Bump to 4.1.4

changelog for 4.1.4

.flake8

@@ -3,14 +3,9 @@
 # E: style errors
 # W: style warnings
 # C: complexity
-# F401: module imported but unused
-# F403: import *
-# F811: redefinition of unused `name` from line `N`
+# D: docstring warnings (unused pydocstyle extension)
 # F841: local variable assigned but never used
-# 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
+ignore = E, C, W, D, F841
 builtins = c, get_config
 exclude =
     .cache,

.github/dependabot.yaml

@@ -0,0 +1,16 @@
+# dependabot.yaml 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: /
+    labels: [ci]
+    schedule:
+      interval: monthly
+      time: "05:00"
+      timezone: Etc/UTC

.github/workflows/release.yml

@@ -1,31 +1,49 @@
-# Build releases and (on tags) publish to PyPI
+# 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
 
-# always build releases (to make sure wheel-building works)
-# but only publish to PyPI on tags
 on:
-  push:
-    branches:
-      - "!dependabot/**"
-    tags:
-      - "*"
   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
+    runs-on: ubuntu-22.04
     steps:
-      - uses: actions/checkout@v2
-      - uses: actions/setup-python@v2
+      - uses: actions/checkout@v4
+      - uses: actions/setup-python@v5
         with:
-          python-version: 3.8
+          python-version: "3.11"
 
-      - uses: actions/setup-node@v1
+      - uses: actions/setup-node@v4
         with:
-          node-version: "14"
+          node-version: "20"
 
-      - name: install build package
+      - name: install build requirements
         run: |
+          npm install -g yarn
           pip install --upgrade pip
           pip install build
           pip freeze
@@ -35,28 +53,21 @@ jobs:
           python -m build --sdist --wheel .
           ls -l dist
 
-      - name: verify wheel
+      - name: verify sdist
         run: |
-          cd dist
-          pip install ./*.whl
-          # verify data-files are installed where they are found
-          cat <<EOF | python
-          import os
-          from jupyterhub._data import DATA_FILES_PATH
-          print(f"DATA_FILES_PATH={DATA_FILES_PATH}")
-          assert os.path.exists(DATA_FILES_PATH), DATA_FILES_PATH
-          for subpath in (
-              "templates/page.html",
-              "static/css/style.min.css",
-              "static/components/jquery/dist/jquery.js",
-          ):
-              path = os.path.join(DATA_FILES_PATH, subpath)
-              assert os.path.exists(path), path
-          print("OK")
-          EOF
+          ./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@v2
+      - uses: actions/upload-artifact@v4
         with:
           name: jupyterhub-${{ github.sha }}
           path: "dist/*"
@@ -72,7 +83,8 @@ jobs:
           twine upload --skip-existing dist/*
 
   publish-docker:
-    runs-on: ubuntu-20.04
+    runs-on: ubuntu-22.04
+    timeout-minutes: 20
 
     services:
       # So that we can test this in PRs/branches
@@ -85,41 +97,38 @@ jobs:
       - 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
+              echo "REGISTRY=quay.io/" >> $GITHUB_ENV
           else
               echo "REGISTRY=localhost:5000/" >> $GITHUB_ENV
           fi
 
-      - uses: actions/checkout@v2
+      - uses: actions/checkout@v4
 
       # 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@25f0500ff22e406f7191a2a8ba8cda16901ca018 # associated tag: v1.0.2
+        uses: docker/setup-qemu-action@v3
 
       - name: Set up Docker Buildx (for multi-arch builds)
-        uses: docker/setup-buildx-action@2a4b53665e15ce7d7049afb11ff1f70ff1610609 # associated tag: v1.1.2
+        uses: docker/setup-buildx-action@v3
         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
+        # 1. Creating a [Robot Account](https://quay.io/organization/jupyterhub?tab=robots) in the JupyterHub
+        # .  Quay.io org
+        # 2. Giving it enough permissions to push to the jupyterhub and singleuser images
+        # 3. Putting the robot account's username and password in GitHub actions environment
         if: env.REGISTRY != 'localhost:5000/'
         run: |
-          docker login -u "${{ secrets.DOCKERHUB_USERNAME }}" -p "${{ secrets.DOCKERHUB_TOKEN }}"
+          docker login -u "${{ secrets.QUAY_USERNAME }}" -p "${{ secrets.QUAY_PASSWORD }}" "${{ env.REGISTRY }}"
+          docker login -u "${{ secrets.DOCKERHUB_USERNAME }}" -p "${{ secrets.DOCKERHUB_TOKEN }}" docker.io
 
+      # 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
@@ -129,15 +138,17 @@ jobs:
       # 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@v1
+        uses: jupyterhub/action-major-minor-tag-calculator@v3
         with:
           githubToken: ${{ secrets.GITHUB_TOKEN }}
-          prefix: "${{ env.REGISTRY }}jupyterhub/jupyterhub:"
+          prefix: >-
+            ${{ env.REGISTRY }}jupyterhub/jupyterhub:
+            jupyterhub/jupyterhub:
           defaultTag: "${{ env.REGISTRY }}jupyterhub/jupyterhub:noref"
           branchRegex: ^\w[\w-.]*$
 
       - name: Build and push jupyterhub
-        uses: docker/build-push-action@e1b7f96249f2e4c8e4ac1519b9608c0d48944a1f # associated tag: v2.4.0
+        uses: docker/build-push-action@v5
         with:
           context: .
           platforms: linux/amd64,linux/arm64
@@ -146,19 +157,21 @@ jobs:
           # array into a comma separated list of tags
           tags: ${{ join(fromJson(steps.jupyterhubtags.outputs.tags)) }}
 
-      # jupyterhub-onbuild
-
+      # image: jupyterhub/jupyterhub-onbuild
+      #
       - name: Get list of jupyterhub-onbuild tags
         id: onbuildtags
-        uses: jupyterhub/action-major-minor-tag-calculator@v1
+        uses: jupyterhub/action-major-minor-tag-calculator@v3
         with:
           githubToken: ${{ secrets.GITHUB_TOKEN }}
-          prefix: "${{ env.REGISTRY }}jupyterhub/jupyterhub-onbuild:"
+          prefix: >-
+            ${{ env.REGISTRY }}jupyterhub/jupyterhub-onbuild:
+            jupyterhub/jupyterhub-onbuild:
           defaultTag: "${{ env.REGISTRY }}jupyterhub/jupyterhub-onbuild:noref"
           branchRegex: ^\w[\w-.]*$
 
       - name: Build and push jupyterhub-onbuild
-        uses: docker/build-push-action@e1b7f96249f2e4c8e4ac1519b9608c0d48944a1f # associated tag: v2.4.0
+        uses: docker/build-push-action@v5
         with:
           build-args: |
             BASE_IMAGE=${{ fromJson(steps.jupyterhubtags.outputs.tags)[0] }}
@@ -167,19 +180,21 @@ jobs:
           push: true
           tags: ${{ join(fromJson(steps.onbuildtags.outputs.tags)) }}
 
-      # jupyterhub-demo
-
+      # image: jupyterhub/jupyterhub-demo
+      #
       - name: Get list of jupyterhub-demo tags
         id: demotags
-        uses: jupyterhub/action-major-minor-tag-calculator@v1
+        uses: jupyterhub/action-major-minor-tag-calculator@v3
         with:
           githubToken: ${{ secrets.GITHUB_TOKEN }}
-          prefix: "${{ env.REGISTRY }}jupyterhub/jupyterhub-demo:"
+          prefix: >-
+            ${{ env.REGISTRY }}jupyterhub/jupyterhub-demo:
+            jupyterhub/jupyterhub-demo:
           defaultTag: "${{ env.REGISTRY }}jupyterhub/jupyterhub-demo:noref"
           branchRegex: ^\w[\w-.]*$
 
       - name: Build and push jupyterhub-demo
-        uses: docker/build-push-action@e1b7f96249f2e4c8e4ac1519b9608c0d48944a1f # associated tag: v2.4.0
+        uses: docker/build-push-action@v5
         with:
           build-args: |
             BASE_IMAGE=${{ fromJson(steps.onbuildtags.outputs.tags)[0] }}
@@ -190,3 +205,26 @@ jobs:
           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@v3
+        with:
+          githubToken: ${{ secrets.GITHUB_TOKEN }}
+          prefix: >-
+            ${{ env.REGISTRY }}jupyterhub/singleuser:
+            jupyterhub/singleuser:
+          defaultTag: "${{ env.REGISTRY }}jupyterhub/singleuser:noref"
+          branchRegex: ^\w[\w-.]*$
+
+      - name: Build and push jupyterhub/singleuser
+        uses: docker/build-push-action@v5
+        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

@@ -0,0 +1,31 @@
+# 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@v3
+        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.
+
+            Thank 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

@@ -0,0 +1,107 @@
+# 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
+        with:
+          # make rediraffecheckdiff requires git history to compare current
+          # commit with the main branch and previous releases.
+          fetch-depth: 0
+
+      - 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/
+
+      # readthedocs doesn't halt on warnings,
+      # so raise any warnings here
+      - name: build docs
+        run: |
+          cd docs
+          make html
+
+      - name: check links
+        run: |
+          cd docs
+          make linkcheck
+
+      # make rediraffecheckdiff compares files for different changesets
+      # these diff targets aren't always available
+      # - compare with base ref (usually 'main', always on 'origin') for pull requests
+      # - only compare with tags when running against jupyterhub/jupyterhub
+      #   to avoid errors on forks, which often lack tags
+      - name: check redirects for this PR
+        if: github.event_name == 'pull_request'
+        run: |
+          cd docs
+          export REDIRAFFE_BRANCH=origin/${{ github.base_ref }}
+          make rediraffecheckdiff
+
+      # this should check currently published 'stable' links for redirects
+      - name: check redirects since last release
+        if: github.repository == 'jupyterhub/jupyterhub'
+        run: |
+          cd docs
+          export REDIRAFFE_BRANCH=$(git describe --tags --abbrev=0)
+          make rediraffecheckdiff
+
+      # longer-term redirect check (fixed version) for older links
+      - name: check redirects since 3.0.0
+        if: github.repository == 'jupyterhub/jupyterhub'
+        run: |
+          cd docs
+          export REDIRAFFE_BRANCH=3.0.0
+          make rediraffecheckdiff

.github/workflows/test-jsx.yml

@@ -0,0 +1,52 @@
+# 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

@@ -1,25 +1,43 @@
 # This is a GitHub workflow defining a set of jobs with a set of steps.
-# ref: https://docs.github.com/en/free-pro-team@latest/actions/reference/workflow-syntax-for-github-actions
+# ref: https://docs.github.com/en/actions/learn-github-actions/workflow-syntax-for-github-actions
 #
 name: Test
 
-# 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:
 
 env:
   # UTF-8 content may be interpreted as ascii and causes errors without this.
   LANG: C.UTF-8
+  SQLALCHEMY_WARN_20: "1"
+
+permissions:
+  contents: read
 
 jobs:
   # Run "pytest jupyterhub/tests" in various configurations
   pytest:
     runs-on: ubuntu-20.04
-    timeout-minutes: 10
+    timeout-minutes: 15
 
     strategy:
       # Keep running even if one variation of the job fail
@@ -38,9 +56,9 @@ jobs:
         #   Tests everything when JupyterHub works against a dedicated mysql or
         #   postgresql server.
         #
-        # nbclassic:
+        # legacy_notebook:
         #   Tests everything when the user instances are started with
-        #   notebook instead of jupyter_server.
+        #   the legacy notebook server instead of jupyter_server.
         #
         # ssl:
         #   Tests everything using internal SSL connections instead of
@@ -53,21 +71,39 @@ jobs:
         # 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: "3.6"
+          - python: "3.7"
             oldest_dependencies: oldest_dependencies
-            nbclassic: nbclassic
-          - python: "3.6"
-            subdomain: subdomain
-          - python: "3.7"
-            db: mysql
-          - python: "3.7"
-            ssl: ssl
+            legacy_notebook: legacy_notebook
           - python: "3.8"
-            db: postgres
-          - python: "3.8"
-            nbclassic: nbclassic
+            jupyter_server: "1.*"
+            subset: singleuser
           - python: "3.9"
+            db: mysql
+          - python: "3.10"
+            db: postgres
+          - python: "3.11"
+            subdomain: subdomain
+            serverextension: serverextension
+          - python: "3.11"
+            ssl: ssl
+            serverextension: serverextension
+          - python: "3.11"
+            subdomain: subdomain
+            noextension: noextension
+            subset: singleuser
+          - python: "3.11"
+            ssl: ssl
+            noextension: noextension
+            subset: singleuser
+          - python: "3.11"
+            browser: browser
+          - python: "3.11"
+            subdomain: subdomain
+            browser: browser
+          - python: "3.11"
             main_dependencies: main_dependencies
 
     steps:
@@ -81,7 +117,7 @@ jobs:
           fi
           if [ "${{ matrix.db }}" == "mysql" ]; then
               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
+              echo "JUPYTERHUB_TEST_DB_URL=mysql+mysqldb://root@127.0.0.1:3306/jupyterhub" >> $GITHUB_ENV
           fi
           if [ "${{ matrix.ssl }}" == "ssl" ]; then
               echo "SSL_ENABLED=1" >> $GITHUB_ENV
@@ -92,33 +128,35 @@ jobs:
               echo "PGPASSWORD=hub[test/:?" >> $GITHUB_ENV
               echo "JUPYTERHUB_TEST_DB_URL=postgresql://test_user:hub%5Btest%2F%3A%3F@127.0.0.1:5432/jupyterhub" >> $GITHUB_ENV
           fi
-          if [ "${{ matrix.jupyter_server }}" != "" ]; then
-              echo "JUPYTERHUB_SINGLEUSER_APP=jupyterhub.tests.mockserverapp.MockServerApp" >> $GITHUB_ENV
+          if [ "${{ matrix.serverextension }}" != "" ]; then
+              echo "JUPYTERHUB_SINGLEUSER_EXTENSION=1" >> $GITHUB_ENV
+          elif [ "${{ matrix.noextension }}" != "" ]; then
+              echo "JUPYTERHUB_SINGLEUSER_EXTENSION=0" >> $GITHUB_ENV
           fi
-      - uses: actions/checkout@v2
-      # NOTE: actions/setup-node@v1 make use of a cache within the GitHub base
+      - uses: actions/checkout@v3
+      # NOTE: actions/setup-node@v3 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@v1
+        uses: actions/setup-node@v3
         with:
           node-version: "14"
-      - name: Install Node dependencies
+      - name: Install Javascript dependencies
         run: |
           npm install
-          npm install -g configurable-http-proxy
-          npm install -g yarn
+          npm install -g configurable-http-proxy yarn
           npm list
 
-      # NOTE: actions/setup-python@v2 make use of a cache within the GitHub base
+      # NOTE: actions/setup-python@v4 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@v2
+        uses: actions/setup-python@v4
         with:
-          python-version: ${{ matrix.python }}
+          python-version: "${{ matrix.python }}"
+
       - name: Install Python dependencies
         run: |
           pip install --upgrade pip
-          pip install --upgrade . -r dev-requirements.txt
+          pip install -e ".[test]"
 
           if [ "${{ matrix.oldest_dependencies }}" != "" ]; then
             # take any dependencies in requirements.txt such as tornado>=5.0
@@ -129,18 +167,27 @@ jobs:
           fi
 
           if [ "${{ matrix.main_dependencies }}" != "" ]; then
-              pip install git+https://github.com/ipython/traitlets#egg=traitlets --force
+              # Tests are broken:
+              # https://github.com/jupyterhub/jupyterhub/issues/4418
+              # pip install git+https://github.com/ipython/traitlets#egg=traitlets --force
+              pip install --upgrade --pre sqlalchemy
           fi
-          if [ "${{ matrix.nbclassic }}" != "" ]; then
+          if [ "${{ matrix.legacy_notebook }}" != "" ]; then
               pip uninstall jupyter_server --yes
-              pip install notebook
+              pip install 'notebook<7'
+          fi
+          if [ "${{ matrix.jupyter_server }}" != "" ]; then
+              pip install "jupyter_server==${{ matrix.jupyter_server }}"
           fi
           if [ "${{ matrix.db }}" == "mysql" ]; then
-              pip install mysql-connector-python
+              pip install mysqlclient
           fi
           if [ "${{ matrix.db }}" == "postgres" ]; then
               pip install psycopg2-binary
           fi
+          if [ "${{ matrix.serverextension }}" != "" ]; then
+            pip install 'jupyter-server>=2'
+          fi
 
           pip freeze
 
@@ -169,42 +216,47 @@ 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: Configure browser tests
+        if: matrix.browser
+        run: echo "PYTEST_ADDOPTS=$PYTEST_ADDOPTS -m browser" >> "${GITHUB_ENV}"
+
+      - name: Ensure browsers are installed for playwright
+        if: matrix.browser
+        run: python -m playwright install --with-deps
+
       - name: Run pytest
-        # FIXME: --color=yes explicitly set because:
-        #        https://github.com/actions/runner/issues/241
         run: |
-          pytest -v --maxfail=2 --color=yes --cov=jupyterhub jupyterhub/tests
-      - name: Run yarn jest test
-        run: |
-          cd jsx && yarn && yarn test
-      - name: Submit codecov report
-        run: |
-          codecov
+          pytest -k "${{ matrix.subset }}" --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@v2
+      - uses: actions/checkout@v3
 
       - name: build images
         run: |
-          docker build -t jupyterhub/jupyterhub .
+          DOCKER_BUILDKIT=1 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

.gitignore

@@ -9,16 +9,21 @@ docs/_build
 docs/build
 docs/source/_static/rest-api
 docs/source/rbac/scope-table.md
+docs/source/reference/metrics.md
+
 .ipynb_checkpoints
+jsx/build/
 # ignore config file at the top-level of the repo
 # but not sub-dirs
 /jupyterhub_config.py
 jupyterhub_cookie_secret
 jupyterhub.sqlite
+jupyterhub.sqlite*
 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

.pre-commit-config.yaml

@@ -1,30 +1,66 @@
+# 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
+#
+
+ci:
+  # pre-commit.ci will open PRs updating our hooks once a month
+  autoupdate_schedule: monthly
+
 repos:
+  # Autoformat: Python code, syntax patterns are modernized
   - repo: https://github.com/asottile/pyupgrade
-    rev: v2.28.0
+    rev: v3.15.0
     hooks:
       - id: pyupgrade
         args:
-          - --py36-plus
-  - repo: https://github.com/asottile/reorder_python_imports
-    rev: v2.6.0
+          - --py37-plus
+
+  # Autoformat: Python code
+  - repo: https://github.com/PyCQA/autoflake
+    rev: v2.2.1
     hooks:
-      - id: reorder-python-imports
+      - id: autoflake
+        # args ref: https://github.com/PyCQA/autoflake#advanced-usage
+        args:
+          - --in-place
+
+  # Autoformat: Python code
+  - repo: https://github.com/pycqa/isort
+    rev: 5.13.2
+    hooks:
+      - id: isort
+
+  # Autoformat: Python code
   - repo: https://github.com/psf/black
-    rev: 21.9b0
+    rev: 24.1.1
     hooks:
       - id: black
+
+  # Autoformat: markdown, yaml, javascript (see the file .prettierignore)
   - repo: https://github.com/pre-commit/mirrors-prettier
-    rev: v2.4.1
+    rev: v4.0.0-alpha.8
     hooks:
       - id: prettier
-  - repo: https://github.com/PyCQA/flake8
-    rev: "3.9.2"
-    hooks:
-      - id: flake8
+
+  # Autoformat and linting, misc. details
   - repo: https://github.com/pre-commit/pre-commit-hooks
-    rev: v4.0.1
+    rev: v4.5.0
     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
-      - id: requirements-txt-fixer
+
+  # Linting: Python code (see the file .flake8)
+  - repo: https://github.com/PyCQA/flake8
+    rev: "7.0.0"
+    hooks:
+      - id: flake8

.prettierignore

@@ -1,2 +1,3 @@
 share/jupyterhub/templates/
 share/jupyterhub/static/js/admin-react.js
+jupyterhub/singleuser/templates/

.readthedocs.yaml

@@ -0,0 +1,25 @@
+# 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

@@ -1,26 +0,0 @@
-# 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

CONTRIBUTING.md

@@ -6,134 +6,9 @@ you can follow the [Jupyter contributor guide](https://jupyter.readthedocs.io/en
 Make sure to also follow [Project Jupyter's Code of Conduct](https://github.com/jupyter/governance/blob/HEAD/conduct/code_of_conduct.md)
 for a friendly and welcoming collaborative environment.
 
-## Setting up a development environment
+Please see our documentation on
 
-<!--
-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?
--->
+- [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)
 
-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).
+If you need some help, feel free to ask on [Gitter](https://gitter.im/jupyterhub/jupyterhub) or [Discourse](https://discourse.jupyter.org/).

Dockerfile

@@ -6,7 +6,7 @@
 #
 # Option 1:
 #
-# FROM jupyterhub/jupyterhub:latest
+# FROM quay.io/jupyterhub/jupyterhub:latest
 #
 # And put your configuration file jupyterhub_config.py in /srv/jupyterhub/jupyterhub_config.py.
 #
@@ -14,88 +14,123 @@
 #
 # Or you can create your jupyterhub config and database on the host machine, and mount it with:
 #
-# docker run -v $PWD:/srv/jupyterhub -t jupyterhub/jupyterhub
+# docker run -v $PWD:/srv/jupyterhub -t quay.io/jupyterhub/jupyterhub
 #
 # NOTE
-# If you base on jupyterhub/jupyterhub-onbuild
+# If you base on quay.io/jupyterhub/jupyterhub-onbuild
 # your jupyterhub_config.py will be added automatically
 # from your docker directory.
 
-ARG BASE_IMAGE=ubuntu:focal-20200729
-FROM $BASE_IMAGE AS builder
+######################################################################
+# This Dockerfile uses multi-stage builds with optimisations to build
+# the JupyterHub wheel on the native architecture only
+# https://www.docker.com/blog/faster-multi-platform-builds-dockerfile-cross-compilation-guide/
 
-USER root
+ARG BASE_IMAGE=ubuntu:22.04
 
-ENV DEBIAN_FRONTEND noninteractive
-RUN apt-get update \
- && apt-get install -yq --no-install-recommends \
+
+######################################################################
+# The JupyterHub wheel is pure Python so can be built for any platform
+# on the native architecture (avoiding QEMU emulation)
+FROM --platform=${BUILDPLATFORM:-linux/amd64} $BASE_IMAGE AS jupyterhub-builder
+
+ENV DEBIAN_FRONTEND=noninteractive
+
+# Don't clear apt cache, and don't combine RUN commands, so that cached layers can
+# be reused in other stages
+
+RUN apt-get update -qq \
+ && apt-get install -yqq --no-install-recommends \
     build-essential \
     ca-certificates \
+    curl \
     locales \
     python3-dev \
     python3-pip \
     python3-pycurl \
+    python3-venv \
+ && python3 -m pip install --no-cache-dir --upgrade setuptools pip build wheel
+# Ubuntu 22.04 comes with Nodejs 12 which is too old for building JupyterHub JS
+# It's fine at runtime though (used only by configurable-http-proxy)
+RUN curl -fsSL https://deb.nodesource.com/setup_18.x | bash - \
+ && apt-get install -yqq --no-install-recommends \
     nodejs \
-    npm \
- && apt-get clean \
- && rm -rf /var/lib/apt/lists/*
-
-RUN python3 -m pip install --upgrade setuptools pip wheel
+ && npm install --global yarn
 
+WORKDIR /src/jupyterhub
 # copy everything except whats in .dockerignore, its a
 # compromise between needing to rebuild and maintaining
 # what needs to be part of the build
-COPY . /src/jupyterhub/
-WORKDIR /src/jupyterhub
+COPY . .
 
-# Build client component packages (they will be copied into ./share and
-# packaged with the built wheel.)
-RUN python3 setup.py bdist_wheel
-RUN python3 -m pip wheel --wheel-dir wheelhouse dist/*.whl
+ARG PIP_CACHE_DIR=/tmp/pip-cache
+RUN --mount=type=cache,target=${PIP_CACHE_DIR} \
+    python3 -m build --wheel
 
 
-FROM $BASE_IMAGE
-
-USER root
+######################################################################
+# All other wheels required by JupyterHub, some are platform specific
+FROM $BASE_IMAGE AS wheel-builder
 
 ENV DEBIAN_FRONTEND=noninteractive
 
-RUN apt-get update \
- && apt-get install -yq --no-install-recommends \
+RUN apt-get update -qq \
+ && apt-get install -yqq --no-install-recommends \
+    build-essential \
     ca-certificates \
     curl \
-    gnupg \
     locales \
+    python3-dev \
     python3-pip \
     python3-pycurl \
-    nodejs \
-    npm \
- && apt-get clean \
- && rm -rf /var/lib/apt/lists/*
+    python3-venv \
+ && python3 -m pip install --no-cache-dir --upgrade setuptools pip build wheel
 
-ENV SHELL=/bin/bash \
+WORKDIR /src/jupyterhub
+
+COPY --from=jupyterhub-builder /src/jupyterhub/dist/*.whl /src/jupyterhub/dist/
+ARG PIP_CACHE_DIR=/tmp/pip-cache
+RUN --mount=type=cache,target=${PIP_CACHE_DIR} \
+    python3 -m pip wheel --wheel-dir wheelhouse dist/*.whl
+
+
+######################################################################
+# The final JupyterHub image, platform specific
+FROM $BASE_IMAGE AS jupyterhub
+
+ENV DEBIAN_FRONTEND=noninteractive \
+    SHELL=/bin/bash \
     LC_ALL=en_US.UTF-8 \
     LANG=en_US.UTF-8 \
-    LANGUAGE=en_US.UTF-8
-
-RUN  locale-gen $LC_ALL
-
-# always make sure pip is up to date!
-RUN python3 -m pip install --no-cache --upgrade setuptools pip
-
-RUN npm install -g configurable-http-proxy@^4.2.0 \
- && rm -rf ~/.npm
-
-# install the wheels we built in the first stage
-COPY --from=builder /src/jupyterhub/wheelhouse /tmp/wheelhouse
-RUN python3 -m pip install --no-cache /tmp/wheelhouse/*
-
-RUN mkdir -p /srv/jupyterhub/
-WORKDIR /srv/jupyterhub/
+    LANGUAGE=en_US.UTF-8 \
+    PYTHONDONTWRITEBYTECODE=1
 
 EXPOSE 8000
 
 LABEL maintainer="Jupyter Project <jupyter@googlegroups.com>"
 LABEL org.jupyter.service="jupyterhub"
 
+WORKDIR /srv/jupyterhub
+
+RUN apt-get update -qq \
+ && apt-get install -yqq --no-install-recommends \
+    ca-certificates \
+    curl \
+    gnupg \
+    locales \
+    python-is-python3 \
+    python3-pip \
+    python3-pycurl \
+    nodejs \
+    npm \
+ && locale-gen $LC_ALL \
+ && npm install -g configurable-http-proxy@^4.2.0 \
+ # clean cache and logs
+ && rm -rf /var/lib/apt/lists/* /var/log/* /var/tmp/* ~/.npm
+# install the wheels we built in the previous stage
+RUN --mount=type=cache,from=wheel-builder,source=/src/jupyterhub/wheelhouse,target=/tmp/wheelhouse \
+    # always make sure pip is up to date!
+    python3 -m pip install --no-compile --no-cache-dir --upgrade setuptools pip \
+ && python3 -m pip install --no-compile --no-cache-dir /tmp/wheelhouse/*
+
 CMD ["jupyterhub"]

MANIFEST.in

@@ -8,6 +8,7 @@ include *requirements.txt
 include Dockerfile
 
 graft onbuild
+graft jsx
 graft jupyterhub
 graft scripts
 graft share
@@ -18,6 +19,10 @@ 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

@@ -8,22 +8,12 @@
 
 ---
 
-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)
 [![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)
-[![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)
 [![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)
@@ -56,9 +46,11 @@ Basic principles for operation are:
   servers.
 
 JupyterHub also provides a
-[REST API](https://petstore3.swagger.io/?url=https://raw.githubusercontent.com/jupyter/jupyterhub/HEAD/docs/rest-api.yml#/default)
+[REST API][]
 for administration of the Hub and its users.
 
+[rest api]: https://jupyterhub.readthedocs.io/en/latest/reference/rest-api.html
+
 ## Installation
 
 ### Check prerequisites
@@ -115,8 +107,7 @@ To start the Hub server, run the command:
 
     jupyterhub
 
-Visit `https://localhost:8000` in your browser, and sign in with your unix
-PAM credentials.
+Visit `http://localhost:8000` in your browser, and sign in with your system username and password.
 
 _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.
@@ -126,7 +117,7 @@ more configuration of the system.
 
 ## Configuration
 
-The [Getting Started](https://jupyterhub.readthedocs.io/en/latest/getting-started/index.html) section of the
+The [Getting Started](https://jupyterhub.readthedocs.io/en/latest/tutorial/index.html#getting-started) section of the
 documentation explains the common steps in setting up JupyterHub.
 
 The [**JupyterHub tutorial**](https://github.com/jupyterhub/jupyterhub-tutorial)
@@ -168,10 +159,10 @@ To start the Hub on a specific url and port `10.0.1.2:443` with **https**:
 
 ## Docker
 
-A starter [**docker image for JupyterHub**](https://hub.docker.com/r/jupyterhub/jupyterhub/)
+A starter [**docker image for JupyterHub**](https://quay.io/repository/jupyterhub/jupyterhub)
 gives a baseline deployment of JupyterHub using Docker.
 
-**Important:** This `jupyterhub/jupyterhub` image contains only the Hub itself,
+**Important:** This `quay.io/jupyterhub/jupyterhub` image contains only the Hub itself,
 with no configuration. In general, one needs to make a derivative image, with
 at least a `jupyterhub_config.py` setting up an Authenticator and/or a Spawner.
 To run the single-user servers, which may be on the same system as the Hub or
@@ -179,7 +170,7 @@ not, Jupyter Notebook version 4 or greater must be installed.
 
 The JupyterHub docker image can be started with the following command:
 
-    docker run -p 8000:8000 -d --name jupyterhub jupyterhub/jupyterhub jupyterhub
+    docker run -p 8000:8000 -d --name jupyterhub quay.io/jupyterhub/jupyterhub jupyterhub
 
 This command will create a container named `jupyterhub` that you can
 **stop and resume** with `docker stop/start`.
@@ -189,7 +180,7 @@ 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 a ssl enabled proxy.
+configuration or by using an 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
@@ -238,9 +229,9 @@ You can also talk with us on our JupyterHub [Gitter](https://gitter.im/jupyterhu
 
 - [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](https://petstore3.swagger.io/?url=https://raw.githubusercontent.com/jupyter/jupyterhub/HEAD/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)
+- [Documentation for JupyterHub](https://jupyterhub.readthedocs.io/en/latest/)
+- [Documentation for JupyterHub's REST API][rest api]
+- [Documentation for Project Jupyter](http://jupyter.readthedocs.io/en/latest/index.html)
 - [Project Jupyter website](https://jupyter.org)
 - [Project Jupyter community](https://jupyter.org/community)
 

RELEASE.md

@@ -0,0 +1,55 @@
+# 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

@@ -0,0 +1,5 @@
+# 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).

ci/check_installed_data.py

@@ -0,0 +1,36 @@
+#!/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/spawn.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",
+    "singleuser/templates/page.html",
+):
+    path = jupyterhub_path / subpath
+    assert path.is_file(), path
+
+print("OK")

ci/check_sdist.py

@@ -0,0 +1,27 @@
+#!/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 [[ "$DB" == "mysql" ]]; then
     # ref server: https://hub.docker.com/_/mysql/
     # ref client: https://dev.mysql.com/doc/refman/5.7/en/setting-environment-variables.html
     #
-    DOCKER_RUN_ARGS="-p 3306:3306 --env MYSQL_ALLOW_EMPTY_PASSWORD=1 mysql:5.7"
+    DOCKER_RUN_ARGS="-p 3306:3306 --env MYSQL_ALLOW_EMPTY_PASSWORD=1 mysql:8.0"
     READINESS_CHECK="mysql --user root --execute \q"
 elif [[ "$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=${PGPASSWORD}" postgres:9.5"
+    DOCKER_RUN_ARGS="-p 5432:5432 --env "POSTGRES_USER=${PGUSER}" --env "POSTGRES_PASSWORD=${PGPASSWORD}" postgres:15.1"
     READINESS_CHECK="psql --command \q"
 else
     echo '$DB must be mysql or postgres'

ci/init-db.sh

@@ -19,8 +19,9 @@ 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_100 _upgrade_122 _upgrade_130; do
+for SUFFIX in '' _upgrade_110 _upgrade_122 _upgrade_130 _upgrade_150 _upgrade_211; do
     $SQL_CLIENT "DROP DATABASE jupyterhub${SUFFIX};" 2>/dev/null || true
     $SQL_CLIENT "CREATE DATABASE jupyterhub${SUFFIX} ${EXTRA_CREATE_DATABASE_ARGS:-};"
 done

demo-image/Dockerfile

@@ -3,7 +3,7 @@
 # This should only be used for demo or testing and not as a base image to build on.
 #
 # It includes the notebook package and it uses the DummyAuthenticator and the SimpleLocalProcessSpawner.
-ARG BASE_IMAGE=jupyterhub/jupyterhub-onbuild
+ARG BASE_IMAGE=quay.io/jupyterhub/jupyterhub-onbuild
 FROM ${BASE_IMAGE}
 
 # Install the notebook package

dev-requirements.txt

@@ -1,20 +0,0 @@
--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
-jupyterlab >=3
-mock
-pre-commit
-pytest>=3.3
-pytest-asyncio
-pytest-cov
-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 +0,0 @@
-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
-
-ARG JUPYTERHUB_VERSION=1.3.0
-RUN pip3 install --no-cache jupyterhub==${JUPYTERHUB_VERSION}
-
-USER nobody
-CMD ["jupyterhub"]

dockerfiles/README.md

@@ -1,20 +0,0 @@
-## What is Dockerfile.alpine
-
-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?
-
-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 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

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

docs/Makefile

@@ -1,217 +1,62 @@
-# Makefile for Sphinx documentation
-#
+# Makefile for Sphinx documentation generated by sphinx-quickstart
+# ----------------------------------------------------------------------------
 
-# You can set these variables from the command line.
-SPHINXOPTS    = "-W"
-SPHINXBUILD   = sphinx-build
-PAPER         =
-BUILDDIR      = build
-
-# User-friendly check for sphinx-build
-ifeq ($(shell which $(SPHINXBUILD) >/dev/null 2>&1; echo $$?), 1)
-$(error The '$(SPHINXBUILD)' command was not found. Make sure you have Sphinx installed, then set the SPHINXBUILD environment variable to point to the full path of the '$(SPHINXBUILD)' executable. Alternatively you can add the directory with the executable to your PATH. If you don't have Sphinx installed, grab it from http://sphinx-doc.org/)
-endif
-
-# Internal variables.
-PAPEROPT_a4     = -D latex_paper_size=a4
-PAPEROPT_letter = -D latex_paper_size=letter
-ALLSPHINXOPTS   = -d $(BUILDDIR)/doctrees $(PAPEROPT_$(PAPER)) $(SPHINXOPTS) source
-# the i18n builder cannot share the environment and doctrees with the others
-I18NSPHINXOPTS  = $(PAPEROPT_$(PAPER)) $(SPHINXOPTS) source
-
-.PHONY: help clean html dirhtml singlehtml pickle json htmlhelp qthelp devhelp epub latex latexpdf text man changes linkcheck doctest coverage gettext
+# You can set these variables from the command line, and also
+# from the environment for the first two.
+SPHINXOPTS    ?= --color -W --keep-going
+SPHINXBUILD   ?= sphinx-build
+SOURCEDIR     = source
+BUILDDIR      = _build
 
+# Put it first so that "make" without argument is like "make help".
 help:
-	@echo "Please use \`make <target>' where <target> is one of"
-	@echo "  html       to make standalone HTML files"
-	@echo "  dirhtml    to make HTML files named index.html in directories"
-	@echo "  singlehtml to make a single large HTML file"
-	@echo "  pickle     to make pickle files"
-	@echo "  json       to make JSON files"
-	@echo "  htmlhelp   to make HTML files and a HTML help project"
-	@echo "  qthelp     to make HTML files and a qthelp project"
-	@echo "  applehelp  to make an Apple Help Book"
-	@echo "  devhelp    to make HTML files and a Devhelp project"
-	@echo "  epub       to make an epub"
-	@echo "  latex      to make LaTeX files, you can set PAPER=a4 or PAPER=letter"
-	@echo "  latexpdf   to make LaTeX files and run them through pdflatex"
-	@echo "  latexpdfja to make LaTeX files and run them through platex/dvipdfmx"
-	@echo "  text       to make text files"
-	@echo "  man        to make manual pages"
-	@echo "  texinfo    to make Texinfo files"
-	@echo "  info       to make Texinfo files and run them through makeinfo"
-	@echo "  gettext    to make PO message catalogs"
-	@echo "  changes    to make an overview of all changed/added/deprecated items"
-	@echo "  xml        to make Docutils-native XML files"
-	@echo "  pseudoxml  to make pseudoxml-XML files for display purposes"
-	@echo "  linkcheck  to check all external links for integrity"
-	@echo "  doctest    to run all doctests embedded in the documentation (if enabled)"
-	@echo "  coverage   to run coverage check of the documentation (if enabled)"
-	@echo "  spelling   to run spell check on documentation"
-	@echo "  metrics    to generate documentation for metrics by inspecting the source code"
+	@$(SPHINXBUILD) -M help "$(SOURCEDIR)" "$(BUILDDIR)" $(SPHINXOPTS)
 
-clean:
-	rm -rf $(BUILDDIR)/*
+.PHONY: help Makefile metrics scopes
 
-node_modules: package.json
-	npm install && touch node_modules
+# Catch-all target: route all unknown targets to Sphinx using the new
+# "make mode" option.
+#
+# Several sphinx-build commands can be used through this, for example:
+#
+# - make clean
+# - make linkcheck
+# - make spelling
+#
+%: Makefile
+	@$(SPHINXBUILD) -M $@ "$(SOURCEDIR)" "$(BUILDDIR)" $(SPHINXOPTS)
 
-rest-api: source/_static/rest-api/index.html
 
-source/_static/rest-api/index.html: rest-api.yml node_modules
-	npm run rest-api
+# Manually added targets - related to code generation
+# ----------------------------------------------------------------------------
 
-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
-
-html: rest-api metrics scopes
-	$(SPHINXBUILD) -b html $(ALLSPHINXOPTS) $(BUILDDIR)/html
+# For local development:
+# - builds the html
+# - NOTE: 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
+	$(SPHINXBUILD) -b html "$(SOURCEDIR)" "$(BUILDDIR)/html" $(SPHINXOPTS)
 	@echo
 	@echo "Build finished. The HTML pages are in $(BUILDDIR)/html."
 
-dirhtml:
-	$(SPHINXBUILD) -b dirhtml $(ALLSPHINXOPTS) $(BUILDDIR)/dirhtml
-	@echo
-	@echo "Build finished. The HTML pages are in $(BUILDDIR)/dirhtml."
+metrics: source/reference/metrics.md
+source/reference/metrics.md:
+	python3 generate-metrics.py
 
-singlehtml:
-	$(SPHINXBUILD) -b singlehtml $(ALLSPHINXOPTS) $(BUILDDIR)/singlehtml
-	@echo
-	@echo "Build finished. The HTML page is in $(BUILDDIR)/singlehtml."
+scopes: source/rbac/scope-table.md
+source/rbac/scope-table.md:
+	python3 source/rbac/generate-scope-table.py
 
-pickle:
-	$(SPHINXBUILD) -b pickle $(ALLSPHINXOPTS) $(BUILDDIR)/pickle
-	@echo
-	@echo "Build finished; now you can process the pickle files."
 
-json:
-	$(SPHINXBUILD) -b json $(ALLSPHINXOPTS) $(BUILDDIR)/json
-	@echo
-	@echo "Build finished; now you can process the JSON files."
+# Manually added targets - related to development
+# ----------------------------------------------------------------------------
 
-htmlhelp:
-	$(SPHINXBUILD) -b htmlhelp $(ALLSPHINXOPTS) $(BUILDDIR)/htmlhelp
-	@echo
-	@echo "Build finished; now you can run HTML Help Workshop with the" \
-	      ".hhp project file in $(BUILDDIR)/htmlhelp."
-
-qthelp:
-	$(SPHINXBUILD) -b qthelp $(ALLSPHINXOPTS) $(BUILDDIR)/qthelp
-	@echo
-	@echo "Build finished; now you can run "qcollectiongenerator" with the" \
-	      ".qhcp project file in $(BUILDDIR)/qthelp, like this:"
-	@echo "# qcollectiongenerator $(BUILDDIR)/qthelp/JupyterHub.qhcp"
-	@echo "To view the help file:"
-	@echo "# assistant -collectionFile $(BUILDDIR)/qthelp/JupyterHub.qhc"
-
-applehelp:
-	$(SPHINXBUILD) -b applehelp $(ALLSPHINXOPTS) $(BUILDDIR)/applehelp
-	@echo
-	@echo "Build finished. The help book is in $(BUILDDIR)/applehelp."
-	@echo "N.B. You won't be able to view it unless you put it in" \
-	      "~/Library/Documentation/Help or install it in your application" \
-	      "bundle."
-
-devhelp:
-	$(SPHINXBUILD) -b devhelp $(ALLSPHINXOPTS) $(BUILDDIR)/devhelp
-	@echo
-	@echo "Build finished."
-	@echo "To view the help file:"
-	@echo "# mkdir -p $$HOME/.local/share/devhelp/JupyterHub"
-	@echo "# ln -s $(BUILDDIR)/devhelp $$HOME/.local/share/devhelp/JupyterHub"
-	@echo "# devhelp"
-
-epub:
-	$(SPHINXBUILD) -b epub $(ALLSPHINXOPTS) $(BUILDDIR)/epub
-	@echo
-	@echo "Build finished. The epub file is in $(BUILDDIR)/epub."
-
-latex:
-	$(SPHINXBUILD) -b latex $(ALLSPHINXOPTS) $(BUILDDIR)/latex
-	@echo
-	@echo "Build finished; the LaTeX files are in $(BUILDDIR)/latex."
-	@echo "Run \`make' in that directory to run these through (pdf)latex" \
-	      "(use \`make latexpdf' here to do that automatically)."
-
-latexpdf:
-	$(SPHINXBUILD) -b latex $(ALLSPHINXOPTS) $(BUILDDIR)/latex
-	@echo "Running LaTeX files through pdflatex..."
-	$(MAKE) -C $(BUILDDIR)/latex all-pdf
-	@echo "pdflatex finished; the PDF files are in $(BUILDDIR)/latex."
-
-latexpdfja:
-	$(SPHINXBUILD) -b latex $(ALLSPHINXOPTS) $(BUILDDIR)/latex
-	@echo "Running LaTeX files through platex and dvipdfmx..."
-	$(MAKE) -C $(BUILDDIR)/latex all-pdf-ja
-	@echo "pdflatex finished; the PDF files are in $(BUILDDIR)/latex."
-
-text:
-	$(SPHINXBUILD) -b text $(ALLSPHINXOPTS) $(BUILDDIR)/text
-	@echo
-	@echo "Build finished. The text files are in $(BUILDDIR)/text."
-
-man:
-	$(SPHINXBUILD) -b man $(ALLSPHINXOPTS) $(BUILDDIR)/man
-	@echo
-	@echo "Build finished. The manual pages are in $(BUILDDIR)/man."
-
-texinfo:
-	$(SPHINXBUILD) -b texinfo $(ALLSPHINXOPTS) $(BUILDDIR)/texinfo
-	@echo
-	@echo "Build finished. The Texinfo files are in $(BUILDDIR)/texinfo."
-	@echo "Run \`make' in that directory to run these through makeinfo" \
-	      "(use \`make info' here to do that automatically)."
-
-info:
-	$(SPHINXBUILD) -b texinfo $(ALLSPHINXOPTS) $(BUILDDIR)/texinfo
-	@echo "Running Texinfo files through makeinfo..."
-	make -C $(BUILDDIR)/texinfo info
-	@echo "makeinfo finished; the Info files are in $(BUILDDIR)/texinfo."
-
-gettext:
-	$(SPHINXBUILD) -b gettext $(I18NSPHINXOPTS) $(BUILDDIR)/locale
-	@echo
-	@echo "Build finished. The message catalogs are in $(BUILDDIR)/locale."
-
-changes:
-	$(SPHINXBUILD) -b changes $(ALLSPHINXOPTS) $(BUILDDIR)/changes
-	@echo
-	@echo "The overview file is in $(BUILDDIR)/changes."
-
-linkcheck:
-	$(SPHINXBUILD) -b linkcheck $(ALLSPHINXOPTS) $(BUILDDIR)/linkcheck
-	@echo
-	@echo "Link check complete; look for any errors in the above output " \
-	      "or in $(BUILDDIR)/linkcheck/output.txt."
-
-spelling:
-	$(SPHINXBUILD) -b spelling $(ALLSPHINXOPTS) $(BUILDDIR)/spelling
-	@echo
-	@echo "Spell check complete; look for any errors in the above output " \
-	      "or in $(BUILDDIR)/spelling/output.txt."
-doctest:
-	$(SPHINXBUILD) -b doctest $(ALLSPHINXOPTS) $(BUILDDIR)/doctest
-	@echo "Testing of doctests in the sources finished, look at the " \
-	      "results in $(BUILDDIR)/doctest/output.txt."
-
-coverage:
-	$(SPHINXBUILD) -b coverage $(ALLSPHINXOPTS) $(BUILDDIR)/coverage
-	@echo "Testing of coverage in the sources finished, look at the " \
-	      "results in $(BUILDDIR)/coverage/python.txt."
-
-xml:
-	$(SPHINXBUILD) -b xml $(ALLSPHINXOPTS) $(BUILDDIR)/xml
-	@echo
-	@echo "Build finished. The XML files are in $(BUILDDIR)/xml."
-
-pseudoxml:
-	$(SPHINXBUILD) -b pseudoxml $(ALLSPHINXOPTS) $(BUILDDIR)/pseudoxml
-	@echo
-	@echo "Build finished. The pseudo-XML files are in $(BUILDDIR)/pseudoxml."
+# For local development:
+# - requires sphinx-autobuild, see
+#   https://sphinxcontrib-spelling.readthedocs.io/en/latest/
+# - builds and rebuilds html on changes to source, but does not re-generate
+#   metrics/scopes files
+# - starts a livereload enabled webserver and opens up a browser
+devenv: html
+	sphinx-autobuild -b html --open-browser "$(SOURCEDIR)" "$(BUILDDIR)/html"

docs/generate-metrics.py

@@ -1,8 +1,6 @@
 import os
-from os.path import join
 
-from pytablewriter import RstSimpleTableWriter
-from pytablewriter.style import Style
+from pytablewriter import MarkdownTableWriter
 
 import jupyterhub.metrics
 
@@ -12,12 +10,11 @@ HERE = os.path.abspath(os.path.dirname(__file__))
 class Generator:
     @classmethod
     def create_writer(cls, table_name, headers, values):
-        writer = RstSimpleTableWriter()
+        writer = MarkdownTableWriter()
         writer.table_name = table_name
         writer.headers = headers
         writer.value_matrix = values
         writer.margin = 1
-        [writer.set_style(header, Style(align="center")) for header in headers]
         return writer
 
     def _parse_metrics(self):
@@ -34,18 +31,17 @@ class Generator:
         if not os.path.exists(generated_directory):
             os.makedirs(generated_directory)
 
-        filename = f"{generated_directory}/metrics.rst"
+        filename = f"{generated_directory}/metrics.md"
         table_name = ""
         headers = ["Type", "Name", "Description"]
         values = self._parse_metrics()
         writer = self.create_writer(table_name, headers, values)
 
-        title = "List of Prometheus Metrics"
-        underline = "============================"
-        content = f"{title}\n{underline}\n{writer.dumps()}"
         with open(filename, 'w') as f:
-            f.write(content)
-        print(f"Generated {filename}.")
+            f.write("# List of Prometheus Metrics\n\n")
+            f.write(writer.dumps())
+            f.write("\n")
+        print(f"Generated {filename}")
 
 
 def main():

docs/make.bat

@@ -1,263 +1,49 @@
 @ECHO OFF
 
+pushd %~dp0
+
 REM Command file for Sphinx documentation
 
+if "%SPHINXBUILD%" == "" (
+	set SPHINXBUILD=--color -W --keep-going
+)
 if "%SPHINXBUILD%" == "" (
 	set SPHINXBUILD=sphinx-build
 )
-set BUILDDIR=build
-set ALLSPHINXOPTS=-d %BUILDDIR%/doctrees %SPHINXOPTS% source
-set I18NSPHINXOPTS=%SPHINXOPTS% source
-if NOT "%PAPER%" == "" (
-	set ALLSPHINXOPTS=-D latex_paper_size=%PAPER% %ALLSPHINXOPTS%
-	set I18NSPHINXOPTS=-D latex_paper_size=%PAPER% %I18NSPHINXOPTS%
-)
+set SOURCEDIR=source
+set BUILDDIR=_build
 
 if "%1" == "" goto help
-
-if "%1" == "help" (
-	:help
-	echo.Please use `make ^<target^>` where ^<target^> is one of
-	echo.  html       to make standalone HTML files
-	echo.  dirhtml    to make HTML files named index.html in directories
-	echo.  singlehtml to make a single large HTML file
-	echo.  pickle     to make pickle files
-	echo.  json       to make JSON files
-	echo.  htmlhelp   to make HTML files and a HTML help project
-	echo.  qthelp     to make HTML files and a qthelp project
-	echo.  devhelp    to make HTML files and a Devhelp project
-	echo.  epub       to make an epub
-	echo.  latex      to make LaTeX files, you can set PAPER=a4 or PAPER=letter
-	echo.  text       to make text files
-	echo.  man        to make manual pages
-	echo.  texinfo    to make Texinfo files
-	echo.  gettext    to make PO message catalogs
-	echo.  changes    to make an overview over all changed/added/deprecated items
-	echo.  xml        to make Docutils-native XML files
-	echo.  pseudoxml  to make pseudoxml-XML files for display purposes
-	echo.  linkcheck  to check all external links for integrity
-	echo.  doctest    to run all doctests embedded in the documentation if enabled
-	echo.  coverage   to run coverage check of the documentation if enabled
-	goto end
-)
-
-if "%1" == "clean" (
-	for /d %%i in (%BUILDDIR%\*) do rmdir /q /s %%i
-	del /q /s %BUILDDIR%\*
-	goto end
-)
+if "%1" == "devenv" goto devenv
+goto default
 
 
-REM Check if sphinx-build is available and fallback to Python version if any
-%SPHINXBUILD% 1>NUL 2>NUL
-if errorlevel 9009 goto sphinx_python
-goto sphinx_ok
-
-:sphinx_python
-
-set SPHINXBUILD=python -m sphinx.__init__
-%SPHINXBUILD% 2> nul
+:default
+%SPHINXBUILD% >NUL 2>NUL
 if errorlevel 9009 (
 	echo.
-	echo.The 'sphinx-build' command was not found. Make sure you have Sphinx
-	echo.installed, then set the SPHINXBUILD environment variable to point
-	echo.to the full path of the 'sphinx-build' executable. Alternatively you
-	echo.may add the Sphinx directory to PATH.
-	echo.
-	echo.If you don't have Sphinx installed, grab it from
-	echo.http://sphinx-doc.org/
+	echo.The 'sphinx-build' command was not found. Open and read README.md!
 	exit /b 1
 )
-
-:sphinx_ok
+%SPHINXBUILD% -M %1 "%SOURCEDIR%" "%BUILDDIR%" %SPHINXOPTS%
+goto end
 
 
-if "%1" == "html" (
-	%SPHINXBUILD% -b html %ALLSPHINXOPTS% %BUILDDIR%/html
-	if errorlevel 1 exit /b 1
+:help
+%SPHINXBUILD% -M help "%SOURCEDIR%" "%BUILDDIR%" %SPHINXOPTS%
+goto end
+
+
+:devenv
+sphinx-autobuild >NUL 2>NUL
+if errorlevel 9009 (
 	echo.
-	echo.Build finished. The HTML pages are in %BUILDDIR%/html.
-	goto end
+	echo.The 'sphinx-autobuild' command was not found. Open and read README.md!
+	exit /b 1
 )
+sphinx-autobuild -b html --open-browser "%SOURCEDIR%" "%BUILDDIR%/html"
+goto end
 
-if "%1" == "dirhtml" (
-	%SPHINXBUILD% -b dirhtml %ALLSPHINXOPTS% %BUILDDIR%/dirhtml
-	if errorlevel 1 exit /b 1
-	echo.
-	echo.Build finished. The HTML pages are in %BUILDDIR%/dirhtml.
-	goto end
-)
-
-if "%1" == "singlehtml" (
-	%SPHINXBUILD% -b singlehtml %ALLSPHINXOPTS% %BUILDDIR%/singlehtml
-	if errorlevel 1 exit /b 1
-	echo.
-	echo.Build finished. The HTML pages are in %BUILDDIR%/singlehtml.
-	goto end
-)
-
-if "%1" == "pickle" (
-	%SPHINXBUILD% -b pickle %ALLSPHINXOPTS% %BUILDDIR%/pickle
-	if errorlevel 1 exit /b 1
-	echo.
-	echo.Build finished; now you can process the pickle files.
-	goto end
-)
-
-if "%1" == "json" (
-	%SPHINXBUILD% -b json %ALLSPHINXOPTS% %BUILDDIR%/json
-	if errorlevel 1 exit /b 1
-	echo.
-	echo.Build finished; now you can process the JSON files.
-	goto end
-)
-
-if "%1" == "htmlhelp" (
-	%SPHINXBUILD% -b htmlhelp %ALLSPHINXOPTS% %BUILDDIR%/htmlhelp
-	if errorlevel 1 exit /b 1
-	echo.
-	echo.Build finished; now you can run HTML Help Workshop with the ^
-.hhp project file in %BUILDDIR%/htmlhelp.
-	goto end
-)
-
-if "%1" == "qthelp" (
-	%SPHINXBUILD% -b qthelp %ALLSPHINXOPTS% %BUILDDIR%/qthelp
-	if errorlevel 1 exit /b 1
-	echo.
-	echo.Build finished; now you can run "qcollectiongenerator" with the ^
-.qhcp project file in %BUILDDIR%/qthelp, like this:
-	echo.^> qcollectiongenerator %BUILDDIR%\qthelp\JupyterHub.qhcp
-	echo.To view the help file:
-	echo.^> assistant -collectionFile %BUILDDIR%\qthelp\JupyterHub.ghc
-	goto end
-)
-
-if "%1" == "devhelp" (
-	%SPHINXBUILD% -b devhelp %ALLSPHINXOPTS% %BUILDDIR%/devhelp
-	if errorlevel 1 exit /b 1
-	echo.
-	echo.Build finished.
-	goto end
-)
-
-if "%1" == "epub" (
-	%SPHINXBUILD% -b epub %ALLSPHINXOPTS% %BUILDDIR%/epub
-	if errorlevel 1 exit /b 1
-	echo.
-	echo.Build finished. The epub file is in %BUILDDIR%/epub.
-	goto end
-)
-
-if "%1" == "latex" (
-	%SPHINXBUILD% -b latex %ALLSPHINXOPTS% %BUILDDIR%/latex
-	if errorlevel 1 exit /b 1
-	echo.
-	echo.Build finished; the LaTeX files are in %BUILDDIR%/latex.
-	goto end
-)
-
-if "%1" == "latexpdf" (
-	%SPHINXBUILD% -b latex %ALLSPHINXOPTS% %BUILDDIR%/latex
-	cd %BUILDDIR%/latex
-	make all-pdf
-	cd %~dp0
-	echo.
-	echo.Build finished; the PDF files are in %BUILDDIR%/latex.
-	goto end
-)
-
-if "%1" == "latexpdfja" (
-	%SPHINXBUILD% -b latex %ALLSPHINXOPTS% %BUILDDIR%/latex
-	cd %BUILDDIR%/latex
-	make all-pdf-ja
-	cd %~dp0
-	echo.
-	echo.Build finished; the PDF files are in %BUILDDIR%/latex.
-	goto end
-)
-
-if "%1" == "text" (
-	%SPHINXBUILD% -b text %ALLSPHINXOPTS% %BUILDDIR%/text
-	if errorlevel 1 exit /b 1
-	echo.
-	echo.Build finished. The text files are in %BUILDDIR%/text.
-	goto end
-)
-
-if "%1" == "man" (
-	%SPHINXBUILD% -b man %ALLSPHINXOPTS% %BUILDDIR%/man
-	if errorlevel 1 exit /b 1
-	echo.
-	echo.Build finished. The manual pages are in %BUILDDIR%/man.
-	goto end
-)
-
-if "%1" == "texinfo" (
-	%SPHINXBUILD% -b texinfo %ALLSPHINXOPTS% %BUILDDIR%/texinfo
-	if errorlevel 1 exit /b 1
-	echo.
-	echo.Build finished. The Texinfo files are in %BUILDDIR%/texinfo.
-	goto end
-)
-
-if "%1" == "gettext" (
-	%SPHINXBUILD% -b gettext %I18NSPHINXOPTS% %BUILDDIR%/locale
-	if errorlevel 1 exit /b 1
-	echo.
-	echo.Build finished. The message catalogs are in %BUILDDIR%/locale.
-	goto end
-)
-
-if "%1" == "changes" (
-	%SPHINXBUILD% -b changes %ALLSPHINXOPTS% %BUILDDIR%/changes
-	if errorlevel 1 exit /b 1
-	echo.
-	echo.The overview file is in %BUILDDIR%/changes.
-	goto end
-)
-
-if "%1" == "linkcheck" (
-	%SPHINXBUILD% -b linkcheck %ALLSPHINXOPTS% %BUILDDIR%/linkcheck
-	if errorlevel 1 exit /b 1
-	echo.
-	echo.Link check complete; look for any errors in the above output ^
-or in %BUILDDIR%/linkcheck/output.txt.
-	goto end
-)
-
-if "%1" == "doctest" (
-	%SPHINXBUILD% -b doctest %ALLSPHINXOPTS% %BUILDDIR%/doctest
-	if errorlevel 1 exit /b 1
-	echo.
-	echo.Testing of doctests in the sources finished, look at the ^
-results in %BUILDDIR%/doctest/output.txt.
-	goto end
-)
-
-if "%1" == "coverage" (
-	%SPHINXBUILD% -b coverage %ALLSPHINXOPTS% %BUILDDIR%/coverage
-	if errorlevel 1 exit /b 1
-	echo.
-	echo.Testing of coverage in the sources finished, look at the ^
-results in %BUILDDIR%/coverage/python.txt.
-	goto end
-)
-
-if "%1" == "xml" (
-	%SPHINXBUILD% -b xml %ALLSPHINXOPTS% %BUILDDIR%/xml
-	if errorlevel 1 exit /b 1
-	echo.
-	echo.Build finished. The XML files are in %BUILDDIR%/xml.
-	goto end
-)
-
-if "%1" == "pseudoxml" (
-	%SPHINXBUILD% -b pseudoxml %ALLSPHINXOPTS% %BUILDDIR%/pseudoxml
-	if errorlevel 1 exit /b 1
-	echo.
-	echo.Build finished. The pseudo-XML files are in %BUILDDIR%/pseudoxml.
-	goto end
-)
 
 :end
+popd

docs/package.json

@@ -1,14 +0,0 @@
-{
-  "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

@@ -1,12 +1,21 @@
--r ../requirements.txt
+# 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 .
 
-alabaster_jupyterhub
-# Temporary fix of #3021. Revert back to released autodoc-traits when
-# 0.1.0 released.
-https://github.com/jupyterhub/autodoc-traits/archive/d22282c1c18c6865436e06d8b329c06fe12a07f8.zip
-myst-parser
-pydata-sphinx-theme
+autodoc-traits
+jupyterhub-sphinx-theme
+myst-parser>=0.19
+pre-commit
 pytablewriter>=0.56
-sphinx>=1.7
+ruamel.yaml
+sphinx>=4
 sphinx-copybutton
 sphinx-jsonschema
+sphinxext-opengraph
+sphinxext-rediraffe

docs/source/_static/custom.css

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

docs/source/admin/upgrading.rst

@@ -1,159 +0,0 @@
-.. _admin/upgrading:
-
-====================
-Upgrading JupyterHub
-====================
-
-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
-document is if you have set up your own JupyterHub without using a
-distribution.
-
-It is long because is pretty detailed! Most likely, upgrading
-JupyterHub is painless, quick and with minimal user interruption.
-
-Read the Changelog
-==================
-
-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 authenticators & spawners you are using, so
-read the changelogs for those too!
-
-Notify your users
-=================
-
-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 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
-nor sign in.
-
-
-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 are using sqlite (the default), you
-   should backup the ``jupyterhub.sqlite`` file.
-#. Your ``jupyterhub_config.py`` file.
-#. 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.
-
-
-Shutdown JupyterHub
-===================
-
-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.
-
-Upgrade JupyterHub packages
-===========================
-
-There are two environments where the ``jupyterhub`` package is installed:
-
-#. 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*. 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 same environment as the hub environment. The hub
-   launched the ``jupyterhub-singleuser`` command in this environment,
-   which in turn starts the notebook server.
-
-You need to make sure the version of the ``jupyterhub`` package matches
-in both these environments. If you installed ``jupyterhub`` with pip,
-you can upgrade it with:
-
-.. code-block:: bash
-
-   python3 -m pip install --upgrade jupyterhub==<version>
-
-Where ``<version>`` is the version of JupyterHub you are upgrading to.
-
-If you used ``conda`` to install ``jupyterhub``, you should upgrade it
-with:
-
-.. code-block:: bash
-
-   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,
-or upgrade them separately.
-
-Upgrade JupyterHub database
-===========================
-
-Once new packages are installed, you need to upgrade the JupyterHub
-database. From the hub environment, in the same directory as your
-``jupyterhub_config.py`` file, you should run:
-
-.. code-block:: bash
-
-   jupyterhub upgrade-db
-
-This should find the location of your database, and run necessary upgrades
-for it.
-
-SQLite database disadvantages
------------------------------
-
-SQLite has some disadvantages when it comes to upgrading JupyterHub. These
-are:
-
--  ``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
-
-What happens if I delete my database?
--------------------------------------
-
-Losing the Hub database is often not a big deal. Information that
-resides only in the Hub database includes:
-
--  active login tokens (user cookies, service tokens)
--  users added via JupyterHub UI, instead of config files
--  info about running servers
-
-If the following conditions are true, you should be fine clearing the
-Hub database and starting over:
-
--  users specified in config file, or login using an external
-   authentication provider (Google, GitHub, LDAP, etc)
--  user servers are stopped during upgrade
--  don't mind causing users to login again after upgrade
-
-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
-   expected.
-#. Check the logs for any errors or deprecation warnings. You
-   might have to update your ``jupyterhub_config.py`` file to
-   deal with any deprecated options.
-
-Congratulations, your JupyterHub has been upgraded!

docs/source/api/app.rst

@@ -1,15 +0,0 @@
-=========================
-Application configuration
-=========================
-
-Module: :mod:`jupyterhub.app`
-=============================
-
-.. automodule:: jupyterhub.app
-
-.. currentmodule:: jupyterhub.app
-
-:class:`JupyterHub`
--------------------
-
-.. autoconfigurable:: JupyterHub

docs/source/api/auth.rst

@@ -1,32 +0,0 @@
-==============
-Authenticators
-==============
-
-Module: :mod:`jupyterhub.auth`
-==============================
-
-.. automodule:: jupyterhub.auth
-
-.. currentmodule:: jupyterhub.auth
-
-:class:`Authenticator`
-----------------------
-
-.. autoconfigurable:: Authenticator
-    :members:
-
-:class:`LocalAuthenticator`
----------------------------
-
-.. autoconfigurable:: LocalAuthenticator
-    :members:
-
-:class:`PAMAuthenticator`
--------------------------
-
-.. autoconfigurable:: PAMAuthenticator
-
-:class:`DummyAuthenticator`
----------------------------
-
-.. autoconfigurable:: DummyAuthenticator

docs/source/api/index.rst

@@ -1,38 +0,0 @@
-.. _api-index:
-
-##############
-JupyterHub API
-##############
-
-:Release: |release|
-:Date: |today|
-
-JupyterHub also provides a REST API for administration of the Hub and users.
-The documentation on `Using JupyterHub's REST API <../reference/rest.html>`_ provides
-information on:
-
-- what you can do with the API
-- creating an API token
-- adding API tokens to the config files
-- 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) <https://petstore3.swagger.io/?url=https://raw.githubusercontent.com/jupyterhub/jupyterhub/HEAD/docs/rest-api.yml#!/default>`__.
-The `OpenAPI Initiative`_ (fka Swagger™) is a project used to describe
-and document RESTful APIs.
-
-JupyterHub API Reference:
-
-.. toctree::
-
-    app
-    auth
-    spawner
-    proxy
-    user
-    service
-    services.auth
-
-
-.. _OpenAPI Initiative: https://www.openapis.org/

docs/source/api/proxy.rst

@@ -1,22 +0,0 @@
-=======
-Proxies
-=======
-
-Module: :mod:`jupyterhub.proxy`
-===============================
-
-.. automodule:: jupyterhub.proxy
-
-.. currentmodule:: jupyterhub.proxy
-
-:class:`Proxy`
---------------
-
-.. autoconfigurable:: Proxy
-    :members:
-
-:class:`ConfigurableHTTPProxy`
-------------------------------
-
-.. autoconfigurable:: ConfigurableHTTPProxy
-    :members: debug, auth_token, check_running_interval, api_url, command

docs/source/api/service.rst

@@ -1,16 +0,0 @@
-========
-Services
-========
-
-Module: :mod:`jupyterhub.services.service`
-==========================================
-
-.. automodule:: jupyterhub.services.service
-
-.. currentmodule:: jupyterhub.services.service
-
-:class:`Service`
-----------------
-
-.. autoconfigurable:: Service
-    :members: name, admin, url, api_token, managed, kind, command, cwd, environment, user, oauth_client_id, server, prefix, proxy_spec

docs/source/api/services.auth.rst

@@ -1,40 +0,0 @@
-=======================
-Services Authentication
-=======================
-
-Module: :mod:`jupyterhub.services.auth`
-=======================================
-
-.. automodule:: jupyterhub.services.auth
-
-.. currentmodule:: jupyterhub.services.auth
-
-
-:class:`HubAuth`
-----------------
-
-.. autoconfigurable:: HubAuth
-    :members:
-
-:class:`HubOAuth`
------------------
-
-.. autoconfigurable:: HubOAuth
-    :members:
-
-
-:class:`HubAuthenticated`
--------------------------
-
-.. autoclass:: HubAuthenticated
-    :members:
-
-:class:`HubOAuthenticated`
---------------------------
-
-.. autoclass:: HubOAuthenticated
-
-:class:`HubOAuthCallbackHandler`
---------------------------------
-
-.. autoclass:: HubOAuthCallbackHandler

docs/source/api/spawner.rst

@@ -1,21 +0,0 @@
-========
-Spawners
-========
-
-Module: :mod:`jupyterhub.spawner`
-=================================
-
-.. automodule:: jupyterhub.spawner
-
-.. currentmodule:: jupyterhub.spawner
-
-:class:`Spawner`
-----------------
-
-.. autoconfigurable:: Spawner
-    :members: options_from_form, poll, start, stop, get_args, get_env, get_state, template_namespace, format_string, create_certs, move_certs
-
-:class:`LocalProcessSpawner`
-----------------------------
-
-.. autoconfigurable:: LocalProcessSpawner

docs/source/api/user.rst

@@ -1,36 +0,0 @@
-=====
-Users
-=====
-
-Module: :mod:`jupyterhub.user`
-==============================
-
-.. automodule:: jupyterhub.user
-
-.. currentmodule:: jupyterhub.user
-
-:class:`UserDict`
------------------
-
-.. autoclass:: UserDict
-    :members:
-
-
-:class:`User`
--------------
-
-.. autoclass:: User
-    :members: escaped_name
-    
-    .. attribute:: name
-    
-      The user's name
-    
-    .. attribute:: server
-    
-        The user's Server data object if running, None otherwise.
-        Has ``ip``, ``port`` attributes.
-
-    .. attribute:: spawner
-    
-        The user's :class:`~.Spawner` instance.

docs/source/conf.py

@@ -1,69 +1,80 @@
+# Configuration file for Sphinx to build our documentation to HTML.
 #
+# Configuration reference: https://www.sphinx-doc.org/en/master/usage/configuration.html
+#
+import contextlib
+import datetime
+import io
 import os
-import sys
+import subprocess
 
-# 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',
-    'myst_parser',
-]
-
-myst_enable_extensions = [
-    'colon_fence',
-    'deflist',
-]
-# The master toctree document.
-master_doc = 'index'
-
-# General information about the project.
-project = 'JupyterHub'
-copyright = '2016, Project Jupyter team'
-author = 'Project Jupyter team'
-
-# Autopopulate version
-from os.path import dirname
-
-docs = dirname(dirname(__file__))
-root = dirname(docs)
-sys.path.insert(0, root)
-
-import jupyterhub
-
-# 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
-
-# Set the default role so we can use `foo` instead of ``foo``
-default_role = 'literal'
-
-# -- 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
 
-# create a temp instance of JupyterHub just to get the output of the generate-config
-# and help --all commands.
+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}"
+
+
+# -- 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",
+    "jupyterhub_sphinx_theme",
+    "myst_parser",
+]
+root_doc = "index"
+source_suffix = [".md"]
+# default_role let's use use `foo` instead of ``foo`` in rST
+default_role = "literal"
+
+
+# -- MyST configuration ------------------------------------------------------
+# ref: https://myst-parser.readthedocs.io/en/latest/configuration.html
+#
+myst_heading_anchors = 2
+
+myst_enable_extensions = [
+    # available extensions: https://myst-parser.readthedocs.io/en/latest/syntax/optional.html
+    "attrs_inline",
+    "colon_fence",
+    "deflist",
+    "fieldlist",
+    "substitution",
+]
+
+myst_substitutions = {
+    # date example: Dev 07, 2022
+    "date": datetime.date.today().strftime("%b %d, %Y").title(),
+    "version": jupyterhub.__version__,
+}
+
+
+# -- 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.
+#
 jupyterhub_app = JupyterHub()
 
 
@@ -80,8 +91,8 @@ 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]
 
@@ -97,133 +108,142 @@ class HelpAllDirective(SphinxDirective):
 
     def run(self):
         # The output of the help command for this version
-        buffer = StringIO()
-        with redirect_stdout(buffer):
-            jupyterhub_app.print_help('--help-all')
+        buffer = io.StringIO()
+        with contextlib.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_css_file("custom.css")
+    app.add_directive("jupyterhub-generate-config", ConfigDirective)
+    app.add_directive("jupyterhub-help-all", HelpAllDirective)
 
 
-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',
-        'JupyterHub Documentation',
-        '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
+# -- 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)
 
 
-# -- manual page output -------------------------------------------------
-
-# One entry per manual page. List of tuples
-# (source start file, name, description, authors, manual section).
-man_pages = [(master_doc, 'jupyterhub', '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',
-        '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', 'scopes'], cwd=docs)
-
-# -- Spell checking -------------------------------------------------------
-
+# -- Spell checking ----------------------------------------------------------
+# ref: https://sphinxcontrib-spelling.readthedocs.io/en/latest/customize.html#configuration-options
+#
+# The "sphinxcontrib.spelling" extension is optionally enabled if its available.
+#
 try:
-    import sphinxcontrib.spelling
+    import sphinxcontrib.spelling  # noqa
 except ImportError:
     pass
 else:
     extensions.append("sphinxcontrib.spelling")
+spelling_word_list_filename = "spelling_wordlist.txt"
 
-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 = "jupyterhub_sphinx_theme"
+html_theme_options = {
+    "icon_links": [
+        {
+            "name": "GitHub",
+            "url": "https://github.com/jupyterhub/jupyterhub",
+            "icon": "fa-brands fa-github",
+        },
+    ],
+    "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
+    r"https?://(localhost|127.0.0.1).*",  # ignore localhost references in auto-links
+    r".*/rest-api.html#.*",  # ignore javascript-resolved internal rest-api links
+    r"https://linux.die.net/.*",  # linux.die.net seems to block requests from CI with 403 sometimes
+    # don't check links to unpublished advisories
+    r"https://github.com/jupyterhub/jupyterhub/security/advisories/.*",
+]
+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),
+    "jupyter-server": ("https://jupyter-server.readthedocs.io/en/stable/", None),
+    "nbgitpuller": ("https://nbgitpuller.readthedocs.io/en/latest", 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 extension helps us relocate content without breaking links. If a
+# document is moved internally, a redirect link should be configured as below to
+# help us not break links.
+#
+# The workflow for adding redirects can be as follows:
+# 1. Change "rediraffe_branch" below to point to the commit/ branch you
+#    want to base off the changes.
+# 2. Option 1: run "make rediraffecheckdiff"
+#       a. Analyze the output of this command.
+#       b. Manually add the redirect entries to the "redirects.txt" file.
+#    Option 2: run "make rediraffewritediff"
+#       a. rediraffe will then automatically add the obvious redirects to redirects.txt.
+#       b. Analyze the output of the command for broken links.
+#       c. Check the "redirects.txt" file for any files that were moved/ renamed but are not listed.
+#       d. Manually add the redirects that have been mised by the automatic builder to "redirects.txt".
+#    Option 3: Do not use the commands above and, instead, do everything manually - by taking
+#    note of the files you have moved or renamed and adding them to the "redirects.txt" file.
+#
+# If you are basing changes off another branch/ commit, always change back
+# rediraffe_branch to main before pushing your changes upstream.
+#
+rediraffe_branch = os.environ.get("REDIRAFFE_BRANCH", "main")
+rediraffe_redirects = "redirects.txt"
+
+# allow 80% match for autogenerated redirects
+rediraffe_auto_redirect_perc = 80
+
+# rediraffe_redirects = {
+# "old-file": "new-folder/new-file-name",
+# }

docs/source/contributing/community.md

@@ -0,0 +1,27 @@
+# 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](https://github.com/jupyterhub/zero-to-jupyterhub-k8s) or [The Littlest JupyterHub](https://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

@@ -1,30 +0,0 @@
-.. _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/contributor-list.md

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

docs/source/contributing/docs.md

@@ -0,0 +1,76 @@
+(contributing-docs)=
+
+# Contributing Documentation
+
+Documentation is often more important than code. This page helps
+you get set up on how to contribute to JupyterHub's documentation.
+
+## Building documentation locally
+
+We use [sphinx](https://www.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) &
+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.
+
+1. Make sure you have successfully completed {ref}`contributing/setup`.
+
+2. Install the packages required to build the docs.
+
+   ```bash
+   python3 -m pip install -r docs/requirements.txt
+   ```
+
+3. Build the html version of the docs. This is the most commonly used
+   output format, so verifying it renders correctly is usually good
+   enough.
+
+   ```bash
+   cd docs
+   make html
+   ```
+
+   This step will display any syntax or formatting errors in the documentation,
+   along with the filename / line number in which they occurred. Fix them,
+   and re-run the `make html` command to re-render the documentation.
+
+4. View the rendered documentation by opening `_build/html/index.html` in
+   a web browser.
+
+   :::{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`
+   :::
+
+(contributing-docs-conventions)=
+
+## Documentation conventions
+
+This section lists various conventions we use in our documentation. This is a
+living document that grows over time, so feel free to add to it / change it!
+
+Our entire documentation does not yet fully conform to these conventions yet,
+so help in making it so would be appreciated!
+
+### `pip` invocation
+
+There are many ways to invoke a `pip` command, we recommend the following
+approach:
+
+```bash
+python3 -m pip
+```
+
+This invokes pip explicitly using the python3 binary that you are
+currently using. This is the **recommended way** to invoke pip
+in our documentation, since it is least likely to cause problems
+with python3 and pip being from different environments.
+
+For more information on how to invoke `pip` commands, see
+[the pip documentation](https://pip.pypa.io/en/stable/).

docs/source/contributing/docs.rst

@@ -1,78 +0,0 @@
-.. _contributing/docs:
-
-==========================
-Contributing Documentation
-==========================
-
-Documentation is often more important than code. This page helps
-you get set up on how to contribute documentation to JupyterHub.
-
-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>`_ &
-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 successfuly completed :ref:`contributing/setup`.
-
-#. Install the packages required to build the docs.
-
-   .. code-block:: bash
-
-      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 as you should is usually good
-   enough.
-
-   .. code-block:: bash
-
-      cd docs
-      make html
-
-   This step will display any syntax or formatting errors in the documentation,
-   along with the filename / line number in which they occurred. Fix them,
-   and re-run the ``make html`` command to re-render the documentation.
-
-#. View the rendered documentation by opening ``build/html/index.html`` in
-   a web browser.
-
-   .. tip::
-
-      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:
-
-Documentation conventions
-=========================
-
-This section lists various conventions we use in our documentation. This is a
-living document that grows over time, so feel free to add to it / change it!
-
-Our entire documentation does not yet fully conform to these conventions yet,
-so help in making it so would be appreciated!
-
-``pip`` invocation
-------------------
-
-There are many ways to invoke a ``pip`` command, we recommend the following
-approach:
-
-.. code-block:: bash
-
-   python3 -m pip
-
-This invokes pip explicitly using the python3 binary that you are
-currently using. This is the **recommended way** to invoke pip
-in our documentation, since it is least likely to cause problems
-with python3 and pip being from different environments.
-
-For more information on how to invoke ``pip`` commands, see
-`the pip documentation <https://pip.pypa.io/en/stable/>`_.

docs/source/contributing/index.md

@@ -0,0 +1,22 @@
+# Contributing
+
+We want you to contribute to JupyterHub in ways that are most exciting
+and useful to you. We value documentation, testing, bug reporting & code equally,
+and are glad to have your contributions in whatever form you wish.
+
+Be sure to first check 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)), which help keep our community welcoming to as many people as possible.
+
+This section covers information about our community, as well as ways that you can connect and get involved.
+
+```{toctree}
+:maxdepth: 2
+
+contributor-list
+community
+setup
+docs
+tests
+roadmap
+security
+```

docs/source/contributing/index.rst

@@ -1,21 +0,0 @@
-============
-Contributing
-============
-
-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>`_)
-helps keep our community welcoming to as many people as possible.
-
-.. toctree::
-   :maxdepth: 2
-
-   community
-   setup
-   docs
-   tests
-   roadmap
-   security

docs/source/contributing/roadmap.md

@@ -4,7 +4,7 @@ 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 a aimed at limiting contributions to what is listed here.
+It is not aimed at limiting contributions to what is listed here.
 
 ## Using the roadmap
 

docs/source/contributing/security.md

@@ -0,0 +1,9 @@
+# Reporting security issues in Jupyter or JupyterHub
+
+If you find a security vulnerability in Jupyter or JupyterHub,
+whether it is a failure of the security model described in [Security Overview](web-security)
+or a failure in implementation,
+please report it to <mailto:security@ipython.org>.
+
+If you prefer to encrypt your security reports,
+you can use {download}`this PGP public key </ipython_security.asc>`.

docs/source/contributing/security.rst

@@ -1,10 +0,0 @@
-Reporting security issues in Jupyter or JupyterHub
-==================================================
-
-If you find a security vulnerability in Jupyter or JupyterHub,
-whether it is a failure of the security model described in :doc:`../reference/websecurity`
-or a failure in implementation,
-please report it to security@ipython.org.
-
-If you prefer to encrypt your security reports,
-you can use :download:`this PGP public key </ipython_security.asc>`.

docs/source/contributing/setup.md

@@ -0,0 +1,175 @@
+(contributing/setup)=
+
+# Setting up a development install
+
+## System requirements
+
+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.
+
+### 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
+installed Python before, the recommended way to install it is to use
+[Miniforge](https://github.com/conda-forge/miniforge#download).
+
+### 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.
+
+### Install git
+
+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.
+
+## 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.
+
+:::{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
+[forum thread](https://discourse.jupyter.org/t/thoughts-on-using-tox/3497) for
+a more detailed discussion.
+:::
+
+1. Clone the [JupyterHub git repository](https://github.com/jupyterhub/jupyterhub)
+   to your computer.
+
+   ```bash
+   git clone https://github.com/jupyterhub/jupyterhub
+   cd jupyterhub
+   ```
+
+2. Make sure the `python` you installed and the `npm` you installed
+   are available to you on the command line.
+
+   ```bash
+   python -V
+   ```
+
+   This should return a version number greater than or equal to 3.6.
+
+   ```bash
+   npm -v
+   ```
+
+   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):
+
+   ```bash
+   npm install -g configurable-http-proxy yarn
+   ```
+
+   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:
+
+   ```bash
+   npm install configurable-http-proxy yarn
+   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:
+
+   ```bash
+   conda install configurable-http-proxy yarn
+   ```
+
+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.
+
+   ```bash
+   python3 -m pip install --editable ".[test]"
+   ```
+
+5. Set up 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).
+   See [The Hub's Database](hub-database) for details on other supported databases.
+
+6. You are now ready to start JupyterHub!
+
+   ```bash
+   jupyterhub
+   ```
+
+7. You can access JupyterHub from your browser at
+   `http://localhost:8000` now.
+
+Happy developing!
+
+## Using DummyAuthenticator & SimpleLocalProcessSpawner
+
+To simplify testing of JupyterHub, it is 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
+configuration:
+
+```bash
+jupyterhub -f testing/jupyterhub_config.py
+```
+
+The default JupyterHub [authenticator](PAMAuthenticator)
+& [spawner](LocalProcessSpawner)
+require your system to have user accounts for each user you want to log in to
+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
+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
+parts, use only SimpleLocalProcessSpawner. Similarly, if you are working on
+just spawner-related parts, use only DummyAuthenticator.
+
+## Troubleshooting
+
+This section lists common ways setting up your development environment may
+fail, and how to fix them. Please add to the list if you encounter yet
+another way it can fail!
+
+### `lessc` not found
+
+If the `python3 -m pip install --editable .` command fails and complains about
+`lessc` being unavailable, you may need to explicitly install some
+additional JavaScript dependencies:
+
+```bash
+npm install
+```
+
+This will fetch client-side JavaScript dependencies necessary to compile
+CSS.
+
+You may also need to manually update JavaScript and CSS after some
+development updates, with:
+
+```bash
+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/setup.rst

@@ -1,188 +0,0 @@
-.. _contributing/setup:
-
-================================
-Setting up a development install
-================================
-
-System requirements
-===================
-
-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.
-
-Install Python
---------------
-
-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,
-and **not** the ‘Python 2’ version!
-
-Install nodejs
---------------
-
-``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>`_
-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.
-
-Setting up a development install
-================================
-
-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
-   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.
-
-1. Clone the `JupyterHub git repository <https://github.com/jupyterhub/jupyterhub>`_
-   to your computer.
-
-   .. code:: bash
-
-      git clone https://github.com/jupyterhub/jupyterhub
-      cd jupyterhub
-
-2. Make sure the ``python`` you installed and the ``npm`` you installed
-   are available to you on the command line.
-
-   .. code:: bash
-
-      python -V
-
-   This should return a version number greater than or equal to 3.5.
-
-   .. code:: bash
-
-      npm -v
-
-   This should return a version number greater than or equal to 5.0.
-
-3. Install ``configurable-http-proxy``. This is required to run
-   JupyterHub.
-
-   .. code:: bash
-
-      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``. If you do not
-   have access to sudo, you may instead run the following commands:
-
-   .. code:: bash
-
-      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.
-
-4. Install the python packages required for JupyterHub development.
-
-   .. code:: bash
-
-      python3 -m pip install -r dev-requirements.txt
-      python3 -m pip install -r requirements.txt
-
-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>`__.
-   See :doc:`/reference/database` for details on other supported databases.
-
-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
-
-8. You can access JupyterHub from your browser at
-   ``http://localhost:8000`` now.
-
-Happy developing!
-
-Using DummyAuthenticator & SimpleLocalProcessSpawner
-====================================================
-
-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
-configuration:
-
-.. code:: bash
-
-   jupyterhub -f testing/jupyterhub_config.py
-
-The default JupyterHub `authenticator
-<https://jupyterhub.readthedocs.io/en/stable/reference/authenticators.html#the-default-pam-authenticator>`_
-& `spawner
-<https://jupyterhub.readthedocs.io/en/stable/api/spawner.html#localprocessspawner>`_
-require your system to have user accounts for each user you want to log in to
-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
-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
-parts, use only SimpleLocalProcessSpawner. Similarly, if you are working on
-just spawner related parts, use only DummyAuthenticator.
-
-Troubleshooting
-===============
-
-This section lists common ways setting up your development environment may
-fail, and how to fix them. Please add to the list if you encounter yet
-another way it can fail!
-
-``lessc`` not found
--------------------
-
-If the ``python3 -m pip install --editable .`` command fails and complains about
-``lessc`` being unavailable, you may need to explicitly install some
-additional JavaScript dependencies:
-
-.. code:: bash
-
-   npm install
-
-This will fetch client-side JavaScript dependencies necessary to compile
-CSS.
-
-You may also need to manually update JavaScript and CSS after some
-development updates, with:
-
-.. code:: bash
-
-   python3 setup.py js    # fetch updated client-side js
-   python3 setup.py css   # recompile CSS from LESS sources

docs/source/contributing/tests.md

@@ -0,0 +1,157 @@
+(contributing-tests)=
+
+# Testing JupyterHub and linting code
+
+Unit testing helps to 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.
+
+## Running the tests
+
+1. 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.
+
+2. You can run all tests in JupyterHub
+
+   ```bash
+   pytest -v jupyterhub/tests
+   ```
+
+   This should display progress as it runs all the tests, printing
+   information about any test failures as they occur.
+
+   If you wish to confirm test coverage the run tests with the `--cov` flag:
+
+   ```bash
+   pytest -v --cov=jupyterhub jupyterhub/tests
+   ```
+
+3. You can also run tests in just a specific file:
+
+   ```bash
+   pytest -v jupyterhub/tests/<test-file-name>
+   ```
+
+4. To run a specific test only, you can do:
+
+   ```bash
+   pytest -v jupyterhub/tests/<test-file-name>::<test-name>
+   ```
+
+   This runs the test with function name `<test-name>` defined in
+   `<test-file-name>`. This is very useful when you are iteratively
+   developing a single test.
+
+   For example, to run the test `test_shutdown` in the file `test_api.py`,
+   you would run:
+
+   ```bash
+   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:
+
+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)
+
+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.
+
+### The Pytest-Asyncio Plugin
+
+When testing the various JupyterHub components and their various implementations, it sometimes becomes necessary to have a running instance of JupyterHub to test against.
+The [`app`](https://github.com/jupyterhub/jupyterhub/blob/270b61992143b29af8c2fab90c4ed32f2f6fe209/jupyterhub/tests/conftest.py#L60) fixture mocks a JupyterHub application for use in testing by:
+
+- enabling ssl if internal certificates are available
+- creating an instance of [MockHub](https://github.com/jupyterhub/jupyterhub/blob/270b61992143b29af8c2fab90c4ed32f2f6fe209/jupyterhub/tests/mocking.py#L221) using any provided configurations as arguments
+- initializing the mocked instance
+- starting the mocked instance
+- finally, a registered finalizer function performs a cleanup and stops the mocked instance
+
+The JupyterHub test suite uses the [pytest-asyncio plugin](https://pytest-asyncio.readthedocs.io/en/latest/) that handles [event-loop](https://docs.python.org/3/library/asyncio-eventloop.html) integration in [Tornado](https://www.tornadoweb.org/en/stable/) applications. This allows for the use of top-level awaits when calling async functions or [fixtures](https://docs.pytest.org/en/6.2.x/fixture.html#what-fixtures-are) during testing. All test functions and fixtures labelled as `async` will run on the same event loop.
+
+```{note}
+With the introduction of [top-level awaits](https://piccolo-orm.com/blog/top-level-await-in-python/), the use of the `io_loop` fixture of the [pytest-tornado plugin](https://www.tornadoweb.org/en/stable/ioloop.html) is no longer necessary. It was initially used to call coroutines. With the upgrades made to `pytest-asyncio`, this usage is now deprecated. It is now, only utilized within the JupyterHub test suite to ensure complete cleanup of resources used during testing such as open file descriptors. This is demonstrated in this [pull request](https://github.com/jupyterhub/jupyterhub/pull/4332).
+More information is provided below.
+```
+
+One of the general goals of the [JupyterHub Pytest Plugin project](https://github.com/jupyterhub/pytest-jupyterhub) is to ensure the MockHub cleanup fully closes and stops all utilized resources during testing so the use of the `io_loop` fixture for teardown is not necessary. This was highlighted in this [issue](https://github.com/jupyterhub/pytest-jupyterhub/issues/30)
+
+For more information on asyncio and event-loops, here are some resources:
+
+- **Read**: [Introduction to the Python event loop](https://www.pythontutorial.net/python-concurrency/python-event-loop)
+- **Read**: [Overview of Async IO in Python 3.7](https://stackabuse.com/overview-of-async-io-in-python-3-7)
+- **Watch**: [Asyncio: Understanding Async / Await in Python](https://www.youtube.com/watch?v=bs9tlDFWWdQ)
+- **Watch**: [Learn Python's AsyncIO #2 - The Event Loop](https://www.youtube.com/watch?v=E7Yn5biBZ58)
+
+## 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.
+
+```bash
+pip install pre-commit
+pre-commit install --install-hooks
+```
+
+To run pre-commit manually you would do:
+
+```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.

docs/source/contributing/tests.rst

@@ -1,68 +0,0 @@
-.. _contributing/tests:
-
-==================
-Testing JupyterHub
-==================
-
-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 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`. 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 
-
-   .. code-block:: bash
-
-      pytest -v jupyterhub/tests
-
-   This should display progress as it runs all the tests, printing
-   information about any test failures as they occur.
-   
-   If you wish to confirm test coverage the run tests with the `--cov` flag:
-
-   .. code-block:: bash
-
-      pytest -v --cov=jupyterhub jupyterhub/tests
-
-#. You can also run tests in just a specific file:
-
-   .. code-block:: bash
-
-      pytest -v jupyterhub/tests/<test-file-name>
-
-#. To run a specific test only, you can do:
-
-   .. code-block:: bash
-
-      pytest -v jupyterhub/tests/<test-file-name>::<test-name>
-
-   This runs the test with function name ``<test-name>`` defined in
-   ``<test-file-name>``. This is very useful when you are iteratively
-   developing a single test.
-
-   For example, to run the test ``test_shutdown`` in the file ``test_api.py``,
-   you would run:
-
-   .. code-block:: bash
-      
-      pytest -v jupyterhub/tests/test_api.py::test_shutdown
-
-
-Troubleshooting Test Failures
-=============================
-
-All the tests are failing
--------------------------
-
-Make sure you have completed all the steps in :ref:`contributing/setup` successfully, and
-can launch ``jupyterhub`` from the terminal.

docs/source/events/index.rst

@@ -1,46 +0,0 @@
-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 at the bottom of this page_.
-
-.. _logging: https://docs.python.org/3/library/logging.html
-.. _`Telemetry System`: https://github.com/jupyter/telemetry
-.. _`JSON schemas`: https://json-schema.org/
-
-How to emit events
-------------------
-
-Event logging is handled by its ``Eventlog`` object. This leverages Python's standing logging_ library to emit, filter, and collect event data. 
-
-
-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 
-    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:
-
-.. code-block::
-
-    import logging
-
-    c.EventLog.handlers = [
-        logging.FileHandler('event.log'),
-    ]
-
-    c.EventLog.allowed_schemas = [
-        'hub.jupyter.org/server-action'
-    ]
-
-The output is a file, ``"event.log"``, with events recorded as JSON data.
-
-
-.. _page:
-
-Event schemas
--------------
-
-.. toctree::
-    :maxdepth: 2
-
-    server-actions.rst

docs/source/explanation/capacity-planning.md

@@ -0,0 +1,308 @@
+# 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://z2jh.jupyter.org
+
+(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://z2jh.jupyter.org) documentation on
+  - [projecting costs](https://z2jh.jupyter.org/en/latest/administrator/cost.html)
+  - [configuring user resources](https://z2jh.jupyter.org/en/latest/jupyterhub/customizing/user-resources.html)
+- Cloud platform cost calculators:
+  - [Google Cloud](https://cloud.google.com/products/calculator/)
+  - [Amazon AWS](https://calculator.aws)
+  - [Microsoft Azure](https://azure.microsoft.com/en-us/pricing/calculator/)

docs/source/explanation/database.md

@@ -0,0 +1,183 @@
+(hub-database)=
+
+# The Hub's Database
+
+JupyterHub uses a database to store information about users, services, and other data needed for operating the Hub.
+This is the **state** of the Hub.
+
+## Why does JupyterHub have a database?
+
+JupyterHub is a **stateful** application (more on that 'state' later).
+Updating JupyterHub's configuration or upgrading the version of JupyterHub requires restarting the JupyterHub process to apply the changes.
+We want to minimize the disruption caused by restarting the Hub process, so it can be a mundane, frequent, routine activity.
+Storing state information outside the process for later retrieval is necessary for this, and one of the main thing databases are for.
+
+A lot of the operations in JupyterHub are also **relationships**, which is exactly what SQL databases are great at.
+For example:
+
+- Given an API token, what user is making the request?
+- Which users don't have running servers?
+- Which servers belong to user X?
+- Which users have not been active in the last 24 hours?
+
+Finally, a database allows us to have more information stored without needing it all loaded in memory,
+e.g. supporting a large number (several thousands) of inactive users.
+
+## What's in the database?
+
+The short answer of what's in the JupyterHub database is "everything."
+JupyterHub's **state** lives in the database.
+That is, everything JupyterHub needs to be aware of to function that _doesn't_ come from the configuration files, such as
+
+- users, roles, role assignments
+- state, urls of running servers
+- Hashed API tokens
+- Short-lived state related to OAuth flow
+- Timestamps for when users, tokens, and servers were last used
+
+### What's _not_ in the database
+
+Not _quite_ all of JupyterHub's state is in the database.
+This mostly involves transient state, such as the 'pending' transitions of Spawners (starting, stopping, etc.).
+Anything not in the database must be reconstructed on Hub restart, and the only sources of information to do that are the database and JupyterHub configuration file(s).
+
+## How does JupyterHub use the database?
+
+JupyterHub makes some _unusual_ choices in how it connects to the database.
+These choices represent trade-offs favoring single-process simplicity and performance at the expense of horizontal scalability (multiple Hub instances).
+
+We often say that the Hub 'owns' the database.
+This ownership means that we assume the Hub is the only process that will talk to the database.
+This assumption enables us to make several caching optimizations that dramatically improve JupyterHub's performance (i.e. data written recently to the database can be read from memory instead of fetched again from the database) that would not work if multiple processes could be interacting with the database at the same time.
+
+Database operations are also synchronous, so while JupyterHub is waiting on a database operation, it cannot respond to other requests.
+This allows us to avoid complex locking mechanisms, because transaction races can only occur during an `await`, so we only need to make sure we've completed any given transaction before the next `await` in a given request.
+
+:::{note}
+We are slowly working to remove these assumptions, and moving to a more traditional db session per-request pattern.
+This will enable multiple Hub instances and enable scaling JupyterHub, but will significantly reduce the number of active users a single Hub instance can serve.
+:::
+
+### Database performance in a typical request
+
+Most authenticated requests to JupyterHub involve a few database transactions:
+
+1. look up the authenticated user (e.g. look up token by hash, then resolve owner and permissions)
+2. record activity
+3. perform any relevant changes involved in processing the request (e.g. create the records for a running server when starting one)
+
+This means that the database is involved in almost every request, but only in quite small, simple queries, e.g.:
+
+- lookup one token by hash
+- lookup one user by name
+- list tokens or servers for one user (typically 1-10)
+- etc.
+
+### The database as a limiting factor
+
+As a result of the above transactions in most requests, database performance is the _leading_ factor in JupyterHub's baseline requests-per-second performance, but that cost does not scale significantly with the number of users, active or otherwise.
+However, the database is _rarely_ a limiting factor in JupyterHub performance in a practical sense, because the main thing JupyterHub does is start, stop, and monitor whole servers, which take far more time than any small database transaction, no matter how many records you have or how slow your database is (within reason).
+Additionally, there is usually _very_ little load on the database itself.
+
+By far the most taxing activity on the database is the 'list all users' endpoint, primarily used by the [idle-culling service](https://github.com/jupyterhub/jupyterhub-idle-culler).
+Database-based optimizations have been added to make even these operations feasible for large numbers of users:
+
+1. State filtering on [GET /hub/api/users?state=active](../reference/rest-api.html#/default/get_users){.external},
+   which limits the number of results in the query to only the relevant subset (added in JupyterHub 1.3), rather than all users.
+2. [Pagination](api-pagination) of all list endpoints, allowing the request of a large number of resources to be more fairly balanced with other Hub activities across multiple requests (added in 2.0).
+
+:::{note}
+It's important to note when discussing performance and limiting factors and that all of this only applies to requests to `/hub/...`.
+The Hub and its database are not involved in most requests to single-user servers (`/user/...`), which is by design, and largely motivated by the fact that the Hub itself doesn't _need_ to be fast because its operations are infrequent and large.
+:::
+
+## Database backends
+
+JupyterHub supports a variety of database backends via [SQLAlchemy][].
+The default is sqlite, which works great for many cases, but you should be able to use many backends supported by SQLAlchemy.
+Usually, this will mean PostgreSQL or MySQL, both of which are officially supported and well tested with JupyterHub, but others may work as well.
+See [SQLAlchemy's docs][sqlalchemy-dialect] for how to connect to different database backends.
+Doing so generally involves:
+
+1. installing a Python package that provides a client implementation, and
+2. setting [](JupyterHub.db_url) to connect to your database with the specified implementation
+
+[sqlalchemy-dialect]: https://docs.sqlalchemy.org/en/20/dialects/
+[sqlalchemy]: https://www.sqlalchemy.org
+
+### Default backend: SQLite
+
+The default database backend for JupyterHub is [SQLite](https://sqlite.org).
+We have chosen SQLite as JupyterHub's default because it's simple (the 'database' is a single file) and ubiquitous (it is in the Python standard library).
+It works very well for testing, small deployments, and workshops.
+
+For production systems, SQLite has some disadvantages when used with JupyterHub:
+
+- `upgrade-db` may not always work, and you may need to start with a fresh database
+- `downgrade-db` **will not** work if you want to rollback to an earlier
+  version, so backup the `jupyterhub.sqlite` file before upgrading (JupyterHub automatically creates a date-stamped backup file when upgrading sqlite)
+
+The sqlite documentation provides a helpful page about [when to use SQLite and
+where traditional RDBMS may be a better choice](https://sqlite.org/whentouse.html).
+
+### Picking your database backend (PostgreSQL, MySQL)
+
+When running a long term deployment or a production system, we recommend using a full-fledged relational database, such as [PostgreSQL](https://www.postgresql.org) or [MySQL](https://www.mysql.com), that supports the SQL `ALTER TABLE` statement, which is used in some database upgrade steps.
+
+In general, you select your database backend with [](JupyterHub.db_url), and can further configure it (usually not necessary) with [](JupyterHub.db_kwargs).
+
+## Notes and Tips
+
+### SQLite
+
+The SQLite database should not be used on NFS. SQLite uses reader/writer locks
+to control access to the database. This locking mechanism might not work
+correctly if the database file is kept on an NFS filesystem. This is because
+`fcntl()` file locking is broken on many NFS implementations. Therefore, you
+should avoid putting SQLite database files on NFS since it will not handle well
+multiple processes which might try to access the file at the same time.
+
+### PostgreSQL
+
+We recommend using PostgreSQL for production if you are unsure whether to use
+MySQL or PostgreSQL or if you do not have a strong preference.
+There is additional configuration required for MySQL that is not needed for PostgreSQL.
+
+For example, to connect to a postgres database with psycopg2:
+
+1. install psycopg2: `pip instal psycopg2` (or `psycopg2-binary` to avoid compilation, which is [not recommended for production][psycopg2-binary])
+2. set authentication via environment variables `PGUSER` and `PGPASSWORD`
+3. configure [](JupyterHub.db_url):
+
+   ```python
+   c.JupyterHub.db_url = "postgres+psycopg2://my-postgres-server:5432/my-db-name"
+   ```
+
+[psycopg2-binary]: https://www.psycopg.org/docs/install.html#psycopg-vs-psycopg-binary
+
+### MySQL / MariaDB
+
+- You should probably use the `pymysql` or `mysqlclient` sqlalchemy provider, or another backend [recommended by sqlalchemy](https://docs.sqlalchemy.org/en/20/dialects/mysql.html#dialect-mysql)
+- You also need to set `pool_recycle` to some value (typically 60 - 300, JupyterHub will default to 60)
+  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
+  sqlalchemy if `pool_recycle` is not set.
+- If you use `utf8mb4` collation with MySQL earlier than 5.7.7 or MariaDB
+  earlier than 10.2.1 you may get an `1709, Index column size too large` error.
+  To fix this you need to set `innodb_large_prefix` to enabled and
+  `innodb_file_format` to `Barracuda` to allow for the index sizes jupyterhub
+  uses. `row_format` will be set to `DYNAMIC` as long as those options are set
+  correctly. Later versions of MariaDB and MySQL should set these values by
+  default, as well as have a default `DYNAMIC` `row_format` and pose no trouble
+  to users.
+
+For example, to connect to a mysql database with mysqlclient:
+
+1. install mysqlclient: `pip install mysqlclient`
+2. configure [](JupyterHub.db_url):
+
+   ```python
+   c.JupyterHub.db_url = "mysql+mysqldb://myuser:mypassword@my-sql-server:3306/my-db-name"
+   ```

docs/source/explanation/index.md

@@ -0,0 +1,14 @@
+# Explanation
+
+_Explanation_ documentation provide big-picture descriptions of how JupyterHub works. This section is meant to build your understanding of particular topics.
+
+```{toctree}
+:maxdepth: 1
+
+capacity-planning
+database
+websecurity
+oauth
+singleuser
+../rbac/index
+```

docs/source/explanation/oauth.md

@@ -1,26 +1,26 @@
 # JupyterHub and OAuth
 
-JupyterHub uses OAuth 2 internally as a mechanism for authenticating users.
+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**.
-More on what that means [below](oauth-terms).
+You can find out more about what that means [below](oauth-terms).
 
-Additionally, JupyterHub is _often_ deployed with [oauthenticator](https://oauthenticator.readthedocs.io),
+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 and _external_ oauth flow, where JupyterHub is a **client**.
+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.
 
-Some relevant points:
+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 they are concerned, only JupyterHub is an OAuth provider,
+  As far as the servers are concerned, only JupyterHub is an OAuth provider,
   and how users authenticate with the Hub itself is irrelevant.
-- When talking to a single-user server,
+- When interacting with a single-user server,
   there are ~always two tokens:
-  a token issued to the server itself to communicate with the Hub API,
-  and a second per-user token in the browser to represent the completed login process and authorized permissions.
+  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)=
@@ -28,66 +28,66 @@ Some relevant points:
 ## Key OAuth terms
 
 Here are some key definitions to keep in mind when we are talking about OAuth.
-You can also read more detail [here](https://www.oauth.com/oauth2-servers/definitions/).
+You can also read more in detail [here](https://www.oauth.com/oauth2-servers/definitions/).
 
-- **provider** the entity responsible for managing identity and authorization,
+- **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,
+  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."
+  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 authorized access to a service or single-user server.
+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 generally goes like this:
+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
+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!
+   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.
+   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's the end of the requests made between the **browser** and the **provider**.
+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 given oauth client's requested permissions have been granted, but the client doesn't know this yet.
-- All requests so far have been made directly by the browser.
-  No requests have originated at the client or provider.
+- 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
 
-Now we get to finish the OAuth process.
-Let's dig into what the oauth client does when it handles
-the oauth callback request with the
+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_.
@@ -95,12 +95,12 @@ the oauth callback request with the
   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 exchanging tokens for information about their owner or permissions ([OpenID Connect](https://openid.net/connect/) does that),
+  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.
+- 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.
-- Last of all, now that credentials have been established,
+- 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
@@ -113,24 +113,24 @@ 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 is contained.
-For bonus points, we are using the double-oauth example of JupyterHub configured with GitHubOAuthenticator.
+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."
+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
+- 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**)
+- 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`
@@ -138,9 +138,9 @@ First request:
 
 Second request, following redirect:
 
-- browser->jupyterhub
+- browser->JupyterHub
 - `GET /hub/api/oauth2/authorize`
-- no credentials, so jupyterhub starts external oauth process _with GitHub_
+- 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`
@@ -154,8 +154,8 @@ 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.
+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.
@@ -171,7 +171,7 @@ Here, GitHub prompts for login and asks for confirmation of authorization
 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`
+GitHub issues an **OAuth code** and redirects to `/hub/oauth_callback?code=github-code`
 
 Next request:
 
@@ -184,7 +184,7 @@ The first:
 
 - JupyterHub->GitHub
 - `POST https://github.com/login/oauth/access_token`
-- request made with oauth **code** from url parameter
+- request made with OAuth **code** from URL parameter
 - response includes an access **token**
 
 The second:
@@ -194,9 +194,9 @@ The second:
 - 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:
+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
+- 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! 🎉
@@ -211,14 +211,14 @@ Now, we get our first repeated request:
   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
+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,
+Inside the internal OAuth callback handler,
 Danez's server makes two API requests to JupyterHub:
 
 The first:
@@ -255,7 +255,7 @@ To authenticate this request, the single token stored in the encrypted cookie is
 
 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.
+See [Scopes in JupyterHub](jupyterhub-scopes) for how JupyterHub uses scopes to determine authorized access to servers and services.
 
 _the end_
 
@@ -271,15 +271,15 @@ 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:
+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,
+- 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),
+- 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 can also itself expire,
+- 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,
@@ -317,9 +317,9 @@ triggering the external login process anew before letting a user proceed.
 - 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.
+  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.
+  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
@@ -352,7 +352,7 @@ Logging out of JupyterHub means clearing and revoking many of these credentials:
 ### 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 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,

docs/source/explanation/singleuser.md

@@ -0,0 +1,109 @@
+(singleuser)=
+
+# The JupyterHub single-user server
+
+When a user logs into JupyterHub, they get a 'server', which we usually call the **single-user server**, because it's a server that's meant for a single JupyterHub user.
+Each JupyterHub user gets a different one (or more than one!).
+
+A single-user server is a process running somewhere that is:
+
+1. accessible over http[s],
+2. authenticated via JupyterHub using OAuth 2.0,
+3. started by a [Spawner](spawners), and
+4. 'owned' by a single JupyterHub user
+
+## The single-user server command
+
+The Spawner's default single-user server startup command, `jupyterhub-singleuser`, launches `jupyter-server`, the same program used when you run `jupyter lab` on your laptop.
+(_It can also launch the legacy `jupyter-notebook` server_).
+That's why JupyterHub looks familiar to folks who are already using Jupyter at home or elsewhere.
+It's the same!
+`jupyterhub-singleuser` _customizes_ that program to change (approximately) one thing: **authenticate requests with JupyterHub**.
+
+(singleuser-auth)=
+
+## Single-user server authentication
+
+Implementation-wise, JupyterHub single-user servers are a special-case of {ref}`services`
+and as such use the same (OAuth) authentication mechanism (more on OAuth in JupyterHub at [](oauth)).
+This is primarily implemented in the {class}`~.HubOAuth` class.
+
+This code resides in `jupyterhub.singleuser` subpackage of JupyterHub.
+The main task of this code is to:
+
+1. resolve a JupyterHub token to a JupyterHub user (authenticate)
+2. check permissions (`access:servers`) for the token to make sure the request should be allowed (authorize)
+3. if not authorized, begin the OAuth process with a redirect to the Hub
+4. after login, store OAuth tokens in a cookie only used by this single-user server
+5. implement logout to clear the cookie
+
+Most of this is implemented in the {class}`~.HubOAuth` class. `jupyterhub.singleuser` is responsible for _adapting_ the base Jupyter Server to use HubOAuth for these tasks.
+
+### JupyterHub authentication extension
+
+By default, `jupyter-server` uses its own cookie to authenticate.
+If that cookie is not present, the server redirects you a login page and asks you to enter a password or token.
+
+Jupyter Server 2.0 introduces two new _APIs_ for customizing authentication: the [IdentityProvider](inv:jupyter-server#jupyter_server.auth.IdentityProvider) and the [Authorizer](inv:jupyter-server#jupyter_server.auth.Authorizer).
+More information can be found in the [Jupyter Server documentation](https://jupyter-server.readthedocs.io).
+
+JupyterHub implements these APIs in `jupyterhub.singleuser.extension`.
+
+The IdentityProvider is responsible for _authenticating_ requests.
+In JupyterHub, that means extracting OAuth tokens from the request and resolving them to a JupyterHub user.
+
+The Authorizer is a _separate_ API for _authorizing_ actions on particular resources.
+Because the JupyterHub IdentityProvider only allows _authenticating_ users who already have the necessary `access:servers` permission to access the server, the default Authorizer only contains a redundant check for this same permission, and ignores the resource inputs.
+However, specifying a _custom_ Authorizer allows for granular permissions, such as read-only access to subsets of a shared server.
+
+### JupyterHub authentication via subclass
+
+Prior to Jupyter Server 2 (i.e. Jupyter Server 1.x or the legacy `jupyter-notebook` server), JupyterHub authentication is applied via _subclass_.
+Originally a subclass of `NotebookApp`,
+this approach works with both `jupyter-server` and `jupyter-notebook`.
+Instead of using the extension mechanisms above,
+the server application is _subclassed_. This worked well in the `jupyter-notebook` days,
+but doesn't fit well with Jupyter Server's extension-based architecture.
+
+### Selecting jupyterhub-singleuser implementation
+
+Using the JupyterHub singleuser-server extension is the default behavior of JupyterHub 4 and Jupyter Server 2, otherwise the subclass approach is taken.
+
+You can opt-out of the extension by setting the environment variable `JUPYTERHUB_SINGLEUSER_EXTENSION=0`:
+
+```python
+c.Spawner.environment.update(
+    {
+        "JUPYTERHUB_SINGLEUSER_EXTENSION": "0",
+    }
+)
+```
+
+The subclass approach will also be taken if you've opted to use the classic notebook server with:
+
+```
+JUPYTERHUB_SINGLEUSER_APP=notebook
+```
+
+which was introduced in JupyterHub 2.
+
+## Other customizations
+
+`jupyterhub-singleuser` makes other small customizations to how the single-user server behaves:
+
+1. logs activity on the single-user server, used in [idle-culling](https://github.com/jupyterhub/jupyterhub-idle-culler).
+2. disables some features that don't make sense in JupyterHub (trash, retrying ports)
+3. loading options such as URLs and SSL configuration from the environment
+4. customize logging for consistency with JupyterHub logs
+
+## Running a single-user server that's not `jupyterhub-singleuser`
+
+By default, `jupyterhub-singleuser` is the same `jupyter-server` used by JupyterLab, Jupyter notebook (>= 7), etc.
+But technically, all JupyterHub cares about is that it is:
+
+1. an http server at the prescribed URL, accessible from the Hub and proxy, and
+2. authenticated via [OAuth](oauth) with the Hub (it doesn't even have to do this, if you want to do your own authentication, as is done in BinderHub)
+
+which means that you can customize JupyterHub to launch _any_ web application that meets these criteria, by following the specifications in {ref}`services`.
+
+Most of the time, though, it's easier to use [jupyter-server-proxy](https://jupyter-server-proxy.readthedocs.io) if you want to launch additional web applications in JupyterHub.

docs/source/explanation/websecurity.md

@@ -0,0 +1,272 @@
+(web-security)=
+
+# Security Overview
+
+The **Security Overview** section helps you learn about:
+
+- the design of JupyterHub with respect to web security
+- the semi-trusted user
+- the available mitigations to protect untrusted users from each other
+- the value of periodic security audits
+
+This overview also helps you obtain a deeper understanding of how JupyterHub
+works.
+
+## Semi-trusted and untrusted users
+
+JupyterHub is designed to be a _simple multi-user server for modestly sized
+groups_ of **semi-trusted** users. While the design reflects serving
+semi-trusted users, JupyterHub can also be suitable for serving **untrusted** users,
+but **is not suitable for untrusted users** in its default configuration.
+
+As a result, using JupyterHub with **untrusted** users means more work by the
+administrator, since much care is required to secure a Hub, with extra caution on
+protecting users from each other.
+
+One aspect of JupyterHub's _design simplicity_ for **semi-trusted** users is that
+the Hub and single-user servers are placed in a _single domain_, behind a
+[_proxy_][configurable-http-proxy]. If the Hub is serving untrusted
+users, many of the web's cross-site protections are not applied between
+single-user servers and the Hub, or between single-user servers and each
+other, since browsers see the whole thing (proxy, Hub, and single user
+servers) as a single website (i.e. single domain).
+
+## Protect users from each other
+
+To protect users from each other, a user must **never** be able to write arbitrary
+HTML and serve it to another user on the Hub's domain. This is prevented by JupyterHub's
+authentication setup because only the owner of a given single-user notebook server is
+allowed to view user-authored pages served by the given single-user notebook
+server.
+
+To protect all users from each other, JupyterHub administrators must
+ensure that:
+
+- A user **does not have permission** to modify their single-user notebook server,
+  including:
+  - the installation of new packages in the Python environment that runs
+    their single-user server;
+  - the creation of new files in any `PATH` directory that precedes the
+    directory containing `jupyterhub-singleuser` (if the `PATH` is used
+    to resolve the single-user executable instead of using an absolute path);
+  - the modification of environment variables (e.g. PATH, PYTHONPATH) for
+    their single-user server;
+  - the modification of the configuration of the notebook server
+    (the `~/.jupyter` or `JUPYTER_CONFIG_DIR` directory).
+  - unrestricted selection of the base environment (e.g. the image used in container-based Spawners)
+
+If any additional services are run on the same domain as the Hub, the services
+**must never** display user-authored HTML that is neither _sanitized_ nor _sandboxed_
+to any user that lacks authentication as the author of a file.
+
+### Sharing access to servers
+
+Because sharing access to servers (via `access:servers` scopes or the sharing feature in JupyterHub 5) by definition means users can serve each other files, enabling sharing is not suitable for untrusted users without also enabling per-user domains.
+
+JupyterHub does not enable any sharing by default.
+
+## Mitigate security issues
+
+The several approaches to mitigating security issues with configuration
+options provided by JupyterHub include:
+
+### Enable user subdomains
+
+JupyterHub provides the ability to run single-user servers on their own
+domains. This means the cross-origin protections between servers has the
+desired effect, and user servers and the Hub are protected from each other.
+
+**Subdomains are the only way to reliably isolate user servers from each other.**
+
+To enable subdomains, set:
+
+```python
+c.JupyterHub.subdomain_host = "https://jupyter.example.org"
+```
+
+When subdomains are enabled, each user's single-user server will be at e.g. `https://username.jupyter.example.org`.
+This also requires all user subdomains to point to the same address,
+which is most easily accomplished with wildcard DNS, where a single A record points to your server and a wildcard CNAME record points to your A record:
+
+```
+A        jupyter.example.org  192.168.1.123
+CNAME  *.jupyter.example.org  jupyter.example.org
+```
+
+Since this spreads the service across multiple domains, you will likely need wildcard SSL as well,
+matching `*.jupyter.example.org`.
+
+Unfortunately, for many institutional domains, wildcard DNS and SSL may not be available.
+
+We also **strongly encourage** serving JupyterHub and user content on a domain that is _not_ a subdomain of any sensitive content.
+For reasoning, see [GitHub's discussion of moving user content to github.io from \*.github.com](https://github.blog/2013-04-09-yummy-cookies-across-domains/).
+
+**If you do plan to serve untrusted users, enabling subdomains is highly encouraged**,
+as it resolves many security issues, which are difficult to unavoidable when JupyterHub is on a single-domain.
+
+:::{important}
+JupyterHub makes no guarantees about protecting users from each other unless subdomains are enabled.
+
+If you want to protect users from each other, you **_must_** enable per-user domains.
+:::
+
+### Disable user config
+
+If subdomains are unavailable or undesirable, JupyterHub provides a
+configuration option `Spawner.disable_user_config = True`, which can be set to prevent
+the user-owned configuration files from being loaded. After implementing this
+option, `PATH`s and package installation are the other things that the
+admin must enforce.
+
+### Prevent spawners from evaluating shell configuration files
+
+For most Spawners, `PATH` is not something users can influence, but it's important that
+the Spawner should _not_ evaluate shell configuration files prior to launching the server.
+
+### Isolate packages in a read-only environment
+
+The user must not have permission to install packages into the environment where the singleuser-server runs.
+On a shared system, package isolation is most easily handled by running the single-user server in
+a root-owned virtualenv with disabled system-site-packages.
+The user must not have permission to install packages into this environment.
+The same principle extends to the images used by container-based deployments.
+If users can select the images in which their servers run, they can disable all security for their own servers.
+
+It is important to note that the control over the environment is only required for the
+single-user server, and not the environment(s) in which the users' kernel(s)
+may run. Installing additional packages in the kernel environment does not
+pose additional risk to the web application's security.
+
+### Encrypt internal connections with SSL/TLS
+
+By default, all communications within JupyterHub—between the proxy, hub, and single
+-user notebooks—are performed unencrypted. Setting the `internal_ssl` flag in
+`jupyterhub_config.py` secures the aforementioned routes. Turning this
+feature on does require that the enabled `Spawner` can use the certificates
+generated by the `Hub` (the default `LocalProcessSpawner` can, for instance).
+
+It is also important to note that this encryption **does not** cover the
+`zmq tcp` sockets between the Notebook client and kernel yet. While users cannot
+submit arbitrary commands to another user's kernel, they can bind to these
+sockets and listen. When serving untrusted users, this eavesdropping can be
+mitigated by setting `KernelManager.transport` to `ipc`. This applies standard
+Unix permissions to the communication sockets thereby restricting
+communication to the socket owner. The `internal_ssl` option will eventually
+extend to securing the `tcp` sockets as well.
+
+### Mitigating same-origin deployments
+
+While per-user domains are **required** for robust protection of users from each other,
+you can mitigate many (but not all) cross-user issues.
+First, it is critical that users cannot modify their server environments, as described above.
+Second, it is important that users do not have `access:servers` permission to any server other than their own.
+
+If users can access each others' servers, additional security measures must be enabled, some of which come with distinct user-experience costs.
+
+Without the [Same-Origin Policy] (SOP) protecting user servers from each other,
+each user server is considered a trusted origin for requests to each other user server (and the Hub itself).
+Servers _cannot_ meaningfully distinguish requests originating from other user servers,
+because SOP implies a great deal of trust, losing many restrictions applied to cross-origin requests.
+
+That means pages served from each user server can:
+
+1. arbitrarily modify the path in the Referer
+2. make fully authorized requests with cookies
+3. access full page contents served from the hub or other servers via popups
+
+JupyterHub uses distinct xsrf tokens stored in cookies on each server path to attempt to limit requests across.
+This has limitations because not all requests are protected by these XSRF tokens,
+and unless additional measures are taken, the XSRF tokens from other user prefixes may be retrieved.
+
+[Same-Origin Policy]: https://developer.mozilla.org/en-US/docs/Web/Security/Same-origin_policy
+
+For example:
+
+- `Content-Security-Policy` header must prohibit popups and iframes from the same origin.
+  The following Content-Security-Policy rules are _insecure_ and readily enable users to access each others' servers:
+
+  - `frame-ancestors: 'self'`
+  - `frame-ancestors: '*'`
+  - `sandbox allow-popups`
+
+- Ideally, pages should use the strictest `Content-Security-Policy: sandbox` available,
+  but this is not feasible in general for JupyterLab pages, which need at least `sandbox allow-same-origin allow-scripts` to work.
+
+The default Content-Security-Policy for single-user servers is
+
+```
+frame-ancestors: 'none'
+```
+
+which prohibits iframe embedding, but not pop-ups.
+
+A more secure Content-Security-Policy that has some costs to user experience is:
+
+```
+frame-ancestors: 'none'; sandbox allow-same-origin allow-scripts
+```
+
+`allow-popups` is not disabled by default because disabling it breaks legitimate functionality, like "Open this in a new tab", and the "JupyterHub Control Panel" menu item.
+To reiterate, the right way to avoid these issues is to enable per-user domains, where none of these concerns come up.
+
+Note: even this level of protection requires administrators maintaining full control over the user server environment.
+If users can modify their server environment, these methods are ineffective, as users can readily disable them.
+
+### Cookie tossing
+
+Cookie tossing is a technique where another server on a subdomain or peer subdomain can set a cookie
+which will be read on another domain.
+This is not relevant unless there are other user-controlled servers on a peer domain.
+
+"Domain-locked" cookies avoid this issue, but have their own restrictions:
+
+- JupyterHub must be served over HTTPS
+- All secure cookies must be set on `/`, not on sub-paths, which means they are shared by all JupyterHub components in a single-domain deployment.
+
+As a result, this option is only recommended when per-user subdomains are enabled,
+to prevent sending all jupyterhub cookies to all user servers.
+
+To enable domain-locked cookies, set:
+
+```python
+c.JupyterHub.cookie_host_prefix_enabled = True
+```
+
+```{versionadded} 4.1
+
+```
+
+### Forced-login
+
+Jupyter servers can share links with `?token=...`.
+JupyterHub prior to 5.0 will accept this request and persist the token for future requests.
+This is useful for enabling admins to create 'fully authenticated' links bypassing login.
+However, it also means users can share their own links that will log other users into their own servers,
+enabling them to serve each other notebooks and other arbitrary HTML, depending on server configuration.
+
+```{versionadded} 4.1
+Setting environment variable `JUPYTERHUB_ALLOW_TOKEN_IN_URL=0` in the single-user environment can opt out of accepting token auth in URL parameters.
+```
+
+```{versionadded} 5.0
+Accepting tokens in URLs is disabled by default, and `JUPYTERHUB_ALLOW_TOKEN_IN_URL=1` environment variable must be set to _allow_ token auth in URL parameters.
+```
+
+## Security audits
+
+We recommend that you do periodic reviews of your deployment's security. It's
+good practice to keep [JupyterHub](https://readthedocs.org/projects/jupyterhub/), [configurable-http-proxy][], and [nodejs
+versions](https://github.com/nodejs/Release) up to date.
+
+A handy website for testing your deployment is
+[Qualsys' SSL analyzer tool](https://www.ssllabs.com/ssltest/analyze.html).
+
+[configurable-http-proxy]: https://github.com/jupyterhub/configurable-http-proxy
+
+## Vulnerability reporting
+
+If you believe you have found a security vulnerability in JupyterHub, or any
+Jupyter project, please report it to
+[security@ipython.org](mailto:security@ipython.org). If you prefer to encrypt
+your security reports, you can use [this PGP public
+key](https://jupyter.org/assets/ipython_security.asc).

docs/source/faq/faq.md

@@ -0,0 +1,76 @@
+# Frequently asked questions
+
+## How do I share links to notebooks?
+
+Sharing links to notebooks is a common activity,
+and can look different depending on what you mean by 'share.'
+Your first instinct might be to copy the URL you see in the browser,
+e.g. `jupyterhub.example/user/yourname/notebooks/coolthing.ipynb`,
+but this usually won't work, depending on the permissions of the person you share the link with.
+
+Unfortunately, 'share' means at least a few things to people in a JupyterHub context.
+We'll cover 3 common cases here, when they are applicable, and what assumptions they make:
+
+1. sharing links that will open the same file on the visitor's own server
+2. sharing links that will bring the visitor to _your_ server (e.g. for real-time collaboration, or RTC)
+3. publishing notebooks and sharing links that will download the notebook into the user's server
+
+### link to the same file on the visitor's server
+
+This is for the case where you have JupyterHub on a shared (or sufficiently similar) filesystem, where you want to share a link that will cause users to login and start their _own_ server, to view or edit the file.
+
+**Assumption:** the same path on someone else's server is valid and points to the same file
+
+This is useful in e.g. classes where you know students have certain files in certain locations, or collaborations where you know you have a shared filesystem where everyone has access to the same files.
+
+A link should look like `https://jupyterhub.example/hub/user-redirect/lab/tree/foo.ipynb`.
+You can hand-craft these URLs from the URL you are looking at, where you see `/user/name/lab/tree/foo.ipynb` use `/hub/user-redirect/lab/tree/foo.ipynb` (replace `/user/name/` with `/hub/user-redirect/`).
+Or you can use JupyterLab's "copy shareable link" in the context menu in the file browser:
+
+![copy shareable link in JupyterLab](../images/shareable_link.webp)
+
+which will produce a correct URL with `/hub/user-redirect/` in it.
+
+### link to the file on your server
+
+This is for the case where you want to both be using _your_ server, e.g. for real-time collaboration (RTC).
+
+**Assumption:** the user has (or should have) access to your server.
+
+**Assumption:** your server is running _or_ the user has permission to start it.
+
+By default, JupyterHub users don't have access to each other's servers, but JupyterHub 2.0 administrators can grant users limited access permissions to each other's servers.
+If the visitor doesn't have access to the server, these links will result in a 403 Permission Denied error.
+
+In many cases, for this situation you can copy the link in your URL bar (`/user/yourname/lab`), or you can add `/tree/path/to/specific/notebook.ipynb` to open a specific file.
+
+The [jupyterlab-link-share] JupyterLab extension generates these links, and even can _grant_ other users access to your server.
+
+[jupyterlab-link-share]: https://github.com/jupyterlab-contrib/jupyterlab-link-share
+
+:::{warning}
+Note that the way the extension _grants_ access is handing over credentials to allow the other user to **_BECOME YOU_**.
+This is usually not appropriate in JupyterHub.
+:::
+
+### link to a published copy
+
+Another way to 'share' notebooks is to publish copies, e.g. pushing the notebook to a git repository and sharing a download link.
+This way is especially useful for course materials,
+where no assumptions are necessary about the user's environment,
+except for having one package installed.
+
+**Assumption:** The [nbgitpuller](inv:nbgitpuller#index) server extension is installed
+
+Unlike the other two methods, nbgitpuller doesn't provide an extension to copy a shareable link for the document you're currently looking at,
+but it does provide a [link generator](inv:nbgitpuller#link),
+which uses the `user-redirect` approach above.
+
+When visiting an nbgitpuller link:
+
+- The visitor will be directed to their own server
+- Your repo will be cloned (or updated if it's already been cloned)
+- and then the file opened when it's ready
+
+[nbgitpuller]: https://nbgitpuller.readthedocs.io
+[nbgitpuller-link]: https://nbgitpuller.readthedocs.io/en/latest/link.html

docs/source/faq/index.md

@@ -0,0 +1,11 @@
+# FAQs
+
+Find answers to some of the most frequently-asked questions around JupyterHub and how it works.
+
+```{toctree}
+:maxdepth: 2
+
+faq
+institutional-faq
+troubleshooting
+```

docs/source/faq/institutional-faq.md

@@ -8,10 +8,16 @@ 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 and customizable
 to the use-cases of large organizations.
 
 ### I keep hearing about Jupyter Notebook, JupyterLab, and now JupyterHub. What’s the difference?
@@ -26,7 +32,7 @@ Here is a quick breakdown of these three tools:
   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 them with infrastructure those users wish to access. It can provide
+  It also connects users with infrastructure they wish to access. It can provide
   remote access to Jupyter Notebooks and JupyterLab for many people.
 
 ## For management
@@ -35,7 +41,7 @@ Here is a quick breakdown of these three tools:
 
 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 allows administrators
+the R tidyverse, and Jupyter Notebooks) on institutional infrastructure. It also gives administrators
 some control over access to resources, security, environments, and authentication.
 
 ### Is JupyterHub mature? Why should we trust it?
@@ -60,12 +66,12 @@ Here is a sample of organizations that use JupyterHub:
 - **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,
-  Minnesota Supercomputing Institute, ALCF, CERN, Lawrence Livermore National Laboratory
+  Minnesota Supercomputing Institute, ALCF, CERN, Lawrence Livermore National Laboratory, HUNT
 - **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
+See the [Gallery of JupyterHub deployments](gallery-of-deployments) for
 a more complete list of JupyterHub deployments at institutions.
 
 ### How does JupyterHub compare with hosted products, like Google Colaboratory, RStudio.cloud, or Anaconda Enterprise?
@@ -78,7 +84,7 @@ 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 enviroments, user interfaces, and
+stack, and can serve a variety of computing environments, 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.
@@ -99,12 +105,12 @@ that we currently suggest are:
   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
-  single machine (in the cloud or under your desk). Better for smaller user groups (4-80) or more
+  machine (in the cloud or under your desk). Better for smaller user groups (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.
@@ -118,14 +124,15 @@ 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).
+  [see the JupyterHub security page](web-security).
 - 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).
+  [JupyterHub on Kubernetes security page](https://z2jh.jupyter.org/en/latest/security.html).
 
 The longer answer: it depends on your deployment. Because JupyterHub is very flexible, it can be used
 in a variety of deployment setups. This often entails connecting your JupyterHub to **other** infrastructure
@@ -134,11 +141,11 @@ 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.
+individuals with experience running secure JupyterHub deployments and will be very glad to help you out.
 
 ### 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.
@@ -191,7 +198,7 @@ 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 compute or data resources, you may increase the
+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.
 
 ### Can I customize the look and feel of a JupyterHub?

docs/source/faq/troubleshooting.md

@@ -1,35 +1,11 @@
+(troubleshooting)=
+
 # Troubleshooting
 
 When troubleshooting, you may see unexpected behaviors or receive an error
-message. This section provide links for identifying the cause of the
+message. This section provides links for identifying the cause of the
 problem and how to resolve it.
 
-[_Behavior_](#behavior)
-
-- JupyterHub proxy fails to start
-- sudospawner fails to run
-- What is the default behavior when none of the lists (admin, allowed,
-  allowed groups) are set?
-- JupyterHub Docker container not accessible at localhost
-
-[_Errors_](#errors)
-
-- 500 error after spawning my single-user server
-
-[_How do I...?_](#how-do-i)
-
-- Use a chained SSL certificate
-- Install JupyterHub without a network connection
-- I want access to the whole filesystem, but still default users to their home directory
-- How do I increase the number of pySpark executors on YARN?
-- How do I use JupyterLab's prerelease version with JupyterHub?
-- How do I set up JupyterHub for a workshop (when users are not known ahead of time)?
-- How do I set up rotating daily logs?
-- Toree integration with HDFS rack awareness script
-- Where do I find Docker images and Dockerfiles related to JupyterHub?
-
-[_Troubleshooting commands_](#troubleshooting-commands)
-
 ## Behavior
 
 ### JupyterHub proxy fails to start
@@ -40,9 +16,9 @@ If you have tried to start the JupyterHub proxy and it fails to start:
   `c.JupyterHub.ip = '*'`; if it is, try `c.JupyterHub.ip = ''`
 - Try starting with `jupyterhub --ip=0.0.0.0`
 
-**Note**: If this occurs on Ubuntu/Debian, check that the you are using a
-recent version of node. Some versions of Ubuntu/Debian come with a version
-of node that is very old, and it is necessary to update node.
+**Note**: If this occurs on Ubuntu/Debian, check that you are using a
+recent version of [Node](https://nodejs.org). Some versions of Ubuntu/Debian come with a very old version
+of Node and it is necessary to update Node.
 
 ### sudospawner fails to run
 
@@ -61,24 +37,24 @@ to the config file, `jupyterhub_config.py`.
 ### What is the default behavior when none of the lists (admin, allowed, allowed groups) are set?
 
 When nothing is given for these lists, there will be no admins, and all users
-who can authenticate on the system (i.e. all the unix users on the server with
+who can authenticate on the system (i.e. all the Unix users on the server with
 a password) will be allowed to start a server. The allowed username set lets you limit
 this to a particular set of users, and admin_users lets you specify who
 among them may use the admin interface (not necessary, unless you need to do
-things like inspect other users' servers, or modify the user list at runtime).
+things like inspect other users' servers or modify the user list at runtime).
 
-### JupyterHub Docker container not accessible at localhost
+### JupyterHub Docker container is not accessible at localhost
 
 Even though the command to start your Docker container exposes port 8000
-(`docker run -p 8000:8000 -d --name jupyterhub jupyterhub/jupyterhub jupyterhub`),
-it is possible that the IP address itself is not accessible/visible. As a result
+(`docker run -p 8000:8000 -d --name jupyterhub quay.io/jupyterhub/jupyterhub jupyterhub`),
+it is possible that the IP address itself is not accessible/visible. As a result,
 when you try http://localhost:8000 in your browser, you are unable to connect
 even though the container is running properly. One workaround is to explicitly
 tell Jupyterhub to start at `0.0.0.0` which is visible to everyone. Try this
 command:
-`docker run -p 8000:8000 -d --name jupyterhub jupyterhub/jupyterhub jupyterhub --ip 0.0.0.0 --port 8000`
+`docker run -p 8000:8000 -d --name jupyterhub quay.io/jupyterhub/jupyterhub jupyterhub --ip 0.0.0.0 --port 8000`
 
-### How can I kill ports from JupyterHub managed services that have been orphaned?
+### How can I kill ports from JupyterHub-managed services that have been orphaned?
 
 I started JupyterHub + nbgrader on the same host without containers. When I try to restart JupyterHub + nbgrader with this configuration, errors appear that the service accounts cannot start because the ports are being used.
 
@@ -92,12 +68,12 @@ Where `<service_port>` is the port used by the nbgrader course service. This con
 
 ### Why am I getting a Spawn failed error message?
 
-After successfully logging in to JupyterHub with a compatible authenticators, I get a 'Spawn failed' error message in the browser. The JupyterHub logs have `jupyterhub KeyError: "getpwnam(): name not found: <my_user_name>`.
+After successfully logging in to JupyterHub with a compatible authenticator, I get a 'Spawn failed' error message in the browser. The JupyterHub logs have `jupyterhub KeyError: "getpwnam(): name not found: <my_user_name>`.
 
 This issue occurs when the authenticator requires a local system user to exist. In these cases, you need to use a spawner
 that does not require an existing system user account, such as `DockerSpawner` or `KubeSpawner`.
 
-### How can I run JupyterHub with sudo but use my current env vars and virtualenv location?
+### How can I run JupyterHub with sudo but use my current environment variables and virtualenv location?
 
 When launching JupyterHub with `sudo jupyterhub` I get import errors and my environment variables don't work.
 
@@ -109,25 +85,11 @@ sudo MY_ENV=abc123 \
   /srv/jupyterhub/jupyterhub
 ```
 
-### How can I view the logs for JupyterHub or the user's Notebook servers when using the DockerSpawner?
-
-Use `docker logs <container>` where `<container>` is the container name defined within `docker-compose.yml`. For example, to view the logs of the JupyterHub container use:
-
-    docker logs hub
-
-By default, the user's notebook server is named `jupyter-<username>` where `username` is the user's username within JupyterHub's db. So if you wanted to see the logs for user `foo` you would use:
-
-    docker logs jupyter-foo
-
-You can also tail logs to view them in real time using the `-f` option:
-
-    docker logs -f hub
-
 ## Errors
 
-### 500 error after spawning my single-user server
+### Error 500 after spawning my single-user server
 
-You receive a 500 error when accessing the URL `/user/<your_name>/...`.
+You receive a 500 error while accessing the URL `/user/<your_name>/...`.
 This is often seen when your single-user server cannot verify your user cookie
 with the Hub.
 
@@ -153,9 +115,9 @@ If everything is working, the response logged will be similar to this:
 
 You should see a similar 200 message, as above, in the Hub log when you first
 visit your single-user notebook server. If you don't see this message in the log, it
-may mean that your single-user notebook server isn't connecting to your Hub.
+may mean that your single-user notebook server is not connecting to your Hub.
 
-If you see 403 (forbidden) like this, it's likely a token problem:
+If you see 403 (forbidden) like this, it is likely a token problem:
 
 ```
 403 GET /hub/api/authorizations/cookie/jupyterhub-token-name/[secret] (@10.0.1.4) 4.14ms
@@ -185,10 +147,10 @@ If you receive a 403 error, the API token for the single-user server is likely
 invalid. Commonly, the 403 error is caused by resetting the JupyterHub
 database (either removing jupyterhub.sqlite or some other action) while
 leaving single-user servers running. This happens most frequently when using
-DockerSpawner, because Docker's default behavior is to stop/start containers
-which resets the JupyterHub database, rather than destroying and recreating
+DockerSpawner because Docker's default behavior is to stop/start containers
+that reset the JupyterHub database, rather than destroying and recreating
 the container every time. This means that the same API token is used by the
-server for its whole life, until the container is rebuilt.
+server for its whole life until the container is rebuilt.
 
 The fix for this Docker case is to remove any Docker containers seeing this
 issue (typically all containers created before a certain point in time):
@@ -201,28 +163,28 @@ your server again.
 
 ##### Proxy settings (403 GET)
 
-When your whole JupyterHub sits behind a organization proxy (_not_ a reverse proxy like NGINX as part of your setup and _not_ the configurable-http-proxy) the environment variables `HTTP_PROXY`, `HTTPS_PROXY`, `http_proxy` and `https_proxy` might be set. This confuses the jupyterhub-singleuser servers: When connecting to the Hub for authorization they connect via the proxy instead of directly connecting to the Hub on localhost. The proxy might deny the request (403 GET). This results in the singleuser server thinking it has a wrong auth token. To circumvent this you should add `<hub_url>,<hub_ip>,localhost,127.0.0.1` to the environment variables `NO_PROXY` and `no_proxy`.
+When your whole JupyterHub sits behind an organization proxy (_not_ a reverse proxy like NGINX as part of your setup and _not_ the configurable-http-proxy) the environment variables `HTTP_PROXY`, `HTTPS_PROXY`, `http_proxy`, and `https_proxy` might be set. This confuses the JupyterHub single-user servers: When connecting to the Hub for authorization they connect via the proxy instead of directly connecting to the Hub on localhost. The proxy might deny the request (403 GET). This results in the single-user server thinking it has the wrong auth token. To circumvent this you should add `<hub_url>,<hub_ip>,localhost,127.0.0.1` to the environment variables `NO_PROXY` and `no_proxy`.
 
 ### Launching Jupyter Notebooks to run as an externally managed JupyterHub service with the `jupyterhub-singleuser` command returns a `JUPYTERHUB_API_TOKEN` error
 
-[JupyterHub services](https://jupyterhub.readthedocs.io/en/stable/reference/services.html) allow processes to interact with JupyterHub's REST API. Example use-cases include:
+{ref}`services` allow processes to interact with JupyterHub's REST API. Example use-cases include:
 
 - **Secure Testing**: provide a canonical Jupyter Notebook for testing production data to reduce the number of entry points into production systems.
-- **Grading Assignments**: provide access to shared Jupyter Notebooks that may be used for management tasks such grading assignments.
+- **Grading Assignments**: provide access to shared Jupyter Notebooks that may be used for management tasks such as grading assignments.
 - **Private Dashboards**: share dashboards with certain group members.
 
 If possible, try to run the Jupyter Notebook as an externally managed service with one of the provided [jupyter/docker-stacks](https://github.com/jupyter/docker-stacks).
 
 Standard JupyterHub installations include a [jupyterhub-singleuser](https://github.com/jupyterhub/jupyterhub/blob/9fdab027daa32c9017845572ad9d5ba1722dbc53/setup.py#L116) command which is built from the `jupyterhub.singleuser:main` method. The `jupyterhub-singleuser` command is the default command when JupyterHub launches single-user Jupyter Notebooks. One of the goals of this command is to make sure the version of JupyterHub installed within the Jupyter Notebook coincides with the version of the JupyterHub server itself.
 
-If you launch a Jupyter Notebook with the `jupyterhub-singleuser` command directly from the command line the Jupyter Notebook won't have access to the `JUPYTERHUB_API_TOKEN` and will return:
+If you launch a Jupyter Notebook with the `jupyterhub-singleuser` command directly from the command line, the Jupyter Notebook won't have access to the `JUPYTERHUB_API_TOKEN` and will return:
 
 ```
     JUPYTERHUB_API_TOKEN env is required to run jupyterhub-singleuser.
     Did you launch it manually?
 ```
 
-If you plan on testing `jupyterhub-singleuser` independently from JupyterHub, then you can set the api token environment variable. For example, if were to run the single-user Jupyter Notebook on the host, then:
+If you plan on testing `jupyterhub-singleuser` independently from JupyterHub, then you can set the API token environment variable. For example, if you were to run the single-user Jupyter Notebook on the host, then:
 
     export JUPYTERHUB_API_TOKEN=my_secret_token
     jupyterhub-singleuser
@@ -243,7 +205,7 @@ With a docker container, pass in the environment variable with the run command:
 Some certificate providers, i.e. Entrust, may provide you with a chained
 certificate that contains multiple files. If you are using a chained
 certificate you will need to concatenate the individual files by appending the
-chain cert and root cert to your host cert:
+chained cert and root cert to your host cert:
 
     cat your_host.crt chain.crt root.crt > your_host-chained.crt
 
@@ -256,7 +218,7 @@ You would then set in your `jupyterhub_config.py` file the `ssl_key` and
 #### Example
 
 Your certificate provider gives you the following files: `example_host.crt`,
-`Entrust_L1Kroot.txt` and `Entrust_Root.txt`.
+`Entrust_L1Kroot.txt`, and `Entrust_Root.txt`.
 
 Concatenate the files appending the chain cert and root cert to your host cert:
 
@@ -275,7 +237,7 @@ where `ssl_cert` is example-chained.crt and ssl_key to your private key.
 
 Then restart JupyterHub.
 
-See also [JupyterHub SSL encryption](./getting-started/security-basics.html#ssl-encryption).
+See also {ref}`ssl-encryption`.
 
 ### Install JupyterHub without a network connection
 
@@ -289,7 +251,7 @@ with npmbox:
     python3 -m pip wheel jupyterhub
     npmbox configurable-http-proxy
 
-### I want access to the whole filesystem, but still default users to their home directory
+### I want access to the whole filesystem and still default users to their home directory
 
 Setting the following in `jupyterhub_config.py` will configure access to
 the entire filesystem and set the default to the user's home directory.
@@ -308,7 +270,7 @@ similar to this one:
 provides additional information. The [pySpark configuration documentation](https://spark.apache.org/docs/0.9.0/configuration.html)
 is also helpful for programmatic configuration examples.
 
-### How do I use JupyterLab's prerelease version with JupyterHub?
+### How do I use JupyterLab's pre-release version with JupyterHub?
 
 While JupyterLab is still under active development, we have had users
 ask about how to try out JupyterLab with JupyterHub.
@@ -321,7 +283,7 @@ For instance:
     python3 -m pip install jupyterlab
     jupyter serverextension enable --py jupyterlab --sys-prefix
 
-The important thing is that jupyterlab is installed and enabled in the
+The important thing is that JupyterLab is installed and enabled in the
 single-user notebook server environment. For system users, this means
 system-wide, as indicated above. For Docker containers, it means inside
 the single-user docker image, etc.
@@ -334,14 +296,14 @@ notebook servers to default to JupyterLab:
 ### How do I set up JupyterHub for a workshop (when users are not known ahead of time)?
 
 1. Set up JupyterHub using OAuthenticator for GitHub authentication
-2. Configure admin list to have workshop leaders be listed with administrator privileges.
+2. Configure the admin list to have workshop leaders listed with administrator privileges.
 
-Users will need a GitHub account to login and be authenticated by the Hub.
+Users will need a GitHub account to log in and be authenticated by the Hub.
 
 ### How do I set up rotating daily logs?
 
 You can do this with [logrotate](https://linux.die.net/man/8/logrotate),
-or pipe to `logger` to use syslog instead of directly to a file.
+or pipe to `logger` to use Syslog instead of directly to a file.
 
 For example, with this logrotate config file:
 
@@ -362,34 +324,9 @@ Or use syslog:
 
     jupyterhub | logger -t jupyterhub
 
-## Troubleshooting commands
-
-The following commands provide additional detail about installed packages,
-versions, and system information that may be helpful when troubleshooting
-a JupyterHub deployment. The commands are:
-
-- System and deployment information
-
-```bash
-jupyter troubleshooting
-```
-
-- Kernel information
-
-```bash
-jupyter kernelspec list
-```
-
-- Debug logs when running JupyterHub
-
-```bash
-jupyterhub --debug
-```
-
 ### Toree integration with HDFS rack awareness script
 
-The Apache Toree kernel will an issue, when running with JupyterHub, if the standard HDFS
-rack awareness script is used. This will materialize in the logs as a repeated WARN:
+The Apache Toree kernel will have an issue when running with JupyterHub if the standard HDFS rack awareness script is used. This will materialize in the logs as a repeated WARN:
 
 ```bash
 16/11/29 16:24:20 WARN ScriptBasedMapping: Exception running /etc/hadoop/conf/topology_script.py some.ip.address
@@ -410,10 +347,49 @@ In order to resolve this issue, there are two potential options.
 
 ### Where do I find Docker images and Dockerfiles related to JupyterHub?
 
-Docker images can be found at the [JupyterHub organization on DockerHub](https://hub.docker.com/u/jupyterhub/).
-The Docker image [jupyterhub/singleuser](https://hub.docker.com/r/jupyterhub/singleuser/)
-provides an example single user notebook server for use with DockerSpawner.
+Docker images can be found at the [JupyterHub organization on Quay.io](https://quay.io/organization/jupyterhub).
+The Docker image [jupyterhub/singleuser](https://quay.io/repository/jupyterhub/singleuser)
+provides an example single-user notebook server for use with DockerSpawner.
 
-Additional single user notebook server images can be found at the [Jupyter
-organization on DockerHub](https://hub.docker.com/r/jupyter/) and information
+Additional single-user notebook server images can be found at the [Jupyter
+organization on Quay.io](https://quay.io/organization/jupyter) and information
 about each image at the [jupyter/docker-stacks repo](https://github.com/jupyter/docker-stacks).
+
+### How can I view the logs for JupyterHub or the user's Notebook servers when using the DockerSpawner?
+
+Use `docker logs <container>` where `<container>` is the container name defined within `docker-compose.yml`. For example, to view the logs of the JupyterHub container use:
+
+    docker logs hub
+
+By default, the user's notebook server is named `jupyter-<username>` where `username` is the user's username within JupyterHub's database.
+So if you wanted to see the logs for user `foo` you would use:
+
+    docker logs jupyter-foo
+
+You can also tail logs to view them in real-time using the `-f` option:
+
+    docker logs -f hub
+
+## Troubleshooting commands
+
+The following commands provide additional detail about installed packages,
+versions, and system information that may be helpful when troubleshooting
+a JupyterHub deployment. The commands are:
+
+- System and deployment information
+
+```bash
+jupyter troubleshoot
+```
+
+- Kernel information
+
+```bash
+jupyter kernelspec list
+```
+
+- Debug logs when running JupyterHub
+
+```bash
+jupyterhub --debug
+```

docs/source/getting-started/faq.md

@@ -1,35 +0,0 @@
-# Frequently asked questions
-
-## 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`).
-
-Sharing links to notebooks is a common activity,
-and can look different based on what you mean.
-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_,
-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.
-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?
-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_,
-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/...`.
-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.
-
-In JupyterLab 2.0, this should also be the result of the "Copy Shareable Link"
-action in the file browser.

docs/source/getting-started/index.rst

@@ -1,19 +0,0 @@
-Get Started
-===========
-
-This section covers how to configure and customize JupyterHub for your
-needs. It contains information about authentication, networking, security, and
-other topics that are relevant to individuals or organizations deploying their
-own JupyterHub.
-
-.. toctree::
-   :maxdepth: 2
-
-   config-basics
-   networking-basics
-   security-basics
-   authenticators-users-basics
-   spawners-basics
-   services-basics
-   faq
-   institutional-faq

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

@@ -1,261 +0,0 @@
-Security settings
-=================
-
-.. important::
-
-   You should not run JupyterHub without SSL encryption on a public network.
-
-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
-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
-is still a good idea to revoke existing tokens.
-
-.. _ssl-encryption:
-
-Enabling SSL encryption
------------------------
-
-Since JupyterHub includes authentication and allows arbitrary code execution,
-you should not run it without SSL (HTTPS).
-
-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``
-configuration file as follows:
-
-.. code-block:: python
-
-    c.JupyterHub.ssl_key = '/path/to/my.key'
-    c.JupyterHub.ssl_cert = '/path/to/my.cert'
-
-
-Some cert files also contain the key, in which case only the cert is needed. It
-is important that these files be put in a secure location on your server, where
-they are not readable by regular users.
-
-If you are using a **chain certificate**, see also chained certificate for SSL
-in the JupyterHub `Troubleshooting FAQ <../troubleshooting.html>`_.
-
-Using letsencrypt
-~~~~~~~~~~~~~~~~~
-
-It is also possible to use `letsencrypt <https://letsencrypt.org/>`_ to obtain
-a free, trusted SSL certificate. If you run letsencrypt using the default
-options, the needed configuration is (replace ``mydomain.tld`` by your fully
-qualified domain name):
-
-.. code-block:: python
-
-    c.JupyterHub.ssl_key = '/etc/letsencrypt/live/{mydomain.tld}/privkey.pem'
-    c.JupyterHub.ssl_cert = '/etc/letsencrypt/live/{mydomain.tld}/fullchain.pem'
-
-If the fully qualified domain name (FQDN) is ``example.com``, the following
-would be the needed configuration:
-
-.. code-block:: python
-
-    c.JupyterHub.ssl_key = '/etc/letsencrypt/live/example.com/privkey.pem'
-    c.JupyterHub.ssl_cert = '/etc/letsencrypt/live/example.com/fullchain.pem'
-
-
-If SSL termination happens outside of the Hub
-~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
-
-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, 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:
-
-Proxy authentication token
---------------------------
-
-The Hub authenticates its requests to the Proxy using a secret token that
-the Hub and Proxy agree upon. Note that this applies to the default
-``ConfigurableHTTPProxy`` implementation. Not all proxy implementations
-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
-
-Generating and storing token in the configuration file
-~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
-
-You can set the value in the configuration file, ``jupyterhub_config.py``:
-
-.. code-block:: python
-
-    c.ConfigurableHTTPProxy.api_token = 'abc123...' # any random string
-
-Generating and storing as an environment variable
-~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
-
-You can pass this value of the proxy authentication token to the Hub and Proxy
-using the ``CONFIGPROXY_AUTH_TOKEN`` environment variable:
-
-.. code-block:: bash
-
-    export CONFIGPROXY_AUTH_TOKEN=$(openssl rand -hex 32)
-
-This environment variable needs to be visible to the Hub and Proxy.
-
-Default if token is not set
-~~~~~~~~~~~~~~~~~~~~~~~~~~~
-
-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).
-
-.. _cookie-secret:
-
-Cookie secret
--------------
-
-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.
-
-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. An example command to generate the
-``jupyterhub_cookie_secret`` file is:
-
-.. code-block:: bash
-
-    openssl rand -hex 32 > /srv/jupyterhub/jupyterhub_cookie_secret
-
-In most deployments of JupyterHub, you should point this to a secure location on
-the file system, such as ``/srv/jupyterhub/jupyterhub_cookie_secret``.
-
-The location of the ``jupyterhub_cookie_secret`` file can be specified in the
-``jupyterhub_config.py`` file as follows:
-
-.. code-block:: python
-
-    c.JupyterHub.cookie_secret_file = '/srv/jupyterhub/jupyterhub_cookie_secret'
-
-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`` 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
-~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
-
-If you would like to avoid the need for files, the value can be loaded in the
-Hub process from the ``JPY_COOKIE_SECRET`` environment variable, which is a
-hex-encoded string. You can set it this way:
-
-.. code-block:: bash
-
-    export JPY_COOKIE_SECRET=$(openssl rand -hex 32)
-
-For security reasons, this environment variable should only be visible to the
-Hub. If you set it dynamically as above, all users will be logged out each time
-the Hub starts.
-
-Generating and storing as a binary string
-~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
-
-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
------------------------------------------
-
-The following cookies are used by the Hub for handling user authentication.
-
-This section was created based on this post_ from Discourse.
-
-.. _post: https://discourse.jupyter.org/t/how-to-force-re-login-for-users/1998/6
-
-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.
-If this cookie is set, then the user is logged in.
-
-Resetting the Hub cookie secret effectively revokes this cookie.
-
-This cookie is restricted to the path ``/hub/``.
-
-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.
-
-Effectively the same as ``jupyterhub-hub-login``, but for the
-single-user server instead of the Hub. It contains an OAuth access token,
-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. 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>``, so that
-only the user’s server receives it.
-
-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 logout of the multiple OAuth cookies.
-
-This cookie is set to ``/`` so all endpoints can receive it, or clear it, etc.
-
-jupyterhub-user-<username>-oauth-state
-~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
-
-A short-lived cookie, used solely to store and validate OAuth state.
-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 your are logged in,
-with an expiration date shorter than ``jupyterhub-hub-login`` or
-``jupyterhub-user-<username>``.
-
-This cookie should not exist after you have successfully logged in.
-
-This cookie is restricted to the path ``/user/<username>``, so that only
-the user’s server receives it.

docs/source/howto/api-only.md

@@ -0,0 +1,128 @@
+(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/howto/configuration/config-ghoauth.md

@@ -5,15 +5,15 @@ 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) for login
+- Using GitHub OAuth (using [OAuthenticator](https://oauthenticator.readthedocs.io/en/latest)) 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
   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`.
+  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 +69,7 @@ c.Spawner.args = ['--NotebookApp.default_url=/notebooks/Welcome.ipynb']
 ```
 
 Using the GitHub Authenticator requires a few additional
-environment variable to be set prior to launching JupyterHub:
+environment variables to be set prior to launching JupyterHub:
 
 ```bash
 export GITHUB_CLIENT_ID=github_id
@@ -79,3 +79,5 @@ 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/howto/configuration/config-proxy.md

@@ -14,7 +14,7 @@ satisfy the following:
 - 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 needed JupyterHub configuration in `jupyterhub_config.py`:
+Let's start out with the 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;
 
-    # Tell all requests to port 80 to be 302 redirected to HTTPS
+    # Redirect the request 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 front end
+    # Managing literal requests to the JupyterHub frontend
     location / {
         proxy_pass http://127.0.0.1:8000;
         proxy_set_header X-Real-IP $remote_addr;
@@ -101,10 +101,10 @@ server {
 If `nginx` is not running on port 443, substitute `$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 line for the root directory
+server blocks as above for `NO_HUB` and simply add a line for the root directory
 of the site as well as the applicable location call:
 
 ```bash
@@ -112,7 +112,7 @@ server {
     listen 80;
     server_name NO_HUB.DOMAIN.TLD;
 
-    # Tell all requests to port 80 to be 302 redirected to HTTPS
+    # Redirect the request to HTTPS
     return 302 https://$host$request_uri;
 }
 
@@ -143,12 +143,12 @@ 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
@@ -157,26 +157,26 @@ 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 proxy_http proxy_wstunnel
+a2enmod ssl rewrite proxy headers 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 websockets on any proxied URL
+- Support for WebSocket 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
@@ -188,15 +188,26 @@ Listen 443
 
   ServerName HUB.DOMAIN.TLD
 
-  # configure SSL
+  # 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
   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
 
-  # Use RewriteEngine to handle websocket connection upgrades
+  # 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
   RewriteEngine On
   RewriteCond %{HTTP:Connection} Upgrade [NC]
   RewriteCond %{HTTP:Upgrade} websocket [NC]
@@ -208,19 +219,20 @@ 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 the jupyterhub under /jhub/ or other location please use the below configurations:
+In case of the need to run JupyterHub under /jhub/ or another 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 [NE.P,L]
- RewriteRule /jhub/(.*) http://127.0.0.1:8000/jhub/$1 [NE,P,L]
+ RewriteRule /jhub/(.*) ws://127.0.0.1:8000/jhub/$1 [P,L]
+ RewriteRule /jhub/(.*) http://127.0.0.1:8000/jhub/$1 [P,L]
 
  ProxyPass /jhub/ http://127.0.0.1:8000/jhub/
  ProxyPassReverse /jhub/  http://127.0.0.1:8000/jhub/
@@ -228,8 +240,8 @@ httpd.conf amendments:
 
 jupyterhub_config.py amendments:
 
-```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/'
+```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/'
 ```

docs/source/howto/configuration/config-sudo.md

@@ -6,14 +6,14 @@ Only do this if you are very sure you must.
 
 ## Overview
 
-There are many Authenticators and Spawners available for JupyterHub. Some, such
-as DockerSpawner or OAuthenticator, do not need any elevated permissions. This
+There are many [Authenticators](authenticators) and [Spawners](spawners) 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
 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
-is to run it as root, spawning user servers with [setuid](http://linux.die.net/man/2/setuid).
+is to run it as root, spawning user servers with [setuid](https://linux.die.net/man/2/setuid).
 But this isn't especially safe, because you have a process running on the
 public web as root.
 
@@ -69,7 +69,8 @@ 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.
+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)
 
 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`:
@@ -90,7 +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:
 
@@ -113,13 +114,13 @@ sudo: a password is required
 
 ## Enable PAM for non-root
 
-By default, [PAM authentication](http://en.wikipedia.org/wiki/Pluggable_authentication_module)
+By default, [PAM authentication](https://en.wikipedia.org/wiki/Pluggable_authentication_module)
 is used by JupyterHub. To use PAM, the process may need to be able to read
 the shadow password database.
 
 ### Shadow group (Linux)
 
-**Note:** On Fedora based distributions there is no clear way to configure
+**Note:** On [Fedora based distributions](https://fedoraproject.org/wiki/List_of_Fedora_remixes) 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).
@@ -150,7 +151,7 @@ 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
@@ -158,16 +159,18 @@ sudo setcap 'cap_net_bind_service=+ep' /usr/bin/node
 ```
 
 However, you may want to further understand the consequences of this.
+([Further reading](https://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
 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).
+instructions](https://ubuntuforums.org/showthread.php?t=992706).
 
 ### Shadow group (FreeBSD)
 
-**NOTE:** This has not been tested and may not work as expected.
+**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!_
 
 ```bash
 $ ls -l /etc/spwd.db /etc/master.passwd
@@ -225,8 +228,8 @@ 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 allow this.
+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`:
 
 ```bash
@@ -253,6 +256,6 @@ $ 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, considering updating to a more recent version
+`login:session-auth`, or similar, consider updating to a more recent version
 of jupyterhub and disabling the opening of PAM sessions with
 `c.PAMAuthenticator.open_sessions=False`.

docs/source/howto/configuration/config-user-env.md

@@ -0,0 +1,263 @@
+# Configuring user environments
+
+To deploy 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.
+
+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`.
+
+**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.
+
+This section will focus on user environments, which includes the following:
+
+- [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.
+
+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.
+
+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
+(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.
+
+## Configuring Jupyter and IPython
+
+[Jupyter](https://jupyter-notebook.readthedocs.io/en/stable/configuring/config_overview.html)
+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.
+
+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}`.
+
+### Jupyter environment configuration priority
+
+When Jupyter runs in an environment (conda or virtualenv), it prefers to load configuration from the environment over each user's own configuration (e.g. in `~/.jupyter`).
+This may cause issues if you use a _shared_ conda environment or virtualenv for users, because e.g. jupyterlab may try to write information like workspaces or settings to the environment instead of the user's own directory.
+This could fail with something like `Permission denied: $PREFIX/etc/jupyter/lab`.
+
+To avoid this issue, set `JUPYTER_PREFER_ENV_PATH=0` in the user environment:
+
+```python
+c.Spawner.environment.update(
+    {
+        "JUPYTER_PREFER_ENV_PATH": "0",
+    }
+)
+```
+
+which tells Jupyter to prefer _user_ configuration paths (e.g. in `~/.jupyter`) to configuration set in the environment.
+
+### 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`:
+
+```python
+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:
+
+```python
+# shutdown the server after no activity for an hour
+c.ServerApp.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
+itself.
+
+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:
+
+```bash
+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:
+
+```bash
+/path/to/python3 -m ipykernel install --prefix=/usr/local
+/path/to/python2 -m ipykernel install --prefix=/usr/local
+```
+
+## Multi-user hosts vs. Containers
+
+There are two broad categories of user environments that depend on what
+Spawner you choose:
+
+- Multi-user hosts (shared system)
+- Container-based
+
+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
+a real system user. In this example, shared configuration and installation
+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.
+
+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.
+
+## Named servers
+
+By default, in a JupyterHub deployment, each user has one server only.
+
+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.
+
+To allow named servers, include this code snippet in your config file:
+
+```python
+c.JupyterHub.allow_named_servers = True
+```
+
+Named servers were implemented in the REST API in JupyterHub 0.8,
+and JupyterHub 1.0 introduces UI for managing named servers via the user home page:
+
+![named servers on the home page](/images/named-servers-home.png)
+
+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.
+
+To limit the number of **named server** per user by setting a constant value, include this code snippet in your config file:
+
+```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.
+
+When using named servers, Spawners may need additional configuration to take the `servername` into account. Whilst `KubeSpawner` takes the `servername` into account by default in [`pod_name_template`](https://jupyterhub-kubespawner.readthedocs.io/en/latest/spawner.html#kubespawner.KubeSpawner.pod_name_template), other Spawners may not. Check the documentation for the specific Spawner to see how singleuser servers are named, for example in `DockerSpawner` this involves modifying the [`name_template`](https://jupyterhub-dockerspawner.readthedocs.io/en/latest/api/index.html) setting to include `servername`, eg. `"{prefix}-{username}-{servername}"`.
+
+(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 (notebook < 7.0), you can set the `JUPYTERHUB_SINGLEUSER_APP` environment variable
+(in the single-user environment) to:
+
+```bash
+export JUPYTERHUB_SINGLEUSER_APP='notebook.notebookapp.NotebookApp'
+```
+
+:::{note}
+
+```
+JUPYTERHUB_SINGLEUSER_APP='notebook.notebookapp.NotebookApp'
+```
+
+is only valid for notebook < 7. notebook v7 is based on jupyter-server,
+and the default jupyter-server application must be used.
+Selecting the new notebook UI is no longer a matter of selecting the server app to launch,
+but only the default URL for users to visit.
+To use notebook v7 with JupyterHub, leave the default singleuser app config alone (or specify `JUPYTERHUB_SINGLEUSER_APP=jupyter-server`) and set the default _URL_ for user servers:
+
+```python
+c.Spawner.default_url = '/tree/'
+```
+
+:::
+
+[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/howto/index.md

@@ -0,0 +1,34 @@
+# How-to
+
+The _How-to_ guides provide practical step-by-step details to help you achieve a particular goal. They are useful when you are trying to get something done but require you to understand and adapt the steps to your specific usecase.
+
+Use the following guides when:
+
+```{toctree}
+:maxdepth: 1
+
+api-only
+proxy
+rest
+separate-proxy
+templates
+upgrading
+log-messages
+
+```
+
+(config-examples)=
+
+## Configuration
+
+The following guides provide examples, including configuration files and tips, for the
+following:
+
+```{toctree}
+:maxdepth: 1
+
+configuration/config-user-env
+configuration/config-ghoauth
+configuration/config-proxy
+configuration/config-sudo
+```

docs/source/howto/log-messages.md

@@ -0,0 +1,72 @@
+# 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/howto/proxy.md

@@ -7,9 +7,12 @@ 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
@@ -138,7 +141,7 @@ async def delete_route(self, routespec):
 
 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
-`routespect`, of dicts whose keys are the same three arguments passed to
+`routespec`, of dicts whose keys are the same three arguments passed to
 `add_route` (`routespec`, `target`, `data`)
 
 ```python
@@ -204,7 +207,7 @@ setup(
 ```
 
 If you have added this metadata to your package,
-users can select your proxy with the configuration:
+admins can select your authenticator with the configuration:
 
 ```python
 c.JupyterHub.proxy_class = 'mything'
@@ -216,7 +219,7 @@ instead of the full
 c.JupyterHub.proxy_class = 'mypackage:MyProxy'
 ```
 
-previously required.
+as previously required.
 Additionally, configurable attributes for your proxy will
 appear in jupyterhub help output and auto-generated configuration files
 via `jupyterhub --generate-config`.

docs/source/howto/rest.md

@@ -1,59 +1,89 @@
+(using-jupyterhub-rest-api)=
+
 # Using JupyterHub's REST API
 
 This section will give you information on:
 
-- 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
+- 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
 
-## 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
-
-A [REST](https://en.wikipedia.org/wiki/Representational_state_transfer)
+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
+
+Using the [JupyterHub REST API](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
+
 ## Create an API token
 
-To send requests using JupyterHub API, you must pass an API token with
+To send requests using the JupyterHub API, you must pass an API token with
 the request.
 
-The preferred way of generating an API token is:
+While JupyterHub is running, any JupyterHub user can request a token via the `token` page.
+This is accessible via a `token` link in the top nav bar from the JupyterHub home page,
+or at the URL `/hub/token`.
+
+:::{figure-md}
+
+![token request page](../images/token-page.png)
+
+JupyterHub's API token page
+:::
+
+:::{figure-md}
+![token-request-success](../images/token-request-success.png)
+
+JupyterHub's token page after successfully requesting a token.
+
+:::
+
+### Register API tokens via configuration
+
+Sometimes, you'll want to pre-generate a token for access to JupyterHub,
+typically for use by external services,
+so that both JupyterHub and the service have access to the same value.
+
+First, you need to generate a good random secret.
+A good way of generating an API token is by running:
 
 ```bash
 openssl rand -hex 32
 ```
 
-This `openssl` command generates a potential token that can then be
-added to JupyterHub using `.api_tokens` configuration setting in
-`jupyterhub_config.py`.
+This `openssl` command generates a random token that can be added to the JupyterHub configuration in `jupyterhub_config.py`.
 
-Alternatively, use the `jupyterhub token` command to generate a token
-for a specific hub user by passing the 'username':
+For external services, this would be registered with JupyterHub via configuration:
 
-```bash
-jupyterhub token <username>
+```python
+c.JupyterHub.services = [
+    {
+        "name": "my-service",
+        "api_token": the_secret_value,
+    },
+]
 ```
 
-This command generates a random string to use as a token and registers
-it for the given user with the Hub's database.
+At this point, requests authenticated with the token will be associated with The service `my-service`.
 
-In [version 0.8.0](../changelog.md), a token request page for
-generating an API token is available from the JupyterHub user interface:
+```{note}
+You can also load additional tokens for users via the `JupyterHub.api_tokens` configuration.
 
-![Request API token page](../images/token-request.png)
-
-![API token success page](../images/token-request-success.png)
+However, this option has been deprecated since the introduction of services.
+```
 
 ## Assigning permissions to a token
 
@@ -65,25 +95,26 @@ Prior to JupyterHub 2.0, there were two levels of permissions:
 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',
+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
+## 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 a token for that user to perform some automations,
-the services mechanism may be a better fit.
-If you have the following configuration:
+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:
 
 ```python
-c.JupyterHub.admin_users = {"service-admin",}
+c.JupyterHub.admin_users = {"service-admin"}
 c.JupyterHub.api_tokens = {
     "secret-token": "service-admin",
 }
@@ -101,9 +132,8 @@ c.JupyterHub.services = [
     },
 ]
 
-# roles are new in JupyterHub 2.0
-# prior to 2.0, only 'admin': True or False
-# was available
+# roles were introduced in JupyterHub 2.0
+# prior to 2.0, only "admin": True or False was available
 
 c.JupyterHub.load_roles = [
     {
@@ -111,7 +141,6 @@ c.JupyterHub.load_roles = [
         "scopes": [
             # specify the permissions the token should have
             "admin:users",
-            "admin:services",
         ],
         "services": [
             # assign the service the above permissions
@@ -124,7 +153,7 @@ c.JupyterHub.load_roles = [
 The token will have the permissions listed in the role
 (see [scopes][] for a list of available permissions),
 but there will no longer be a user account created to house it.
-The main noticeable difference is that there will be no notebook server associated with the account
+The main noticeable difference between a user and a service 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
@@ -135,9 +164,8 @@ Authorization header.
 ### Use requests
 
 Using the popular Python [requests](https://docs.python-requests.org)
-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:
+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
 
 ```python
 import requests
@@ -175,7 +203,8 @@ r.json()
 ```
 
 The same API token can also authorize access to the [Jupyter Notebook REST API][]
-provided by notebook servers managed by JupyterHub if it has the necessary `access:users:servers` scope:
+
+provided by notebook servers managed by JupyterHub if it has the necessary `access:servers` scope.
 
 (api-pagination)=
 
@@ -244,7 +273,7 @@ with your request, in which case a response will look like:
 
 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.
+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:
@@ -258,7 +287,7 @@ Pagination is enabled on the `GET /users`, `GET /groups`, and `GET /proxy` REST
 
 ## Enabling users to spawn multiple named-servers via the API
 
-With JupyterHub version 0.8, support for multiple servers per user has landed.
+Support for multiple servers per user was introduced in JupyterHub [version 0.8.](changelog)
 Prior to that, each user could only launch a single default server via the API
 like this:
 
@@ -274,9 +303,9 @@ First you must enable named-servers by including the following setting in the `j
 
 `c.JupyterHub.allow_named_servers = True`
 
-If using the [zero-to-jupyterhub-k8s](https://github.com/jupyterhub/zero-to-jupyterhub-k8s) set-up to run JupyterHub,
+If you are 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/):
+the following as part of the `config.yaml` file, as per the [tutorial](https://z2jh.jupyter.org/en/latest/):
 
 ```bash
 hub:
@@ -302,12 +331,9 @@ or kubernetes pods.
 
 ## Learn more about the API
 
-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][].
+You can see the full [JupyterHub REST API](jupyterhub-rest-api) for more details.
 
-[interactive style on swagger's petstore]: https://petstore3.swagger.io/?url=https://raw.githubusercontent.com/jupyterhub/jupyterhub/HEAD/docs/rest-api.yml#!/default
 [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

docs/source/howto/separate-proxy.md

@@ -1,8 +1,10 @@
+(separate-proxy)=
+
 # Running proxy separately from the hub
 
 ## Background
 
-The thing which users directly connect to is the proxy, by default
+The thing which users directly connect to is the proxy, which by default is
 `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
@@ -10,16 +12,15 @@ 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, but everytime you restart the
-hub, all user connections also get restarted. But it's also simple to
+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
 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 currently
-actively starting the hub.
+to reconfigure the hub while only interrupting users who are waiting for their notebook server to start.
+starting their notebook server.
 
 The default JupyterHub proxy is
-[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.
+[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.
 
 ## Configuration options
 
@@ -40,9 +41,14 @@ 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 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
+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
 configuration files, all configuration is via the command line and
 environment variables.
 
@@ -57,14 +63,14 @@ 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 are configured in the hub if the hub is starting the proxy - you
-need to move the options to here.
+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.
 
 ## Docker image
 
 You can use [jupyterhub configurable-http-proxy docker
-image](https://hub.docker.com/r/jupyterhub/configurable-http-proxy/)
+image](https://quay.io/repository/jupyterhub/configurable-http-proxy)
 to run the proxy.
 
 ## See also

docs/source/howto/templates.md

@@ -1,28 +1,29 @@
 # Working with templates and UI
 
 The pages of the JupyterHub application are generated from
-[Jinja](http://jinja.pocoo.org/) templates. These allow the header, for
+[Jinja](https://jinja.palletsprojects.com) templates. These allow the header, for
 example, to be defined once and incorporated into all pages. By providing
-your own templates, you can have complete control over JupyterHub's
+your own template(s), you can have complete control over JupyterHub's
 appearance.
 
 ## Custom Templates
 
-JupyterHub will look for custom templates in all of the paths in the
-`JupyterHub.template_paths` configuration option, falling back on the
+JupyterHub will look for custom templates in all paths included in the
+`JupyterHub.template_paths` configuration option, falling back on these
 [default templates](https://github.com/jupyterhub/jupyterhub/tree/HEAD/share/jupyterhub/templates)
-if no custom template with that name is found. This fallback
-behavior is new in version 0.9; previous versions searched only those paths
+if no custom template(s) with specified name(s) are found. This fallback
+behavior is new in version 0.9; previous versions searched only the paths
 explicitly included in `template_paths`. You may override as many
 or as few templates as you desire.
 
 ## Extending Templates
 
-Jinja provides a mechanism to [extend templates](http://jinja.pocoo.org/docs/2.10/templates/#template-inheritance).
-A base template can define a `block`, and child templates can replace or
-supplement the material in the block. The
-[JupyterHub templates](https://github.com/jupyterhub/jupyterhub/tree/HEAD/share/jupyterhub/templates)
-make extensive use of blocks, which allows you to customize parts of the
+Jinja provides a mechanism to [extend templates](https://jinja.palletsprojects.com/en/3.0.x/templates/#template-inheritance).
+
+A base template can define `block`(s) within itself that child templates can fill up or
+supply content to. The
+[JupyterHub default templates](https://github.com/jupyterhub/jupyterhub/tree/HEAD/share/jupyterhub/templates)
+make extensive use of blocks, thus allowing you to customize parts of the
 interface easily.
 
 In general, a child template can extend a base template, `page.html`, by beginning with:
@@ -40,15 +41,15 @@ file with this block:
 {% extends "templates/page.html" %}
 ```
 
-By defining `block`s with same name as in the base template, child templates
+By defining `block`s with the same name as in the base template, child templates
 can replace those sections with custom content. The content from the base
-template can be included with the `{{ super() }}` directive.
+template can be included in the child template with the `{{ super() }}` directive.
 
 ### Example
 
 To add an additional message to the spawn-pending page, below the existing
-text about the server starting up, place this content in a file named
-`spawn_pending.html` in a directory included in the
+text about the server starting up, place the content below in a file named
+`spawn_pending.html`. This directory must also be included in the
 `JupyterHub.template_paths` configuration option.
 
 ```html
@@ -61,7 +62,7 @@ text about the server starting up, place this content in a file named
 
 To add announcements to be displayed on a page, you have two options:
 
-- Extend the page templates as described above
+- [Extend the page templates as described above](#extending-templates)
 - Use configuration variables
 
 ### Announcement Configuration Variables
@@ -71,10 +72,10 @@ the top of all pages. The more specific variables
 `announcement_login`, `announcement_spawn`, `announcement_home`, and
 `announcement_logout` are more specific and only show on their
 respective pages (overriding the global `announcement` variable).
-Note that changing these variables require a restart, unlike direct
+Note that changing these variables requires a restart, unlike direct
 template extension.
 
-You can get the same effect by extending templates, which allows you
+Alternatively, you can get the same effect by extending templates, which allows you
 to update the messages without restarting. Set
 `c.JupyterHub.template_paths` as mentioned above, and then create a
 template (for example, `login.html`) with:
@@ -84,5 +85,5 @@ template (for example, `login.html`) with:
 ```
 
 Extending `page.html` puts the message on all pages, but note that
-extending `page.html` take precedence over an extension of a specific
+extending `page.html` takes precedence over an extension of a specific
 page (unlike the variable-based approach above).

docs/source/howto/upgrading.md

@@ -0,0 +1,141 @@
+(upgrading-jupyterhub)=
+
+# Upgrading JupyterHub
+
+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.
+
+This documentation is lengthy because it is quite 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) 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
+read the changelogs for those too!
+
+## Notify your users
+
+If you use 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`
+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.
+
+## Backup database & config
+
+Before doing an upgrade, it is critical to back up:
+
+1. 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.
+2. Your `jupyterhub_config.py` file.
+3. 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.
+
+## Shut down 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
+supervisor of some sort (`systemd` or `supervisord` or even `docker`).
+Use the supervisor-specific command to stop the JupyterHub process.
+
+## Upgrade JupyterHub packages
+
+There are two environments where the `jupyterhub` package is installed:
+
+1. The _hub environment_: where the JupyterHub server process
+   runs. This is started with the `jupyterhub` command, and is what
+   people generally think of as JupyterHub.
+2. The _notebook user environments_: 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
+   launched the `jupyterhub-singleuser` command in this environment,
+   which in turn starts the notebook server.
+
+You need to make sure the version of the `jupyterhub` package matches
+in both these environments. If you installed `jupyterhub` with pip,
+you can upgrade it with:
+
+```bash
+python3 -m pip install --upgrade jupyterhub==<version>
+```
+
+Where `<version>` is the version of JupyterHub you are upgrading to.
+
+If you used `conda` to install `jupyterhub`, you should upgrade it
+with:
+
+```bash
+conda install -c conda-forge jupyterhub==<version>
+```
+
+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
+or upgrade them separately.
+
+## Upgrade JupyterHub database
+
+Once new packages are installed, you need to upgrade the JupyterHub
+database. From the hub environment, in the same directory as your
+`jupyterhub_config.py` file, you should run:
+
+```bash
+jupyterhub upgrade-db
+```
+
+This should find the location of your database, and run the necessary upgrades
+for it.
+
+### 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
+  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.
+
+### What happens if I delete my database?
+
+Losing the Hub database is often not a big deal. Information that
+resides only in the Hub database includes:
+
+- active login tokens (user cookies, service tokens)
+- users added via JupyterHub UI, instead of config files
+- info about running servers
+
+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
+  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
+
+## Start JupyterHub
+
+Once the database upgrade is completed, start the `jupyterhub`
+process again.
+
+1. Log in and start the server to make sure things work as
+   expected.
+2. Check the logs for any errors or deprecation warnings. You
+   might have to update your `jupyterhub_config.py` file to
+   deal with any deprecated options.
+
+Congratulations, your JupyterHub has been upgraded!