + iJava kernel for online Java exercises. Used in lecture Statistical Natural Language Processing.
+    - [nbgraderutils](https://github.com/dice-group/nbgraderutils): Use JupyterHub + nbgrader + iJava kernel for online Java exercises. Used in lecture Statistical Natural Language Processing.
 
 ### Penn State University
 
-- [Press release](https://news.psu.edu/story/523093/2018/05/24/new-open-source-web-apps-available-students-and-faculty): "New open-source web apps available for students and faculty"
+- [Press release](https://news.psu.edu/story/523093/2018/05/24/new-open-source-web-apps-available-students-and-faculty): "New open-source web apps available for students and faculty" (but Hub is currently down; checked 04/26/19)
 
 ### University of Rochester CIRC
 
@@ -135,34 +125,33 @@ easy to do with RStudio too.
 ### University of California San Diego
 
 - San Diego Supercomputer Center - Andrea Zonca
-
-  - [Deploy JupyterHub on a Supercomputer with SSH](https://zonca.github.io/2017/05/jupyterhub-hpc-batchspawner-ssh.html)
-  - [Run Jupyterhub on a Supercomputer](https://zonca.github.io/2015/04/jupyterhub-hpc.html)
-  - [Deploy JupyterHub on a VM for a Workshop](https://zonca.github.io/2016/04/jupyterhub-sdsc-cloud.html)
-  - [Customize your Python environment in Jupyterhub](https://zonca.github.io/2017/02/customize-python-environment-jupyterhub.html)
-  - [Jupyterhub deployment on multiple nodes with Docker Swarm](https://zonca.github.io/2016/05/jupyterhub-docker-swarm.html)
-  - [Sample deployment of Jupyterhub in HPC on SDSC Comet](https://zonca.github.io/2017/02/sample-deployment-jupyterhub-hpc.html)
+    - [Deploy JupyterHub on a Supercomputer with SSH](https://zonca.github.io/2017/05/jupyterhub-hpc-batchspawner-ssh.html)
+    - [Run Jupyterhub on a Supercomputer](https://zonca.github.io/2015/04/jupyterhub-hpc.html)
+    - [Deploy JupyterHub on a VM for a Workshop](https://zonca.github.io/2016/04/jupyterhub-sdsc-cloud.html)
+    - [Customize your Python environment in Jupyterhub](https://zonca.github.io/2017/02/customize-python-environment-jupyterhub.html)
+    - [Jupyterhub deployment on multiple nodes with Docker Swarm](https://zonca.github.io/2016/05/jupyterhub-docker-swarm.html)
+    - [Sample deployment of Jupyterhub in HPC on SDSC Comet](https://zonca.github.io/2017/02/sample-deployment-jupyterhub-hpc.html)
 
 - Educational Technology Services - Paul Jamason
-  - [jupyterhub.ucsd.edu](https://jupyterhub.ucsd.edu)
+    - [jupyterhub.ucsd.edu](https://jupyterhub.ucsd.edu)
 
 ### TACC University of Texas
 
 ### Texas A&M
 
 - Kristen Thyng - Oceanography
-  - [Teaching with JupyterHub and nbgrader](http://kristenthyng.com/blog/2016/09/07/jupyterhub+nbgrader/)
+    - [Teaching with JupyterHub and nbgrader](http://kristenthyng.com/blog/2016/09/07/jupyterhub+nbgrader/)
 
 ### Elucidata
-
-- What's new in Jupyter Notebooks @[Elucidata](https://elucidata.io/):
-  - [Using Jupyter Notebooks with Jupyterhub on GCP, managed by GKE](https://medium.com/elucidata/why-you-should-be-using-a-jupyter-notebook-8385a4ccd93d)
+  - What's new in Jupyter Notebooks @[Elucidata](https://elucidata.io/):
+      - Using Jupyter Notebooks with Jupyterhub on GCP, managed by GKE
+            - https://medium.com/elucidata/why-you-should-be-using-a-jupyter-notebook-8385a4ccd93d
 
 ## Service Providers
 
 ### AWS
 
-- [Run Jupyter Notebook and JupyterHub on Amazon EMR](https://aws.amazon.com/blogs/big-data/running-jupyter-notebook-and-jupyterhub-on-amazon-emr/)
+- [running-jupyter-notebook-and-jupyterhub-on-amazon-emr](https://aws.amazon.com/blogs/big-data/running-jupyter-notebook-and-jupyterhub-on-amazon-emr/)
 
 ### Google Cloud Platform
 
@@ -175,28 +164,28 @@ easy to do with RStudio too.
 
 ### Microsoft Azure
 
-- [Azure Data Science Virtual Machine release notes](https://docs.microsoft.com/en-us/azure/machine-learning/machine-learning-data-science-linux-dsvm-intro)
+- https://docs.microsoft.com/en-us/azure/machine-learning/machine-learning-data-science-linux-dsvm-intro
 
 ### Rackspace Carina
 
 - https://getcarina.com/blog/learning-how-to-whale/
-- http://carolynvanslyck.com/talk/carina/jupyterhub/#/ (but carolynvanslyck is currently down; checked 10/26/22)
+- http://carolynvanslyck.com/talk/carina/jupyterhub/#/
 
 ### Hadoop
 
 - [Deploying JupyterHub on Hadoop](https://jupyterhub-on-hadoop.readthedocs.io)
 
+
 ## Miscellaneous
 
 - https://medium.com/@ybarraud/setting-up-jupyterhub-with-sudospawner-and-anaconda-844628c0dbee#.rm3yt87e1
-- [Mailing list UT deployment](https://groups.google.com/forum/#!topic/jupyter/nkPSEeMr8c0)
-- [JupyterHub setup on Centos](https://gist.github.com/johnrc/604971f7d41ebf12370bf5729bf3e0a4)
-- [Deploy JupyterHub to Docker Swarm](https://jupyterhub.surge.sh/#/welcome)
+- https://groups.google.com/forum/#!topic/jupyter/nkPSEeMr8c0 Mailing list UT deployment
+- JupyterHub setup on Centos https://gist.github.com/johnrc/604971f7d41ebf12370bf5729bf3e0a4
+- Deploy JupyterHub to Docker Swarm https://jupyterhub.surge.sh/#/welcome
 - http://www.laketide.com/building-your-lab-part-3/
 - http://estrellita.hatenablog.com/entry/2015/07/31/083202
 - http://www.walkingrandomly.com/?p=5734
 - https://wrdrd.com/docs/consulting/education-technology
 - https://bitbucket.org/jackhale/fenics-jupyter
 - [LinuxCluster blog](https://linuxcluster.wordpress.com/category/application/jupyterhub/)
-- [Network Technology](https://arnesund.com/tag/jupyterhub/)
-- [Spark Cluster on OpenStack with Multi-User Jupyter Notebook](https://arnesund.com/2015/09/21/spark-cluster-on-openstack-with-multi-user-jupyter-notebook/)
+- [Network Technology](https://arnesund.com/tag/jupyterhub/) [Spark Cluster on OpenStack with Multi-User Jupyter Notebook](https://arnesund.com/2015/09/21/spark-cluster-on-openstack-with-multi-user-jupyter-notebook/)

docs/source/getting-started/authenticators-users-basics.md

@@ -1,14 +1,15 @@
 # Authentication and User Basics
 
-The default Authenticator uses [PAM][] (Pluggable Authentication Module) to authenticate system users with
+The default Authenticator uses [PAM][] to authenticate system users with
 their username and password. With the default Authenticator, any user
 with an account and password on the system will be allowed to login.
 
-## Create a set of allowed users (`allowed_users`)
+## Create a set of allowed users
 
 You can restrict which users are allowed to login with a set,
 `Authenticator.allowed_users`:
 
+
 ```python
 c.Authenticator.allowed_users = {'mal', 'zoe', 'inara', 'kaylee'}
 ```
@@ -16,36 +17,24 @@ c.Authenticator.allowed_users = {'mal', 'zoe', 'inara', 'kaylee'}
 Users in the `allowed_users` set are added to the Hub database when the Hub is
 started.
 
-```{warning}
-If this configuration value is not set, then **all authenticated users will be allowed into your hub**.
-```
-
 ## Configure admins (`admin_users`)
 
-```{note}
-As of JupyterHub 2.0, the full permissions of `admin_users`
-should not be required.
-Instead, you can assign [roles](define-role-target) to users or groups
-with only the scopes they require.
-```
-
 Admin users of JupyterHub, `admin_users`, can add and remove users from
 the user `allowed_users` set. `admin_users` can take actions on other users'
 behalf, such as stopping and restarting their servers.
 
-A set of initial admin users, `admin_users` can be configured as follows:
+A set of initial admin users, `admin_users` can configured be as follows:
 
 ```python
 c.Authenticator.admin_users = {'mal', 'zoe'}
 ```
-
 Users in the admin set are automatically added to the user `allowed_users` set,
 if they are not already present.
 
-Each Authenticator may have different ways of determining whether a user is an
-administrator. By default, JupyterHub uses the PAMAuthenticator which provides the
-`admin_groups` option and can set administrator status based on a user
-group. For example, we can let any user in the `wheel` group be an admin:
+Each authenticator may have different ways of determining whether a user is an
+administrator. By default JupyterHub use the PAMAuthenticator which provide the
+`admin_groups` option and can determine administrator status base on a user
+groups. For example we can let any users in the `wheel` group be admin:
 
 ```python
 c.PAMAuthenticator.admin_groups = {'wheel'}
@@ -53,19 +42,19 @@ c.PAMAuthenticator.admin_groups = {'wheel'}
 
 ## Give admin access to other users' notebook servers (`admin_access`)
 
-Since the default `JupyterHub.admin_access` setting is `False`, the admins
+Since the default `JupyterHub.admin_access` setting is False, the admins
 do not have permission to log in to the single user notebook servers
-owned by _other users_. If `JupyterHub.admin_access` is set to `True`,
-then admins have permission to log in _as other users_ on their
-respective machines for debugging. **As a courtesy, you should make
+owned by *other users*. If `JupyterHub.admin_access` is set to True,
+then admins have permission to log in *as other users* on their
+respective machines, for debugging. **As a courtesy, you should make
 sure your users know if admin_access is enabled.**
 
 ## Add or remove users from the Hub
 
-Users can be added to and removed from the Hub via the admin
+Users can be added to and removed from the Hub via either the admin
 panel or the REST API. When a user is **added**, the user will be
-automatically added to the `allowed_users` set and database. Restarting the Hub
-will not require manually updating the `allowed_users` set in your config file,
+automatically added to the allowed users set and database. Restarting the Hub
+will not require manually updating the allowed users set in your config file,
 as the users will be loaded from the database.
 
 After starting the Hub once, it is not sufficient to **remove** a user
@@ -76,12 +65,12 @@ fresh.
 
 ## Use LocalAuthenticator to create system users
 
-The `LocalAuthenticator` is a special kind of Authenticator that has
+The `LocalAuthenticator` is a special kind of authenticator that has
 the ability to manage users on the local system. When you try to add a
 new user to the Hub, a `LocalAuthenticator` will check if the user
 already exists. If you set the configuration value, `create_system_users`,
 to `True` in the configuration file, the `LocalAuthenticator` has
-the ability to add users to the system. The setting in the config
+the privileges to add users to the system. The setting in the config
 file is:
 
 ```python
@@ -91,7 +80,7 @@ c.LocalAuthenticator.create_system_users = True
 Adding a user to the Hub that doesn't already exist on the system will
 result in the Hub creating that user via the system `adduser` command
 line tool. This option is typically used on hosted deployments of
-JupyterHub to avoid the need to manually create all your users before
+JupyterHub, to avoid the need to manually create all your users before
 launching the service. This approach is not recommended when running
 JupyterHub in situations where JupyterHub users map directly onto the
 system's UNIX users.
@@ -101,25 +90,24 @@ system's UNIX users.
 JupyterHub's [OAuthenticator][] currently supports the following
 popular services:
 
-- [Auth0](https://oauthenticator.readthedocs.io/en/latest/api/gen/oauthenticator.auth0.html#module-oauthenticator.auth0)
-- [Azure AD](https://oauthenticator.readthedocs.io/en/latest/api/gen/oauthenticator.azuread.html#module-oauthenticator.azuread)
-- [Bitbucket](https://oauthenticator.readthedocs.io/en/latest/api/gen/oauthenticator.bitbucket.html#module-oauthenticator.bitbucket)
-- [CILogon](https://oauthenticator.readthedocs.io/en/latest/api/gen/oauthenticator.cilogon.html#module-oauthenticator.cilogon)
-- [GitHub](https://oauthenticator.readthedocs.io/en/latest/api/gen/oauthenticator.github.html#module-oauthenticator.github)
-- [GitLab](https://oauthenticator.readthedocs.io/en/latest/api/gen/oauthenticator.gitlab.html#module-oauthenticator.gitlab)
-- [Globus](https://oauthenticator.readthedocs.io/en/latest/api/gen/oauthenticator.globus.html#module-oauthenticator.globus)
-- [Google](https://oauthenticator.readthedocs.io/en/latest/api/gen/oauthenticator.google.html#module-oauthenticator.google)
-- [MediaWiki](https://oauthenticator.readthedocs.io/en/latest/api/gen/oauthenticator.mediawiki.html#module-oauthenticator.mediawiki)
-- [Okpy](https://oauthenticator.readthedocs.io/en/latest/api/gen/oauthenticator.okpy.html#module-oauthenticator.okpy)
-- [OpenShift](https://oauthenticator.readthedocs.io/en/latest/api/gen/oauthenticator.openshift.html#module-oauthenticator.openshift)
+- Auth0
+- Bitbucket
+- CILogon
+- GitHub
+- GitLab
+- Globus
+- Google
+- MediaWiki
+- Okpy
+- OpenShift
 
-A [generic implementation](https://oauthenticator.readthedocs.io/en/latest/api/gen/oauthenticator.generic.html#module-oauthenticator.generic), which you can use for OAuth authentication
+A generic implementation, which you can use for OAuth authentication
 with any provider, is also available.
 
 ## Use DummyAuthenticator for testing
 
-The `DummyAuthenticator` is a simple Authenticator that
-allows for any username or password unless a global password has been set. If
+The :class:`~jupyterhub.auth.DummyAuthenticator` is a simple authenticator that
+allows for any username/password unless if a global password has been set. If
 set, it will allow for any username as long as the correct password is provided.
 To set a global password, add this to the config file:
 
@@ -127,5 +115,5 @@ To set a global password, add this to the config file:
 c.DummyAuthenticator.password = "some_password"
 ```
 
-[pam]: https://en.wikipedia.org/wiki/Pluggable_authentication_module
-[oauthenticator]: https://github.com/jupyterhub/oauthenticator
+[PAM]: https://en.wikipedia.org/wiki/Pluggable_authentication_module
+[OAuthenticator]: https://github.com/jupyterhub/oauthenticator

docs/source/getting-started/config-basics.md

@@ -1,6 +1,6 @@
 # Configuration Basics
 
-This section contains basic information about configuring settings for a JupyterHub
+The section contains basic information about configuring settings for a JupyterHub
 deployment. The [Technical Reference](../reference/index)
 documentation provides additional details.
 
@@ -44,30 +44,30 @@ jupyterhub -f /etc/jupyterhub/jupyterhub_config.py
 ```
 
 The IPython documentation provides additional information on the
-[config system](http://ipython.readthedocs.io/en/stable/development/config.html)
+[config system](http://ipython.readthedocs.io/en/stable/development/config)
 that Jupyter uses.
 
 ## Configure using command line options
 
-To display all command line options that are available for configuration run the following command:
+To display all command line options that are available for configuration:
 
 ```bash
     jupyterhub --help-all
 ```
 
 Configuration using the command line options is done when launching JupyterHub.
-For example, to start JupyterHub on `10.0.1.2:443` with https, you
+For example, to start JupyterHub on ``10.0.1.2:443`` with https, you
 would enter:
 
 ```bash
     jupyterhub --ip 10.0.1.2 --port 443 --ssl-key my_ssl.key --ssl-cert my_ssl.cert
 ```
 
-All configurable options may technically be set on the command line,
+All configurable options may technically be set on the command-line,
 though some are inconvenient to type. To set a particular configuration
 parameter, `c.Class.trait`, you would use the command line option,
 `--Class.trait`, when starting JupyterHub. For example, to configure the
-`c.Spawner.notebook_dir` trait from the command line, use the
+`c.Spawner.notebook_dir` trait from the command-line, use the
 `--Spawner.notebook_dir` option:
 
 ```bash
@@ -77,24 +77,24 @@ jupyterhub --Spawner.notebook_dir='~/assignments'
 ## Configure for various deployment environments
 
 The default authentication and process spawning mechanisms can be replaced, and
-specific [authenticators](authenticators-users-basics) and
-[spawners](spawners-basics) can be set in the configuration file.
+specific [authenticators](./authenticators-users-basics) and
+[spawners](./spawners-basics) can be set in the configuration file.
 This enables JupyterHub to be used with a variety of authentication methods or
 process control and deployment environments. [Some examples](../reference/config-examples),
-meant as illustrations, are:
+meant as illustration, are:
 
 - Using GitHub OAuth instead of PAM with [OAuthenticator](https://github.com/jupyterhub/oauthenticator)
 - Spawning single-user servers with Docker, using the [DockerSpawner](https://github.com/jupyterhub/dockerspawner)
 
 ## Run the proxy separately
 
-This is _not_ strictly necessary, but useful in many cases. If you
-use a custom proxy (e.g. Traefik), this is also not needed.
+This is *not* strictly necessary, but useful in many cases.  If you
+use a custom proxy (e.g. Traefik), this also not needed.
 
-Connections to user servers go through the proxy, and _not_ the hub
-itself. If the proxy stays running when the hub restarts (for
-maintenance, re-configuration, etc.), then user connections are not
-interrupted. For simplicity, by default the hub starts the proxy
+Connections to user servers go through the proxy, and *not* the hub
+itself.  If the proxy stays running when the hub restarts (for
+maintenance, re-configuration, etc.), then use connections are not
+interrupted.  For simplicity, by default the hub starts the proxy
 automatically, so if the hub restarts, the proxy restarts, and user
-connections are interrupted. It is easy to run the proxy separately,
+connections are interrupted.  It is easy to run the proxy separately,
 for information see [the separate proxy page](../reference/separate-proxy).

docs/source/getting-started/faq.md

@@ -1,6 +1,7 @@
 # Frequently asked questions
 
-## How do I share links to notebooks?
+
+### How do I share links to notebooks?
 
 In short, where you see `/user/name/notebooks/foo.ipynb` use `/hub/user-redirect/notebooks/foo.ipynb` (replace `/user/name` with `/hub/user-redirect`).
 
@@ -10,24 +11,23 @@ Your first instinct might be to copy the URL you see in the browser,
 e.g. `hub.jupyter.org/user/yourname/notebooks/coolthing.ipynb`.
 However, let's break down what this URL means:
 
-`hub.jupyter.org/user/yourname/` is the URL prefix handled by _your server_,
+`hub.jupyter.org/user/yourname/` is the URL prefix handled by *your server*,
 which means that sharing this URL is asking the person you share the link with
-to come to _your server_ and look at the exact same file.
+to come to *your server* and look at the exact same file.
 In most circumstances, this is forbidden by permissions because the person you share with does not have access to your server.
 What actually happens when someone visits this URL will depend on whether your server is running and other factors.
 
-**But what is our actual goal?**
-
+But what is our actual goal?
 A typical situation is that you have some shared or common filesystem,
 such that the same path corresponds to the same document
 (either the exact same document or another copy of it).
 Typically, what folks want when they do sharing like this
-is for each visitor to open the same file _on their own server_,
+is for each visitor to open the same file *on their own server*,
 so Breq would open `/user/breq/notebooks/foo.ipynb` and
 Seivarden would open `/user/seivarden/notebooks/foo.ipynb`, etc.
 
 JupyterHub has a special URL that does exactly this!
-It's called `/hub/user-redirect/...`.
+It's called `/hub/user-redirect/...` and after the visitor logs in,
 So if you replace `/user/yourname` in your URL bar
 with `/hub/user-redirect` any visitor should get the same
 URL on their own server, rather than visiting yours.

docs/source/getting-started/institutional-faq.md

@@ -8,40 +8,34 @@ broken down by their roles within organizations.
 ### Is it appropriate for adoption within a larger institutional context?
 
 Yes! JupyterHub has been used at-scale for large pools of users, as well
-as complex and high-performance computing.
-For example,
-
-- UC Berkeley uses
-  JupyterHub for its Data Science Education Program courses (serving over
-  3,000 students).
-- The Pangeo project uses JupyterHub to provide access
-  to scalable cloud computing with Dask.
-
-JupyterHub is stable and customizable
+as complex and high-performance computing. For example, UC Berkeley uses
+JupyterHub for its Data Science Education Program courses (serving over
+3,000 students). The Pangeo project uses JupyterHub to provide access
+to scalable cloud computing with Dask. JupyterHub is stable customizable
 to the use-cases of large organizations.
 
 ### I keep hearing about Jupyter Notebook, JupyterLab, and now JupyterHub. What’s the difference?
 
 Here is a quick breakdown of these three tools:
 
-- **The Jupyter Notebook** is a document specification (the `.ipynb`) file that interweaves
+* **The Jupyter Notebook** is a document specification (the `.ipynb`) file that interweaves
   narrative text with code cells and their outputs. It is also a graphical interface
   that allows users to edit these documents. There are also several other graphical interfaces
   that allow users to edit the `.ipynb` format (nteract, Jupyter Lab, Google Colab, Kaggle, etc).
-- **JupyterLab** is a flexible and extendible user interface for interactive computing. It
+* **JupyterLab** is a flexible and extendible user interface for interactive computing. It
   has several extensions that are tailored for using Jupyter Notebooks, as well as extensions
   for other parts of the data science stack.
-- **JupyterHub** is an application that manages interactive computing sessions for **multiple users**.
-  It also connects users with infrastructure they wish to access. It can provide
-  remote access to Jupyter Notebooks and JupyterLab for many people.
+* **JupyterHub** is an application that manages interactive computing sessions for **multiple users**.
+  It also connects them with infrastructure those users wish to access. It can provide
+  remote access to Jupyter Notebooks and Jupyter Lab for many people.
 
 ## For management
 
 ### Briefly, what problem does JupyterHub solve for us?
 
 JupyterHub provides a shared platform for data science and collaboration.
-It allows users to utilize familiar data science workflows (such as the scientific Python stack,
-the R tidyverse, and Jupyter Notebooks) on institutional infrastructure. It also gives administrators
+It allows users to utilize familiar data science workflows (such as the scientific python stack,
+the R tidyverse, and Jupyter Notebooks) on institutional infrastructure. It also allows administrators
 some control over access to resources, security, environments, and authentication.
 
 ### Is JupyterHub mature? Why should we trust it?
@@ -56,20 +50,20 @@ scalable infrastructure, large datasets, and high-performance computing.
 JupyterHub is used at a variety of institutions in academia,
 industry, and government research labs. It is most-commonly used by two kinds of groups:
 
-- Small teams (e.g., data science teams, research labs, or collaborative projects) to provide a
+* Small teams (e.g., data science teams, research labs, or collaborative projects) to provide a
   shared resource for interactive computing, collaboration, and analytics.
-- Large teams (e.g., a department, a large class, or a large group of remote users) to provide
+* Large teams (e.g., a department, a large class, or a large group of remote users) to provide
   access to organizational hardware, data, and analytics environments at scale.
 
-Here is a sample of organizations that use JupyterHub:
+Here are a sample of organizations that use JupyterHub:
 
-- **Universities and colleges**: UC Berkeley, UC San Diego, Cal Poly SLO, Harvard University, University of Chicago,
+* **Universities and colleges**: UC Berkeley, UC San Diego, Cal Poly SLO, Harvard University, University of Chicago,
   University of Oslo, University of Sheffield, Université Paris Sud, University of Versailles
-- **Research laboratories**: NASA, NCAR, NOAA, the Large Synoptic Survey Telescope, Brookhaven National Lab,
+* **Research laboratories**: NASA, NCAR, NOAA, the Large Synoptic Survey Telescope, Brookhaven National Lab,
   Minnesota Supercomputing Institute, ALCF, CERN, Lawrence Livermore National Laboratory
-- **Online communities**: Pangeo, Quantopian, mybinder.org, MathHub, Open Humans
-- **Computing infrastructure providers**: NERSC, San Diego Supercomputing Center, Compute Canada
-- **Companies**: Capital One, SANDVIK code, Globus
+* **Online communities**: Pangeo, Quantopian, mybinder.org, MathHub, Open Humans
+* **Computing infrastructure providers**: NERSC, San Diego Supercomputing Center, Compute Canada
+* **Companies**: Capital One, SANDVIK code, Globus
 
 See the [Gallery of JupyterHub deployments](../gallery-jhub-deployments.md) for
 a more complete list of JupyterHub deployments at institutions.
@@ -84,7 +78,7 @@ gives administrators more control over their setup and hardware.
 
 Because JupyterHub is an open-source, community-driven tool, it can be extended and
 modified to fit an institution's needs. It plays nicely with the open source data science
-stack, and can serve a variety of computing environments, user interfaces, and
+stack, and can serve a variety of computing enviroments, user interfaces, and
 computational hardware. It can also be deployed anywhere - on enterprise cloud infrastructure, on
 High-Performance-Computing machines, on local hardware, or even on a single laptop, which
 is not possible with most other tools for shared interactive computing.
@@ -101,16 +95,17 @@ The most common way to set up a JupyterHub is to use a JupyterHub distribution,
 and opinionated ways to set up a JupyterHub on particular kinds of infrastructure. The two distributions
 that we currently suggest are:
 
-- [Zero to JupyterHub for Kubernetes](https://z2jh.jupyter.org) is a scalable JupyterHub deployment and
+* [Zero to JupyterHub for Kubernetes](https://z2jh.jupyter.org) is a scalable JupyterHub deployment and
   guide that runs on Kubernetes. Better for larger or dynamic user groups (50-10,000) or more complex
   compute/data needs.
-- [The Littlest JupyterHub](https://tljh.jupyter.org) is a lightweight JupyterHub that runs on a single
-  machine (in the cloud or under your desk). Better for smaller user groups (4-80) or more
+* [The Littlest JupyterHub](https://tljh.jupyter.org) is a lightweight JupyterHub that runs on a single
+  single machine (in the cloud or under your desk). Better for smaller usergroups (4-80) or more
   lightweight computational resources.
 
+
 ### Does JupyterHub run well in the cloud?
 
-**Yes** - most deployments of JupyterHub are run via cloud infrastructure and on a variety of cloud providers.
+Yes - most deployments of JupyterHub are run via cloud infrastructure and on a variety of cloud providers.
 Depending on the distribution of JupyterHub that you'd like to use, you can also connect your JupyterHub
 deployment with a number of other cloud-native services so that users have access to other resources from
 their interactive computing sessions.
@@ -124,14 +119,13 @@ as more resources are needed - allowing you to utilize the benefits of a flexibl
 
 ### Is JupyterHub secure?
 
-The short answer: yes.  
-JupyterHub as a standalone application has been battle-tested at an institutional
+The short answer: yes. JupyterHub as a standalone application has been battle-tested at an institutional
 level for several years, and makes a number of "default" security decisions that are reasonable for most
 users.
 
-- For security considerations in the base JupyterHub application,
-  [see the JupyterHub security page](https://jupyterhub.readthedocs.io/en/stable/reference/websecurity.html).
-- For security considerations when deploying JupyterHub on Kubernetes, see the
+* For security considerations in the base JupyterHub application,
+  [see the JupyterHub security page](https://jupyterhub.readthedocs.io/en/stable/reference/websecurity.html)
+* For security considerations when deploying JupyterHub on Kubernetes, see the
   [JupyterHub on Kubernetes security page](https://zero-to-jupyterhub.readthedocs.io/en/latest/security.html).
 
 The longer answer: it depends on your deployment. Because JupyterHub is very flexible, it can be used
@@ -141,15 +135,17 @@ in these cases, and the security of your JupyterHub deployment will often depend
 
 If you are worried about security, don't hesitate to reach out to the JupyterHub community in the
 [Jupyter Community Forum](https://discourse.jupyter.org/c/jupyterhub). This community of practice has many
-individuals with experience running secure JupyterHub deployments and will be very glad to help you out.
+individuals with experience running secure JupyterHub deployments.
+
 
 ### Does JupyterHub provide computing or data infrastructure?
 
-**No** - JupyterHub manages user sessions and can _control_ computing infrastructure, but it does not provide these
+No - JupyterHub manages user sessions and can *control* computing infrastructure, but it does not provide these
 things itself. You are expected to run JupyterHub on your own infrastructure (local or in the cloud). Moreover,
 JupyterHub has no internal concept of "data", but is designed to be able to communicate with data repositories
 (again, either locally or remotely) for use within interactive computing sessions.
 
+
 ### How do I manage users?
 
 JupyterHub offers a few options for managing your users. Upon setting up a JupyterHub, you can choose what
@@ -158,7 +154,7 @@ email address, or choose a username / password when they first log-in, or offloa
 another service such as an organization's OAuth.
 
 The users of a JupyterHub are stored locally, and can be modified manually by an administrator of the JupyterHub.
-Moreover, the _active_ users on a JupyterHub can be found on the administrator's page. This page
+Moreover, the *active* users on a JupyterHub can be found on the administrator's page. This page
 gives you the abiltiy to stop or restart kernels, inspect user filesystems, and even take over user
 sessions to assist them with debugging.
 
@@ -186,11 +182,12 @@ connect with other infrastructure tools (like Dask or Spark). This allows users
 scalable or high-performance resources from within their JupyterHub sessions. The logic of
 how those resources are controlled is taken care of by the non-JupyterHub application.
 
+
 ### Can JupyterHub be used with my high-performance computing resources?
 
 Yes - JupyterHub can provide access to many kinds of computing infrastructure.
 Especially when combined with other open-source schedulers such as Dask, you can manage fairly
-complex computing infrastructures from the interactive sessions of a JupyterHub. For example
+complex computing infrastructure from the interactive sessions of a JupyterHub. For example
 [see the Dask HPC page](https://docs.dask.org/en/latest/setup/hpc.html).
 
 ### How much resources do user sessions take?
@@ -198,8 +195,8 @@ complex computing infrastructures from the interactive sessions of a JupyterHub.
 This is highly configurable by the administrator. If you wish for your users to have simple
 data analytics environments for prototyping and light data exploring, you can restrict their
 memory and CPU based on the resources that you have available. If you'd like your JupyterHub
-to serve as a gateway to high-performance computing or data resources, you may increase the
-resources available on user machines, or connect them with computing infrastructures elsewhere.
+to serve as a gateway to high-performance compute or data resources, you may increase the
+resources available on user machines, or connect them with computing infrastructure elsewhere.
 
 ### Can I customize the look and feel of a JupyterHub?
 
@@ -221,14 +218,16 @@ the technologies your JupyterHub will use (e.g., dev-ops knowledge with cloud co
 In general, the base JupyterHub deployment is not the bottleneck for setup, it is connecting
 your JupyterHub with the various services and tools that you wish to provide to your users.
 
+
 ### How well does JupyterHub scale? What are JupyterHub's limitations?
 
 JupyterHub works well at both a small scale (e.g., a single VM or machine) as well as a
-high scale (e.g., a scalable Kubernetes cluster). It can be used for teams as small as 2, and
+high scale (e.g., a scalable Kubernetes cluster). It can be used for teams as small a 2, and
 for user bases as large as 10,000. The scalability of JupyterHub largely depends on the
 infrastructure on which it is deployed. JupyterHub has been designed to be lightweight and
 flexible, so you can tailor your JupyterHub deployment to your needs.
 
+
 ### Is JupyterHub resilient? What happens when a machine goes down?
 
 For JupyterHubs that are deployed in a containerized environment (e.g., Kubernetes), it is
@@ -256,7 +255,7 @@ share their results with one another.
 
 JupyterHub also provides a computational framework to share computational narratives between
 different levels of an organization. For example, data scientists can share Jupyter Notebooks
-rendered as [Voilà dashboards](https://voila.readthedocs.io/en/stable/) with those who are not
+rendered as [voila dashboards](https://voila.readthedocs.io/en/stable/) with those who are not
 familiar with programming, or create publicly-available interactive analyses to allow others to
 interact with your work.
 

docs/source/getting-started/networking-basics.md

@@ -11,7 +11,7 @@ This section will help you with basic proxy and network configuration to:
 
 The Proxy's main IP address setting determines where JupyterHub is available to users.
 By default, JupyterHub is configured to be available on all network interfaces
-(`''`) on port 8000. _Note_: Use of `'*'` is discouraged for IP configuration;
+(`''`) on port 8000. *Note*: Use of `'*'` is discouraged for IP configuration;
 instead, use of `'0.0.0.0'` is preferred.
 
 Changing the Proxy's main IP address and port can be done with the following
@@ -41,9 +41,9 @@ port.
 
 ## Set the Proxy's REST API communication URL (optional)
 
-By default, the proxy's REST API listens on port 8081 of `localhost` only.
-The Hub service talks to the proxy via a REST API on a secondary port.
-The REST API URL (hostname and port) can be configured separately and override the default settings.
+By default, this REST API listens on port 8001 of `localhost` only.
+The Hub service talks to the proxy via a REST API on a secondary port. The
+API URL can be configured separately and override the default settings.
 
 ### Set api_url
 
@@ -74,7 +74,7 @@ The Hub service listens only on `localhost` (port 8081) by default.
 The Hub needs to be accessible from both the proxy and all Spawners.
 When spawning local servers, an IP address setting of `localhost` is fine.
 
-If _either_ the Proxy _or_ (more likely) the Spawners will be remote or
+If *either* the Proxy *or* (more likely) the Spawners will be remote or
 isolated in containers, the Hub must listen on an IP that is accessible.
 
 ```python
@@ -82,20 +82,20 @@ c.JupyterHub.hub_ip = '10.0.1.4'
 c.JupyterHub.hub_port = 54321
 ```
 
-**Added in 0.8:** The `c.JupyterHub.hub_connect_ip` setting is the IP address or
+**Added in 0.8:** The `c.JupyterHub.hub_connect_ip` setting is the ip address or
 hostname that other services should use to connect to the Hub. A common
 configuration for, e.g. docker, is:
 
 ```python
 c.JupyterHub.hub_ip = '0.0.0.0'  # listen on all interfaces
-c.JupyterHub.hub_connect_ip = '10.0.1.4'  # IP as seen on the docker network. Can also be a hostname.
+c.JupyterHub.hub_connect_ip = '10.0.1.4'  # ip as seen on the docker network. Can also be a hostname.
 ```
 
 ## Adjusting the hub's URL
 
-The hub will most commonly be running on a hostname of its own. If it
+The hub will most commonly be running on a hostname of its own.  If it
 is not – for example, if the hub is being reverse-proxied and being
 exposed at a URL such as `https://proxy.example.org/jupyter/` – then
-you will need to tell JupyterHub the base URL of the service. In such
+you will need to tell JupyterHub the base URL of the service.  In such
 a case, it is both necessary and sufficient to set
 `c.JupyterHub.base_url = '/jupyter/'` in the configuration.

docs/source/getting-started/security-basics.rst

@@ -5,17 +5,17 @@ Security settings
 
    You should not run JupyterHub without SSL encryption on a public network.
 
-Security is the most important aspect of configuring Jupyter.
-Three (3) configuration settings are the main aspects of security configuration:
+Security is the most important aspect of configuring Jupyter. Three
+configuration settings are the main aspects of security configuration:
 
 1. :ref:`SSL encryption <ssl-encryption>` (to enable HTTPS)
 2. :ref:`Cookie secret <cookie-secret>` (a key for encrypting browser cookies)
 3. Proxy :ref:`authentication token <authentication-token>` (used for the Hub and
    other services to authenticate to the Proxy)
 
-The Hub hashes all secrets (e.g. auth tokens) before storing them in its
+The Hub hashes all secrets (e.g., auth tokens) before storing them in its
 database. A loss of control over read-access to the database should have
-minimal impact on your deployment. If your database has been compromised, it
+minimal impact on your deployment; if your database has been compromised, it
 is still a good idea to revoke existing tokens.
 
 .. _ssl-encryption:
@@ -31,7 +31,7 @@ Using an SSL certificate
 
 This will require you to obtain an official, trusted SSL certificate or create a
 self-signed certificate. Once you have obtained and installed a key and
-certificate, you need to specify their locations in the ``jupyterhub_config.py``
+certificate you need to specify their locations in the ``jupyterhub_config.py``
 configuration file as follows:
 
 .. code-block:: python
@@ -72,13 +72,13 @@ would be the needed configuration:
 If SSL termination happens outside of the Hub
 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
 
-In certain cases, for example, if the hub is running behind a reverse proxy, and
+In certain cases, for example if the hub is running behind a reverse proxy, and
 `SSL termination is being provided by NGINX <https://www.nginx.com/resources/admin-guide/nginx-ssl-termination/>`_,
 it is reasonable to run the hub without SSL.
 
-To achieve this, remove ``c.JupyterHub.ssl_key`` and ``c.JupyterHub.ssl_cert``
-from your configuration (setting them to ``None`` or an empty string does not
-have the same effect, and will result in an error).
+To achieve this, simply omit the configuration settings
+``c.JupyterHub.ssl_key`` and ``c.JupyterHub.ssl_cert``
+(setting them to ``None`` does not have the same effect, and is an error).
 
 .. _authentication-token:
 
@@ -92,7 +92,7 @@ use an auth token.
 
 The value of this token should be a random string (for example, generated by
 ``openssl rand -hex 32``). You can store it in the configuration file or an
-environment variable.
+environment variable
 
 Generating and storing token in the configuration file
 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
@@ -118,8 +118,8 @@ This environment variable needs to be visible to the Hub and Proxy.
 Default if token is not set
 ~~~~~~~~~~~~~~~~~~~~~~~~~~~
 
-If you do not set the Proxy authentication token, the Hub will generate a random
-key itself. This means that any time you restart the Hub, you **must also
+If you don't set the Proxy authentication token, the Hub will generate a random
+key itself, which means that any time you restart the Hub you **must also
 restart the Proxy**. If the proxy is a subprocess of the Hub, this should happen
 automatically (this is the default configuration).
 
@@ -128,7 +128,7 @@ automatically (this is the default configuration).
 Cookie secret
 -------------
 
-The cookie secret is an encryption key, used to encrypt the browser cookies,
+The cookie secret is an encryption key, used to encrypt the browser cookies
 which are used for authentication. Three common methods are described for
 generating and configuring the cookie secret.
 
@@ -136,8 +136,8 @@ Generating and storing as a cookie secret file
 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
 
 The cookie secret should be 32 random bytes, encoded as hex, and is typically
-stored in a ``jupyterhub_cookie_secret`` file. Below, is an example command to generate the
-``jupyterhub_cookie_secret`` file:
+stored in a ``jupyterhub_cookie_secret`` file. An example command to generate the
+``jupyterhub_cookie_secret`` file is:
 
 .. code-block:: bash
 
@@ -155,7 +155,7 @@ The location of the ``jupyterhub_cookie_secret`` file can be specified in the
 
 If the cookie secret file doesn't exist when the Hub starts, a new cookie
 secret is generated and stored in the file. The file must not be readable by
-``group`` or ``other``, otherwise the server won't start. The recommended permissions
+``group`` or ``other`` or the server won't start. The recommended permissions
 for the cookie secret file are ``600`` (owner-only rw).
 
 Generating and storing as an environment variable
@@ -176,13 +176,19 @@ the Hub starts.
 Generating and storing as a binary string
 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
 
-You can also set the cookie secret, as a binary string,
-in the configuration file (``jupyterhub_config.py``) itself:
+You can also set the cookie secret in the configuration file
+itself, ``jupyterhub_config.py``, as a binary string:
 
 .. code-block:: python
 
     c.JupyterHub.cookie_secret = bytes.fromhex('64 CHAR HEX STRING')
 
+
+.. important::
+
+   If the cookie secret value changes for the Hub, all single-user notebook
+   servers must also be restarted.
+
 .. _cookies:
 
 Cookies used by JupyterHub authentication
@@ -198,7 +204,7 @@ jupyterhub-hub-login
 ~~~~~~~~~~~~~~~~~~~~
 
 This is the login token used when visiting Hub-served pages that are
-protected by authentication, such as the main home, the spawn form, etc.
+protected by authentication such as the main home, the spawn form, etc.
 If this cookie is set, then the user is logged in.
 
 Resetting the Hub cookie secret effectively revokes this cookie.
@@ -209,7 +215,7 @@ jupyterhub-user-<username>
 ~~~~~~~~~~~~~~~~~~~~~~~~~~
 
 This is the cookie used for authenticating with a single-user server.
-It is set by the single-user server, after OAuth with the Hub.
+It is set by the single-user server after OAuth with the Hub.
 
 Effectively the same as ``jupyterhub-hub-login``, but for the
 single-user server instead of the Hub. It contains an OAuth access token,
@@ -218,13 +224,14 @@ which is checked with the Hub to authenticate the browser.
 Each OAuth access token is associated with a session id (see ``jupyterhub-session-id`` section
 below).
 
-To avoid hitting the Hub on every request, the authentication response is cached.
-The cache key is comprised of both the token and session id, to avoid a stale cache.
+To avoid hitting the Hub on every request, the authentication response
+is cached. And to avoid a stale cache the cache key is comprised of both
+the token and session id.
 
 Resetting the Hub cookie secret effectively revokes this cookie.
 
-This cookie is restricted to the path ``/user/<username>``,
-to ensure that only the user’s server receives it.
+This cookie is restricted to the path ``/user/<username>``, so that
+only the user’s server receives it.
 
 jupyterhub-session-id
 ~~~~~~~~~~~~~~~~~~~~~
@@ -232,9 +239,9 @@ jupyterhub-session-id
 This is a random string, meaningless in itself, and the only cookie
 shared by the Hub and single-user servers.
 
-Its sole purpose is to coordinate the logout of the multiple OAuth cookies.
+Its sole purpose is to coordinate logout of the multiple OAuth cookies.
 
-This cookie is set to ``/`` so all endpoints can receive it, clear it, etc.
+This cookie is set to ``/`` so all endpoints can receive it, or clear it, etc.
 
 jupyterhub-user-<username>-oauth-state
 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
@@ -244,7 +251,7 @@ It is only set while OAuth between the single-user server and the Hub
 is processing.
 
 If you use your browser development tools, you should see this cookie
-for a very brief moment before you are logged in,
+for a very brief moment before your are logged in,
 with an expiration date shorter than ``jupyterhub-hub-login`` or
 ``jupyterhub-user-<username>``.
 

docs/source/getting-started/services-basics.md

@@ -2,7 +2,7 @@
 
 When working with JupyterHub, a **Service** is defined as a process
 that interacts with the Hub's REST API. A Service may perform a specific
-action or task. For example, shutting down individuals' single user
+or action or task. For example, shutting down individuals' single user
 notebook servers that have been idle for some time is a good example of
 a task that could be automated by a Service. Let's look at how the
 [jupyterhub_idle_culler][] script can be used as a Service.
@@ -16,15 +16,15 @@ document will:
 - clarify that API tokens can be used to authenticate to
   single-user servers as of [version 0.8.0](../changelog)
 - show how the [jupyterhub_idle_culler][] script can be:
-  - used in a Hub-managed service
-  - run as a standalone script
+    - used in a Hub-managed service
+    - run as a standalone script
 
 Both examples for `jupyterhub_idle_culler` will communicate tasks to the
 Hub via the REST API.
 
 ## API Token basics
 
-### Step 1: Generate an API token
+### Create an API token
 
 To run such an external service, an API token must be created and
 provided to the service.
@@ -43,12 +43,12 @@ generating an API token is available from the JupyterHub user interface:
 
 ![API TOKEN success page](../images/token-request-success.png)
 
-### Step 2: Pass environment variable with token to the Hub
+### Pass environment variable with token to the Hub
 
 In the case of `cull_idle_servers`, it is passed as the environment
 variable called `JUPYTERHUB_API_TOKEN`.
 
-### Step 3: Use API tokens for services and tasks that require external access
+### Use API tokens for services and tasks that require external access
 
 While API tokens are often associated with a specific user, API tokens
 can be used by services that require external access for activities
@@ -62,12 +62,12 @@ c.JupyterHub.services = [
 ]
 ```
 
-### Step 4: Restart JupyterHub
+### Restart JupyterHub
 
 Upon restarting JupyterHub, you should see a message like below in the
 logs:
 
-```none
+```
 Adding API token for <username>
 ```
 
@@ -78,55 +78,34 @@ single-user servers, and only cookies can be used for authentication.
 0.8 supports using JupyterHub API tokens to authenticate to single-user
 servers.
 
-## How to configure the idle culler to run as a Hub-Managed Service
+## Configure the idle culler to run as a Hub-Managed Service
 
-### Step 1: Install the idle culler:
+Install the idle culler:
 
 ```
 pip install jupyterhub-idle-culler
 ```
 
-### Step 2: In `jupyterhub_config.py`, add the following dictionary for the `idle-culler` Service to the `c.JupyterHub.services` list:
+In `jupyterhub_config.py`, add the following dictionary for the
+`idle-culler` Service to the `c.JupyterHub.services` list:
 
 ```python
 c.JupyterHub.services = [
     {
         'name': 'idle-culler',
+        'admin': True,
         'command': [sys.executable, '-m', 'jupyterhub_idle_culler', '--timeout=3600'],
     }
 ]
-
-c.JupyterHub.load_roles = [
-    {
-        "name": "list-and-cull", # name the role
-        "services": [
-            "idle-culler", # assign the service to this role
-        ],
-        "scopes": [
-            # declare what permissions the service should have
-            "list:users", # list users
-            "read:users:activity", # read user last-activity
-            "admin:servers", # start/stop servers
-        ],
-    }
-]
 ```
 
 where:
 
-- `command` indicates that the Service will be launched as a
+- `'admin': True` indicates that the Service has 'admin' permissions, and
+- `'command'` indicates that the Service will be launched as a
   subprocess, managed by the Hub.
 
-```{versionchanged} 2.0
-Prior to 2.0, the idle-culler required 'admin' permissions.
-It now needs the scopes:
-
-- `list:users` to access the user list endpoint
-- `read:users:activity` to read activity info
-- `admin:servers` to start/stop servers
-```
-
-## How to run `cull-idle` manually as a standalone script
+## Run `cull-idle` manually as a standalone script
 
 Now you can run your script by providing it
 the API token and it will authenticate through the REST API to
@@ -135,8 +114,7 @@ interact with it.
 This will run the idle culler service manually. It can be run as a standalone
 script anywhere with access to the Hub, and will periodically check for idle
 servers and shut them down via the Hub's REST API. In order to shutdown the
-servers, the token given to `cull-idle` must have permission to list users
-and admin their servers.
+servers, the token given to cull-idle must have admin privileges.
 
 Generate an API token and store it in the `JUPYTERHUB_API_TOKEN` environment
 variable. Run `jupyterhub_idle_culler` manually.

docs/source/getting-started/spawners-basics.md

@@ -1,12 +1,12 @@
 # Spawners and single-user notebook servers
 
-A Spawner starts each single-user notebook server. Since the single-user server is an instance of `jupyter notebook`, an entire separate
-multi-process application, many aspects of that server can be configured and there are a lot
-of ways to express that configuration.
+Since the single-user server is an instance of `jupyter notebook`, an entire separate
+multi-process application, there are many aspect of that server can configure, and a lot of ways
+to express that configuration.
 
 At the JupyterHub level, you can set some values on the Spawner. The simplest of these is
 `Spawner.notebook_dir`, which lets you set the root directory for a user's server. This root
-notebook directory is the highest-level directory users will be able to access in the notebook
+notebook directory is the highest level directory users will be able to access in the notebook
 dashboard. In this example, the root notebook directory is set to `~/notebooks`, where `~` is
 expanded to the user's home directory.
 
@@ -14,13 +14,13 @@ expanded to the user's home directory.
 c.Spawner.notebook_dir = '~/notebooks'
 ```
 
-You can also specify extra command line arguments to the notebook server with:
+You can also specify extra command-line arguments to the notebook server with:
 
 ```python
 c.Spawner.args = ['--debug', '--profile=PHYS131']
 ```
 
-This could be used to set the user's default page for the single-user server:
+This could be used to set the users default page for the single user server:
 
 ```python
 c.Spawner.args = ['--NotebookApp.default_url=/notebooks/Welcome.ipynb']

docs/source/index-admin.rst

@@ -9,7 +9,5 @@ well as other information relevant to running your own JupyterHub over time.
    :maxdepth: 2
 
    troubleshooting
-   admin/capacity-planning
    admin/upgrading
-   admin/log-messages
    changelog

docs/source/index.rst

@@ -1,32 +1,32 @@
 ==========
 JupyterHub
 ==========
+
 `JupyterHub`_ is the best way to serve `Jupyter notebook`_ for multiple users.
-Because JupyterHub manages a separate Jupyter environment for each user,
-it can be used in a class of students, a corporate data science group, or a scientific
+It can be used in a class of students, a corporate data science group or scientific
 research group. It is a multi-user **Hub** that spawns, manages, and proxies multiple
 instances of the single-user `Jupyter notebook`_ server.
 
-JupyterHub offers distributions for different use cases. As of now, you can find two main cases:
+To make life easier, JupyterHub has distributions. Be sure to
+take a look at them before continuing with the configuration of the broad
+original system of `JupyterHub`_. Today, you can find two main cases:
 
-1. `The Littlest JupyterHub <https://github.com/jupyterhub/the-littlest-jupyterhub>`__ distribution is suitable if you need a small number of users (1-100) and a single server with a simple environment.
-2. `Zero to JupyterHub with Kubernetes <https://github.com/jupyterhub/zero-to-jupyterhub-k8s>`__ allows you to deploy dynamic servers on the cloud if you need even more users.
+1. If you need a simple case for a small amount of users (0-100) and single server
+   take a look at
+   `The Littlest JupyterHub <https://github.com/jupyterhub/the-littlest-jupyterhub>`__ distribution.
+2. If you need to allow for even more users, a dynamic amount of servers can be used on a cloud,
+   take a look at the `Zero to JupyterHub with Kubernetes <https://github.com/jupyterhub/zero-to-jupyterhub-k8s>`__ .
 
 
-JupyterHub can be used in a collaborative environment by both both small (0-100 users) and 
-large teams (more than 100 users) such as a class of students, corporate data science group 
-or scientific research group. It has distributions which are developed to serve the needs of 
-each of these teams respectively. 
-
-JupyterHub is made up of four subsystems:
+Four subsystems make up JupyterHub:
 
 * a **Hub** (tornado process) that is the heart of JupyterHub
 * a **configurable http proxy** (node-http-proxy) that receives the requests from the client's browser
 * multiple **single-user Jupyter notebook servers** (Python/IPython/tornado) that are monitored by Spawners
 * an **authentication class** that manages how users can access the system
 
-Additionally, optional configurations can be added through a `config.py` file and manage users 
-kernels on an admin panel. A simplification of the whole system is displayed in the figure below:
+
+Besides these central pieces, you can add optional configurations through a `config.py` file and manage users kernels on an admin panel. A simplification of the whole system can be seen in the figure below:
 
 .. image:: images/jhub-fluxogram.jpeg
    :alt: JupyterHub subsystems
@@ -43,7 +43,7 @@ JupyterHub performs the following functions:
   notebook servers
 
 For convenient administration of the Hub, its users, and services,
-JupyterHub also provides a :doc:`REST API <reference/rest-api>`.
+JupyterHub also provides a `REST API`_.
 
 The JupyterHub team and Project Jupyter value our community, and JupyterHub
 follows the Jupyter `Community Guides <https://jupyter.readthedocs.io/en/latest/community/content-community.html>`_.
@@ -56,22 +56,17 @@ Contents
 Distributions
 -------------
 
-A JupyterHub **distribution** is tailored 
-towards a particular set of use cases. These are generally easier 
-to set up than setting up JupyterHub from scratch, assuming they fit your use case.
+A JupyterHub **distribution** is tailored towards a particular set of
+use cases. These are generally easier to set up than setting up
+JupyterHub from scratch, assuming they fit your use case.
 
-Today, you can find two main use cases:
+The two popular ones are:
 
-1. If you need a simple case for a small amount of users (0-100) and single server
-   take a look at
-   `The Littlest JupyterHub <https://github.com/jupyterhub/the-littlest-jupyterhub>`__ distribution.
-2. If you need to allow for a larger number of machines and users, 
-   a dynamic amount of servers can be used on a cloud,
-   take a look at the `Zero to JupyterHub with Kubernetes <https://github.com/jupyterhub/zero-to-jupyterhub-k8s>`__ distribution.
-   This distribution runs JupyterHub on top of  `Kubernetes <https://k8s.io>`_.
-
-*It is important to evaluate these distributions before you can continue with the 
-configuration of JupyterHub*.
+* `Zero to JupyterHub on Kubernetes <http://z2jh.jupyter.org>`_, for
+  running JupyterHub on top of `Kubernetes <https://k8s.io>`_. This
+  can scale to large number of machines & users.
+* `The Littlest JupyterHub <http://tljh.jupyter.org>`_, for an easy
+  to set up & run JupyterHub supporting 1-100 users on a single machine.
 
 Installation Guide
 ------------------
@@ -113,23 +108,16 @@ API Reference
 
    api/index
 
-RBAC Reference
---------------
-
-.. toctree::
-   :maxdepth: 2
-
-   rbac/index
-
 Contributing
 ------------
 
-We welcome you to contribute to JupyterHub in ways that are most exciting
-& useful to you. We value documentation, testing, bug reporting & code equally
+We want you to contribute to JupyterHub in ways that are most exciting
+& useful to you. We value documentation, testing, bug reporting & code equally,
 and are glad to have your contributions in whatever form you wish :)
 
-Our `Code of Conduct <https://github.com/jupyter/governance/blob/HEAD/conduct/code_of_conduct.md>`_ and `reporting guidelines <https://github.com/jupyter/governance/blob/HEAD/conduct/reporting_online.md>`_
-help keep our community welcoming to as many people as possible.
+Our `Code of Conduct <https://github.com/jupyter/governance/blob/master/conduct/code_of_conduct.md>`_
+(`reporting guidelines <https://github.com/jupyter/governance/blob/master/conduct/reporting_online.md>`_)
+helps keep our community welcoming to as many people as possible.
 
 .. toctree::
    :maxdepth: 2
@@ -153,9 +141,10 @@ Indices and tables
 
 Questions? Suggestions?
 =======================
-All questions and suggestions are welcome. Please feel free to use our `Jupyter Discourse Forum <https://discourse.jupyter.org/>`_ to contact our team.
 
-Looking forward to hearing from you!
+- `Jupyter mailing list <https://groups.google.com/forum/#!forum/jupyter>`_
+- `Jupyter website <https://jupyter.org>`_
 
 .. _JupyterHub: https://github.com/jupyterhub/jupyterhub
 .. _Jupyter notebook: https://jupyter-notebook.readthedocs.io/en/latest/
+.. _REST API: http://petstore.swagger.io/?url=https://raw.githubusercontent.com/jupyterhub/jupyterhub/master/docs/rest-api.yml#!/default

docs/source/installation-guide-hard.md

@@ -0,0 +1,347 @@
+# Install JupyterHub and JupyterLab from the ground up
+
+The combination of [JupyterHub](https://jupyterhub.readthedocs.io) and [JupyterLab](https://jupyterlab.readthedocs.io)
+is a great way to make shared computing resources available to a group.
+
+These instructions are a guide for a manual, 'bare metal' install of [JupyterHub](https://jupyterhub.readthedocs.io)
+and [JupyterLab](https://jupyterlab.readthedocs.io). This is ideal for running on a single server: build a beast
+of a machine and share it within your lab, or use a virtual machine from any VPS or cloud provider.
+
+This guide has similar goals to [The Littlest JupyterHub](https://the-littlest-jupyterhub.readthedocs.io) setup
+script. However, instead of bundling all these step for you into one installer, we will perform every step manually.
+This makes it easy to customize any part (e.g. if you want to run other services on the same system and need to make them
+work together), as well as giving you full control and understanding of your setup.
+
+
+## Prerequisites
+
+Your own server with administrator (root) access. This could be a local machine, a remotely hosted one, or a cloud instance
+or VPS. Each user who will access JupyterHub should have a standard user account on the machine. The install will be done
+through the command line - useful if you log into your machine remotely using SSH.
+
+This tutorial was tested on **Ubuntu 18.04**. No other Linux distributions have been tested, but the instructions
+should be reasonably straightforward to adapt.
+
+
+## Goals
+
+JupyterLab enables access to a multiple 'kernels', each one being a given environment for a given language. The most
+common is a Python environment, for scientific computing usually one managed by the `conda` package manager.
+
+This guide will set up JupyterHub and JupyterLab seperately from the Python environment. In other words, we treat
+JupyterHub+JupyterLab as a 'app' or webservice, which will connect to the kernels available on the system. Specifically:
+
+- We will create an installation of JupyterHub and JupyterLab using a virtualenv under `/opt` using the system Python.
+
+- We will install conda globally.
+
+- We will create a shared conda environment which can be used (but not modified) by all users.
+
+- We will show how users can create their own private conda environments, where they can install whatever they like.
+
+
+The default JupyterHub Authenticator uses PAM to authenticate system users with their username and password. One can
+[choose the authenticator](https://jupyterhub.readthedocs.io/en/stable/reference/authenticators.html#authenticators)
+that best suits their needs. In this guide we will use the default Authenticator because it makes it easy for everyone to manage data
+in their home folder and to mix and match different services and access methods (e.g. SSH) which all work using the
+Linux system user accounts. Therefore, each user of JupyterHub will need a standard system user account.
+
+Another goal of this guide is to use system provided packages wherever possible. This has the advantage that these packages
+get automatic patches and security updates (be sure to turn on automatic updates in Ubuntu). This means less maintenance
+work and a more reliable system.
+
+## Part 1: JupyterHub and JupyterLab
+
+### Setup the JupyterHub and JupyterLab in a virtual environment
+
+First we create a virtual environment under '/opt/jupyterhub'. The '/opt' folder is where apps not belonging to the operating
+system are [commonly installed](https://unix.stackexchange.com/questions/11544/what-is-the-difference-between-opt-and-usr-local).
+Both jupyterlab and jupyterhub will be installed into this virtualenv. Create it with the command:
+
+```sh
+sudo python3 -m venv /opt/jupyterhub/
+```
+
+Now we use pip to install the required Python packages into the new virtual environment. Be sure to install
+`wheel` first. Since we are separating the user interface from the computing kernels, we don't install
+any Python scientific packages here. The only exception is `ipywidgets` because this is needed to allow connection
+between interactive tools running in the kernel and the user interface.
+
+Note that we use `/opt/jupyterhub/bin/python3 -m pip install` each time - this [makes sure](https://snarky.ca/why-you-should-use-python-m-pip/)
+that the packages are installed to the correct virtual environment.
+
+Perform the install using the following commands:
+
+```sh
+sudo /opt/jupyterhub/bin/python3 -m pip install wheel
+sudo /opt/jupyterhub/bin/python3 -m pip install jupyterhub jupyterlab
+sudo /opt/jupyterhub/bin/python3 -m pip install ipywidgets
+```
+
+JupyterHub also currently defaults to requiring `configurable-http-proxy`, which needs `nodejs` and `npm`. The versions
+of these available in Ubuntu therefore need to be installed first (they are a bit old but this is ok for our needs):
+
+```sh
+sudo apt install nodejs npm
+```
+
+Then install `configurable-http-proxy`:
+
+```sh
+sudo npm install -g configurable-http-proxy
+```
+
+### Create the configuration for JupyterHub
+
+Now we start creating configuration files. To keep everything together, we put all the configuration into the folder
+created for the virtualenv, under `/opt/jupyterhub/etc/`. For each thing needing configuration, we will create a further
+subfolder and necessary files.
+
+First create the folder for the JupyterHub configuration and navigate to it:
+
+```sh
+sudo mkdir -p /opt/jupyterhub/etc/jupyterhub/
+cd /opt/jupyterhub/etc/jupyterhub/
+```
+Then generate the default configuration file
+
+```sh
+sudo /opt/jupyterhub/bin/jupyterhub --generate-config
+```
+This will produce the default configuration file `/opt/jupyterhub/etc/jupyterhub/jupyterhub_config.py`
+
+You will need to edit the configuration file to make the JupyterLab interface by the default.
+Set the following configuration option in your `jupyterhub_config.py` file:
+
+```python
+c.Spawner.default_url = '/lab'
+```
+
+Further configuration options may be found in the documentation.
+
+### Setup Systemd service
+
+We will setup JupyterHub to run as a system service using Systemd (which is responsible for managing all services and
+servers that run on startup in Ubuntu). We will create a service file in a suitable location in the virtualenv folder
+and then link it to the system services. First create the folder for the service file:
+
+```sh
+sudo mkdir -p /opt/jupyterhub/etc/systemd
+```
+
+Then create the following text file using your [favourite editor](https://micro-editor.github.io/) at
+```sh
+/opt/jupyterhub/etc/systemd/jupyterhub.service
+```
+
+Paste the following service unit definition into the file:
+
+```
+[Unit]
+Description=JupyterHub
+After=syslog.target network.target
+
+[Service]
+User=root
+Environment="PATH=/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/opt/jupyterhub/bin"
+ExecStart=/opt/jupyterhub/bin/jupyterhub -f /opt/jupyterhub/etc/jupyterhub/jupyterhub_config.py
+
+[Install]
+WantedBy=multi-user.target
+```
+
+This sets up the environment to use the virtual environment we created, tells Systemd how to start jupyterhub using
+the configuration file we created, specifies that jupyterhub will be started as the `root` user (needed so that it can
+start jupyter on behalf of other logged in users), and specifies that jupyterhub should start on boot after the network
+is enabled.
+
+Finally, we need to make systemd aware of our service file. First we symlink our file into systemd's directory:
+
+```sh
+sudo ln -s /opt/jupyterhub/etc/systemd/jupyterhub.service /etc/systemd/system/jupyterhub.service
+```
+
+Then tell systemd to reload its configuration files
+
+```sh
+sudo systemctl daemon-reload
+```
+
+And finally enable the service
+
+```sh
+sudo systemctl enable jupyterhub.service
+```
+
+The service will start on reboot, but we can start it straight away using:
+
+```sh
+sudo systemctl start jupyterhub.service
+```
+
+...and check that it's running using:
+
+```sh
+sudo systemctl status jupyterhub.service
+```
+
+You should now be already be able to access jupyterhub using `<your servers ip>:8000` (assuming you haven't already set
+up a firewall or something). However, when you log in the jupyter notebooks will be trying to use the Python virtualenv
+that was created to install JupyterHub, this is not what we want. So on to part 2
+
+## Part 2: Conda environments
+
+### Install conda for the whole system
+
+We will use `conda` to manage Python environments. We will install the officially maintained `conda` packages for Ubuntu,
+this means they will get automatic updates with the rest of the system. Setup repo for the official Conda debian packages,
+instructions are copied from [here](https://docs.conda.io/projects/conda/en/latest/user-guide/install/rpm-debian.html):
+
+Install Anacononda public gpg key to trusted store
+```sh
+curl https://repo.anaconda.com/pkgs/misc/gpgkeys/anaconda.asc | gpg --dearmor > conda.gpg
+sudo install -o root -g root -m 644 conda.gpg /etc/apt/trusted.gpg.d/
+```
+
+Add Debian repo
+
+```sh
+echo "deb [arch=amd64] https://repo.anaconda.com/pkgs/misc/debrepo/conda stable main" | sudo tee /etc/apt/sources.list.d/conda.list
+```
+
+Install conda
+
+```sh
+sudo apt update
+sudo apt install conda
+```
+
+This will install conda into the folder `/opt/conda/`, with the conda command available at `/opt/conda/bin/conda`.
+
+Finally, we can make conda more easily available to users by symlinking the conda shell setup script to the profile
+'drop in' folder so that it gets run on login
+
+```sh
+sudo ln -s /opt/conda/etc/profile.d/conda.sh /etc/profile.d/conda.sh
+```
+
+### Install a default conda environment for all users
+
+First create a folder for conda envs (might exist already):
+```sh
+sudo mkdir /opt/conda/envs/
+```
+
+Then create a conda environment to your liking within that folder. Here we have called it 'python' because it will
+be the obvious default - call it whatever you like. You can install whatever you like into this environment, but you MUST at least install `ipykernel`.
+
+```sh
+sudo /opt/conda/bin/conda create --prefix /opt/conda/envs/python python=3.7 ipykernel
+```
+
+Once your env is set up as desired, make it visible to Jupyter by installing the kernel spec. There are two options here:
+
+1 ) Install into the JupyterHub virtualenv - this ensures it overrides the default python version. It will only be visible
+to the JupyterHub installation we have just created. This is useful to avoid conda environments appearing where they are not expected.
+
+```sh
+sudo /opt/conda/envs/python/bin/python -m ipykernel install --prefix=/opt/jupyterhub/ --name 'python' --display-name "Python (default)"
+```
+
+2 ) Install it system-wide by putting it into `/usr/local`. It will be visible to any parallel install of JupyterHub or
+JupyterLab, and will persist even if you later delete or modify the JupyterHub installation. This is useful if the kernels
+might be used by other services, or if you want to modify the JupyterHub installation independently from the conda environments.
+
+```sh
+sudo /opt/conda/envs/python/bin/python -m ipykernel install --prefix /usr/local/ --name 'python' --display-name "Python (default)"
+````
+
+### Setting up users' own conda environments
+
+There is relatively little for the administrator to do here, as users will have to set up their own environments using the shell.
+On login they should run `conda init` or  `/opt/conda/bin/conda`. The can then use conda to set up their environment,
+although they must also install `ipykernel`. Once done, they can enable their kernel using:
+
+```sh
+/path/to/kernel/env/bin/python -m ipykernel install --name 'python-my-env' --display-name "Python My Env"
+```
+
+This will place the kernel spec into their home folder, where Jupyter will look for it on startup.
+
+
+## Setting up a reverse proxy
+
+The guide so far results in JupyterHub running on port 8000. It is not generally advisable to run open web services in
+this way - instead, use a reverse proxy running on standard HTTP/HTTPS ports.
+
+> **Important**: Be aware of the security implications especially if you are running a server that is accessible from the open internet
+> i.e. not protected within an institutional intranet or private home/office network. You should set up a firewall and
+> HTTPS encryption, which is outside of the scope of this guide. For HTTPS consider using [LetsEncrypt](https://letsencrypt.org/)
+> or setting up a [self-signed certificate](https://www.digitalocean.com/community/tutorials/how-to-create-a-self-signed-ssl-certificate-for-nginx-in-ubuntu-18-04).
+> Firewalls may be set up using `ufw` or `firewalld` and combined with `fail2ban`.
+
+### Using Nginx
+Nginx is a mature and established web server and reverse proxy and is easy to install using `sudo apt install nginx`.
+Details on using Nginx as a reverse proxy can be found elsewhere. Here, we will only outline the additional steps needed
+to setup JupyterHub with Nginx and host it at a given URL e.g. `<your-server-ip-or-url>/jupyter`.
+This could be useful for example if you are running several services or web pages on the same server.
+
+To achieve this needs a few tweaks to both the JupyterHub configuration and the Nginx config. First, edit the
+configuration file `/opt/jupyterhub/etc/jupyterhub/jupyterhub_config.py` and add the line:
+
+```python
+c.JupyterHub.bind_url = 'http://:8000/jupyter'
+```
+
+where `/jupyter` will be the relative URL of the JupyterHub.
+
+Now Nginx must be configured with a to pass all traffic from `/jupyter` to the the local address `127.0.0.1:8000`.
+Add the following snippet to your nginx configuration file (e.g. `/etc/nginx/sites-available/default`).
+
+```
+  location /jupyter/ {
+    # NOTE important to also set base url of jupyterhub to /jupyter in its config
+    proxy_pass http://127.0.0.1:8000;
+
+    proxy_redirect   off;
+    proxy_set_header X-Real-IP $remote_addr;
+    proxy_set_header Host $host;
+    proxy_set_header X-Forwarded-For $proxy_add_x_forwarded_for;
+    proxy_set_header X-Forwarded-Proto $scheme;
+
+    # websocket headers
+    proxy_set_header Upgrade $http_upgrade;
+    proxy_set_header Connection $connection_upgrade;
+
+  }
+```
+
+Also add this snippet before the *server* block:
+
+```
+map $http_upgrade $connection_upgrade {
+        default upgrade;
+        '' close;
+    }
+```
+
+Nginx will not run if there are errors in the configuration, check your configuration using:
+
+```sh
+nginx -t
+```
+
+If there are no errors, you can restart the Nginx service for the new configuration to take effect.
+
+```sh
+sudo systemctl restart nginx.service
+```
+
+
+## Getting started using your new JupyterHub
+
+Once you have setup JupyterHub and Nginx proxy as described, you can browse to your JupyterHub IP or URL
+(e.g. if your server IP address is `123.456.789.1` and you decided to host JupyterHub at the `/jupyter` URL, browse
+to `123.456.789.1/jupyter`). You will find a login page where you enter your Linux username and password. On login
+you will be presented with the JupyterLab interface, with the file browser pane showing the contents of your users'
+home directory on the server.

docs/source/installation-guide-hard.rst

@@ -1,6 +0,0 @@
-:orphan:
-
-JupyterHub the hard way
-=======================
-
-This guide has moved to https://github.com/jupyterhub/jupyterhub-the-hard-way/blob/HEAD/docs/installation-guide-hard.md

docs/source/installation-guide.rst

@@ -11,3 +11,4 @@ running on your own infrastructure.
    quickstart
    quickstart-docker
    installation-basics
+   installation-guide-hard

docs/source/quickstart-docker.rst

@@ -1,69 +1,49 @@
-Install JupyterHub with Docker
-==============================
+Using Docker
+============
 
+.. important::
 
-The JupyterHub `docker image <https://hub.docker.com/r/jupyterhub/jupyterhub/>`_ is the fastest way to set up Jupyterhub in your local development environment.
+   We highly recommend following the `Zero to JupyterHub`_ tutorial for
+   installing JupyterHub.
+
+Alternate installation using Docker
+-----------------------------------
+
+A ready to go `docker image <https://hub.docker.com/r/jupyterhub/jupyterhub/>`_
+gives a straightforward deployment of JupyterHub.
 
 .. note::
+
     This ``jupyterhub/jupyterhub`` docker image is only an image for running
     the Hub service itself. It does not provide the other Jupyter components,
     such as Notebook installation, which are needed by the single-user servers.
     To run the single-user servers, which may be on the same system as the Hub or
-    not, `JupyterLab <https://jupyterlab.readthedocs.io/>`_ or Jupyter Notebook must be installed.
+    not, Jupyter Notebook version 4 or greater must be installed.
 
+Starting JupyterHub with docker
+-------------------------------
 
-.. important::
-    We strongly recommend that you follow the `Zero to JupyterHub`_ tutorial to
-    install JupyterHub.
-   
-   
-Prerequisites
--------------
-You should have `Docker`_ installed on a Linux/Unix based system.
-
-
-Run the Docker Image
---------------------
-
-To pull the latest JupyterHub image and start the `jupyterhub` container, run this command in your terminal.
-::
+The JupyterHub docker image can be started with the following command::
 
     docker run -d -p 8000:8000 --name jupyterhub jupyterhub/jupyterhub jupyterhub
 
+This command will create a container named ``jupyterhub`` that you can
+**stop and resume** with ``docker stop/start``.
 
-This command exposes the Jupyter container on port:8000. Navigate to `http://localhost:8000` in a web browser to access the JupyterHub console.
-
-You can stop and resume the container by running `docker stop` and `docker start` respectively.
-::
-
-    # find the container id
-    docker ps
-
-    # stop the running container
-    docker stop  <container-id>
-
-    # resume the paused container
-    docker start <container-id>
-
+The Hub service will be listening on all interfaces at port 8000, which makes
+this a good choice for **testing JupyterHub on your desktop or laptop**.
 
 If you want to run docker on a computer that has a public IP then you should
 (as in MUST) **secure it with ssl** by adding ssl options to your docker
-configuration or using an ssl enabled proxy.
+configuration or using a ssl enabled proxy.
 
 `Mounting volumes <https://docs.docker.com/engine/admin/volumes/volumes/>`_
-enables you to persist and store the data generated by the docker container, even when you stop the container. 
-The persistent data can be stored on the host system, outside the container.
+will allow you to store data outside the docker image (host system) so it will
+be persistent, even when you start a new image.
 
-
-Create System Users
--------------------
-
-Spawn a root shell in your docker container by running this command in the terminal.::
-
-    docker exec -it jupyterhub bash
-
-The created accounts will be used for authentication in JupyterHub's default
+The command ``docker exec -it jupyterhub bash`` will spawn a root shell in your
+docker container. You can use the root shell to **create system users in the container**.
+These accounts will be used for authentication in JupyterHub's default
 configuration.
 
 .. _Zero to JupyterHub: https://zero-to-jupyterhub.readthedocs.io/en/latest/
-.. _Docker: https://www.docker.com/

docs/source/quickstart.md

@@ -4,27 +4,27 @@
 
 Before installing JupyterHub, you will need:
 
-- a Linux/Unix-based system
-- [Python](https://www.python.org/downloads/) 3.6 or greater. An understanding
-  of using [`pip`](https://pip.pypa.io) or
+- a Linux/Unix based system
+- [Python](https://www.python.org/downloads/) 3.5 or greater. An understanding
+  of using [`pip`](https://pip.pypa.io/en/stable/) or
   [`conda`](https://conda.io/docs/get-started.html) for
   installing Python packages is helpful.
 - [nodejs/npm](https://www.npmjs.com/). [Install nodejs/npm](https://docs.npmjs.com/getting-started/installing-node),
   using your operating system's package manager.
 
-  - If you are using **`conda`**, the nodejs and npm dependencies will be installed for
+  * If you are using **`conda`**, the nodejs and npm dependencies will be installed for
     you by conda.
 
-  - If you are using **`pip`**, install a recent version of
+  * If you are using **`pip`**, install a recent version of
     [nodejs/npm](https://docs.npmjs.com/getting-started/installing-node).
     For example, install it on Linux (Debian/Ubuntu) using:
 
     ```
-    sudo apt-get install nodejs npm
+    sudo apt-get install npm nodejs-legacy
     ```
           
-    [nodesource][] is a great resource to get more recent versions of the nodejs runtime,
-    if your system package manager only has an old version of Node.js (e.g. 10 or older).
+    The `nodejs-legacy` package installs the `node` executable and is currently
+    required for npm to work on Debian/Ubuntu.
 
 - A [pluggable authentication module (PAM)](https://en.wikipedia.org/wiki/Pluggable_authentication_module) 
   to use the [default Authenticator](./getting-started/authenticators-users-basics.md).
@@ -33,17 +33,11 @@ Before installing JupyterHub, you will need:
 - TLS certificate and key for HTTPS communication
 - Domain name
 
-[nodesource]: https://github.com/nodesource/distributions#table-of-contents
-
 Before running the single-user notebook servers (which may be on the same
 system as the Hub or not), you will need:
 
-- [JupyterLab][] version 3 or greater,
-  or [Jupyter Notebook][]
-  4 or greater.
-
-[jupyterlab]: https://jupyterlab.readthedocs.io
-[jupyter notebook]: https://jupyter.readthedocs.io/en/latest/install.html
+- [Jupyter Notebook](https://jupyter.readthedocs.io/en/latest/install.html)
+  version 4 or greater
 
 ## Installation
 
@@ -54,14 +48,14 @@ JupyterHub can be installed with `pip` (and the proxy with `npm`) or `conda`:
 ```bash
 python3 -m pip install jupyterhub
 npm install -g configurable-http-proxy
-python3 -m pip install jupyterlab notebook  # needed if running the notebook servers in the same environment
+python3 -m pip install notebook  # needed if running the notebook servers locally
 ```
 
 **conda** (one command installs jupyterhub and proxy):
 
 ```bash
 conda install -c conda-forge jupyterhub  # installs jupyterhub and proxy
-conda install jupyterlab notebook  # needed if running the notebook servers in the same environment
+conda install notebook  # needed if running the notebook servers locally
 ```
 
 Test your installation. If installed, these commands should return the packages'
@@ -80,16 +74,16 @@ To start the Hub server, run the command:
 jupyterhub
 ```
 
-Visit `http://localhost:8000` in your browser, and sign in with your Unix
+Visit `https://localhost:8000` in your browser, and sign in with your unix
 credentials.
 
 To **allow multiple users to sign in** to the Hub server, you must start
-`jupyterhub` as a _privileged user_, such as root:
+`jupyterhub` as a *privileged user*, such as root:
 
 ```bash
 sudo jupyterhub
 ```
 
 The [wiki](https://github.com/jupyterhub/jupyterhub/wiki/Using-sudo-to-run-JupyterHub-without-root-privileges)
-describes how to run the server as a _less privileged user_. This requires
+describes how to run the server as a *less privileged user*. This requires
 additional configuration of the system.

docs/source/rbac/generate-scope-table.py

@@ -1,161 +0,0 @@
-"""
-This script updates two files with the RBAC scope descriptions found in
-`scopes.py`.
-
-The files are:
-
-    1. scope-table.md
-
-       This file is git ignored and referenced by the documentation.
-
-    2. rest-api.yml
-
-       This file is JupyterHub's REST API schema. Both a version and the RBAC
-       scopes descriptions are updated in it.
-"""
-import os
-from collections import defaultdict
-from pathlib import Path
-from subprocess import run
-
-from pytablewriter import MarkdownTableWriter
-from ruamel.yaml import YAML
-
-from jupyterhub import __version__
-from jupyterhub.scopes import scope_definitions
-
-HERE = os.path.abspath(os.path.dirname(__file__))
-DOCS = Path(HERE).parent.parent.absolute()
-REST_API_YAML = DOCS.joinpath("source", "_static", "rest-api.yml")
-SCOPE_TABLE_MD = Path(HERE).joinpath("scope-table.md")
-
-
-class ScopeTableGenerator:
-    def __init__(self):
-        self.scopes = scope_definitions
-
-    @classmethod
-    def create_writer(cls, table_name, headers, values):
-        writer = MarkdownTableWriter()
-        writer.table_name = table_name
-        writer.headers = headers
-        writer.value_matrix = values
-        writer.margin = 1
-        return writer
-
-    def _get_scope_relationships(self):
-        """Returns a tuple of dictionary of all scope-subscope pairs and a list of just subscopes:
-
-        ({scope: subscope}, [subscopes])
-
-        used for creating hierarchical scope table in _parse_scopes()
-        """
-        pairs = []
-        for scope, data in self.scopes.items():
-            subscopes = data.get('subscopes')
-            if subscopes is not None:
-                for subscope in subscopes:
-                    pairs.append((scope, subscope))
-            else:
-                pairs.append((scope, None))
-        subscopes = [pair[1] for pair in pairs]
-        pairs_dict = defaultdict(list)
-        for scope, subscope in pairs:
-            pairs_dict[scope].append(subscope)
-        return pairs_dict, subscopes
-
-    def _get_top_scopes(self, subscopes):
-        """Returns a list of highest level scopes
-        (not a subscope of any other scopes)"""
-        top_scopes = []
-        for scope in self.scopes.keys():
-            if scope not in subscopes:
-                top_scopes.append(scope)
-        return top_scopes
-
-    def _parse_scopes(self):
-        """Returns a list of table rows where row:
-        [indented scopename string, scope description string]"""
-        scope_pairs, subscopes = self._get_scope_relationships()
-        top_scopes = self._get_top_scopes(subscopes)
-
-        table_rows = []
-        md_indent = "   "
-
-        def _add_subscopes(table_rows, scopename, depth=0):
-            description = self.scopes[scopename]['description']
-            doc_description = self.scopes[scopename].get('doc_description', '')
-            if doc_description:
-                description = doc_description
-            table_row = [f"{md_indent * depth}`{scopename}`", description]
-            table_rows.append(table_row)
-            for subscope in scope_pairs[scopename]:
-                if subscope:
-                    _add_subscopes(table_rows, subscope, depth + 1)
-
-        for scope in top_scopes:
-            _add_subscopes(table_rows, scope)
-
-        return table_rows
-
-    def write_table(self):
-        """Generates the RBAC scopes reference documentation as a markdown table
-        and writes it to the .gitignored `scope-table.md`."""
-        filename = SCOPE_TABLE_MD
-        table_name = ""
-        headers = ["Scope", "Grants permission to:"]
-        values = self._parse_scopes()
-        writer = self.create_writer(table_name, headers, values)
-
-        title = "Table 1. Available scopes and their hierarchy"
-        content = f"{title}\n{writer.dumps()}"
-        with open(filename, 'w') as f:
-            f.write(content)
-        print(f"Generated {filename}.")
-        print(
-            "Run 'make clean' before 'make html' to ensure the built scopes.html contains latest scope table changes."
-        )
-
-    def write_api(self):
-        """Loads `rest-api.yml` and writes it back with a dynamically set
-        JupyterHub version field and list of RBAC scopes descriptions from
-        `scopes.py`."""
-        filename = REST_API_YAML
-
-        yaml = YAML(typ="rt")
-        yaml.preserve_quotes = True
-        yaml.indent(mapping=2, offset=2, sequence=4)
-
-        scope_dict = {}
-        with open(filename) as f:
-            content = yaml.load(f.read())
-
-        content["info"]["version"] = __version__
-        for scope in self.scopes:
-            description = self.scopes[scope]['description']
-            doc_description = self.scopes[scope].get('doc_description', '')
-            if doc_description:
-                description = doc_description
-            scope_dict[scope] = description
-        content['components']['securitySchemes']['oauth2']['flows'][
-            'authorizationCode'
-        ]['scopes'] = scope_dict
-
-        with open(filename, 'w') as f:
-            yaml.dump(content, f)
-
-        run(
-            ['pre-commit', 'run', 'prettier', '--files', filename],
-            cwd=HERE,
-            check=False,
-        )
-
-
-def main():
-    table_generator = ScopeTableGenerator()
-    table_generator.write_table()
-    table_generator.write_api()
-
-
-if __name__ == "__main__":
-    main()

docs/source/rbac/index.md

@@ -1,39 +0,0 @@
-(RBAC)=
-
-# JupyterHub RBAC
-
-Role Based Access Control (RBAC) in JupyterHub serves to provide fine grained control of access to Jupyterhub's API resources.
-
-RBAC is new in JupyterHub 2.0.
-
-## Motivation
-
-The JupyterHub API requires authorization to access its APIs.
-This ensures that an arbitrary user, or even an unauthenticated third party, are not allowed to perform such actions.
-For instance, the behaviour prior to adoption of RBAC is that creating or deleting users requires _admin rights_.
-
-The prior system is functional, but lacks flexibility. If your Hub serves a number of users in different groups, you might want to delegate permissions to other users or automate certain processes.
-Prior to RBAC, appointing a 'group-only admin' or a bot that culls idle servers, requires granting full admin rights to all actions. This poses a risk of the user or service intentionally or unintentionally accessing and modifying any data within the Hub and violates the [principle of least privilege](https://en.wikipedia.org/wiki/Principle_of_least_privilege).
-
-To remedy situations like this, JupyterHub is transitioning to an RBAC system. By equipping users, groups and services with _roles_ that supply them with a collection of permissions (_scopes_), administrators are able to fine-tune which parties are granted access to which resources.
-
-## Definitions
-
-**Scopes** are specific permissions used to evaluate API requests. For example: the API endpoint `users/servers`, which enables starting or stopping user servers, is guarded by the scope `servers`.
-
-Scopes are not directly assigned to requesters. Rather, when a client performs an API call, their access will be evaluated based on their assigned roles.
-
-**Roles** are collections of scopes that specify the level of what a client is allowed to do. For example, a group administrator may be granted permission to control the servers of group members, but not to create, modify or delete group members themselves.
-Within the RBAC framework, this is achieved by assigning a role to the administrator that covers exactly those privileges.
-
-## Technical Overview
-
-```{toctree}
-:maxdepth: 2
-
-roles
-scopes
-use-cases
-tech-implementation
-upgrade
-```

docs/source/rbac/roles.md

@@ -1,159 +0,0 @@
-# Roles
-
-JupyterHub provides four (4) roles that are available by default:
-
-```{admonition} **Default roles**
-- `user` role provides a {ref}`default user scope <default-user-scope-target>` `self` that grants access to the user's own resources.
-- `admin` role contains all available scopes and grants full rights to all actions. This role **cannot be edited**.
-- `token` role provides a {ref}`default token scope <default-token-scope-target>` `inherit` that resolves to the same permissions as the owner of the token has.
-- `server` role allows for posting activity of "itself" only.
-
-**These roles cannot be deleted.**
-```
-
-We call these 'default' roles because they are available by default and have a default collection of scopes.
-However, you can define the scopes associated with each role (excluding the admin role) to suit your needs,
-as seen [below](overriding-default-roles).
-
-The `user`, `admin`, and `token` roles, by default, all preserve the permissions prior to Role-based Access Control (RBAC).
-Only the `server` role is changed from pre-2.0, to reduce its permissions to activity-only
-instead of the default of a full access token.
-
-Additional custom roles can also be defined (see {ref}`define-role-target`).
-Roles can be assigned to the following entities:
-
-- Users
-- Services
-- Groups
-
-An entity can have zero, one, or multiple roles, and there are no restrictions on which roles can be assigned to which entity. Roles can be added to or removed from entities at any time.
-
-**Users** \
-When a new user gets created, they are assigned their default role, `user`. Additionally, if the user is created with admin privileges (via `c.Authenticator.admin_users` in `jupyterhub_config.py` or `admin: true` via API), they will be also granted `admin` role. If existing user's admin status changes via API or `jupyterhub_config.py`, their default role will be updated accordingly (after next startup for the latter).
-
-**Services** \
-Services do not have a default role. Services without roles have no access to the guarded API end-points. So, most services will require assignment of a role in order to function.
-
-**Groups** \
-A group does not require any role, and has no roles by default. If a user is a member of a group, they automatically inherit any of the group's permissions (see {ref}`resolving-roles-scopes-target` for more details). This is useful for assigning a set of common permissions to several users.
-
-**Tokens** \
-A token’s permissions are evaluated based on their owning entity. Since a token is always issued for a user or service, it can never have more permissions than its owner. If no specific scopes are requested for a new token, the token is assigned the scopes of the `token` role.
-
-(define-role-target)=
-
-## Defining Roles
-
-Roles can be defined or modified in the configuration file as a list of dictionaries. An example:
-
-% TODO: think about loading users into roles if membership has been changed via API.
-% What should be the result?
-
-```python
-# in jupyterhub_config.py
-
-c.JupyterHub.load_roles = [
- {
-   'name': 'server-rights',
-   'description': 'Allows parties to start and stop user servers',
-   'scopes': ['servers'],
-   'users': ['alice', 'bob'],
-   'services': ['idle-culler'],
-   'groups': ['admin-group'],
- }
-]
-```
-
-The role `server-rights` now allows the starting and stopping of servers by any of the following:
-
-- users `alice` and `bob`
-- the service `idle-culler`
-- any member of the `admin-group`.
-
-```{attention}
-Tokens cannot be assigned roles through role definition but may be assigned specific roles when requested via API (see {ref}`requesting-api-token-target`).
-```
-
-Another example:
-
-```python
-# in jupyterhub_config.py
-
-c.JupyterHub.load_roles = [
- {
-   'description': 'Read-only user models',
-   'name': 'reader',
-   'scopes': ['read:users'],
-   'services': ['external'],
-   'users': ['maria', 'joe']
- }
-]
-```
-
-The role `reader` allows users `maria` and `joe` and service `external` to read (but not modify) any user’s model.
-
-```{admonition} Requirements
-:class: warning
-In a role definition, the `name` field is required, while all other fields are optional.\
-**Role names must:**
-- be 3 - 255 characters
-- use ascii lowercase, numbers, 'unreserved' URL punctuation `-_.~`
-- start with a letter
-- end with letter or number.
-
-`users`, `services`, and `groups` only accept objects that already exist in the database or are defined previously in the file.
-It is not possible to implicitly add a new user to the database by defining a new role.
-```
-
-If no scopes are defined for _new role_, JupyterHub will raise a warning. Providing non-existing scopes will result in an error.
-
-In case the role with a certain name already exists in the database, its definition and scopes will be overwritten. This holds true for all roles except the `admin` role, which cannot be overwritten; an error will be raised if trying to do so. All the role bearers permissions present in the definition will change accordingly.
-
-(overriding-default-roles)=
-
-### Overriding Default Roles
-
-Role definitions can include those of the "default" roles listed above (admin excluded),
-if the default scopes associated with those roles do not suit your deployment.
-For example, to specify what permissions the $JUPYTERHUB_API_TOKEN issued to all single-user servers
-has,
-define the `server` role.
-
-To restore the JupyterHub 1.x behavior of servers being able to do anything their owners can do,
-use the scope `inherit` (for 'inheriting' the owner's permissions):
-
-```python
-c.JupyterHub.load_roles = [
- {
-   'name': 'server',
-   'scopes': ['inherit'],
- }
-]
-```
-
-or, better yet, identify the specific [scopes][] you want server environments to have access to.
-
-[scopes]: available-scopes-target
-
-If you don't want to get too detailed,
-one option is the `self` scope,
-which will have no effect on non-admin users,
-but will restrict the token issued to admin user servers to only have access to their own resources,
-instead of being able to take actions on behalf of all other users.
-
-```python
-c.JupyterHub.load_roles = [
- {
-   'name': 'server',
-   'scopes': ['self'],
- }
-]
-```
-
-(removing-roles-target)=
-
-## Removing Roles
-
-Only the entities present in the role definition in the `jupyterhub_config.py` remain the role bearers. If a user, service or group is removed from the role definition, they will lose the role on the next startup.
-
-Once a role is loaded, it remains in the database until removing it from the `jupyterhub_config.py` and restarting the Hub. All previously defined role bearers will lose the role and associated permissions. Default roles, even if previously redefined through the config file and removed, will not be deleted from the database.

docs/source/rbac/scopes.md

@@ -1,303 +0,0 @@
-# Scopes in JupyterHub
-
-A scope has a syntax-based design that reveals which resources it provides access to. Resources are objects with a type, associated data, relationships to other resources, and a set of methods that operate on them (see [RESTful API](https://restful-api-design.readthedocs.io/en/latest/resources.html) documentation for more information).
-
-`<resource>` in the RBAC scope design refers to the resource name in the [JupyterHub's API](../reference/rest-api.rst) endpoints in most cases. For instance, `<resource>` equal to `users` corresponds to JupyterHub's API endpoints beginning with _/users_.
-
-(scope-conventions-target)=
-
-## Scope conventions
-
-- `<resource>` \
-  The top-level `<resource>` scopes, such as `users` or `groups`, grant read, write, and list permissions to the resource itself as well as its sub-resources. For example, the scope `users:activity` is included in the scope `users`.
-
-- `read:<resource>` \
-  Limits permissions to read-only operations on single resources.
-
-- `list:<resource>` \
-  Read-only access to listing endpoints.
-  Use `read:<resource>:<subresource>` to control what fields are returned.
-
-- `admin:<resource>` \
-  Grants additional permissions such as create/delete on the corresponding resource in addition to read and write permissions.
-
-- `access:<resource>` \
-  Grants access permissions to the `<resource>` via API or browser.
-
-- `<resource>:<subresource>` \
-  The {ref}`vertically filtered <vertical-filtering-target>` scopes provide access to a subset of the information granted by the `<resource>` scope. E.g., the scope `users:activity` only provides permission to post user activity.
-
-- `<resource>!<object>=<objectname>` \
-  {ref}`horizontal-filtering-target` is implemented by the `!<object>=<objectname>`scope structure. A resource (or sub-resource) can be filtered based on `user`, `server`, `group` or `service` name. For instance, `<resource>!user=charlie` limits access to only return resources of user `charlie`. \
-  Only one filter per scope is allowed, but filters for the same scope have an additive effect; a larger filter can be used by supplying the scope multiple times with different filters.
-
-By adding a scope to an existing role, all role bearers will gain the associated permissions.
-
-## Metascopes
-
-Metascopes do not follow the general scope syntax. Instead, a metascope resolves to a set of scopes, which can refer to different resources, based on their owning entity. In JupyterHub, there are currently two metascopes:
-
-1. default user scope `self`, and
-2. default token scope `inherit`.
-
-(default-user-scope-target)=
-
-### Default user scope
-
-Access to the user's own resources and subresources is covered by metascope `self`. This metascope includes the user's model, activity, servers and tokens. For example, `self` for a user named "gerard" includes:
-
-- `users!user=gerard` where the `users` scope provides access to the full user model and activity. The filter restricts this access to the user's own resources.
-- `servers!user=gerard` which grants the user access to their own servers without being able to create/delete any.
-- `tokens!user=gerard` which allows the user to access, request and delete their own tokens.
-- `access:servers!user=gerard` which allows the user to access their own servers via API or browser.
-
-The `self` scope is only valid for user entities. In other cases (e.g., for services) it resolves to an empty set of scopes.
-
-(default-token-scope-target)=
-
-### Default token scope
-
-The token metascope `inherit` causes the token to have the same permissions as the token's owner. For example, if a token owner has roles containing the scopes `read:groups` and `read:users`, the `inherit` scope resolves to the set of scopes `{read:groups, read:users}`.
-
-If the token owner has default `user` role, the `inherit` scope resolves to `self`, which will subsequently be expanded to include all the user-specific scopes (or empty set in the case of services).
-
-If the token owner is a member of any group with roles, the group scopes will also be included in resolving the `inherit` scope.
-
-(horizontal-filtering-target)=
-
-## Horizontal filtering
-
-Horizontal filtering, also called _resource filtering_, is the concept of reducing the payload of an API call to cover only the subset of the _resources_ that the scopes of the client provides them access to.
-Requested resources are filtered based on the filter of the corresponding scope. For instance, if a service requests a user list (guarded with scope `read:users`) with a role that only contains scopes `read:users!user=hannah` and `read:users!user=ivan`, the returned list of user models will be an intersection of all users and the collection `{hannah, ivan}`. In case this intersection is empty, the API call returns an HTTP 404 error, regardless if any users exist outside of the clients scope filter collection.
-
-In case a user resource is being accessed, any scopes with _group_ filters will be expanded to filters for each _user_ in those groups.
-
-(self-referencing-filters)=
-
-### Self-referencing filters
-
-There are some 'shortcut' filters,
-which can be applied to all scopes,
-that filter based on the entities associated with the request.
-
-The `!user` filter is a special horizontal filter that strictly refers to the **"owner only"** scopes, where _owner_ is a user entity. The filter resolves internally into `!user=<ownerusername>` ensuring that only the owner's resources may be accessed through the associated scopes.
-
-For example, the `server` role assigned by default to server tokens contains `access:servers!user` and `users:activity!user` scopes. This allows the token to access and post activity of only the servers owned by the token owner.
-
-:::{versionadded} 3.0
-`!service` and `!server` filters.
-:::
-
-In addition to `!user`, _tokens_ may have filters `!service`
-or `!server`, which expand similarly to `!service=servicename`
-and `!server=servername`.
-This only applies to tokens issued via the OAuth flow.
-In these cases, the name is the _issuing_ entity (a service or single-user server),
-so that access can be restricted to the issuing service,
-e.g. `access:servers!server` would grant access only to the server that requested the token.
-
-These filters can be applied to any scope.
-
-(vertical-filtering-target)=
-
-## Vertical filtering
-
-Vertical filtering, also called _attribute filtering_, is the concept of reducing the payload of an API call to cover only the _attributes_ of the resources that the scopes of the client provides them access to. This occurs when the client scopes are subscopes of the API endpoint that is called.
-For instance, if a client requests a user list with the only scope being `read:users:groups`, the returned list of user models will contain only a list of groups per user.
-In case the client has multiple subscopes, the call returns the union of the data the client has access to.
-
-The payload of an API call can be filtered both horizontally and vertically simultaneously. For instance, performing an API call to the endpoint `/users/` with the scope `users:name!user=juliette` returns a payload of `[{name: 'juliette'}]` (provided that this name is present in the database).
-
-(available-scopes-target)=
-
-## Available scopes
-
-Table below lists all available scopes and illustrates their hierarchy. Indented scopes indicate subscopes of the scope(s) above them.
-
-There are four exceptions to the general {ref}`scope conventions <scope-conventions-target>`:
-
-- `read:users:name` is a subscope of both `read:users` and `read:servers`. \
-  The `read:servers` scope requires access to the user name (server owner) due to named servers distinguished internally in the form `!server=username/servername`.
-
-- `read:users:activity` is a subscope of both `read:users` and `users:activity`. \
-  Posting activity via the `users:activity`, which is not included in `users` scope, needs to check the last valid activity of the user.
-
-- `read:roles:users` is a subscope of both `read:roles` and `admin:users`. \
-  Admin privileges to the _users_ resource include the information about user roles.
-
-- `read:roles:groups` is a subscope of both `read:roles` and `admin:groups`. \
-  Similar to the `read:roles:users` above.
-
-```{include} scope-table.md
-
-```
-
-:::{versionadded} 3.0
-The `admin-ui` scope is added to explicitly grant access to the admin page,
-rather than combining `admin:users` and `admin:servers` permissions.
-This means a deployment can enable the admin page with only a subset of functionality enabled.
-
-Note that this means actions to take _via_ the admin UI
-and access _to_ the admin UI are separated.
-For example, it generally doesn't make sense to grant
-`admin-ui` without at least `list:users` for at least some subset of users.
-
-For example:
-
-```python
-c.JupyterHub.load_roles = [
-  {
-    "name": "instructor-data8",
-    "scopes": [
-      # access to the admin page
-      "admin-ui",
-      # list users in the class group
-      "list:users!group=students-data8",
-      # start/stop servers for users in the class
-      "admin:servers!group=students-data8",
-      # access servers for users in the class
-      "access:servers!group=students-data8",
-    ],
-    "group": ["instructors-data8"],
-  }
-]
-```
-
-will grant instructors in the data8 course permission to:
-
-1. view the admin UI
-2. see students in the class (but not all users)
-3. start/stop/access servers for users in the class
-4. but _not_ permission to administer the users themselves (e.g. change their permissions, etc.)
-   :::
-
-```{Caution}
-Note that only the {ref}`horizontal filtering <horizontal-filtering-target>` can be added to scopes to customize them. \
-Metascopes `self` and `all`, `<resource>`, `<resource>:<subresource>`, `read:<resource>`, `admin:<resource>`, and `access:<resource>` scopes are predefined and cannot be changed otherwise.
-```
-
-(custom-scopes)=
-
-### Custom scopes
-
-:::{versionadded} 3.0
-:::
-
-JupyterHub 3.0 introduces support for custom scopes.
-Services that use JupyterHub for authentication and want to implement their own granular access may define additional _custom_ scopes and assign them to users with JupyterHub roles.
-
-% Note: keep in sync with pattern/description in jupyterhub/scopes.py
-
-Custom scope names must start with `custom:`
-and contain only lowercase ascii letters, numbers, hyphen, underscore, colon, and asterisk (`-_:*`).
-The part after `custom:` must start with a letter or number.
-Scopes may not end with a hyphen or colon.
-
-The only strict requirement is that a custom scope definition must have a `description`.
-It _may_ also have `subscopes` if you are defining multiple scopes that have a natural hierarchy,
-
-For example:
-
-```python
-c.JupyterHub.custom_scopes = {
-    "custom:myservice:read": {
-        "description": "read-only access to myservice",
-    },
-    "custom:myservice:write": {
-        "description": "write access to myservice",
-        # write permission implies read permission
-        "subscopes": [
-            "custom:myservice:read",
-        ],
-    },
-}
-
-c.JupyterHub.load_roles = [
-    # graders have read-only access to the service
-    {
-        "name": "service-user",
-        "groups": ["graders"],
-        "scopes": [
-            "custom:myservice:read",
-            "access:service!service=myservice",
-        ],
-    },
-    # instructors have read and write access to the service
-    {
-        "name": "service-admin",
-        "groups": ["instructors"],
-        "scopes": [
-            "custom:myservice:write",
-            "access:service!service=myservice",
-        ],
-    },
-]
-```
-
-In the above configuration, two scopes are defined:
-
-- `custom:myservice:read` grants read-only access to the service, and
-- `custom:myservice:write` grants write access to the service
-- write access _implies_ read access via the `subscope`
-
-These custom scopes are assigned to two groups via `roles`:
-
-- users in the group `graders` are granted read access to the service
-- users in the group `instructors` are
-- both are granted _access_ to the service via `access:service!service=myservice`
-
-When the service completes OAuth, it will retrieve the user model from `/hub/api/user`.
-This model includes a `scopes` field which is a list of authorized scope for the request,
-which can be used.
-
-```python
-def require_scope(scope):
-    """decorator to require a scope to perform an action"""
-    def wrapper(func):
-        @functools.wraps(func)
-        def wrapped_func(request):
-            user = fetch_hub_api_user(request.token)
-            if scope not in user["scopes"]:
-                raise HTTP403(f"Requires scope {scope}")
-            else:
-                return func()
-    return wrapper
-
-@require_scope("custom:myservice:read")
-async def read_something(request):
-    ...
-
-@require_scope("custom:myservice:write")
-async def write_something(request):
-    ...
-```
-
-If you use {class}`~.HubOAuthenticated`, this check is performed automatically
-against the `.hub_scopes` attribute of each Handler
-(the default is populated from `$JUPYTERHUB_OAUTH_ACCESS_SCOPES` and usually `access:services!service=myservice`).
-
-:::{versionchanged} 3.0
-The JUPYTERHUB_OAUTH_SCOPES environment variable is deprecated and renamed to JUPYTERHUB_OAUTH_ACCESS_SCOPES,
-to avoid ambiguity with JUPYTERHUB_OAUTH_CLIENT_ALLOWED_SCOPES
-:::
-
-```python
-from tornado import web
-from jupyterhub.services.auth import HubOAuthenticated
-
-class MyHandler(HubOAuthenticated, BaseHandler):
-    hub_scopes = ["custom:myservice:read"]
-
-    @web.authenticated
-    def get(self):
-        ...
-```
-
-Existing scope filters (`!user=`, etc.) may be applied to custom scopes.
-Custom scope _filters_ are NOT supported.
-
-### Scopes and APIs
-
-The scopes are also listed in the [](../reference/rest-api.rst) documentation. Each API endpoint has a list of scopes which can be used to access the API; if no scopes are listed, the API is not authenticated and can be accessed without any permissions (i.e., no scopes).
-
-Listed scopes by each API endpoint reflect the "lowest" permissions required to gain any access to the corresponding API. For example, posting user's activity (_POST /users/:name/activity_) needs `users:activity` scope. If scope `users` is passed during the request, the access will be granted as the required scope is a subscope of the `users` scope. If, on the other hand, `read:users:activity` scope is passed, the access will be denied.

docs/source/rbac/tech-implementation.md

@@ -1,99 +0,0 @@
-# Technical Implementation
-
-[Roles](roles) are stored in the database, where they are associated with users, services, and groups. Roles can be added or modified as explained in the {ref}`define-role-target` section. Users, services, groups, and tokens can gain, change, and lose roles. This is currently achieved via `jupyterhub_config.py` (see {ref}`define-role-target`) and will be made available via API in the future. The latter will allow for changing a user's role, and thereby its permissions, without the need to restart JupyterHub.
-
-Roles and scopes utilities can be found in `roles.py` and `scopes.py` modules. Scope variables take on five different formats that are reflected throughout the utilities via specific nomenclature:
-
-```{admonition} **Scope variable nomenclature**
-:class: tip
-- _scopes_ \
-  List of scopes that may contain abbreviations (used in role definitions). E.g., `["users:activity!user", "self"]`.
-- _expanded scopes_ \
-  Set of fully expanded scopes without abbreviations (i.e., resolved metascopes, filters, and subscopes). E.g., `{"users:activity!user=charlie", "read:users:activity!user=charlie"}`.
-- _parsed scopes_ \
-  Dictionary representation of expanded scopes. E.g., `{"users:activity": {"user": ["charlie"]}, "read:users:activity": {"users": ["charlie"]}}`.
-- _intersection_ \
-  Set of expanded scopes as intersection of 2 expanded scope sets.
-- _identify scopes_ \
-  Set of expanded scopes needed for identity (whoami) endpoints.
-```
-
-(resolving-roles-scopes-target)=
-
-## Resolving roles and scopes
-
-**Resolving roles** involves determining which roles a user, service, or group has, extracting the list of scopes from each role and combining them into a single set of scopes.
-
-**Resolving scopes** involves expanding scopes into all their possible subscopes (_expanded scopes_), parsing them into the format used for access evaluation (_parsed scopes_) and, if applicable, comparing two sets of scopes (_intersection_). All procedures take into account the scope hierarchy, {ref}`vertical <vertical-filtering-target>` and {ref}`horizontal filtering <horizontal-filtering-target>`, limiting or elevated permissions (`read:<resource>` or `admin:<resource>`, respectively), and metascopes.
-
-Roles and scopes are resolved on several occasions, for example when requesting an API token with specific scopes or when making an API request. The following sections provide more details.
-
-(requesting-api-token-target)=
-
-### Requesting API token with specific scopes
-
-:::{versionchanged} 3.0
-API tokens have _scopes_ instead of roles,
-so that their permissions cannot be updated.
-
-You may still request roles for a token,
-but those roles will be evaluated to the corresponding _scopes_ immediately.
-
-Prior to 3.0, tokens stored _roles_,
-which meant their scopes were resolved on each request.
-:::
-
-API tokens grant access to JupyterHub's APIs. The [RBAC framework](./index.md) allows for requesting tokens with specific permissions.
-
-RBAC is involved in several stages of the OAuth token flow.
-
-When requesting a token via the tokens API (`/users/:name/tokens`), or the token page (`/hub/token`),
-if no scopes are requested, the token is issued with the permissions stored on the default `token` role
-(provided the requester is allowed to create the token).
-
-OAuth tokens are also requested via OAuth flow
-
-If the token is requested with any scopes, the permissions of requesting entity are checked against the requested permissions to ensure the token would not grant its owner additional privileges.
-
-If a token has any scopes that its owner does not possess
-at the time of making the API request, those scopes are removed.
-The API request is resolved without additional errors using the scope _intersection_;
-the Hub logs a warning in this case (see {ref}`Figure 2 <api-request-chart>`).
-
-Resolving a token's scope (yellow box in {ref}`Figure 1 <token-request-chart>`) corresponds to resolving all the roles of the token's owner (including the roles associated with their groups) and the token's own scopes into a set of scopes. The two sets are compared (Resolve the scopes box in orange in {ref}`Figure 1 <token-request-chart>`), taking into account the scope hierarchy.
-If the token's scopes are a subset of the token owner's scopes, the token is issued with the requested scopes; if not, JupyterHub will raise an error.
-
-{ref}`Figure 1 <token-request-chart>` below illustrates the steps involved. The orange rectangles highlight where in the process the roles and scopes are resolved.
-
-```{figure} ../images/rbac-token-request-chart.png
-:align: center
-:name: token-request-chart
-
-Figure 1. Resolving roles and scopes during API token request
-```
-
-### Making an API request
-
-With the RBAC framework, each authenticated JupyterHub API request is guarded by a scope decorator that specifies which scopes are required in order to gain the access to the API.
-
-When an API request is made, the requesting API token's scopes are again intersected with its owner's (yellow box in {ref}`Figure 2 <api-request-chart>`) to ensure that the token does not grant more permissions than its owner has at the request time (e.g., due to changing/losing roles).
-If the owner's roles do not include some scopes of the token, only the _intersection_ of the token's and owner's scopes will be used. For example, using a token with scope `users` whose owner's role scope is `read:users:name` will result in only the `read:users:name` scope being passed on. In the case of no _intersection_, an empty set of scopes will be used.
-
-The passed scopes are compared to the scopes required to access the API as follows:
-
-- if the API scopes are present within the set of passed scopes, the access is granted and the API returns its "full" response
-
-- if that is not the case, another check is utilized to determine if subscopes of the required API scopes can be found in the passed scope set:
-
-  - if found, the RBAC framework employs the {ref}`filtering <vertical-filtering-target>` procedures to refine the API response to access only resource attributes corresponding to the passed scopes. For example, providing a scope `read:users:activity!group=class-C` for the `GET /users` API will return a list of user models from group `class-C` containing only the `last_activity` attribute for each user model
-
-  - if not found, the access to API is denied
-
-{ref}`Figure 2 <api-request-chart>` illustrates this process highlighting the steps where the role and scope resolutions as well as filtering occur in orange.
-
-```{figure} ../images/rbac-api-request-chart.png
-:align: center
-:name: api-request-chart
-
-Figure 2. Resolving roles and scopes when an API request is made
-```

docs/source/rbac/upgrade.md

@@ -1,54 +0,0 @@
-# Upgrading JupyterHub with RBAC framework
-
-RBAC framework requires different database setup than any previous JupyterHub versions due to eliminating the distinction between OAuth and API tokens (see {ref}`oauth-vs-api-tokens-target` for more details). This requires merging the previously two different database tables into one. By doing so, all existing tokens created before the upgrade no longer comply with the new database version and must be replaced.
-
-This is achieved by the Hub deleting all existing tokens during the database upgrade and recreating the tokens loaded via the `jupyterhub_config.py` file with updated structure. However, any manually issued or stored tokens are not recreated automatically and must be manually re-issued after the upgrade.
-
-No other database records are affected.
-
-(rbac-upgrade-steps-target)=
-
-## Upgrade steps
-
-1. All running **servers must be stopped** before proceeding with the upgrade.
-2. To upgrade the Hub, follow the [Upgrading JupyterHub](../admin/upgrading.rst) instructions.
-   ```{attention}
-   We advise against defining any new roles in the `jupyterhub.config.py` file right after the upgrade is completed and JupyterHub restarted for the first time. This preserves the 'current' state of the Hub. You can define and assign new roles on any other following startup.
-   ```
-3. After restarting the Hub **re-issue all tokens that were previously issued manually** (i.e., not through the `jupyterhub_config.py` file).
-
-When the JupyterHub is restarted for the first time after the upgrade, all users, services and tokens stored in the database or re-loaded through the configuration file will be assigned their default role. Any newly added entities after that will be assigned their default role only if no other specific role is requested for them.
-
-## Changing the permissions after the upgrade
-
-Once all the {ref}`upgrade steps <rbac-upgrade-steps-target>` above are completed, the RBAC framework will be available for utilization. You can define new roles, modify default roles (apart from `admin`) and assign them to entities as described in the {ref}`define-role-target` section.
-
-We recommended the following procedure to start with RBAC:
-
-1. Identify which admin users and services you would like to grant only the permissions they need through the new roles.
-2. Strip these users and services of their admin status via API or UI. This will change their roles from `admin` to `user`.
-   ```{note}
-   Stripping entities of their roles is currently available only via `jupyterhub_config.py` (see {ref}`removing-roles-target`).
-   ```
-3. Define new roles that you would like to start using with appropriate scopes and assign them to these entities in `jupyterhub_config.py`.
-4. Restart the JupyterHub for the new roles to take effect.
-
-(oauth-vs-api-tokens-target)=
-
-## OAuth vs API tokens
-
-### Before RBAC
-
-Previous JupyterHub versions utilize two types of tokens, OAuth token and API token.
-
-OAuth token is issued by the Hub to a single-user server when the user logs in. The token is stored in the browser cookie and is used to identify the user who owns the server during the OAuth flow. This token by default expires when the cookie reaches its expiry time of 2 weeks (or after 1 hour in JupyterHub versions < 1.3.0).
-
-API token is issued by the Hub to a single-user server when launched and is used to communicate with the Hub's APIs such as posting activity or completing the OAuth flow. This token has no expiry by default.
-
-API tokens can also be issued to users via API ([_/hub/token_](../reference/urls.md) or [_POST /users/:username/tokens_](../reference/rest-api.rst)) and services via `jupyterhub_config.py` to perform API requests.
-
-### With RBAC
-
-The RBAC framework allows for granting tokens different levels of permissions via scopes attached to roles. The 'only identify' purpose of the separate OAuth tokens is no longer required. API tokens can be used for every action, including the login and authentication, for which an API token with no role (i.e., no scope in {ref}`available-scopes-target`) is used.
-
-OAuth tokens are therefore dropped from the Hub upgraded with the RBAC framework.

docs/source/rbac/use-cases.md

@@ -1,130 +0,0 @@
-# Use Cases
-
-To determine which scopes a role should have, one can follow these steps:
-
-1. Determine what actions the role holder should have/have not access to
-2. Match the actions against the [JupyterHub's APIs](../reference/rest-api.rst)
-3. Check which scopes are required to access the APIs
-4. Combine scopes and subscopes if applicable
-5. Customize the scopes with filters if needed
-6. Define the role with required scopes and assign to users/services/groups/tokens
-
-Below, different use cases are presented on how to use the [RBAC framework](./index.md)
-
-## Service to cull idle servers
-
-Finding and shutting down idle servers can save a lot of computational resources.
-**We can make use of [jupyterhub-idle-culler](https://github.com/jupyterhub/jupyterhub-idle-culler) to manage this for us.**
-Below follows a short tutorial on how to add a cull-idle service in the RBAC system.
-
-1. Install the cull-idle server script with `pip install jupyterhub-idle-culler`.
-2. Define a new service `idle-culler` and a new role for this service:
-
-   ```python
-   # in jupyterhub_config.py
-
-   c.JupyterHub.services = [
-       {
-           "name": "idle-culler",
-           "command": [
-               sys.executable, "-m",
-               "jupyterhub_idle_culler",
-               "--timeout=3600"
-           ],
-       }
-   ]
-
-   c.JupyterHub.load_roles = [
-       {
-           "name": "idle-culler",
-           "description": "Culls idle servers",
-           "scopes": ["read:users:name", "read:users:activity", "servers"],
-           "services": ["idle-culler"],
-       }
-   ]
-   ```
-
-   ```{important}
-   Note that in the RBAC system the `admin` field in the `idle-culler` service definition is omitted. Instead, the `idle-culler` role provides the service with only the permissions it needs.
-
-   If the optional actions of deleting the idle servers and/or removing inactive users are desired, **change the following scopes** in the `idle-culler` role definition:
-   - `servers` to `admin:servers` for deleting servers
-   - `read:users:name`, `read:users:activity` to `admin:users` for deleting users.
-   ```
-
-3. Restart JupyterHub to complete the process.
-
-## API launcher
-
-A service capable of creating/removing users and launching multiple servers should have access to:
-
-1. _POST_ and _DELETE /users_
-2. _POST_ and _DELETE /users/:name/server_ or _/users/:name/servers/:server_name_
-3. Creating/deleting servers
-
-The scopes required to access the API enpoints:
-
-1. `admin:users`
-2. `servers`
-3. `admin:servers`
-
-From the above, the role definition is:
-
-```python
-# in jupyterhub_config.py
-
-c.JupyterHub.load_roles = [
-    {
-        "name": "api-launcher",
-        "description": "Manages servers",
-        "scopes": ["admin:users", "admin:servers"],
-        "services": [<service_name>]
-    }
-]
-```
-
-If needed, the scopes can be modified to limit the permissions to e.g. a particular group with `!group=groupname` filter.
-
-## Group admin roles
-
-Roles can be used to specify different group member privileges.
-
-For example, a group of students `class-A` may have a role allowing all group members to access information about their group. Teacher `johan`, who is a student of `class-A` but a teacher of another group of students `class-B`, can have additional role permitting him to access information about `class-B` students as well as start/stop their servers.
-
-The roles can then be defined as follows:
-
-```python
-# in jupyterhub_config.py
-
-c.JupyterHub.load_groups = {
-    'class-A': ['johan', 'student1', 'student2'],
-    'class-B': ['student3', 'student4']
-}
-
-c.JupyterHub.load_roles = [
-    {
-        'name': 'class-A-student',
-        'description': 'Grants access to information about the group',
-        'scopes': ['read:groups!group=class-A'],
-        'groups': ['class-A']
-    },
-    {
-        'name': 'class-B-student',
-        'description': 'Grants access to information about the group',
-        'scopes': ['read:groups!group=class-B'],
-        'groups': ['class-B']
-    },
-    {
-        'name': 'teacher',
-        'description': 'Allows for accessing information about teacher group members and starting/stopping their servers',
-        'scopes': [ 'read:users!group=class-B', 'servers!group=class-B'],
-        'users': ['johan']
-    }
-]
-```
-
-In the above example, `johan` has privileges inherited from `class-A-student` role and the `teacher` role on top of those.
-
-```{note}
-The scope filters (`!group=`) limit the privileges only to the particular groups. `johan` can access the servers and information of `class-B` group members only.
-```

docs/source/reference/api-only.md

@@ -1,128 +0,0 @@
-(api-only)=
-
-# Deploying JupyterHub in "API only mode"
-
-As a service for deploying and managing Jupyter servers for users, JupyterHub
-exposes this functionality _primarily_ via a [REST API](rest).
-For convenience, JupyterHub also ships with a _basic_ web UI built using that REST API.
-The basic web UI enables users to click a button to quickly start and stop their servers,
-and it lets admins perform some basic user and server management tasks.
-
-The REST API has always provided additional functionality beyond what is available in the basic web UI.
-Similarly, we avoid implementing UI functionality that is also not available via the API.
-With JupyterHub 2.0, the basic web UI will **always** be composed using the REST API.
-In other words, no UI pages should rely on information not available via the REST API.
-Previously, some admin UI functionality could only be achieved via admin pages,
-such as paginated requests.
-
-## Limited UI customization via templates
-
-The JupyterHub UI is customizable via extensible HTML [templates](templates),
-but this has some limited scope to what can be customized.
-Adding some content and messages to existing pages is well supported,
-but changing the page flow and what pages are available are beyond the scope of what is customizable.
-
-## Rich UI customization with REST API based apps
-
-Increasingly, JupyterHub is used purely as an API for managing Jupyter servers
-for other Jupyter-based applications that might want to present a different user experience.
-If you want a fully customized user experience,
-you can now disable the Hub UI and use your own pages together with the JupyterHub REST API
-to build your own web application to serve your users,
-relying on the Hub only as an API for managing users and servers.
-
-One example of such an application is [BinderHub][], which powers https://mybinder.org,
-and motivates many of these changes.
-
-BinderHub is distinct from a traditional JupyterHub deployment
-because it uses temporary users created for each launch.
-Instead of presenting a login page,
-users are presented with a form to specify what environment they would like to launch:
-
-![Binder launch form](../images/binderhub-form.png)
-
-When a launch is requested:
-
-1. an image is built, if necessary
-2. a temporary user is created,
-3. a server is launched for that user, and
-4. when running, users are redirected to an already running server with an auth token in the URL
-5. after the session is over, the user is deleted
-
-This means that a lot of JupyterHub's UI flow doesn't make sense:
-
-- there is no way for users to login
-- the human user doesn't map onto a JupyterHub `User` in a meaningful way
-- when a server isn't running, there isn't a 'restart your server' action available because the user has been deleted
-- users do not have any access to any Hub functionality, so presenting pages for those features would be confusing
-
-BinderHub is one of the motivating use cases for JupyterHub supporting being used _only_ via its API.
-We'll use BinderHub here as an example of various configuration options.
-
-[binderhub]: https://binderhub.readthedocs.io
-
-## Disabling Hub UI
-
-`c.JupyterHub.hub_routespec` is a configuration option to specify which URL prefix should be routed to the Hub.
-The default is `/` which means that the Hub will receive all requests not already specified to be routed somewhere else.
-
-There are three values that are most logical for `hub_routespec`:
-
-- `/` - this is the default, and used in most deployments.
-  It is also the only option prior to JupyterHub 1.4.
-- `/hub/` - this serves only Hub pages, both UI and API
-- `/hub/api` - this serves _only the Hub API_, so all Hub UI is disabled,
-  aside from the OAuth confirmation page, if used.
-
-If you choose a hub routespec other than `/`,
-the main JupyterHub feature you will lose is the automatic handling of requests for `/user/:username`
-when the requested server is not running.
-
-JupyterHub's handling of this request shows this page,
-telling you that the server is not running,
-with a button to launch it again:
-
-![screenshot of hub page for server not running](../images/server-not-running.png)
-
-If you set `hub_routespec` to something other than `/`,
-it is likely that you also want to register another destination for `/` to handle requests to not-running servers.
-If you don't, you will see a default 404 page from the proxy:
-
-![screenshot of CHP default 404](../images/chp-404.png)
-
-For mybinder.org, the default "start my server" page doesn't make sense,
-because when a server is gone, there is no restart action.
-Instead, we provide hints about how to get back to a link to start a _new_ server:
-
-![screenshot of mybinder.org 404](../images/binder-404.png)
-
-To achieve this, mybinder.org registers a route for `/` that goes to a custom endpoint
-that runs nginx and only serves this static HTML error page.
-This is set with
-
-```python
-c.Proxy.extra_routes = {
-    "/": "http://custom-404-entpoint/",
-}
-```
-
-You may want to use an alternate behavior, such as redirecting to a landing page,
-or taking some other action based on the requested page.
-
-If you use `c.JupyterHub.hub_routespec = "/hub/"`,
-then all the Hub pages will be available,
-and only this default-page-404 issue will come up.
-
-If you use `c.JupyterHub.hub_routespec = "/hub/api/"`,
-then only the Hub _API_ will be available,
-and all UI will be up to you.
-mybinder.org takes this last option,
-because none of the Hub UI pages really make sense.
-Binder users don't have any reason to know or care that JupyterHub happens
-to be an implementation detail of how their environment is managed.
-Seeing Hub error pages and messages in that situation is more likely to be confusing than helpful.
-
-:::{versionadded} 1.4
-
-`c.JupyterHub.hub_routespec` and `c.Proxy.extra_routes` are new in JupyterHub 1.4.
-:::

docs/source/reference/authenticators.md

@@ -1,6 +1,6 @@
 # Authenticators
 
-The {class}`.Authenticator` is the mechanism for authorizing users to use the
+The [Authenticator][] is the mechanism for authorizing users to use the
 Hub and single user notebook servers.
 
 ## The default PAM Authenticator
@@ -31,12 +31,13 @@ popular services:
 - Okpy
 - OpenShift
 
-A [generic implementation](https://github.com/jupyterhub/oauthenticator/blob/master/oauthenticator/generic.py), which you can use for OAuth authentication with any provider, is also available.
+A generic implementation, which you can use for OAuth authentication
+with any provider, is also available.
 
 ## The Dummy Authenticator
 
 When testing, it may be helpful to use the
-{class}`jupyterhub.auth.DummyAuthenticator`. This allows for any username and
+:class:`~jupyterhub.auth.DummyAuthenticator`. This allows for any username and
 password unless if a global password has been set. Once set, any username will
 still be accepted but the correct password will need to be provided.
 
@@ -88,6 +89,7 @@ class DictionaryAuthenticator(Authenticator):
             return data['username']
 ```
 
+
 #### Normalize usernames
 
 Since the Authenticator and Spawner both use the same username,
@@ -109,10 +111,11 @@ When using `PAMAuthenticator`, you can set
 normalize usernames using PAM (basically round-tripping them: username
 to uid to username), which is useful in case you use some external
 service that allows multiple usernames mapping to the same user (such
-as ActiveDirectory, yes, this really happens). When
-`pam_normalize_username` is on, usernames are _not_ normalized to
+as ActiveDirectory, yes, this really happens).  When
+`pam_normalize_username` is on, usernames are *not* normalized to
 lowercase.
 
+
 #### Validate usernames
 
 In most cases, there is a very limited set of acceptable usernames.
@@ -129,6 +132,7 @@ To only allow usernames that start with 'w':
 c.Authenticator.username_pattern = r'w.*'
 ```
 
+
 ### How to write a custom authenticator
 
 You can use custom Authenticator subclasses to enable authentication
@@ -136,11 +140,12 @@ via other mechanisms. One such example is using [GitHub OAuth][].
 
 Because the username is passed from the Authenticator to the Spawner,
 a custom Authenticator and Spawner are often used together.
-For example, the Authenticator methods, {meth}`.Authenticator.pre_spawn_start`
-and {meth}`.Authenticator.post_spawn_stop`, are hooks that can be used to do
+For example, the Authenticator methods, [pre_spawn_start(user, spawner)][]
+and [post_spawn_stop(user, spawner)][], are hooks that can be used to do
 auth-related startup (e.g. opening PAM sessions) and cleanup
 (e.g. closing PAM sessions).
 
+
 See a list of custom Authenticators [on the wiki](https://github.com/jupyterhub/jupyterhub/wiki/Authenticators).
 
 If you are interested in writing a custom authenticator, you can read
@@ -164,7 +169,7 @@ setup(
 ```
 
 If you have added this metadata to your package,
-admins can select your authenticator with the configuration:
+users can select your authenticator with the configuration:
 
 ```python
 c.JupyterHub.authenticator_class = 'myservice'
@@ -181,6 +186,7 @@ Additionally, configurable attributes for your authenticator will
 appear in jupyterhub help output and auto-generated configuration files
 via `jupyterhub --generate-config`.
 
+
 ### Authentication state
 
 JupyterHub 0.8 adds the ability to persist state related to authentication,
@@ -214,22 +220,25 @@ To store auth_state, two conditions must be met:
    export JUPYTERHUB_CRYPT_KEY=$(openssl rand -hex 32)
    ```
 
+
 JupyterHub uses [Fernet](https://cryptography.io/en/latest/fernet/) to encrypt auth_state.
 To facilitate key-rotation, `JUPYTERHUB_CRYPT_KEY` may be a semicolon-separated list of encryption keys.
 If there are multiple keys present, the **first** key is always used to persist any new auth_state.
 
+
 #### Using auth_state
 
 Typically, if `auth_state` is persisted it is desirable to affect the Spawner environment in some way.
 This may mean defining environment variables, placing certificate in the user's home directory, etc.
-The {meth}`Authenticator.pre_spawn_start` method can be used to pass information from authenticator state
+The `Authenticator.pre_spawn_start` method can be used to pass information from authenticator state
 to Spawner environment:
 
 ```python
 class MyAuthenticator(Authenticator):
-    async def authenticate(self, handler, data=None):
-        username = await identify_user(handler, data)
-        upstream_token = await token_for_user(username)
+    @gen.coroutine
+    def authenticate(self, handler, data=None):
+        username = yield identify_user(handler, data)
+        upstream_token = yield token_for_user(username)
         return {
             'name': username,
             'auth_state': {
@@ -237,68 +246,20 @@ class MyAuthenticator(Authenticator):
             },
         }
 
-    async def pre_spawn_start(self, user, spawner):
+    @gen.coroutine
+    def pre_spawn_start(self, user, spawner):
         """Pass upstream_token to spawner via environment variable"""
-        auth_state = await user.get_auth_state()
+        auth_state = yield user.get_auth_state()
         if not auth_state:
             # auth_state not enabled
             return
         spawner.environment['UPSTREAM_TOKEN'] = auth_state['upstream_token']
 ```
 
-Note that environment variable names and values are always strings, so passing multiple values means setting multiple environment variables or serializing more complex data into a single variable, e.g. as a JSON string.
-
-auth state can also be used to configure the spawner via _config_ without subclassing
-by setting `c.Spawner.auth_state_hook`. This function will be called with `(spawner, auth_state)`,
-only when auth_state is defined.
-
-For example:
-(for KubeSpawner)
-
-```python
-def auth_state_hook(spawner, auth_state):
-    spawner.volumes = auth_state['user_volumes']
-    spawner.mounts = auth_state['user_mounts']
-
-c.Spawner.auth_state_hook = auth_state_hook
-```
-
-(authenticator-groups)=
-
-## Authenticator-managed group membership
-
-:::{versionadded} 2.2
-:::
-
-Some identity providers may have their own concept of group membership that you would like to preserve in JupyterHub.
-This is now possible with `Authenticator.managed_groups`.
-
-You can set the config:
-
-```python
-c.Authenticator.manage_groups = True
-```
-
-to enable this behavior.
-The default is False for Authenticators that ship with JupyterHub,
-but may be True for custom Authenticators.
-Check your Authenticator's documentation for manage_groups support.
-
-If True, {meth}`.Authenticator.authenticate` and {meth}`.Authenticator.refresh_user` may include a field `groups`
-which is a list of group names the user should be a member of:
-
-- Membership will be added for any group in the list
-- Membership in any groups not in the list will be revoked
-- Any groups not already present in the database will be created
-- If `None` is returned, no changes are made to the user's group membership
-
-If authenticator-managed groups are enabled,
-all group-management via the API is disabled.
-
 ## pre_spawn_start and post_spawn_stop hooks
 
-Authenticators use two hooks, {meth}`.Authenticator.pre_spawn_start` and
-{meth}`.Authenticator.post_spawn_stop(user, spawner)` to add pass additional state information
+Authenticators uses two hooks, [pre_spawn_start(user, spawner)][] and
+[post_spawn_stop(user, spawner)][] to add pass additional state information
 between the authenticator and a spawner. These hooks are typically used auth-related
 startup, i.e. opening a PAM session, and auth-related cleanup, i.e. closing a
 PAM session.
@@ -307,7 +268,11 @@ PAM session.
 
 Beginning with version 0.8, JupyterHub is an OAuth provider.
 
-[pam]: https://en.wikipedia.org/wiki/Pluggable_authentication_module
-[oauth]: https://en.wikipedia.org/wiki/OAuth
-[github oauth]: https://developer.github.com/v3/oauth/
-[oauthenticator]: https://github.com/jupyterhub/oauthenticator
+
+[Authenticator]: https://github.com/jupyterhub/jupyterhub/blob/master/jupyterhub/auth.py
+[PAM]: https://en.wikipedia.org/wiki/Pluggable_authentication_module
+[OAuth]: https://en.wikipedia.org/wiki/OAuth
+[GitHub OAuth]: https://developer.github.com/v3/oauth/
+[OAuthenticator]: https://github.com/jupyterhub/oauthenticator
+[pre_spawn_start(user, spawner)]: https://jupyterhub.readthedocs.io/en/latest/api/auth.html#jupyterhub.auth.Authenticator.pre_spawn_start
+[post_spawn_stop(user, spawner)]: https://jupyterhub.readthedocs.io/en/latest/api/auth.html#jupyterhub.auth.Authenticator.post_spawn_stop

docs/source/reference/config-ghoauth.md

@@ -3,17 +3,18 @@
 In this example, we show a configuration file for a fairly standard JupyterHub
 deployment with the following assumptions:
 
-- Running JupyterHub on a single cloud server
-- Using SSL on the standard HTTPS port 443
-- Using GitHub OAuth (using [OAuthenticator](https://oauthenticator.readthedocs.io/en/latest)) for login
-- Using the default spawner (to configure other spawners, uncomment and edit
+* Running JupyterHub on a single cloud server
+* Using SSL on the standard HTTPS port 443
+* Using GitHub OAuth (using oauthenticator) for login
+* Using the default spawner (to configure other spawners, uncomment and edit
   `spawner_class` as well as follow the instructions for your desired spawner)
-- Users exist locally on the server
-- Users' notebooks to be served from `~/assignments` to allow users to browse
+* Users exist locally on the server
+* Users' notebooks to be served from `~/assignments` to allow users to browse
   for notebooks within other users' home directories
-- You want the landing page for each user to be a `Welcome.ipynb` notebook in
-  their assignments directory
-- All runtime files are put into `/srv/jupyterhub` and log files in `/var/log`
+* You want the landing page for each user to be a `Welcome.ipynb` notebook in
+  their assignments directory.
+* All runtime files are put into `/srv/jupyterhub` and log files in `/var/log`.
+
 
 The `jupyterhub_config.py` file would have these settings:
 
@@ -69,7 +70,7 @@ c.Spawner.args = ['--NotebookApp.default_url=/notebooks/Welcome.ipynb']
 ```
 
 Using the GitHub Authenticator requires a few additional
-environment variables to be set prior to launching JupyterHub:
+environment variable to be set prior to launching JupyterHub:
 
 ```bash
 export GITHUB_CLIENT_ID=github_id
@@ -79,5 +80,3 @@ export CONFIGPROXY_AUTH_TOKEN=super-secret
 # append log output to log file /var/log/jupyterhub.log
 jupyterhub -f /etc/jupyterhub/jupyterhub_config.py &>> /var/log/jupyterhub.log
 ```
-
-Visit the [Github OAuthenticator reference](https://oauthenticator.readthedocs.io/en/latest/api/gen/oauthenticator.github.html) to see the full list of options for configuring Github OAuth with JupyterHub.

docs/source/reference/config-proxy.md

@@ -6,15 +6,15 @@ SSL port `443`. This could be useful if the JupyterHub server machine is also
 hosting other domains or content on `443`. The goal in this example is to
 satisfy the following:
 
-- JupyterHub is running on a server, accessed _only_ via `HUB.DOMAIN.TLD:443`
-- On the same machine, `NO_HUB.DOMAIN.TLD` strictly serves different content,
+* JupyterHub is running on a server, accessed *only* via `HUB.DOMAIN.TLD:443`
+* On the same machine, `NO_HUB.DOMAIN.TLD` strictly serves different content,
   also on port `443`
-- `nginx` or `apache` is used as the public access point (which means that
-  only nginx/apache will bind to `443`)
-- After testing, the server in question should be able to score at least an A on the
+* `nginx` or `apache` is used as the public access point (which means that
+  only nginx/apache will bind  to `443`)
+* After testing, the server in question should be able to score at least an A on the
   Qualys SSL Labs [SSL Server Test](https://www.ssllabs.com/ssltest/)
 
-Let's start out with the needed JupyterHub configuration in `jupyterhub_config.py`:
+Let's start out with needed JupyterHub configuration in `jupyterhub_config.py`:
 
 ```python
 # Force the proxy to only listen to connections to 127.0.0.1 (on port 8000)
@@ -30,15 +30,15 @@ This can take a few minutes:
 openssl dhparam -out /etc/ssl/certs/dhparam.pem 4096
 ```
 
-## Nginx
+## nginx
 
 This **`nginx` config file** is fairly standard fare except for the two
 `location` blocks within the main section for HUB.DOMAIN.tld.
-To create a new site for jupyterhub in your Nginx config, make a new file
+To create a new site for jupyterhub in your nginx config, make a new file
 in `sites.enabled`, e.g. `/etc/nginx/sites.enabled/jupyterhub.conf`:
 
 ```bash
-# Top-level HTTP config for WebSocket headers
+# top-level http config for websocket headers
 # If Upgrade is defined, Connection = upgrade
 # If Upgrade is empty, Connection = close
 map $http_upgrade $connection_upgrade {
@@ -51,7 +51,7 @@ server {
     listen 80;
     server_name HUB.DOMAIN.TLD;
 
-    # Redirect the request to HTTPS
+    # Tell all requests to port 80 to be 302 redirected to HTTPS
     return 302 https://$host$request_uri;
 }
 
@@ -75,7 +75,7 @@ server {
     ssl_stapling_verify on;
     add_header Strict-Transport-Security max-age=15768000;
 
-    # Managing literal requests to the JupyterHub frontend
+    # Managing literal requests to the JupyterHub front end
     location / {
         proxy_pass http://127.0.0.1:8000;
         proxy_set_header X-Real-IP $remote_addr;
@@ -86,7 +86,6 @@ server {
         proxy_http_version 1.1;
         proxy_set_header Upgrade $http_upgrade;
         proxy_set_header Connection $connection_upgrade;
-        proxy_set_header X-Scheme $scheme;
 
         proxy_buffering off;
     }
@@ -101,10 +100,10 @@ server {
 If `nginx` is not running on port 443, substitute `$http_host` for `$host` on
 the lines setting the `Host` header.
 
-`nginx` will now be the front-facing element of JupyterHub on `443` which means
+`nginx` will now be the front facing element of JupyterHub on `443` which means
 it is also free to bind other servers, like `NO_HUB.DOMAIN.TLD` to the same port
 on the same machine and network interface. In fact, one can simply use the same
-server blocks as above for `NO_HUB` and simply add a line for the root directory
+server blocks as above for `NO_HUB` and simply add line for the root directory
 of the site as well as the applicable location call:
 
 ```bash
@@ -112,7 +111,7 @@ server {
     listen 80;
     server_name NO_HUB.DOMAIN.TLD;
 
-    # Redirect the request to HTTPS
+    # Tell all requests to port 80 to be 302 redirected to HTTPS
     return 302 https://$host$request_uri;
 }
 
@@ -143,12 +142,11 @@ Now restart `nginx`, restart the JupyterHub, and enjoy accessing
 `https://HUB.DOMAIN.TLD` while serving other content securely on
 `https://NO_HUB.DOMAIN.TLD`.
 
-### SELinux permissions for Nginx
-
+### SELinux permissions for nginx
 On distributions with SELinux enabled (e.g. Fedora), one may encounter permission errors
-when the Nginx service is started.
+when the nginx service is started.
 
-We need to allow Nginx to perform network relay and connect to the JupyterHub port. The
+We need to allow nginx to perform network relay and connect to the jupyterhub port. The
 following commands do that:
 
 ```bash
@@ -156,27 +154,27 @@ semanage port -a -t http_port_t -p tcp 8000
 setsebool -P httpd_can_network_relay 1
 setsebool -P httpd_can_network_connect 1
 ```
+Replace 8000 with the port the jupyterhub server is running from.
 
-Replace 8000 with the port the JupyterHub server is running from.
 
 ## Apache
 
-As with Nginx above, you can use [Apache](https://httpd.apache.org) as the reverse proxy.
-First, we will need to enable the Apache modules that we are going to need:
+As with nginx above, you can use [Apache](https://httpd.apache.org) as the reverse proxy.
+First, we will need to enable the apache modules that we are going to need:
 
 ```bash
-a2enmod ssl rewrite proxy headers proxy_http proxy_wstunnel
+a2enmod ssl rewrite proxy proxy_http proxy_wstunnel
 ```
 
-Our Apache configuration is equivalent to the Nginx configuration above:
+Our Apache configuration is equivalent to the nginx configuration above:
 
 - Redirect HTTP to HTTPS
 - Good SSL Configuration
-- Support for WebSocket on any proxied URL
+- Support for websockets on any proxied URL
 - JupyterHub is running locally at http://127.0.0.1:8000
 
 ```bash
-# Redirect HTTP to HTTPS
+# redirect HTTP to HTTPS
 Listen 80
 <VirtualHost HUB.DOMAIN.TLD:80>
   ServerName HUB.DOMAIN.TLD
@@ -188,26 +186,15 @@ Listen 443
 
   ServerName HUB.DOMAIN.TLD
 
-  # Enable HTTP/2, if available
-  Protocols h2 http/1.1
-
-  # HTTP Strict Transport Security (mod_headers is required) (63072000 seconds)
-  Header always set Strict-Transport-Security "max-age=63072000"
-
-  # Configure SSL
+  # configure SSL
   SSLEngine on
   SSLCertificateFile /etc/letsencrypt/live/HUB.DOMAIN.TLD/fullchain.pem
   SSLCertificateKeyFile /etc/letsencrypt/live/HUB.DOMAIN.TLD/privkey.pem
+  SSLProtocol All -SSLv2 -SSLv3
   SSLOpenSSLConfCmd DHParameters /etc/ssl/certs/dhparam.pem
+  SSLCipherSuite EECDH+AESGCM:EDH+AESGCM:AES256+EECDH:AES256+EDH
 
-  # Intermediate configuration from SSL-config.mozilla.org (2022-03-03)
-  # Please note, that this configuration might be outdated - please update it accordingly using https://ssl-config.mozilla.org/
-  SSLProtocol             all -SSLv3 -TLSv1 -TLSv1.1
-  SSLCipherSuite          ECDHE-ECDSA-AES128-GCM-SHA256:ECDHE-RSA-AES128-GCM-SHA256:ECDHE-ECDSA-AES256-GCM-SHA384:ECDHE-RSA-AES256-GCM-SHA384:ECDHE-ECDSA-CHACHA20-POLY1305:ECDHE-RSA-CHACHA20-POLY1305:DHE-RSA-AES128-GCM-SHA256:DHE-RSA-AES256-GCM-SHA384
-  SSLHonorCipherOrder     off
-  SSLSessionTickets       off
-
-  # Use RewriteEngine to handle WebSocket connection upgrades
+  # Use RewriteEngine to handle websocket connection upgrades
   RewriteEngine On
   RewriteCond %{HTTP:Connection} Upgrade [NC]
   RewriteCond %{HTTP:Upgrade} websocket [NC]
@@ -219,29 +206,26 @@ Listen 443
     # proxy to JupyterHub
     ProxyPass         http://127.0.0.1:8000/
     ProxyPassReverse  http://127.0.0.1:8000/
-    RequestHeader     set "X-Forwarded-Proto" expr=%{REQUEST_SCHEME}
   </Location>
 </VirtualHost>
 ```
 
-In case of the need to run JupyterHub under /jhub/ or another location please use the below configurations:
  
+In case of the need to run the jupyterhub under /jhub/ or other location please use the below configurations:
 - JupyterHub running locally at http://127.0.0.1:8000/jhub/ or other location
 
 httpd.conf amendments:
-
 ```bash
- RewriteRule /jhub/(.*) ws://127.0.0.1:8000/jhub/$1 [P,L]
- RewriteRule /jhub/(.*) http://127.0.0.1:8000/jhub/$1 [P,L]
+ RewriteRule /jhub/(.*) ws://127.0.0.1:8000/jhub/$1 [NE.P,L]
+ RewriteRule /jhub/(.*) http://127.0.0.1:8000/jhub/$1 [NE,P,L]
  
  ProxyPass /jhub/ http://127.0.0.1:8000/jhub/
  ProxyPassReverse /jhub/  http://127.0.0.1:8000/jhub/
-```
+ ```
  
 jupyterhub_config.py amendments:
-
-```python
-# The public facing URL of the whole JupyterHub application.
-# This is the address on which the proxy will bind. Sets protocol, IP, base_url
-c.JupyterHub.bind_url = 'http://127.0.0.1:8000/jhub/'
-```
+ ```bash
+  --The public facing URL of the whole JupyterHub application.
+  --This is the address on which the proxy will bind. Sets protocol, ip, base_url
+  c.JupyterHub.bind_url = 'http://127.0.0.1:8000/jhub/'
+  ```

docs/source/reference/config-sudo.md

@@ -6,10 +6,10 @@ Only do this if you are very sure you must.
 
 ## Overview
 
-There are many [Authenticators](../getting-started/authenticators-users-basics) and [Spawners](../getting-started/spawners-basics) available for JupyterHub. Some, such
-as [DockerSpawner](https://github.com/jupyterhub/dockerspawner) or [OAuthenticator](https://github.com/jupyterhub/oauthenticator), do not need any elevated permissions. This
+There are many Authenticators and Spawners available for JupyterHub. Some, such
+as DockerSpawner or OAuthenticator, do not need any elevated permissions. This
 document describes how to get the full default behavior of JupyterHub while
-running notebook servers as real system users on a shared system, without
+running notebook servers as real system users on a shared system without 
 running the Hub itself as root.
 
 Since JupyterHub needs to spawn processes as other users, the simplest way
@@ -53,6 +53,7 @@ To do this we add to `/etc/sudoers` (use `visudo` for safe editing of sudoers):
 - give `rhea` permission to run `JUPYTER_CMD` on behalf of `JUPYTER_USERS` 
   without entering a password
 
+
 For example:
 
 ```bash
@@ -69,8 +70,7 @@ Cmnd_Alias JUPYTER_CMD = /usr/local/bin/sudospawner
 rhea ALL=(JUPYTER_USERS) NOPASSWD:JUPYTER_CMD
 ```
 
-It might be useful to modify `secure_path` to add commands in path. (Search for
-`secure_path` in the [sudo docs](https://www.sudo.ws/man/1.8.14/sudoers.man.html)
+It might be useful to modify `secure_path` to add commands in path.
 
 As an alternative to adding every user to the `/etc/sudoers` file, you can
 use a group in the last line above, instead of `JUPYTER_USERS`:
@@ -91,7 +91,7 @@ $ adduser -G jupyterhub newuser
 Test that the new user doesn't need to enter a password to run the sudospawner
 command.
 
-This should prompt for your password to switch to `rhea`, but _not_ prompt for
+This should prompt for your password to switch to rhea, but *not* prompt for
 any password for the second switch. It should show some help output about
 logging options:
 
@@ -120,7 +120,7 @@ the shadow password database.
 
 ### Shadow group (Linux)
 
-**Note:** On [Fedora based distributions](https://fedoraproject.org/wiki/List_of_Fedora_remixes) there is no clear way to configure
+**Note:** On Fedora based distributions there is no clear way to configure
 the PAM database to allow sufficient access for authenticating with the target user's password
 from JupyterHub. As a workaround we recommend use an
 [alternative authentication method](https://github.com/jupyterhub/jupyterhub/wiki/Authenticators).
@@ -151,15 +151,13 @@ We want our new user to be able to read the shadow passwords, so add it to the s
     $ sudo usermod -a -G shadow rhea
 ```
 
-If you want jupyterhub to serve pages on a restricted port (such as port 80 for HTTP),
+If you want jupyterhub to serve pages on a restricted port (such as port 80 for http), 
 then you will need to give `node` permission to do so:
 
 ```bash
 sudo setcap 'cap_net_bind_service=+ep' /usr/bin/node
 ```
-
 However, you may want to further understand the consequences of this.
-([Further reading](http://man7.org/linux/man-pages/man7/capabilities.7.html))
 
 You may also be interested in limiting the amount of CPU any process can use
 on your server. `cpulimit` is a useful tool that is available for many Linux
@@ -167,10 +165,10 @@ distributions' packaging system. This can be used to keep any user's process
 from using too much CPU cycles. You can configure it accoring to [these
 instructions](http://ubuntuforums.org/showthread.php?t=992706).
 
+
 ### Shadow group (FreeBSD)
 
-**NOTE:** This has not been tested on FreeBSD and may not work as expected on
-the FreeBSD platform. _Do not use in production without verifying that it works properly!_
+**NOTE:** This has not been tested and may not work as expected.
 
 ```bash
 $ ls -l /etc/spwd.db /etc/master.passwd
@@ -229,8 +227,8 @@ And try logging in.
 ## Troubleshooting: SELinux
 
 If you still get a generic `Permission denied` `PermissionError`, it's possible SELinux is blocking you.  
-Here's how you can make a module to resolve this.
-First, put this in a file named `sudo_exec_selinux.te`:
+Here's how you can make a module to allow this.
+First, put this in a file  named `sudo_exec_selinux.te`:
 
 ```bash
 module sudo_exec_selinux 1.1;
@@ -256,6 +254,6 @@ $ semodule -i sudo_exec_selinux.pp
 ## Troubleshooting: PAM session errors
 
 If the PAM authentication doesn't work and you see errors for
-`login:session-auth`, or similar, consider updating to a more recent version
+`login:session-auth`, or similar, considering updating to a more recent version
 of jupyterhub and disabling the opening of PAM sessions with
 `c.PAMAuthenticator.open_sessions=False`.

docs/source/reference/config-user-env.md

@@ -1,47 +1,52 @@
 # Configuring user environments
 
-To deploy JupyterHub means you are providing Jupyter notebook environments for
+Deploying JupyterHub means you are providing Jupyter notebook environments for
 multiple users. Often, this includes a desire to configure the user
-environment in a custom way.
+environment in some way.
 
 Since the `jupyterhub-singleuser` server extends the standard Jupyter notebook
 server, most configuration and documentation that applies to Jupyter Notebook
 applies to the single-user environments. Configuration of user environments
-typically does not occur through JupyterHub itself, but rather through system-wide
-configuration of Jupyter, which is inherited by `jupyterhub-singleuser`.
+typically does not occur through JupyterHub itself, but rather through system-
+wide configuration of Jupyter, which is inherited by `jupyterhub-singleuser`.
 
-**Tip:** When searching for configuration tips for JupyterHub user environments, you might want to remove JupyterHub from your search because there are a lot more people out there configuring Jupyter than JupyterHub and the configuration is the same.
+**Tip:** When searching for configuration tips for JupyterHub user
+environments, try removing JupyterHub from your search because there are a lot
+more people out there configuring Jupyter than JupyterHub and the
+configuration is the same.
 
-This section will focus on user environments, which includes the following:
+This section will focus on user environments, including:
+
+- Installing packages
+- Configuring Jupyter and IPython
+- Installing kernelspecs
+- Using containers vs. multi-user hosts
 
-- [Installing packages](#installing-packages)
-- [Configuring Jupyter and IPython](#configuring-jupyter-and-ipython)
-- [Installing kernelspecs](#installing-kernelspecs)
-- [Using containers vs. multi-user hosts](#multi-user-hosts-vs-containers)
 
 ## Installing packages
 
-To make packages available to users, you will typically install packages system-wide or in a shared environment.
+To make packages available to users, you generally will install packages
+system-wide or in a shared environment.
 
-This installation location should always be in the same environment where
-`jupyterhub-singleuser` itself is installed in, and must be _readable and
-executable_ by your users. If you want your users to be able to install additional
-packages, the installation location must also be _writable_ by your users.
+This installation location should always be in the same environment that
+`jupyterhub-singleuser` itself is installed in, and must be *readable and
+executable* by your users. If you want users to be able to install additional
+packages, it must also be *writable* by your users.
+
+If you are using a standard system Python install, you would use:
 
-If you are using a standard Python installation on your system, use the following command:
 
 ```bash
 sudo python3 -m pip install numpy
 ```
 
-to install the numpy package in the default Python 3 environment on your system
+to install the numpy package in the default system Python 3 environment
 (typically `/usr/local`).
 
 You may also use conda to install packages. If you do, you should make sure
 that the conda environment has appropriate permissions for users to be able to
-run Python code in the env. The env must be _readable and executable_ by all
-users. Additionally it must be _writeable_ if you want users to install
-additional packages.
+run Python code in the env.
+
 
 ## Configuring Jupyter and IPython
 
@@ -49,17 +54,23 @@ additional packages.
 and [IPython](https://ipython.readthedocs.io/en/stable/development/config.html)
 have their own configuration systems.
 
-As a JupyterHub administrator, you will typically want to install and configure environments for all JupyterHub users. For example, let's say you wish for each student in a class to have the same user environment configuration.
+As a JupyterHub administrator, you will typically want to install and configure
+environments for all JupyterHub users. For example, you wish for each student in
+a class to have the same user environment configuration.
+
+Jupyter and IPython support **"system-wide"** locations for configuration, which
+is the logical place to put global configuration that you want to affect all
+users. It's generally more efficient to configure user environments "system-wide",
+and it's a good idea to avoid creating files in users' home directories.
 
-Jupyter and IPython support **"system-wide"** locations for configuration, which is the logical place to put global configuration that you want to affect all users. It's generally more efficient to configure user environments "system-wide", and it's a good practice to avoid creating files in the users' home directories.
 The typical locations for these config files are:
-
 - **system-wide** in `/etc/{jupyter|ipython}`
 - **env-wide** (environment wide) in `{sys.prefix}/etc/{jupyter|ipython}`.
 
 ### Example: Enable an extension system-wide
 
-For example, to enable the `cython` IPython extension for all of your users, create the file `/etc/ipython/ipython_config.py`:
+For example, to enable the `cython` IPython extension for all of your users,
+create the file `/etc/ipython/ipython_config.py`:
 
 ```python
 c.InteractiveShellApp.extensions.append("cython")
@@ -67,39 +78,32 @@ c.InteractiveShellApp.extensions.append("cython")
 
 ### Example: Enable a Jupyter notebook configuration setting for all users
 
-:::{note}
-These examples configure the Jupyter ServerApp, which is used by JupyterLab, the default in JupyterHub 2.0.
-
-If you are using the classing Jupyter Notebook server,
-the same things should work,
-with the following substitutions:
-
-- Search for `jupyter_server_config`, and replace with `jupyter_notebook_config`
-- Search for `NotebookApp`, and replace with `ServerApp`
-
-:::
-
-To enable Jupyter notebook's internal idle-shutdown behavior (requires notebook ≥ 5.4), set the following in the `/etc/jupyter/jupyter_server_config.py` file:
+To enable Jupyter notebook's internal idle-shutdown behavior (requires
+notebook ≥ 5.4), set the following in the `/etc/jupyter/jupyter_notebook_config.py`
+file:
 
 ```python
 # shutdown the server after no activity for an hour
-c.ServerApp.shutdown_no_activity_timeout = 60 * 60
+c.NotebookApp.shutdown_no_activity_timeout = 60 * 60
 # shutdown kernels after no activity for 20 minutes
 c.MappingKernelManager.cull_idle_timeout = 20 * 60
 # check for idle kernels every two minutes
 c.MappingKernelManager.cull_interval = 2 * 60
 ```
 
+
 ## Installing kernelspecs
 
-You may have multiple Jupyter kernels installed and want to make sure that they are available to all of your users. This means installing kernelspecs either system-wide (e.g. in /usr/local/) or in the `sys.prefix` of JupyterHub
+You may have multiple Jupyter kernels installed and want to make sure that
+they are available to all of your users. This means installing kernelspecs
+either system-wide (e.g. in /usr/local/) or in the `sys.prefix` of JupyterHub
 itself.
 
-Jupyter kernelspec installation is system-wide by default, but some kernels
+Jupyter kernelspec installation is system wide by default, but some kernels
 may default to installing kernelspecs in your home directory. These will need
 to be moved system-wide to ensure that they are accessible.
 
-To see where your kernelspecs are, you can use the following command:
+You can see where your kernelspecs are with:
 
 ```bash
 jupyter kernelspec list
@@ -107,13 +111,15 @@ jupyter kernelspec list
 
 ### Example: Installing kernels system-wide
 
-Let's assume that I have a Python 2 and Python 3 environment that I want to make sure are available, I can install their specs **system-wide** (in /usr/local) using the following command:
+Assuming I have a Python 2 and Python 3 environment that I want to make
+sure are available, I can install their specs system-wide (in /usr/local) with:
 
 ```bash
-/path/to/python3 -m ipykernel install --prefix=/usr/local
-/path/to/python2 -m ipykernel install --prefix=/usr/local
+/path/to/python3 -m IPython kernel install --prefix=/usr/local
+/path/to/python2 -m IPython kernel install --prefix=/usr/local
 ```
 
+
 ## Multi-user hosts vs. Containers
 
 There are two broad categories of user environments that depend on what
@@ -126,25 +132,31 @@ How you configure user environments for each category can differ a bit
 depending on what Spawner you are using.
 
 The first category is a **shared system (multi-user host)** where
-each user has a JupyterHub account, a home directory as well as being
+each user has a JupyterHub account and a home directory as well as being
 a real system user. In this example, shared configuration and installation
-must be in a 'system-wide' location, such as `/etc/`, or `/usr/local`
+must be in a 'system-wide' location, such as `/etc/` or `/usr/local`
 or a custom prefix such as `/opt/conda`.
 
 When JupyterHub uses **container-based** Spawners (e.g. KubeSpawner or
-DockerSpawner), the 'system-wide' environment is really the container image used for users.
+DockerSpawner), the 'system-wide' environment is really the container image
+which you are using for users.
 
-In both cases, you want to _avoid putting configuration in user home
-directories_ because users can change those configuration settings. Also, home directories typically persist once they are created, thereby making it difficult for admins to update later.
+In both cases, you want to *avoid putting configuration in user home
+directories* because users can change those configuration settings. Also,
+home directories typically persist once they are created, so they are
+difficult for admins to update later.
 
 ## Named servers
 
-By default, in a JupyterHub deployment, each user has one server only.
+By default, in a JupyterHub deployment each user has exactly one server.
 
 JupyterHub can, however, have multiple servers per user.
-This is mostly useful in deployments where users can configure the environment in which their server will start (e.g. resource requests on an HPC cluster), so that a given user can have multiple configurations running at the same time, without having to stop and restart their own server.
+This is most useful in deployments where users can configure the environment
+in which their server will start (e.g. resource requests on an HPC cluster),
+so that a given user can have multiple configurations running at the same time,
+without having to stop and restart their one server.
 
-To allow named servers, include this code snippet in your config file:
+To allow named servers:
 
 ```python
 c.JupyterHub.allow_named_servers = True
@@ -160,66 +172,10 @@ as well as the admin page:
 ![named servers on the admin page](../images/named-servers-admin.png)
 
 Named servers can be accessed, created, started, stopped, and deleted
-from these pages. Activity tracking is now per server as well.
+from these pages. Activity tracking is now per-server as well.
 
-To limit the number of **named server** per user by setting a constant value, include this code snippet in your config file:
+The number of named servers per user can be limited by setting
 
 ```python
 c.JupyterHub.named_server_limit_per_user = 5
 ```
-
-Alternatively, to use a callable/awaitable based on the handler object, include this code snippet in your config file:
-
-```python
-def named_server_limit_per_user_fn(handler):
-    user = handler.current_user
-    if user and user.admin:
-        return 0
-    return 5
-
-c.JupyterHub.named_server_limit_per_user = named_server_limit_per_user_fn
-```
-
-This can be useful for quota service implementations. The example above limits the number of named servers for non-admin users only.
-
-If `named_server_limit_per_user` is set to `0`, no limit is enforced.
-
-(classic-notebook-ui)=
-
-## Switching back to the classic notebook
-
-By default, the single-user server launches JupyterLab,
-which is based on [Jupyter Server][].
-
-This is the default server when running JupyterHub ≥ 2.0.
-To switch to using the legacy Jupyter Notebook server, you can set the `JUPYTERHUB_SINGLEUSER_APP` environment variable
-(in the single-user environment) to:
-
-```bash
-export JUPYTERHUB_SINGLEUSER_APP='notebook.notebookapp.NotebookApp'
-```
-
-[jupyter server]: https://jupyter-server.readthedocs.io
-[jupyter notebook]: https://jupyter-notebook.readthedocs.io
-
-:::{versionchanged} 2.0
-
-JupyterLab is now the default single-user UI, if available,
-which is based on the [Jupyter Server][],
-no longer the legacy [Jupyter Notebook][] server.
-JupyterHub prior to 2.0 launched the legacy notebook server (`jupyter notebook`),
-and the Jupyter server could be selected by specifying the following:
-
-```python
-# jupyterhub_config.py
-c.Spawner.cmd = ["jupyter-labhub"]
-```
-
-Alternatively, for an otherwise customized Jupyter Server app,
-set the environment variable using the following command:
-
-```bash
-export JUPYTERHUB_SINGLEUSER_APP='jupyter_server.serverapp.ServerApp'
-```
-
-:::

docs/source/reference/database.md

@@ -47,7 +47,7 @@ additional configuration required for MySQL that is not needed for PostgreSQL.
 - You should use the `pymysql` sqlalchemy provider (the other one, MySQLdb,
   isn't available for py3).
 - You also need to set `pool_recycle` to some value (typically 60 - 300) 
-  which depends on your MySQL setup. This is necessary since MySQL kills
+  which depends on your  MySQL setup. This is necessary since MySQL kills
   connections serverside if they've been idle for a while, and the connection
   from the hub will be idle for longer than most connections. This behavior
   will lead to frustrating 'the connection has gone away' errors from

docs/source/reference/index.rst

@@ -16,12 +16,9 @@ what happens under-the-hood when you deploy and configure your JupyterHub.
    proxy
    separate-proxy
    rest
-   rest-api
-   server-api
    monitoring
    database
    templates
-   api-only
    ../events/index
    config-user-env
    config-examples
@@ -29,4 +26,3 @@ what happens under-the-hood when you deploy and configure your JupyterHub.
    config-proxy
    config-sudo
    config-reference
-   oauth

docs/source/reference/oauth.md

@@ -1,373 +0,0 @@
-# JupyterHub and OAuth
-
-JupyterHub uses [OAuth 2](https://oauth.net/2/) as an internal mechanism for authenticating users.
-As such, JupyterHub itself always functions as an OAuth **provider**.
-You can find out more about what that means [below](oauth-terms).
-
-Additionally, JupyterHub is _often_ deployed with [OAuthenticator](https://oauthenticator.readthedocs.io),
-where an external identity provider, such as GitHub or KeyCloak, is used to authenticate users.
-When this is the case, there are _two_ nested OAuth flows:
-an _internal_ OAuth flow where JupyterHub is the **provider**,
-and an _external_ OAuth flow, where JupyterHub is the **client**.
-
-This means that when you are using JupyterHub, there is always _at least one_ and often two layers of OAuth involved in a user logging in and accessing their server.
-
-The following points are noteworthy:
-
-- Single-user servers _never_ need to communicate with or be aware of the upstream provider configured in your Authenticator.
-  As far as the servers are concerned, only JupyterHub is an OAuth provider,
-  and how users authenticate with the Hub itself is irrelevant.
-- When interacting with a single-user server,
-  there are ~always two tokens:
-  first, a token issued to the server itself to communicate with the Hub API,
-  and second, a per-user token in the browser to represent the completed login process and authorized permissions.
-  More on this [later](two-tokens).
-
-(oauth-terms)=
-
-## Key OAuth terms
-
-Here are some key definitions to keep in mind when we are talking about OAuth.
-You can also read more in detail [here](https://www.oauth.com/oauth2-servers/definitions/).
-
-- **provider**: The entity responsible for managing identity and authorization;
-  always a web server.
-  JupyterHub is _always_ an OAuth provider for JupyterHub's components.
-  When OAuthenticator is used, an external service, such as GitHub or KeyCloak, is also an OAuth provider.
-- **client**: An entity that requests OAuth **tokens** on a user's behalf;
-  generally a web server of some kind.
-  OAuth **clients** are services that _delegate_ authentication and/or authorization
-  to an OAuth **provider**.
-  JupyterHub _services_ or single-user _servers_ are OAuth **clients** of the JupyterHub **provider**.
-  When OAuthenticator is used, JupyterHub is itself _also_ an OAuth **client** for the external OAuth **provider**, e.g. GitHub.
-- **browser**: A user's web browser, which makes requests and stores things like cookies.
-- **token**: The secret value used to represent a user's authorization. This is the final product of the OAuth process.
-- **code**: A short-lived temporary secret that the **client** exchanges
-  for a **token** at the conclusion of OAuth,
-  in what's generally called the "OAuth callback handler."
-
-## One oauth flow
-
-OAuth **flow** is what we call the sequence of HTTP requests involved in authenticating a user and issuing a token, ultimately used for authorizing access to a service or single-user server.
-
-A single OAuth flow typically goes like this:
-
-### OAuth request and redirect
-
-1. A **browser** makes an HTTP request to an OAuth **client**.
-2. There are no credentials, so the client _redirects_ the browser to an "authorize" page on the OAuth **provider** with some extra information:
-   - the OAuth **client ID** of the client itself.
-   - the **redirect URI** to be redirected back to after completion.
-   - the **scopes** requested, which the user should be presented with to confirm.
-     This is the "X would like to be able to Y on your behalf. Allow this?" page you see on all the "Login with ..." pages around the Internet.
-3. During this authorize step,
-   the browser must be _authenticated_ with the provider.
-   This is often already stored in a cookie,
-   but if not the provider webapp must begin its _own_ authentication process before serving the authorization page.
-   This _may_ even begin another OAuth flow!
-4. After the user tells the provider that they want to proceed with the authorization,
-   the provider records this authorization in a short-lived record called an **OAuth code**.
-5. Finally, the oauth provider redirects the browser _back_ to the oauth client's "redirect URI"
-   (or "OAuth callback URI"),
-   with the OAuth code in a URL parameter.
-
-That marks the end of the requests made between the **browser** and the **provider**.
-
-### State after redirect
-
-At this point:
-
-- The browser is authenticated with the _provider_.
-- The user's authorized permissions are recorded in an _OAuth code_.
-- The _provider_ knows that the permissions requested by the OAuth client have been granted, but the client doesn't know this yet.
-- All the requests so far have been made directly by the browser.
-  No requests have originated from the client or provider.
-
-### OAuth Client Handles Callback Request
-
-At this stage, we get to finish the OAuth process.
-Let's dig into what the OAuth client does when it handles
-the OAuth callback request.
-
-- The OAuth client receives the _code_ and makes an API request to the _provider_ to exchange the code for a real _token_.
-  This is the first direct request between the OAuth _client_ and the _provider_.
-- Once the token is retrieved, the client _usually_
-  makes a second API request to the _provider_
-  to retrieve information about the owner of the token (the user).
-  This is the step where behavior diverges for different OAuth providers.
-  Up to this point, all OAuth providers are the same, following the OAuth specification.
-  However, OAuth does not define a standard for issuing tokens in exchange for information about their owner or permissions ([OpenID Connect](https://openid.net/connect/) does that),
-  so this step may be different for each OAuth provider.
-- Finally, the OAuth client stores its own record that the user is authorized in a cookie.
-  This could be the token itself, or any other appropriate representation of successful authentication.
-- Now that credentials have been established,
-  the browser can be redirected to the _original_ URL where it started,
-  to try the request again.
-  If the client wasn't able to keep track of the original URL all this time
-  (not always easy!),
-  you might end up back at a default landing page instead of where you started the login process. This is frustrating!
-
-😮‍💨 _phew_.
-
-So that's _one_ OAuth process.
-
-## Full sequence of OAuth in JupyterHub
-
-Let's go through the above OAuth process in JupyterHub,
-with specific examples of each HTTP request and what information it contains.
-For bonus points, we are using the double-OAuth example of JupyterHub configured with GitHubOAuthenticator.
-
-To disambiguate, we will call the OAuth process where JupyterHub is the **provider** "internal OAuth,"
-and the one with JupyterHub as a **client** "external OAuth."
-
-Our starting point:
-
-- a user's single-user server is running. Let's call them `danez`
-- Jupyterhub is running with GitHub as an OAuth provider (this means two full instances of OAuth),
-- Danez has a fresh browser session with no cookies yet.
-
-First request:
-
-- browser->single-user server running JupyterLab or Jupyter Classic
-- `GET /user/danez/notebooks/mynotebook.ipynb`
-- no credentials, so single-user server (as an OAuth **client**) starts internal OAuth process with JupyterHub (the **provider**)
-- response: 302 redirect -> `/hub/api/oauth2/authorize`
-  with:
-  - client-id=`jupyterhub-user-danez`
-  - redirect-uri=`/user/danez/oauth_callback` (we'll come back later!)
-
-Second request, following redirect:
-
-- browser->JupyterHub
-- `GET /hub/api/oauth2/authorize`
-- no credentials, so JupyterHub starts external OAuth process _with GitHub_
-- response: 302 redirect -> `https://github.com/login/oauth/authorize`
-  with:
-  - client-id=`jupyterhub-client-uuid`
-  - redirect-uri=`/hub/oauth_callback` (we'll come back later!)
-
-_pause_ This is where JupyterHub configuration comes into play.
-Recall, in this case JupyterHub is using:
-
-```python
-c.JupyterHub.authenticator_class = 'github'
-```
-
-That means authenticating a request to the Hub itself starts
-a _second_, external OAuth process with GitHub as a provider.
-This external OAuth process is optional, though.
-If you were using the default username+password PAMAuthenticator,
-this redirect would have been to `/hub/login` instead, to present the user
-with a login form.
-
-Third request, following redirect:
-
-- browser->GitHub
-- `GET https://github.com/login/oauth/authorize`
-
-Here, GitHub prompts for login and asks for confirmation of authorization
-(more redirects if you aren't logged in to GitHub yet, but ultimately back to this `/authorize` URL).
-
-After successful authorization
-(either by looking up a pre-existing authorization,
-or recording it via form submission)
-GitHub issues an **OAuth code** and redirects to `/hub/oauth_callback?code=github-code`
-
-Next request:
-
-- browser->JupyterHub
-- `GET /hub/oauth_callback?code=github-code`
-
-Inside the callback handler, JupyterHub makes two API requests:
-
-The first:
-
-- JupyterHub->GitHub
-- `POST https://github.com/login/oauth/access_token`
-- request made with OAuth **code** from URL parameter
-- response includes an access **token**
-
-The second:
-
-- JupyterHub->GitHub
-- `GET https://api.github.com/user`
-- request made with access **token** in the `Authorization` header
-- response is the user model, including username, email, etc.
-
-Now the external OAuth callback request completes with:
-
-- set cookie on `/hub/` path, recording jupyterhub authentication so we don't need to do external OAuth with GitHub again for a while
-- redirect -> `/hub/api/oauth2/authorize`
-
-🎉 At this point, we have completed our first OAuth flow! 🎉
-
-Now, we get our first repeated request:
-
-- browser->jupyterhub
-- `GET /hub/api/oauth2/authorize`
-- this time with credentials,
-  so jupyterhub either
-  1. serves the internal authorization confirmation page, or
-  2. automatically accepts authorization (shortcut taken when a user is visiting their own server)
-- redirect -> `/user/danez/oauth_callback?code=jupyterhub-code`
-
-Here, we start the same OAuth callback process as before, but at Danez's single-user server for the _internal_ OAuth.
-
-- browser->single-user server
-- `GET /user/danez/oauth_callback`
-
-(in handler)
-
-Inside the internal OAuth callback handler,
-Danez's server makes two API requests to JupyterHub:
-
-The first:
-
-- single-user server->JupyterHub
-- `POST /hub/api/oauth2/token`
-- request made with oauth code from url parameter
-- response includes an API token
-
-The second:
-
-- single-user server->JupyterHub
-- `GET /hub/api/user`
-- request made with token in the `Authorization` header
-- response is the user model, including username, groups, etc.
-
-Finally completing `GET /user/danez/oauth_callback`:
-
-- response sets cookie, storing encrypted access token
-- _finally_ redirects back to the original `/user/danez/notebooks/mynotebook.ipynb`
-
-Final request:
-
-- browser -> single-user server
-- `GET /user/danez/notebooks/mynotebook.ipynb`
-- encrypted jupyterhub token in cookie
-
-To authenticate this request, the single token stored in the encrypted cookie is passed to the Hub for verification:
-
-- single-user server -> Hub
-- `GET /hub/api/user`
-- browser's token in Authorization header
-- response: user model with name, groups, etc.
-
-If the user model matches who should be allowed (e.g. Danez),
-then the request is allowed.
-See {doc}`../rbac/scopes` for how JupyterHub uses scopes to determine authorized access to servers and services.
-
-_the end_
-
-## Token caches and expiry
-
-Because tokens represent information from an external source,
-they can become 'stale,'
-or the information they represent may no longer be accurate.
-For example: a user's GitHub account may no longer be authorized to use JupyterHub,
-that should ultimately propagate to revoking access and force logging in again.
-
-To handle this, OAuth tokens and the various places they are stored can _expire_,
-which should have the same effect as no credentials,
-and trigger the authorization process again.
-
-In JupyterHub's internal OAuth, we have these layers of information that can go stale:
-
-- The OAuth client has a **cache** of Hub responses for tokens,
-  so it doesn't need to make API requests to the Hub for every request it receives.
-  This cache has an expiry of five minutes by default,
-  and is governed by the configuration `HubAuth.cache_max_age` in the single-user server.
-- The internal OAuth token is stored in a cookie, which has its own expiry (default: 14 days),
-  governed by `JupyterHub.cookie_max_age_days`.
-- The internal OAuth token itself can also expire,
-  which is by default the same as the cookie expiry,
-  since it makes sense for the token itself and the place it is stored to expire at the same time.
-  This is governed by `JupyterHub.cookie_max_age_days` first,
-  or can overridden by `JupyterHub.oauth_token_expires_in`.
-
-That's all for _internal_ auth storage,
-but the information from the _external_ authentication provider
-(could be PAM or GitHub OAuth, etc.) can also expire.
-Authenticator configuration governs when JupyterHub needs to ask again,
-triggering the external login process anew before letting a user proceed.
-
-- `jupyterhub-hub-login` cookie stores that a browser is authenticated with the Hub.
-  This expires according to `JupyterHub.cookie_max_age_days` configuration,
-  with a default of 14 days.
-  The `jupyterhub-hub-login` cookie is encrypted with `JupyterHub.cookie_secret`
-  configuration.
-- {meth}`.Authenticator.refresh_user` is a method to refresh a user's auth info.
-  By default, it does nothing, but it can return an updated user model if a user's information has changed,
-  or force a full login process again if needed.
-- {attr}`.Authenticator.auth_refresh_age` configuration governs how often
-  `refresh_user()` will be called to check if a user must login again (default: 300 seconds).
-- {attr}`.Authenticator.refresh_pre_spawn` configuration governs whether
-  `refresh_user()` should be called prior to spawning a server,
-  to force fresh auth info when a server is launched (default: False).
-  This can be useful when Authenticators pass access tokens to spawner environments, to ensure they aren't getting a stale token that's about to expire.
-
-**So what happens when these things expire or get stale?**
-
-- If the HubAuth **token response cache** expires,
-  when a request is made with a token,
-  the Hub is asked for the latest information about the token.
-  This usually has no visible effect, since it is just refreshing a cache.
-  If it turns out that the token itself has expired or been revoked,
-  the request will be denied.
-- If the token has expired, but is still in the cookie:
-  when the token response cache expires,
-  the next time the server asks the hub about the token,
-  no user will be identified and the internal OAuth process begins again.
-- If the token _cookie_ expires, the next browser request will be made with no credentials,
-  and the internal OAuth process will begin again.
-  This will usually have the form of a transparent redirect browsers won't notice.
-  However, if this occurs on an API request in a long-lived page visit
-  such as a JupyterLab session, the API request may fail and require
-  a page refresh to get renewed credentials.
-- If the _JupyterHub_ cookie expires, the next time the browser makes a request to the Hub,
-  the Hub's authorization process must begin again (e.g. login with GitHub).
-  Hub cookie expiry on its own **does not** mean that a user can no longer access their single-user server!
-- If credentials from the upstream provider (e.g. GitHub) become stale or outdated,
-  these will not be refreshed until/unless `refresh_user` is called
-  _and_ `refresh_user()` on the given Authenticator is implemented to perform such a check.
-  At this point, few Authenticators implement `refresh_user` to support this feature.
-  If your Authenticator does not or cannot implement `refresh_user`,
-  the only way to force a check is to reset the `JupyterHub.cookie_secret` encryption key,
-  which invalidates the `jupyterhub-hub-login` cookie for all users.
-
-### Logging out
-
-Logging out of JupyterHub means clearing and revoking many of these credentials:
-
-- The `jupyterhub-hub-login` cookie is revoked, meaning the next request to the Hub itself will require a new login.
-- The token stored in the `jupyterhub-user-username` cookie for the single-user server
-  will be revoked, based on its associaton with `jupyterhub-session-id`, but the _cookie itself cannot be cleared at this point_
-- The shared `jupyterhub-session-id` is cleared, which ensures that the HubAuth **token response cache** will not be used,
-  and the next request with the expired token will ask the Hub, which will inform the single-user server that the token has expired
-
-## Extra bits
-
-(two-tokens)=
-
-### A tale of two tokens
-
-**TODO**: discuss API token issued to server at startup ($JUPYTERHUB_API_TOKEN)
-and OAuth-issued token in the cookie,
-and some details of how JupyterLab currently deals with that.
-They are different, and JupyterLab should be making requests using the token from the cookie,
-not the token from the server,
-but that is not currently the case.
-
-### Redirect loops
-
-In general, an authenticated web endpoint has this behavior,
-based on the authentication/authorization state of the browser:
-
-- If authorized, allow the request to happen
-- If authenticated (I know who you are) but not authorized (you are not allowed), fail with a 403 permission denied error
-- If not authenticated, start a redirect process to establish authorization,
-  which should end in a redirect back to the original URL to try again.
-  **This is why problems in authentication result in redirect loops!**
-  If the second request fails to detect the authentication that should have been established during the redirect,
-  it will start the authentication redirect process over again,
-  and keep redirecting in a loop until the browser balks.

docs/source/reference/proxy.md

@@ -7,12 +7,9 @@ Hub manages by default as a subprocess (it can be run externally, as well, and
 typically is in production deployments).
 
 The upside to CHP, and why we use it by default, is that it's easy to install
-and run (if you have nodejs, you are set!). The downsides are that
-
-- it's a single process and
-- does not support any persistence of the routing table.
-
-So if the proxy process dies, your whole JupyterHub instance is inaccessible
+and run (if you have nodejs, you are set!). The downsides are that it's a
+single process and does not support any persistence of the routing table. So
+if the proxy process dies, your whole JupyterHub instance is inaccessible
 until the Hub notices, restarts the proxy, and restores the routing table. For
 deployments that want to avoid such a single point of failure, or leverage
 existing proxy infrastructure in their chosen deployment (such as Kubernetes
@@ -57,7 +54,7 @@ class MyProxy(Proxy):
         """Stop the proxy"""
 ```
 
-These methods **may** be coroutines.
+These methods **may** be  coroutines.
 
 `c.Proxy.should_start` is a configurable flag that determines whether the
 Hub should call these methods when the Hub itself starts and stops.
@@ -106,7 +103,7 @@ route to be proxied, such as `/user/name/`. A routespec will:
 
 When adding a route, JupyterHub may pass a JSON-serializable dict as a `data`
 argument that should be attached to the proxy route. When that route is
-retrieved, the `data` argument should be returned as well. If your proxy
+retrieved, the `data` argument should be returned as well. If your  proxy
 implementation doesn't support storing data attached to routes, then your
 Python wrapper may have to handle storing the `data` piece itself, e.g in a
 simple file or database.
@@ -139,9 +136,9 @@ async def delete_route(self, routespec):
 
 ### Retrieving routes
 
-For retrieval, you only _need_ to implement a single method that retrieves all
+For retrieval, you only *need* to implement a single method that retrieves all
 routes. The return value for this function should be a dictionary, keyed by
-`routespec`, of dicts whose keys are the same three arguments passed to
+`routespect`, of dicts whose keys are the same three arguments passed to
 `add_route` (`routespec`, `target`, `data`)
 
 ```python
@@ -207,7 +204,7 @@ setup(
 ```
 
 If you have added this metadata to your package,
-admins can select your authenticator with the configuration:
+users can select your proxy with the configuration:
 
 ```python
 c.JupyterHub.proxy_class = 'mything'
@@ -219,15 +216,7 @@ instead of the full
 c.JupyterHub.proxy_class = 'mypackage:MyProxy'
 ```
 
-as previously required.
+previously required.
 Additionally, configurable attributes for your proxy will
 appear in jupyterhub help output and auto-generated configuration files
 via `jupyterhub --generate-config`.
-
-### Index of proxies
-
-A list of the proxies that are currently available for JupyterHub (that we know about).
-
-1. [`jupyterhub/configurable-http-proxy`](https://github.com/jupyterhub/configurable-http-proxy) The default proxy which uses node-http-proxy
-2. [`jupyterhub/traefik-proxy`](https://github.com/jupyterhub/traefik-proxy) The proxy which configures traefik proxy server for jupyterhub
-3. [`AbdealiJK/configurable-http-proxy`](https://github.com/AbdealiJK/configurable-http-proxy) A pure python implementation of the configurable-http-proxy

docs/source/reference/rest-api.md

@@ -1,27 +0,0 @@
-# JupyterHub REST API
-
-Below is an interactive view of JupyterHub's OpenAPI specification.
-
-<!-- client-rendered openapi UI copied from FastAPI -->
-
-<link type="text/css" rel="stylesheet" href="https://cdn.jsdelivr.net/npm/swagger-ui-dist@3/swagger-ui.css">
-<script src="https://cdn.jsdelivr.net/npm/swagger-ui-dist@4.1/swagger-ui-bundle.js"></script>
-<!-- `SwaggerUIBundle` is now available on the page -->
-
-<!-- render the ui here -->
-<div id="openapi-ui"></div>
-
-<script>
-const ui = SwaggerUIBundle({
-  url: '../_static/rest-api.yml',
-  dom_id: '#openapi-ui',
-  presets: [
-    SwaggerUIBundle.presets.apis,
-    SwaggerUIBundle.SwaggerUIStandalonePreset
-  ],
-  layout: "BaseLayout",
-  deepLinking: true,
-  showExtensions: true,
-  showCommonExtensions: true,
-});
-</script>

docs/source/reference/rest-api.rst

@@ -0,0 +1,14 @@
+:orphan:
+
+===================
+JupyterHub REST API
+===================
+
+.. this doc exists as a resolvable link target
+.. which _static files are not
+
+.. meta::
+    :http-equiv=refresh: 0;url=../_static/rest-api/index.html
+
+The rest API docs are `here <../_static/rest-api/index.html>`_
+if you are not redirected automatically.

docs/source/reference/rest.md

@@ -1,39 +1,34 @@
-(rest-api)=
-
 # Using JupyterHub's REST API
 
 This section will give you information on:
 
-- What you can do with the API
-- How to create an API token
-- Assigning permissions to a token
-- Updating to admin services
-- Making an API request programmatically using the requests library
-- Paginating API requests
-- Enabling users to spawn multiple named-servers via the API
-- Learn more about JupyterHub's API
-
-Before we discuss about JupyterHub's REST API, you can learn about [REST APIs here](https://en.wikipedia.org/wiki/Representational_state_transfer). A REST
-API provides a standard way for users to get and send information to the
-Hub.
+- what you can do with the API
+- create an API token
+- add API tokens to the config files
+- make an API request programmatically using the requests library
+- learn more about JupyterHub's API
 
 ## What you can do with the API
 
 Using the [JupyterHub REST API][], you can perform actions on the Hub,
 such as:
 
-- Checking which users are active
-- Adding or removing users
-- Stopping or starting single user notebook servers
-- Authenticating services
-- Communicating with an individual Jupyter server's REST API
+- checking which users are active
+- adding or removing users
+- stopping or starting single user notebook servers
+- authenticating services
+
+A [REST](https://en.wikipedia.org/wiki/Representational_state_transfer)
+API provides a standard way for users to get and send information to the
+Hub.
 
 ## Create an API token
 
-To send requests using the JupyterHub API, you must pass an API token with
+To send requests using JupyterHub API, you must pass an API token with
 the request.
 
-The preferred way of generating an API token is by running:
+As of [version 0.6.0](../changelog.md), the preferred way of
+generating an API token is:
 
 ```bash
 openssl rand -hex 32
@@ -43,12 +38,8 @@ This `openssl` command generates a potential token that can then be
 added to JupyterHub using `.api_tokens` configuration setting in
 `jupyterhub_config.py`.
 
-```{note}
-The api_tokens configuration has been softly deprecated since the introduction of services.
-```
-
-Alternatively, you can use the `jupyterhub token` command to generate a token
-for a specific hub user by passing the **username**:
+Alternatively, use the `jupyterhub token` command to generate a token
+for a specific hub user by passing the 'username':
 
 ```bash
 jupyterhub token <username>
@@ -57,92 +48,61 @@ jupyterhub token <username>
 This command generates a random string to use as a token and registers
 it for the given user with the Hub's database.
 
-In [version 0.8.0](../changelog.md), a token request page for
+In [version 0.8.0](../changelog.md), a TOKEN request page for
 generating an API token is available from the JupyterHub user interface:
 
-:::{figure-md}
+![Request API TOKEN page](../images/token-request.png)
 
-![token request page](../images/token-request.png)
+![API TOKEN success page](../images/token-request-success.png)
 
-JupyterHub's API token page
-:::
+## Add API tokens to the config file
 
-:::{figure-md}
-![token-request-success](../images/token-request-success.png)
+**This is deprecated. We are in no rush to remove this feature,
+but please consider if service tokens are right for you.**
 
-JupyterHub's token page after successfully requesting a token.
-
-:::
-
-## Assigning permissions to a token
-
-Prior to JupyterHub 2.0, there were two levels of permissions:
-
-1. user, and
-2. admin
-
-where a token would always have full permissions to do whatever its owner could do.
-
-In JupyterHub 2.0,
-specific permissions are now defined as '**scopes**',
-and can be assigned both at the user/service level,
-and at the individual token level.
-
-This allows e.g. a user with full admin permissions to request a token with limited permissions.
-
-## Updating to admin services
-
-```{note}
-The `api_tokens` configuration has been softly deprecated since the introduction of services.
-We have no plans to remove it,
-but deployments are encouraged to use service configuration instead.
-```
-
-If you have been using `api_tokens` to create an admin user
-and the token for that user to perform some automations, then
-the services' mechanism may be a better fit if you have the following configuration:
+You may also add a dictionary of API tokens and usernames to the hub's
+configuration file, `jupyterhub_config.py` (note that
+the **key** is the 'secret-token' while the **value** is the 'username'):
 
 ```python
-c.JupyterHub.admin_users = {"service-admin"}
+c.JupyterHub.api_tokens = {
+    'secret-token': 'username',
+}
+```
+
+### Updating to admin services
+
+The `api_tokens` configuration has been softly deprecated since the introduction of services.
+We have no plans to remove it,
+but users are encouraged to use service configuration instead.
+
+If you have been using `api_tokens` to create an admin user
+and a token for that user to perform some automations,
+the services mechanism may be a better fit.
+If you have the following configuration:
+
+```python
+c.JupyterHub.admin_users = {"service-admin",}
 c.JupyterHub.api_tokens = {
     "secret-token": "service-admin",
 }
 ```
 
-This can be updated to create a service, with the following configuration:
+This can be updated to create an admin service, with the following configuration:
 
 ```python
 c.JupyterHub.services = [
     {
-        # give the token a name
-        "name": "service-admin",
+        "name": "service-token",
+        "admin": True,
         "api_token": "secret-token",
-        # "admin": True, # if using JupyterHub 1.x
     },
 ]
-
-# roles were introduced in JupyterHub 2.0
-# prior to 2.0, only "admin": True or False was available
-
-c.JupyterHub.load_roles = [
-    {
-        "name": "service-role",
-        "scopes": [
-            # specify the permissions the token should have
-            "admin:users",
-        ],
-        "services": [
-            # assign the service the above permissions
-            "service-admin",
-        ],
-    }
-]
 ```
 
-The token will have the permissions listed in the role
-(see [scopes][] for a list of available permissions),
+The token will have the same admin permissions,
 but there will no longer be a user account created to house it.
-The main noticeable difference between a user and a service is that there will be no notebook server associated with the account
+The main noticeable difference is that there will be no notebook server associated with the account
 and the service will not show up in the various user list pages and APIs.
 
 ## Make an API request
@@ -152,9 +112,10 @@ Authorization header.
 
 ### Use requests
 
-Using the popular Python [requests](https://docs.python-requests.org)
-library, an API GET request is made, and the request sends an API token for
-authorization. The response contains information about the users, here's example code to make an API request for the users of a JupyterHub deployment
+Using the popular Python [requests](http://docs.python-requests.org/en/master/)
+library, here's example code to make an API request for the users of a JupyterHub
+deployment. An API GET request is made, and the request sends an API token for
+authorization. The response contains information about the users:
 
 ```python
 import requests
@@ -163,9 +124,9 @@ api_url = 'http://127.0.0.1:8081/hub/api'
 
 r = requests.get(api_url + '/users',
     headers={
-        'Authorization': f'token {token}',
-    }
-)
+             'Authorization': 'token %s' % token,
+            }
+    )
 
 r.raise_for_status()
 users = r.json()
@@ -183,100 +144,23 @@ data = {'name': 'mygroup', 'users': ['user1', 'user2']}
 
 r = requests.post(api_url + '/groups/formgrade-data301/users',
     headers={
-        'Authorization': f'token {token}',
-    },
-    json=data,
+             'Authorization': 'token %s' % token,
+            },
+    json=data
 )
 r.raise_for_status()
 r.json()
 ```
 
 The same API token can also authorize access to the [Jupyter Notebook REST API][]
+provided by notebook servers managed by JupyterHub if one of the following is true:
 
-provided by notebook servers managed by JupyterHub if it has the necessary `access:servers` scope.
-
-(api-pagination)=
-
-## Paginating API requests
-
-```{versionadded} 2.0
-
-```
-
-Pagination is available through the `offset` and `limit` query parameters on
-list endpoints, which can be used to return ideally sized windows of results.
-Here's example code demonstrating pagination on the `GET /users`
-endpoint to fetch the first 20 records.
-
-```python
-import os
-import requests
-
-api_url = 'http://127.0.0.1:8081/hub/api'
-
-r = requests.get(
-    api_url + '/users?offset=0&limit=20',
-    headers={
-        "Accept": "application/jupyterhub-pagination+json",
-        "Authorization": f"token {token}",
-    },
-)
-r.raise_for_status()
-r.json()
-```
-
-For backward-compatibility, the default structure of list responses is unchanged.
-However, this lacks pagination information (e.g. is there a next page),
-so if you have enough users that they won't fit in the first response,
-it is a good idea to opt-in to the new paginated list format.
-There is a new schema for list responses which include pagination information.
-You can request this by including the header:
-
-```
-Accept: application/jupyterhub-pagination+json
-```
-
-with your request, in which case a response will look like:
-
-```python
-{
-  "items": [
-    {
-      "name": "username",
-      "kind": "user",
-      ...
-    },
-  ],
-  "_pagination": {
-    "offset": 0,
-    "limit": 20,
-    "total": 50,
-    "next": {
-      "offset": 20,
-      "limit": 20,
-      "url": "http://127.0.0.1:8081/hub/api/users?limit=20&offset=20"
-    }
-  }
-}
-```
-
-where the list results (same as pre-2.0) will be in `items`,
-and pagination info will be in `_pagination`.
-The `next` field will include the `offset`, `limit`, and `url` for requesting the next page.
-`next` will be `null` if there is no next page.
-
-Pagination is governed by two configuration options:
-
-- `JupyterHub.api_page_default_limit` - the page size, if `limit` is unspecified in the request
-  and the new pagination API is requested
-  (default: 50)
-- `JupyterHub.api_page_max_limit` - the maximum page size a request can ask for (default: 200)
-
-Pagination is enabled on the `GET /users`, `GET /groups`, and `GET /proxy` REST endpoints.
+1. The token is for the same user as the owner of the notebook
+2. The token is tied to an admin user or service **and** `c.JupyterHub.admin_access` is set to `True`
 
 ## Enabling users to spawn multiple named-servers via the API
 
-Support for multiple servers per user was introduced in JupyterHub [version 0.8.](../changelog.md)
+With JupyterHub version 0.8, support for multiple servers per user has landed.
 Prior to that, each user could only launch a single default server via the API
 like this:
 
@@ -285,14 +169,14 @@ curl -X POST -H "Authorization: token <token>" "http://127.0.0.1:8081/hub/api/us
 ```
 
 With the named-server functionality, it's now possible to launch more than one
-specifically named servers against a given user. This could be used, for instance,
+specifically named servers against a given user.  This could be used, for instance,
 to launch each server based on a different image.
 
 First you must enable named-servers by including the following setting in the `jupyterhub_config.py` file.
 
 `c.JupyterHub.allow_named_servers = True`
 
-If you are using the [zero-to-jupyterhub-k8s](https://github.com/jupyterhub/zero-to-jupyterhub-k8s) set-up to run JupyterHub,
+If using the [zero-to-jupyterhub-k8s](https://github.com/jupyterhub/zero-to-jupyterhub-k8s) set-up to run JupyterHub,
 then instead of editing the `jupyterhub_config.py` file directly, you could pass
 the following as part of the `config.yaml` file, as per the [tutorial](https://zero-to-jupyterhub.readthedocs.io/en/latest/):
 
@@ -303,7 +187,6 @@ hub:
 ```
 
 With that setting in place, a new named-server is activated like this:
-
 ```bash
 curl -X POST -H "Authorization: token <token>" "http://127.0.0.1:8081/hub/api/users/<user>/servers/<serverA>"
 curl -X POST -H "Authorization: token <token>" "http://127.0.0.1:8081/hub/api/users/<user>/servers/<serverB>"
@@ -318,11 +201,15 @@ will need to be able to handle the case of multiple servers per user and ensure
 uniqueness of names, particularly if servers are spawned via docker containers
 or kubernetes pods.
 
+
 ## Learn more about the API
 
-You can see the full [JupyterHub REST API][] for more details.
+You can see the full [JupyterHub REST API][] for details. This REST API Spec can
+be viewed in a more [interactive style on swagger's petstore][].
+Both resources contain the same information and differ only in its display.
+Note: The Swagger specification is being renamed the [OpenAPI Initiative][].
 
-[openapi initiative]: https://www.openapis.org/
-[jupyterhub rest api]: ./rest-api
-[scopes]: ../rbac/scopes.md
-[jupyter notebook rest api]: https://petstore3.swagger.io/?url=https://raw.githubusercontent.com/jupyter/notebook/HEAD/notebook/services/api/api.yaml
+[interactive style on swagger's petstore]: http://petstore.swagger.io/?url=https://raw.githubusercontent.com/jupyterhub/jupyterhub/master/docs/rest-api.yml#!/default
+[OpenAPI Initiative]: https://www.openapis.org/
+[JupyterHub REST API]: ./rest-api
+[Jupyter Notebook REST API]: http://petstore.swagger.io/?url=https://raw.githubusercontent.com/jupyter/notebook/master/notebook/services/api/api.yaml

docs/source/reference/separate-proxy.md

@@ -1,24 +1,27 @@
 # Running proxy separately from the hub
 
+
 ## Background
 
-The thing which users directly connect to is the proxy, which by default is
-`configurable-http-proxy`. The proxy either redirects users to the
+The thing which users directly connect to is the proxy, by default
+`configurable-http-proxy`.  The proxy either redirects users to the
 hub (for login and managing servers), or to their own single-user
-servers. Thus, as long as the proxy stays running, access to existing
+servers.  Thus, as long as the proxy stays running, access to existing
 servers continues, even if the hub itself restarts or goes down.
 
 When you first configure the hub, you may not even realize this
-because the proxy is automatically managed by the hub. This is great
-for getting started and even most use-cases, although, everytime you restart the
-hub, all user connections are also restarted. However, it is also simple to
+because the proxy is automatically managed by the hub.  This is great
+for getting started and even most use, but everytime you restart the
+hub, all user connections also get restarted.  But it's also simple to
 run the proxy as a service separate from the hub, so that you are free
-to reconfigure the hub while only interrupting users who are waiting for their notebook server to start.
-starting their notebook server.
+to reconfigure the hub while only interrupting users who are currently
+actively starting the hub.
 
 The default JupyterHub proxy is
-[configurable-http-proxy](https://github.com/jupyterhub/configurable-http-proxy). If you are using a different proxy, such
-as [Traefik](https://github.com/traefik/traefik), these instructions are probably not relevant to you.
+[configurable-http-proxy](https://github.com/jupyterhub/configurable-http-proxy),
+and that page has some docs.  If you are using a different proxy, such
+as Traefik, these instructions are probably not relevant to you.
+
 
 ## Configuration options
 
@@ -34,25 +37,24 @@ it yourself).
 token for authenticating communication with the proxy.
 
 `c.ConfigurableHTTPProxy.api_url = 'http://localhost:8001'` should be
-set to the URL which the hub uses to connect _to the proxy's API_.
+set to the URL which the hub uses to connect *to the proxy's API*.
+
 
 ## Proxy configuration
 
-You need to configure a service to start the proxy. An example
-command line argument for this is:
-
-```bash
-$ configurable-http-proxy --ip=127.0.0.1 --port=8000 --api-ip=127.0.0.1 --api-port=8001 --default-target=http://localhost:8081 --error-target=http://localhost:8081/hub/error
-```
-
-(Details on how to do this is out of the scope of this tutorial. For example, it might be a
-systemd service configured within another docker container). The proxy has no
+You need to configure a service to start the proxy.  An example
+command line for this is `configurable-http-proxy --ip=127.0.0.1
+--port=8000 --api-ip=127.0.0.1 --api-port=8001
+--default-target=http://localhost:8081
+--error-target=http://localhost:8081/hub/error`.  (Details for how to
+do this is out of scope for this tutorial - for example it might be a
+systemd service on within another docker cotainer).  The proxy has no
 configuration files, all configuration is via the command line and
 environment variables.
 
 `--api-ip` and `--api-port` (which tells the proxy where to listen) should match the hub's `ConfigurableHTTPProxy.api_url`.
 
-`--ip`, `-port`, and other options configure the _user_ connections to the proxy.
+`--ip`, `-port`, and other options configure the *user* connections to the proxy.
 
 `--default-target` and `--error-target` should point to the hub, and used when users navigate to the proxy originally.
 
@@ -61,9 +63,10 @@ match the token given to `c.ConfigurableHTTPProxy.auth_token`.
 
 You should check the [configurable-http-proxy
 options](https://github.com/jupyterhub/configurable-http-proxy) to see
-what other options are needed, for example, SSL options. Note that
-these options are configured in the hub if the hub is starting the proxy, so you
-need to configure the options there.
+what other options are needed, for example SSL options.  Note that
+these are configured in the hub if the hub is starting the proxy - you
+need to move the options to here.
+
 
 ## Docker image
 
@@ -71,6 +74,7 @@ You can use [jupyterhub configurable-http-proxy docker
 image](https://hub.docker.com/r/jupyterhub/configurable-http-proxy/)
 to run the proxy.
 
+
 ## See also
 
-- [jupyterhub configurable-http-proxy](https://github.com/jupyterhub/configurable-http-proxy)
+* [jupyterhub configurable-http-proxy](https://github.com/jupyterhub/configurable-http-proxy)