publish releases on push to tags

2.0 changelog

.circleci/config.yml

@@ -1,75 +0,0 @@
-# Python CircleCI 2.0 configuration file
-# Updating CircleCI configuration from v1 to v2
-# Check https://circleci.com/docs/2.0/language-python/ for more details
-#
-version: 2
-jobs:
-  build:
-    machine: true
-    steps:
-      - checkout
-      - run:
-          name: build images
-          command: |
-            docker build -t jupyterhub/jupyterhub .
-            docker build -t jupyterhub/jupyterhub-onbuild onbuild
-            docker build -t jupyterhub/jupyterhub:alpine -f dockerfiles/Dockerfile.alpine .
-            docker build -t jupyterhub/singleuser singleuser
-      - run:
-          name: smoke test jupyterhub
-          command: |
-            docker run --rm -it jupyterhub/jupyterhub jupyterhub --help
-
-  docs:
-    # This is the base environment that Circle will use
-    docker:
-      - image: circleci/python:3.6-stretch
-    steps:
-      # Get our data and merge with upstream
-      - run: sudo apt-get update
-      - checkout
-      # Update our path
-      - run: echo "export PATH=~/.local/bin:$PATH" >> $BASH_ENV
-      # Restore cached files to speed things up
-      - restore_cache:
-          keys:
-            - cache-pip
-      # Install the packages needed to build our documentation
-      - run:
-          name: Install NodeJS
-          command: |
-            # From https://github.com/nodesource/distributions/blob/master/README.md#debinstall
-            curl -sL https://deb.nodesource.com/setup_13.x | sudo -E bash -
-            sudo apt-get install -y nodejs
-
-      - run:
-          name: Install dependencies
-          command: |
-            python3 -m pip install --user -r dev-requirements.txt
-            python3 -m pip install --user -r docs/requirements.txt
-            sudo npm install -g configurable-http-proxy
-            sudo python3 -m pip install --editable .
-
-      # Cache some files for a speedup in subsequent builds
-      - save_cache:
-          key: cache-pip
-          paths:
-            - ~/.cache/pip
-      # Build the docs
-      - run:
-          name: Build docs to store
-          command: |
-            cd docs
-            make html
-      # Tell Circle to store the documentation output in a folder that we can access later
-      - store_artifacts:
-          path: docs/build/html/
-          destination: html
-
-# Tell CircleCI to use this workflow when it builds the site
-workflows:
-  version: 2
-  default:
-    jobs:
-      - build
-      - docs

.github/ISSUE_TEMPLATE/bug_report.md

@@ -1,39 +0,0 @@
----
-name: Issue report
-about: Create a report to help us improve
-
----
-
-<!---
-Hi! Thanks for using JupyterHub.
-
-If you are reporting an issue with JupyterHub, please use the GitHub search feature to check if your issue has been asked already. If it has, please add your comments to the existing issue.
-
-Some tips:
-- Running `jupyter troubleshoot` from the command line, if possible, and posting
-its output would also be helpful.
-- Running JupyterHub in `--debug` mode (`jupyterhub --debug`) can also be helpful for troubleshooting.
---->
-
-**Describe the bug**
-A clear and concise description of what the bug is.
-
-<!---Add description here--->
-
-**To Reproduce**
-<!---
-Please share the steps to reproduce the behavior:
-1. Go to '...'
-2. Click on '....'
-3. Scroll down to '....'
-4. See error
---->
-
-**Expected behavior**
-<!---
-A clear and concise description of what you expected to happen.
---->
-
-**Compute Information**
- - Operating System
- - JupyterHub Version [e.g. 22]

.github/ISSUE_TEMPLATE/installation-and-configuration-issues.md

@@ -1,22 +0,0 @@
----
-name: Installation and configuration questions
-about: Installation and configuration assistance
-
----
-
-<!---
-If you are reading this message, you have probably already searched the existing
-GitHub issues for JupyterHub. If you haven't tried a search, we encourage you to do so.
-
-If you are unsure where to ask your question (Jupyter, JupyterHub, JupyterLab, etc.),
-please ask on our [Discourse Q&A channel](https://discourse.jupyter.org/c/questions).
-
-If you have a quick question about JupyterHub installation or configuratation, you
-may ask on the [JupyterHub gitter channel](https://gitter.im/jupyterhub/jupyterhub).
-
-:sunny: Please be patient. We are volunteers and will address your question when we are able. :sunny:
-
-If after trying the above steps, you still have an in-depth installation or
-configuration question, such as a possible bug, please file an issue below and include
-any relevant details.
---->

.github/workflows/release.yml

@@ -0,0 +1,192 @@
+# Build releases and (on tags) publish to PyPI
+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:
+
+jobs:
+  build-release:
+    runs-on: ubuntu-20.04
+    steps:
+      - uses: actions/checkout@v2
+      - uses: actions/setup-python@v2
+        with:
+          python-version: 3.8
+
+      - uses: actions/setup-node@v1
+        with:
+          node-version: "14"
+
+      - name: install build package
+        run: |
+          pip install --upgrade pip
+          pip install build
+          pip freeze
+
+      - name: build release
+        run: |
+          python -m build --sdist --wheel .
+          ls -l dist
+
+      - name: verify wheel
+        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
+
+      # ref: https://github.com/actions/upload-artifact#readme
+      - uses: actions/upload-artifact@v2
+        with:
+          name: jupyterhub-${{ github.sha }}
+          path: "dist/*"
+          if-no-files-found: error
+
+      - name: Publish to PyPI
+        if: startsWith(github.ref, 'refs/tags/')
+        env:
+          TWINE_USERNAME: __token__
+          TWINE_PASSWORD: ${{ secrets.PYPI_PASSWORD }}
+        run: |
+          pip install twine
+          twine upload --skip-existing dist/*
+
+  publish-docker:
+    runs-on: ubuntu-20.04
+
+    services:
+      # So that we can test this in PRs/branches
+      local-registry:
+        image: registry:2
+        ports:
+          - 5000:5000
+
+    steps:
+      - name: Should we push this image to a public registry?
+        run: |
+          if [ "${{ startsWith(github.ref, 'refs/tags/') || (github.ref == 'refs/heads/main') }}" = "true" ]; then
+              # Empty => Docker Hub
+              echo "REGISTRY=" >> $GITHUB_ENV
+          else
+              echo "REGISTRY=localhost:5000/" >> $GITHUB_ENV
+          fi
+
+      - uses: actions/checkout@v2
+
+      # Setup docker to build for multiple platforms, see:
+      # https://github.com/docker/build-push-action/tree/v2.4.0#usage
+      # https://github.com/docker/build-push-action/blob/v2.4.0/docs/advanced/multi-platform.md
+
+      - name: Set up QEMU (for docker buildx)
+        uses: docker/setup-qemu-action@25f0500ff22e406f7191a2a8ba8cda16901ca018 # associated tag: v1.0.2
+
+      - name: Set up Docker Buildx (for multi-arch builds)
+        uses: docker/setup-buildx-action@2a4b53665e15ce7d7049afb11ff1f70ff1610609 # associated tag: v1.1.2
+        with:
+          # Allows pushing to registry on localhost:5000
+          driver-opts: network=host
+
+      - name: Setup push rights to Docker Hub
+        # This was setup by...
+        # 1. Creating a Docker Hub service account "jupyterhubbot"
+        # 2. Creating a access token for the service account specific to this
+        #    repository: https://hub.docker.com/settings/security
+        # 3. Making the account part of the "bots" team, and granting that team
+        #    permissions to push to the relevant images:
+        #    https://hub.docker.com/orgs/jupyterhub/teams/bots/permissions
+        # 4. Registering the username and token as a secret for this repo:
+        #    https://github.com/jupyterhub/jupyterhub/settings/secrets/actions
+        if: env.REGISTRY != 'localhost:5000/'
+        run: |
+          docker login -u "${{ secrets.DOCKERHUB_USERNAME }}" -p "${{ secrets.DOCKERHUB_TOKEN }}"
+
+      # https://github.com/jupyterhub/action-major-minor-tag-calculator
+      # If this is a tagged build this will return additional parent tags.
+      # E.g. 1.2.3 is expanded to Docker tags
+      # [{prefix}:1.2.3, {prefix}:1.2, {prefix}:1, {prefix}:latest] unless
+      # this is a backported tag in which case the newer tags aren't updated.
+      # For branches this will return the branch name.
+      # If GITHUB_TOKEN isn't available (e.g. in PRs) returns no tags [].
+      - name: Get list of jupyterhub tags
+        id: jupyterhubtags
+        uses: jupyterhub/action-major-minor-tag-calculator@v1
+        with:
+          githubToken: ${{ secrets.GITHUB_TOKEN }}
+          prefix: "${{ env.REGISTRY }}jupyterhub/jupyterhub:"
+          defaultTag: "${{ env.REGISTRY }}jupyterhub/jupyterhub:noref"
+          branchRegex: ^\w[\w-.]*$
+
+      - name: Build and push jupyterhub
+        uses: docker/build-push-action@e1b7f96249f2e4c8e4ac1519b9608c0d48944a1f # associated tag: v2.4.0
+        with:
+          context: .
+          platforms: linux/amd64,linux/arm64
+          push: true
+          # tags parameter must be a string input so convert `gettags` JSON
+          # array into a comma separated list of tags
+          tags: ${{ join(fromJson(steps.jupyterhubtags.outputs.tags)) }}
+
+      # jupyterhub-onbuild
+
+      - name: Get list of jupyterhub-onbuild tags
+        id: onbuildtags
+        uses: jupyterhub/action-major-minor-tag-calculator@v1
+        with:
+          githubToken: ${{ secrets.GITHUB_TOKEN }}
+          prefix: "${{ env.REGISTRY }}jupyterhub/jupyterhub-onbuild:"
+          defaultTag: "${{ env.REGISTRY }}jupyterhub/jupyterhub-onbuild:noref"
+          branchRegex: ^\w[\w-.]*$
+
+      - name: Build and push jupyterhub-onbuild
+        uses: docker/build-push-action@e1b7f96249f2e4c8e4ac1519b9608c0d48944a1f # associated tag: v2.4.0
+        with:
+          build-args: |
+            BASE_IMAGE=${{ fromJson(steps.jupyterhubtags.outputs.tags)[0] }}
+          context: onbuild
+          platforms: linux/amd64,linux/arm64
+          push: true
+          tags: ${{ join(fromJson(steps.onbuildtags.outputs.tags)) }}
+
+      # jupyterhub-demo
+
+      - name: Get list of jupyterhub-demo tags
+        id: demotags
+        uses: jupyterhub/action-major-minor-tag-calculator@v1
+        with:
+          githubToken: ${{ secrets.GITHUB_TOKEN }}
+          prefix: "${{ env.REGISTRY }}jupyterhub/jupyterhub-demo:"
+          defaultTag: "${{ env.REGISTRY }}jupyterhub/jupyterhub-demo:noref"
+          branchRegex: ^\w[\w-.]*$
+
+      - name: Build and push jupyterhub-demo
+        uses: docker/build-push-action@e1b7f96249f2e4c8e4ac1519b9608c0d48944a1f # associated tag: v2.4.0
+        with:
+          build-args: |
+            BASE_IMAGE=${{ fromJson(steps.onbuildtags.outputs.tags)[0] }}
+          context: demo-image
+          # linux/arm64 currently fails:
+          # ERROR: Could not build wheels for argon2-cffi which use PEP 517 and cannot be installed directly
+          # ERROR: executor failed running [/bin/sh -c python3 -m pip install notebook]: exit code: 1
+          platforms: linux/amd64
+          push: true
+          tags: ${{ join(fromJson(steps.demotags.outputs.tags)) }}

.github/workflows/test.yml

@@ -0,0 +1,215 @@
+# 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
+#
+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:
+  push:
+  workflow_dispatch:
+
+env:
+  # UTF-8 content may be interpreted as ascii and causes errors without this.
+  LANG: C.UTF-8
+
+jobs:
+  # Run "pytest jupyterhub/tests" in various configurations
+  pytest:
+    runs-on: ubuntu-20.04
+    timeout-minutes: 10
+
+    strategy:
+      # Keep running even if one variation of the job fail
+      fail-fast: false
+      matrix:
+        # We run this job multiple times with different parameterization
+        # specified below, these parameters have no meaning on their own and
+        # gain meaning on how job steps use them.
+        #
+        # subdomain:
+        #   Tests everything when JupyterHub is configured to add routes for
+        #   users with dedicated subdomains like user1.jupyter.example.com
+        #   rather than jupyter.example.com/user/user1.
+        #
+        # db: [mysql/postgres]
+        #   Tests everything when JupyterHub works against a dedicated mysql or
+        #   postgresql server.
+        #
+        # jupyter_server:
+        #   Tests everything when the user instances are started with
+        #   jupyter_server instead of notebook.
+        #
+        # ssl:
+        #   Tests everything using internal SSL connections instead of
+        #   unencrypted HTTP
+        #
+        # main_dependencies:
+        #   Tests everything when the we use the latest available dependencies
+        #   from: ipytraitlets.
+        #
+        # NOTE: Since only the value of these parameters are presented in the
+        #       GitHub UI when the workflow run, we avoid using true/false as
+        #       values by instead duplicating the name to signal true.
+        include:
+          - python: "3.6"
+            oldest_dependencies: oldest_dependencies
+          - python: "3.6"
+            subdomain: subdomain
+          - python: "3.7"
+            db: mysql
+          - python: "3.7"
+            ssl: ssl
+          - python: "3.8"
+            db: postgres
+          - python: "3.8"
+            jupyter_server: jupyter_server
+          - python: "3.9"
+            main_dependencies: main_dependencies
+
+    steps:
+      # NOTE: In GitHub workflows, environment variables are set by writing
+      #       assignment statements to a file. They will be set in the following
+      #       steps as if would used `export MY_ENV=my-value`.
+      - name: Configure environment variables
+        run: |
+          if [ "${{ matrix.subdomain }}" != "" ]; then
+              echo "JUPYTERHUB_TEST_SUBDOMAIN_HOST=http://localhost.jovyan.org:8000" >> $GITHUB_ENV
+          fi
+          if [ "${{ 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" >> $GITHUB_ENV
+          fi
+          if [ "${{ matrix.ssl }}" == "ssl" ]; then
+              echo "SSL_ENABLED=1" >> $GITHUB_ENV
+          fi
+          if [ "${{ matrix.db }}" == "postgres" ]; then
+              echo "PGHOST=127.0.0.1" >> $GITHUB_ENV
+              echo "PGUSER=test_user" >> $GITHUB_ENV
+              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
+          fi
+      - uses: actions/checkout@v2
+      # NOTE: actions/setup-node@v1 make use of a cache within the GitHub base
+      #       environment and setup in a fraction of a second.
+      - name: Install Node v14
+        uses: actions/setup-node@v1
+        with:
+          node-version: "14"
+      - name: Install Node dependencies
+        run: |
+          npm install
+          npm install -g configurable-http-proxy
+          npm install -g yarn
+          npm list
+
+      # NOTE: actions/setup-python@v2 make use of a cache within the GitHub base
+      #       environment and setup in a fraction of a second.
+      - name: Install Python ${{ matrix.python }}
+        uses: actions/setup-python@v2
+        with:
+          python-version: ${{ matrix.python }}
+      - name: Install Python dependencies
+        run: |
+          pip install --upgrade pip
+          pip install --upgrade . -r dev-requirements.txt
+
+          if [ "${{ matrix.oldest_dependencies }}" != "" ]; then
+            # take any dependencies in requirements.txt such as tornado>=5.0
+            # and transform them to tornado==5.0 so we can run tests with
+            # the earliest-supported versions
+            cat requirements.txt | grep '>=' | sed -e 's@>=@==@g' > oldest-requirements.txt
+            pip install -r oldest-requirements.txt
+          fi
+
+          if [ "${{ matrix.main_dependencies }}" != "" ]; then
+              pip install git+https://github.com/ipython/traitlets#egg=traitlets --force
+          fi
+          if [ "${{ matrix.jupyter_server }}" != "" ]; then
+              pip uninstall notebook --yes
+              pip install jupyter_server
+          fi
+          if [ "${{ matrix.db }}" == "mysql" ]; then
+              pip install mysql-connector-python
+          fi
+          if [ "${{ matrix.db }}" == "postgres" ]; then
+              pip install psycopg2-binary
+          fi
+
+          pip freeze
+
+      # NOTE: If you need to debug this DB setup step, consider the following.
+      #
+      # 1. mysql/postgressql are database servers we start as docker containers,
+      #    and we use clients named mysql/psql.
+      #
+      # 2. When we start a database server we need to pass environment variables
+      #    explicitly as part of the `docker run` command. These environment
+      #    variables are named differently from the similarly named environment
+      #    variables used by the clients.
+      #
+      #    - mysql    server ref: https://hub.docker.com/_/mysql/
+      #    - mysql    client ref: https://dev.mysql.com/doc/refman/5.7/en/environment-variables.html
+      #    - postgres server ref: https://hub.docker.com/_/postgres/
+      #    - psql     client ref: https://www.postgresql.org/docs/9.5/libpq-envars.html
+      #
+      # 3. When we connect, they should use 127.0.0.1 rather than the
+      #    default way of connecting which leads to errors like below both for
+      #    mysql and postgresql unless we set MYSQL_HOST/PGHOST to 127.0.0.1.
+      #
+      #    - ERROR 2002 (HY000): Can't connect to local MySQL server through socket '/var/run/mysqld/mysqld.sock' (2)
+      #
+      - name: Start a database server (${{ matrix.db }})
+        if: ${{ matrix.db }}
+        run: |
+          if [ "${{ matrix.db }}" == "mysql" ]; then
+              sudo apt-get update
+              sudo apt-get install -y mysql-client
+              DB=mysql bash ci/docker-db.sh
+              DB=mysql bash ci/init-db.sh
+          fi
+          if [ "${{ matrix.db }}" == "postgres" ]; then
+              sudo apt-get update
+              sudo apt-get install -y postgresql-client
+              DB=postgres bash ci/docker-db.sh
+              DB=postgres bash ci/init-db.sh
+          fi
+
+      - 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
+
+  docker-build:
+    runs-on: ubuntu-20.04
+    timeout-minutes: 10
+
+    steps:
+      - uses: actions/checkout@v2
+
+      - name: build images
+        run: |
+          docker build -t jupyterhub/jupyterhub .
+          docker build -t jupyterhub/jupyterhub-onbuild onbuild
+          docker build -t jupyterhub/jupyterhub:alpine -f dockerfiles/Dockerfile.alpine .
+          docker build -t jupyterhub/singleuser singleuser
+
+      - name: smoke test jupyterhub
+        run: |
+          docker run --rm -t jupyterhub/jupyterhub jupyterhub --help
+
+      - name: verify static files
+        run: |
+          docker run --rm -t -v $PWD/dockerfiles:/io jupyterhub/jupyterhub python3 /io/test.py

.gitignore

@@ -8,6 +8,7 @@ dist
 docs/_build
 docs/build
 docs/source/_static/rest-api
+docs/source/rbac/scope-table.md
 .ipynb_checkpoints
 # ignore config file at the top-level of the repo
 # but not sub-dirs
@@ -24,5 +25,10 @@ MANIFEST
 .coverage.*
 htmlcov
 .idea/
+.vscode/
 .pytest_cache
 pip-wheel-metadata
+docs/source/reference/metrics.rst
+oldest-requirements.txt
+jupyterhub-proxy.pid
+examples/server-api/service-token

.pre-commit-config.yaml

@@ -1,20 +1,30 @@
 repos:
-- repo: https://github.com/asottile/reorder_python_imports
-  rev: v1.8.0
-  hooks:
-  - id: reorder-python-imports
-    language_version: python3.6
-- repo: https://github.com/ambv/black
-  rev: 19.10b0
-  hooks:
-  - id: black
-- repo: https://github.com/pre-commit/pre-commit-hooks
-  rev: v2.4.0
-  hooks:
-  - id: end-of-file-fixer
-  - id: check-json
-  - id: check-yaml
-  - id: check-case-conflict
-  - id: check-executables-have-shebangs
-  - id: requirements-txt-fixer
-  - id: flake8
+  - repo: https://github.com/asottile/pyupgrade
+    rev: v2.26.0
+    hooks:
+      - id: pyupgrade
+        args:
+          - --py36-plus
+  - repo: https://github.com/asottile/reorder_python_imports
+    rev: v2.6.0
+    hooks:
+      - id: reorder-python-imports
+  - repo: https://github.com/psf/black
+    rev: 21.8b0
+    hooks:
+      - id: black
+  - repo: https://github.com/pre-commit/mirrors-prettier
+    rev: v2.4.0
+    hooks:
+      - id: prettier
+  - repo: https://github.com/PyCQA/flake8
+    rev: "3.9.2"
+    hooks:
+      - id: flake8
+  - repo: https://github.com/pre-commit/pre-commit-hooks
+    rev: v4.0.1
+    hooks:
+      - id: end-of-file-fixer
+      - id: check-case-conflict
+      - id: check-executables-have-shebangs
+      - id: requirements-txt-fixer

.prettierignore

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

.travis.yml

@@ -1,100 +0,0 @@
-language: python
-sudo: false
-cache:
-  - pip
-python:
-  - 3.6
-  - 3.5
-  - nightly
-env:
-  global:
-    - MYSQL_HOST=127.0.0.1
-    - MYSQL_TCP_PORT=13306
-services:
-  - postgresql
-  - docker
-
-# installing dependencies
-before_install:
-  - set -e
-  - nvm install 6; nvm use 6
-  - npm install
-  - npm install -g configurable-http-proxy
-  - |
-    # setup database
-    if [[ $JUPYTERHUB_TEST_DB_URL == mysql* ]]; then
-      unset MYSQL_UNIX_PORT
-      DB=mysql bash ci/docker-db.sh
-      DB=mysql bash ci/init-db.sh
-      # FIXME: mysql-connector-python 8.0.16 incorrectly decodes bytes to str
-      # ref: https://bugs.mysql.com/bug.php?id=94944
-      pip install 'mysql-connector-python==8.0.11'
-    elif [[ $JUPYTERHUB_TEST_DB_URL == postgresql* ]]; then
-      psql -c "CREATE USER $PGUSER WITH PASSWORD '$PGPASSWORD';" -U postgres
-      DB=postgres bash ci/init-db.sh
-      pip install psycopg2-binary
-    fi
-install:
-  - pip install --upgrade pip
-  - pip install --upgrade --pre -r dev-requirements.txt .
-  - pip freeze
-
-# running tests
-script:
-  - |
-    # run tests
-    if [[ -z "$TEST" ]]; then
-      pytest -v --maxfail=2 --cov=jupyterhub jupyterhub/tests
-    fi
-  - |
-    # run autoformat
-    if [[ "$TEST" == "lint" ]]; then
-      pre-commit run --all-files
-    fi
-  - |
-    # build docs
-    if [[ "$TEST" == "docs" ]]; then
-      pushd docs
-      pip install --upgrade -r requirements.txt
-      pip install --upgrade alabaster_jupyterhub
-      make html
-      popd
-    fi
-after_success:
-  - codecov
-after_failure:
-  - |
-    # point to auto-lint-fix
-    if [[ "$TEST" == "lint" ]]; then
-      echo "You can install pre-commit hooks to automatically run formatting"
-      echo "on each commit with:"
-      echo "    pre-commit install"
-      echo "or you can run by hand on staged files with"
-      echo "    pre-commit run"
-      echo "or after-the-fact on already committed files with"
-      echo "    pre-commit run --all-files"
-    fi
-matrix:
-  fast_finish: true
-  include:
-    - python: 3.6
-      env: TEST=lint
-    - python: 3.6
-      env: TEST=docs
-    - python: 3.6
-      env: JUPYTERHUB_TEST_SUBDOMAIN_HOST=http://localhost.jovyan.org:8000
-    - python: 3.6
-      env:
-        - JUPYTERHUB_TEST_DB_URL=mysql+mysqlconnector://root@127.0.0.1:$MYSQL_TCP_PORT/jupyterhub
-    - python: 3.6
-      env:
-        - PGUSER=jupyterhub
-        - PGPASSWORD=hub[test/:?
-        # password in url is url-encoded (urllib.parse.quote($PGPASSWORD, safe=''))
-        - JUPYTERHUB_TEST_DB_URL=postgresql://jupyterhub:hub%5Btest%2F%3A%3F@127.0.0.1/jupyterhub
-    - python: 3.7
-      dist: xenial
-    - python: 3.8
-      if: tag IS present
-  allow_failures:
-    - python: nightly

CHECKLIST-Release.md

@@ -2,24 +2,24 @@
 
 - [ ] Upgrade Docs prior to Release
 
-    - [ ] Change log
-    - [ ] New features documented
-    - [ ] Update the contributor list - thank you page
+  - [ ] 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
+  - [ ] 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)
+  - [ ] Email Jupyter and Jupyter In Education mailing lists
+  - [ ] Tweet (optional)
 
 - [ ] Increment the version number for the next release
 

CODE_OF_CONDUCT.md

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

CONTRIBUTING.md

@@ -1,50 +1,58 @@
 # Contributing to JupyterHub
 
 Welcome! As a [Jupyter](https://jupyter.org) project,
-you can follow the [Jupyter contributor guide](https://jupyter.readthedocs.io/en/latest/contributor/content-contributor.html).
+you can follow the [Jupyter contributor guide](https://jupyter.readthedocs.io/en/latest/contributing/content-contributor.html).
 
-Make sure to also follow [Project Jupyter's Code of Conduct](https://github.com/jupyter/governance/blob/master/conduct/code_of_conduct.md)
+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
 
+<!--
+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?
+-->
+
 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
-    ```
+   ```bash
+   git clone https://github.com/jupyterhub/jupyterhub
+   ```
 2. do a development install with pip
 
-    ```bash
-    cd jupyterhub
-    python3 -m pip install --editable .
-    ```
+   ```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
-    ```
+   ```bash
+   python3 -m pip install -r dev-requirements.txt
+   ```
+
 4. install configurable-http-proxy with npm:
 
-    ```bash
-    npm install -g configurable-http-proxy
-    ```
+   ```bash
+   npm install -g configurable-http-proxy
+   ```
+
 5. set up pre-commit hooks for automatic code formatting, etc.
 
-    ```bash
-    pre-commit install
-    ```
+   ```bash
+   pre-commit install
+   ```
 
-    You can also invoke the pre-commit hook manually at any time with
+   You can also invoke the pre-commit hook manually at any time with
 
-    ```bash
-    pre-commit run
-    ```
+   ```bash
+   pre-commit run
+   ```
 
 ## Contributing
 
@@ -60,12 +68,12 @@ 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/ambv/black#editor-integration)
+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
+`pre-commit run --all-files`. You need to make the fixing commit
 yourself after that.
 
 ## Testing
@@ -128,4 +136,4 @@ 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.
+When in doubt, feel free to [ask](https://gitter.im/jupyterhub/jupyterhub).

COPYING.md

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

Dockerfile

@@ -21,8 +21,7 @@
 # your jupyterhub_config.py will be added automatically
 # from your docker directory.
 
-# https://github.com/tianon/docker-brew-ubuntu-core/commit/d4313e13366d24a97bd178db4450f63e221803f1
-ARG BASE_IMAGE=ubuntu:bionic-20191029@sha256:6e9f67fa63b0323e9a1e587fd71c561ba48a034504fb804fd26fd8800039835d
+ARG BASE_IMAGE=ubuntu:focal-20200729
 FROM $BASE_IMAGE AS builder
 
 USER root
@@ -30,6 +29,7 @@ USER root
 ENV DEBIAN_FRONTEND noninteractive
 RUN apt-get update \
  && apt-get install -yq --no-install-recommends \
+    build-essential \
     ca-certificates \
     locales \
     python3-dev \
@@ -40,19 +40,18 @@ RUN apt-get update \
  && apt-get clean \
  && rm -rf /var/lib/apt/lists/*
 
-# copy only what we need to avoid unnecessary rebuilds
-COPY package.json \
-     pyproject.toml \
-     README.md \
-     requirements.txt \
-     setup.py \
-     /src/jupyterhub/
-COPY jupyterhub/ /src/jupyterhub/jupyterhub
-COPY share/ /src/jupyterhub/share
-
-WORKDIR /src/jupyterhub
 RUN python3 -m pip install --upgrade setuptools pip wheel
-RUN python3 -m pip wheel -v --wheel-dir wheelhouse .
+
+# 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
+
+# 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
 
 
 FROM $BASE_IMAGE

README.md

@@ -6,27 +6,37 @@
 **[License](#license)** |
 **[Help and Resources](#help-and-resources)**
 
+---
+
+Please note that this repository is participating in a study into the sustainability of open source projects. Data will be gathered about this repository for approximately the next 12 months, starting from 2021-06-11.
+
+Data collected will include the number of contributors, number of PRs, time taken to close/merge these PRs, and issues closed.
+
+For more information, please visit
+[our informational page](https://sustainable-open-science-and-software.github.io/) or download our [participant information sheet](https://sustainable-open-science-and-software.github.io/assets/PIS_sustainable_software.pdf).
+
+---
 
 # [JupyterHub](https://github.com/jupyterhub/jupyterhub)
 
-
-[![PyPI](https://img.shields.io/pypi/v/jupyterhub.svg)](https://pypi.python.org/pypi/jupyterhub)
-[![Documentation Status](https://readthedocs.org/projects/jupyterhub/badge/?version=latest)](https://jupyterhub.readthedocs.org/en/latest/?badge=latest)
-[![Build Status](https://travis-ci.org/jupyterhub/jupyterhub.svg?branch=master)](https://travis-ci.org/jupyterhub/jupyterhub)
-[![Circle CI](https://circleci.com/gh/jupyterhub/jupyterhub.svg?style=shield&circle-token=b5b65862eb2617b9a8d39e79340b0a6b816da8cc)](https://circleci.com/gh/jupyterhub/jupyterhub)
-[![codecov.io](https://codecov.io/github/jupyterhub/jupyterhub/coverage.svg?branch=master)](https://codecov.io/github/jupyterhub/jupyterhub?branch=master)
-[![GitHub](https://img.shields.io/badge/issue_tracking-github-blue.svg)](https://github.com/jupyterhub/jupyterhub/issues)
-[![Discourse](https://img.shields.io/badge/help_forum-discourse-blue.svg)](https://discourse.jupyter.org/c/jupyterhub)
-[![Gitter](https://img.shields.io/badge/social_chat-gitter-blue.svg)](https://gitter.im/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)
+[![Gitter](https://img.shields.io/badge/social_chat-gitter-blue?logo=gitter)](https://gitter.im/jupyterhub/jupyterhub)
 
 With [JupyterHub](https://jupyterhub.readthedocs.io) you can create a
-**multi-user Hub** which spawns, manages, and proxies multiple instances of the
+**multi-user Hub** that spawns, manages, and proxies multiple instances of the
 single-user [Jupyter notebook](https://jupyter-notebook.readthedocs.io)
 server.
 
 [Project Jupyter](https://jupyter.org) created JupyterHub to support many
 users. The Hub can offer notebook servers to a class of students, a corporate
-data science workgroup, a scientific research project, or a high performance
+data science workgroup, a scientific research project, or a high-performance
 computing group.
 
 ## Technical overview
@@ -40,38 +50,30 @@ Three main actors make up JupyterHub:
 Basic principles for operation are:
 
 - Hub launches a proxy.
-- Proxy forwards all requests to Hub by default.
-- Hub handles login, and spawns single-user servers on demand.
-- Hub configures proxy to forward url prefixes to the single-user notebook
+- The Proxy forwards all requests to Hub by default.
+- Hub handles login and spawns single-user servers on demand.
+- Hub configures proxy to forward URL prefixes to the single-user notebook
   servers.
 
 JupyterHub also provides a
-[REST API](http://petstore.swagger.io/?url=https://raw.githubusercontent.com/jupyter/jupyterhub/master/docs/rest-api.yml#/default)
+[REST API](https://petstore3.swagger.io/?url=https://raw.githubusercontent.com/jupyter/jupyterhub/HEAD/docs/rest-api.yml#/default)
 for administration of the Hub and its users.
 
 ## Installation
 
-
 ### Check prerequisites
 
 - A Linux/Unix based system
-- [Python](https://www.python.org/downloads/) 3.5 or greater
+- [Python](https://www.python.org/downloads/) 3.6 or greater
 - [nodejs/npm](https://www.npmjs.com/)
 
-  * If you are using **`conda`**, the nodejs and npm dependencies will be installed for
+  - If you are using **`conda`**, the nodejs and npm dependencies will be installed for
     you by conda.
 
-  * If you are using **`pip`**, install a recent version of
+  - If you are using **`pip`**, install a recent version (at least 12.0) of
     [nodejs/npm](https://docs.npmjs.com/getting-started/installing-node).
-    For example, install it on Linux (Debian/Ubuntu) using:
-
-    ```
-    sudo apt-get install npm nodejs-legacy
-    ```
-
-    The `nodejs-legacy` package installs the `node` executable and is currently
-    required for npm to work on Debian/Ubuntu.
 
+- If using the default PAM Authenticator, a [pluggable authentication module (PAM)](https://en.wikipedia.org/wiki/Pluggable_authentication_module).
 - TLS certificate and key for HTTPS communication
 - Domain name
 
@@ -85,12 +87,11 @@ To install JupyterHub along with its dependencies including nodejs/npm:
 conda install -c conda-forge jupyterhub
 ```
 
-If you plan to run notebook servers locally, install the Jupyter notebook
-or JupyterLab:
+If you plan to run notebook servers locally, install JupyterLab or Jupyter notebook:
 
 ```bash
-conda install notebook
 conda install jupyterlab
+conda install notebook
 ```
 
 #### Using `pip`
@@ -99,13 +100,13 @@ JupyterHub can be installed with `pip`, and the proxy with `npm`:
 
 ```bash
 npm install -g configurable-http-proxy
-python3 -m pip install jupyterhub    
+python3 -m pip install jupyterhub
 ```
 
-If you plan to run notebook servers locally, you will need to install the
-[Jupyter notebook](https://jupyter.readthedocs.io/en/latest/install.html)
-package:
+If you plan to run notebook servers locally, you will need to install
+[JupyterLab or Jupyter notebook](https://jupyter.readthedocs.io/en/latest/install.html):
 
+    python3 -m pip install --upgrade jupyterlab
     python3 -m pip install --upgrade notebook
 
 ### Run the Hub server
@@ -117,10 +118,10 @@ To start the Hub server, run the command:
 Visit `https://localhost:8000` in your browser, and sign in with your unix
 PAM credentials.
 
-*Note*: To allow multiple users to sign into the server, you will need to
-run the `jupyterhub` command as a *privileged user*, such as root.
+_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.
 The [wiki](https://github.com/jupyterhub/jupyterhub/wiki/Using-sudo-to-run-JupyterHub-without-root-privileges)
-describes how to run the server as a *less privileged user*, which requires
+describes how to run the server as a _less privileged user_, which requires
 more configuration of the system.
 
 ## Configuration
@@ -139,7 +140,7 @@ To generate a default config file with settings and descriptions:
 
 ### Start the Hub
 
-To start the Hub on a specific url and port ``10.0.1.2:443`` with **https**:
+To start the Hub on a specific url and port `10.0.1.2:443` with **https**:
 
     jupyterhub --ip 10.0.1.2 --port 443 --ssl-key my_ssl.key --ssl-cert my_ssl.cert
 
@@ -201,7 +202,7 @@ These accounts will be used for authentication in JupyterHub's default configura
 ## Contributing
 
 If you would like to contribute to the project, please read our
-[contributor documentation](http://jupyter.readthedocs.io/en/latest/contributor/content-contributor.html)
+[contributor documentation](https://jupyter.readthedocs.io/en/latest/contributing/content-contributor.html)
 and the [`CONTRIBUTING.md`](CONTRIBUTING.md). The `CONTRIBUTING.md` file
 explains how to set up a development installation, how to run the test suite,
 and how to contribute to documentation.
@@ -228,18 +229,17 @@ docker container or Linux VM.
 We use a shared copyright model that enables all contributors to maintain the
 copyright on their contributions.
 
-All code is licensed under the terms of the revised BSD license.
+All code is licensed under the terms of the [revised BSD license](./COPYING.md).
 
 ## Help and resources
 
-We encourage you to ask questions on the [Jupyter mailing list](https://groups.google.com/forum/#!forum/jupyter).
-To participate in development discussions or get help, talk with us on
-our JupyterHub [Gitter](https://gitter.im/jupyterhub/jupyterhub) channel.
+We encourage you to ask questions and share ideas on the [Jupyter community forum](https://discourse.jupyter.org/).
+You can also talk with us on our JupyterHub [Gitter](https://gitter.im/jupyterhub/jupyterhub) channel.
 
 - [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](http://petstore.swagger.io/?url=https://raw.githubusercontent.com/jupyter/jupyterhub/master/docs/rest-api.yml#/default)
+- [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)
 - [Project Jupyter website](https://jupyter.org)
 - [Project Jupyter community](https://jupyter.org/community)

bower-lite

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

ci/docker-db.sh

@@ -1,59 +1,60 @@
 #!/usr/bin/env bash
-# source this file to setup postgres and mysql
-# for local testing (as similar as possible to docker)
+# The goal of this script is to start a database server as a docker container.
+#
+# Required environment variables:
+# - DB: The database server to start, either "postgres" or "mysql".
+#
+# - PGUSER/PGPASSWORD: For the creation of a postgresql user with associated
+#   password.
 
 set -eu
 
-export MYSQL_HOST=127.0.0.1
-export MYSQL_TCP_PORT=${MYSQL_TCP_PORT:-13306}
-export PGHOST=127.0.0.1
-NAME="hub-test-$DB"
-DOCKER_RUN="docker run -d --name $NAME"
+# Stop and remove any existing database container
+DOCKER_CONTAINER="hub-test-$DB"
+docker rm -f "$DOCKER_CONTAINER" 2>/dev/null || true
 
-docker rm -f "$NAME" 2>/dev/null || true
+# Prepare environment variables to startup and await readiness of either a mysql
+# or postgresql server.
+if [[ "$DB" == "mysql" ]]; then
+    # Environment variables can influence both the mysql server in the docker
+    # container and the mysql client.
+    #
+    # 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"
+    READINESS_CHECK="mysql --user root --execute \q"
+elif [[ "$DB" == "postgres" ]]; then
+    # Environment variables can influence both the postgresql server in the
+    # docker container and the postgresql client (psql).
+    #
+    # ref server: https://hub.docker.com/_/postgres/
+    # ref client: https://www.postgresql.org/docs/9.5/libpq-envars.html
+    #
+    # POSTGRES_USER / POSTGRES_PASSWORD will create a user on startup of the
+    # postgres server, but PGUSER and PGPASSWORD are the environment variables
+    # used by the postgresql client psql, so we configure the user based on how
+    # we want to connect.
+    #
+    DOCKER_RUN_ARGS="-p 5432:5432 --env "POSTGRES_USER=${PGUSER}" --env "POSTGRES_PASSWORD=${PGPASSWORD}" postgres:9.5"
+    READINESS_CHECK="psql --command \q"
+else
+    echo '$DB must be mysql or postgres'
+    exit 1
+fi
 
-case "$DB" in
-"mysql")
-  RUN_ARGS="-e MYSQL_ALLOW_EMPTY_PASSWORD=1 -p $MYSQL_TCP_PORT:3306 mysql:5.7"
-  CHECK="mysql --host $MYSQL_HOST --port $MYSQL_TCP_PORT --user root -e \q"
-  ;;
-"postgres")
-  RUN_ARGS="-p 5432:5432 postgres:9.5"
-  CHECK="psql --user postgres -c \q"
-  ;;
-*)
-  echo '$DB must be mysql or postgres'
-  exit 1
-esac
-
-$DOCKER_RUN $RUN_ARGS
+# Start the database server
+docker run --detach --name "$DOCKER_CONTAINER" $DOCKER_RUN_ARGS
 
+# Wait for the database server to start
 echo -n "waiting for $DB "
 for i in {1..60}; do
-  if $CHECK; then
-    echo 'done'
-    break
-  else
-    echo -n '.'
-    sleep 1
-  fi
+    if $READINESS_CHECK; then
+        echo 'done'
+        break
+    else
+        echo -n '.'
+        sleep 1
+    fi
 done
-$CHECK
-
-case "$DB" in
-"mysql")
-  ;;
-"postgres")
-  # create the user
-  psql --user postgres -c "CREATE USER $PGUSER WITH PASSWORD '$PGPASSWORD';"
-  ;;
-*)
-esac
-
-echo -e "
-Set these environment variables:
-
-    export MYSQL_HOST=127.0.0.1
-    export MYSQL_TCP_PORT=$MYSQL_TCP_PORT
-    export PGHOST=127.0.0.1
-"
+$READINESS_CHECK

ci/init-db.sh

@@ -1,27 +1,26 @@
 #!/usr/bin/env bash
-# initialize jupyterhub databases for testing
+# The goal of this script is to initialize a running database server with clean
+# databases for use during tests.
+#
+# Required environment variables:
+# - DB: The database server to start, either "postgres" or "mysql".
 
 set -eu
 
-MYSQL="mysql --user root --host $MYSQL_HOST --port $MYSQL_TCP_PORT -e "
-PSQL="psql --user postgres -c "
-
-case "$DB" in
-"mysql")
-  EXTRA_CREATE='CHARACTER SET utf8 COLLATE utf8_general_ci'
-  SQL="$MYSQL"
-  ;;
-"postgres")
-  SQL="$PSQL"
-  ;;
-*)
-  echo '$DB must be mysql or postgres'
-  exit 1
-esac
+# Prepare env vars SQL_CLIENT and EXTRA_CREATE_DATABASE_ARGS
+if [[ "$DB" == "mysql" ]]; then
+    SQL_CLIENT="mysql --user root --execute "
+    EXTRA_CREATE_DATABASE_ARGS='CHARACTER SET utf8 COLLATE utf8_general_ci'
+elif [[ "$DB" == "postgres" ]]; then
+    SQL_CLIENT="psql --command "
+else
+    echo '$DB must be mysql or postgres'
+    exit 1
+fi
 
+# Configure a set of databases in the database server for upgrade tests
 set -x
-
-for SUFFIX in '' _upgrade_072 _upgrade_081 _upgrade_094; do
-    $SQL "DROP DATABASE jupyterhub${SUFFIX};" 2>/dev/null || true
-    $SQL "CREATE DATABASE jupyterhub${SUFFIX} ${EXTRA_CREATE:-};"
+for SUFFIX in '' _upgrade_100 _upgrade_122 _upgrade_130; 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

@@ -0,0 +1,16 @@
+# Demo JupyterHub Docker image
+#
+# 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
+FROM ${BASE_IMAGE}
+
+# Install the notebook package
+RUN python3 -m pip install notebook
+
+# Create a demo user
+RUN useradd --create-home demo
+RUN chown demo .
+
+USER demo

demo-image/README.md

@@ -0,0 +1,26 @@
+## Demo Dockerfile
+
+This is a demo JupyterHub Docker image to help you get a quick overview of what
+JupyterHub is and how it works.
+
+It uses the SimpleLocalProcessSpawner to spawn new user servers and
+DummyAuthenticator for authentication.
+The DummyAuthenticator allows you to log in with any username & password and the
+SimpleLocalProcessSpawner allows starting servers without having to create a
+local user for each JupyterHub user.
+
+### Important!
+
+This should only be used for demo or testing purposes!
+It shouldn't be used as a base image to build on.
+
+### Try it
+
+1. `cd` to the root of your jupyterhub repo.
+
+2. Build the demo image with `docker build -t jupyterhub-demo demo-image`.
+
+3. Run the demo image with `docker run -d -p 8000:8000 jupyterhub-demo`.
+
+4. Visit http://localhost:8000 and login with any username and password
+5. Happy demo-ing :tada:!

demo-image/jupyterhub_config.py

@@ -0,0 +1,7 @@
+# Configuration file for jupyterhub-demo
+
+c = get_config()
+
+# Use DummyAuthenticator and SimpleSpawner
+c.JupyterHub.spawner_class = "simple"
+c.JupyterHub.authenticator_class = "dummy"

dev-requirements.txt

@@ -10,9 +10,9 @@ html5lib  # needed for beautifulsoup
 mock
 notebook
 pre-commit
+pytest>=3.3
 pytest-asyncio
 pytest-cov
-pytest>=3.3
 requests-mock
 # blacklist urllib3 releases affected by https://github.com/urllib3/urllib3/issues/1683
 # I *think* this should only affect testing, not production

dockerfiles/Dockerfile.alpine

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

dockerfiles/README.md

@@ -1,20 +1,20 @@
 ## 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
+
+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. 
+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"
+- 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

@@ -0,0 +1,9 @@
+import os
+
+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"):
+    path = os.path.join(DATA_FILES_PATH, sub_path)
+    assert os.path.exists(path), path

docs/Makefile

@@ -48,6 +48,7 @@ help:
 	@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"
 
 clean:
 	rm -rf $(BUILDDIR)/*
@@ -60,7 +61,17 @@ rest-api: source/_static/rest-api/index.html
 source/_static/rest-api/index.html: rest-api.yml node_modules
 	npm run rest-api
 
-html: rest-api
+metrics: source/reference/metrics.rst
+
+source/reference/metrics.rst: generate-metrics.py
+	python3 generate-metrics.py
+
+scopes: source/rbac/scope-table.md
+
+source/rbac/scope-table.md: source/rbac/generate-scope-table.py
+	python3 source/rbac/generate-scope-table.py
+
+html: rest-api metrics scopes
 	$(SPHINXBUILD) -b html $(ALLSPHINXOPTS) $(BUILDDIR)/html
 	@echo
 	@echo "Build finished. The HTML pages are in $(BUILDDIR)/html."

docs/environment.yml

@@ -1,20 +0,0 @@
-# ReadTheDocs uses the `environment.yaml` so make sure to update that as well
-# if you change the dependencies of JupyterHub in the various `requirements.txt`
-name: jhub_docs
-channels:
-  - conda-forge
-dependencies:
-- pip
-- nodejs
-- python=3.6
-- alembic
-- jinja2
-- pamela
-- recommonmark==0.6.0
-- requests
-- sqlalchemy>=1
-- tornado>=5.0
-- traitlets>=4.1
-- sphinx>=1.7
-- pip:
-  - -r requirements.txt

docs/generate-metrics.py

@@ -0,0 +1,57 @@
+import os
+from os.path import join
+
+from pytablewriter import RstSimpleTableWriter
+from pytablewriter.style import Style
+
+import jupyterhub.metrics
+
+HERE = os.path.abspath(os.path.dirname(__file__))
+
+
+class Generator:
+    @classmethod
+    def create_writer(cls, table_name, headers, values):
+        writer = RstSimpleTableWriter()
+        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):
+        table_rows = []
+        for name in dir(jupyterhub.metrics):
+            obj = getattr(jupyterhub.metrics, name)
+            if obj.__class__.__module__.startswith('prometheus_client.'):
+                for metric in obj.describe():
+                    table_rows.append([metric.type, metric.name, metric.documentation])
+        return table_rows
+
+    def prometheus_metrics(self):
+        generated_directory = f"{HERE}/source/reference"
+        if not os.path.exists(generated_directory):
+            os.makedirs(generated_directory)
+
+        filename = f"{generated_directory}/metrics.rst"
+        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}.")
+
+
+def main():
+    doc_generator = Generator()
+    doc_generator.prometheus_metrics()
+
+
+if __name__ == "__main__":
+    main()

docs/requirements.txt

@@ -1,10 +1,12 @@
-# ReadTheDocs uses the `environment.yaml` so make sure to update that as well
-# if you change this file
 -r ../requirements.txt
+
 alabaster_jupyterhub
-autodoc-traits
-git+https://github.com/pandas-dev/pandas-sphinx-theme.git@master
-recommonmark==0.5.0
+# 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
+pytablewriter>=0.56
+sphinx>=1.7
 sphinx-copybutton
 sphinx-jsonschema
-sphinx>=1.7

docs/source/_static/custom.css

@@ -1,106 +1,4 @@
-div#helm-chart-schema h2,
-div#helm-chart-schema h3,
-div#helm-chart-schema h4,
-div#helm-chart-schema h5,
-div#helm-chart-schema h6 {
-    font-family: courier new;
-}
-
-h3, h3 ~ * {
-  margin-left: 3% !important;
-}
-
-h4, h4 ~ * {
-  margin-left: 6% !important;
-}
-
-h5, h5 ~ * {
-  margin-left: 9% !important;
-}
-
-h6, h6 ~ * {
-  margin-left: 12% !important;
-}
-
-h7, h7 ~ * {
-  margin-left: 15% !important;
-}
-
-img.logo {
-  width:100%
-}
-
-.right-next {
-    float: right;
-    max-width: 45%;
-    overflow: auto;
-    text-overflow: ellipsis;
-    white-space: nowrap;
-}
-
-.right-next::after{
-    content: ' »';
-}
-
-.left-prev {
-    float: left;
-    max-width: 45%;
-    overflow: auto;
-    text-overflow: ellipsis;
-    white-space: nowrap;
-}
-
-.left-prev::before{
-    content: '« ';
-}
-
-.prev-next-bottom {
-  margin-top: 3em;
-}
-
-.prev-next-top {
-  margin-bottom: 1em;
-}
-
-/* Sidebar TOC and headers */
-
-div.sphinxsidebarwrapper div {
-    margin-bottom: .8em;
-}
-div.sphinxsidebar h3 {
-    font-size: 1.3em;
-    padding-top: 0px;
-    font-weight: 800;
-    margin-left: 0px !important;
-}
-
-div.sphinxsidebar p.caption {
-    font-size: 1.2em;
-    margin-bottom: 0px;
-    margin-left: 0px !important;
-    font-weight: 900;
-    color: #767676;
-}
-
-div.sphinxsidebar ul {
-    font-size: .8em;
-    margin-top: 0px;
-    padding-left: 3%;
-    margin-left: 0px !important;
-}
-
-div.relations ul {
-    font-size: 1em;
-    margin-left: 0px !important;
-}
-
-div#searchbox form {
-    margin-left: 0px !important;
-}
-
-/* body elements */
-.toctree-wrapper span.caption-text {
-    color: #767676;
-    font-style: italic;
-    font-weight: 300;
-}
+/* Added to avoid logo being too squeezed */
+.navbar-brand {
+  height: 4rem !important;
+}

docs/source/_templates/navigation.html

@@ -1,16 +0,0 @@
-{# Custom template for navigation.html
-
-   alabaster theme does not provide blocks for titles to
-   be overridden so this custom theme handles title and
-   toctree for sidebar
-#}
-<h3>{{ _('Table of Contents') }}</h3>
-{{ toctree(includehidden=theme_sidebar_includehidden, collapse=theme_sidebar_collapse) }}
-{% if theme_extra_nav_links %}
-<hr />
-<ul>
-    {% for text, uri in theme_extra_nav_links.items() %}
-    <li class="toctree-l1"><a href="{{ uri }}">{{ text }}</a></li>
-    {% endfor %}
-</ul>
-{% endif %}

docs/source/_templates/relations.html

@@ -1,17 +0,0 @@
-{# Custom template for relations.html
-
-   alabaster theme does not provide previous/next page by default
-#}
-<div class="relations">
-<h3>Navigation</h3>
-<ul>
-  <li><a href="{{ pathto(master_doc) }}">Documentation Home</a><ul>
-  {%- if prev %}
-  <li><a href="{{ prev.link|e }}" title="Previous">Previous topic</a></li>
-  {%- endif %}
-  {%- if next %}
-  <li><a href="{{ next.link|e }}" title="Next">Next topic</a></li>
-  {%- endif %}
-  </ul>
-</ul>
-</div>

docs/source/api/index.rst

@@ -18,7 +18,7 @@ information on:
 - learning more about JupyterHub's API
 
 The same JupyterHub API spec, as found here, is available in an interactive form
-`here (on swagger's petstore) <http://petstore.swagger.io/?url=https://raw.githubusercontent.com/jupyterhub/jupyterhub/master/docs/rest-api.yml#!/default>`__.
+`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.
 

docs/source/conf.py

@@ -1,7 +1,5 @@
-# -*- coding: utf-8 -*-
 #
 import os
-import shlex
 import sys
 
 # Set paths
@@ -20,17 +18,20 @@ extensions = [
     'autodoc_traits',
     'sphinx_copybutton',
     'sphinx-jsonschema',
+    'myst_parser',
 ]
 
-templates_path = ['_templates']
-
+myst_enable_extensions = [
+    'colon_fence',
+    'deflist',
+]
 # The master toctree document.
 master_doc = 'index'
 
 # General information about the project.
-project = u'JupyterHub'
-copyright = u'2016, Project Jupyter team'
-author = u'Project Jupyter team'
+project = 'JupyterHub'
+copyright = '2016, Project Jupyter team'
+author = 'Project Jupyter team'
 
 # Autopopulate version
 from os.path import dirname
@@ -54,27 +55,72 @@ todo_include_todos = False
 # Set the default role so we can use `foo` instead of ``foo``
 default_role = 'literal'
 
-# -- Source -------------------------------------------------------------
+# -- 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
 
-import recommonmark
-from recommonmark.transform import AutoStructify
+# create a temp instance of JupyterHub just to get the output of the generate-config
+# and help --all commands.
+jupyterhub_app = JupyterHub()
+
+
+class ConfigDirective(SphinxDirective):
+    """Generate the configuration file output for use in the documentation."""
+
+    has_content = False
+    required_arguments = 0
+    optional_arguments = 0
+    final_argument_whitespace = False
+    option_spec = {}
+
+    def run(self):
+        # 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, '$HOME', 1)
+        par = nodes.literal_block(text=generated_config)
+        return [par]
+
+
+class HelpAllDirective(SphinxDirective):
+    """Print the output of jupyterhub help --all for use in the documentation."""
+
+    has_content = False
+    required_arguments = 0
+    optional_arguments = 0
+    final_argument_whitespace = False
+    option_spec = {}
+
+    def run(self):
+        # The output of the help command for this version
+        buffer = StringIO()
+        with redirect_stdout(buffer):
+            jupyterhub_app.print_help('--help-all')
+        all_help = buffer.getvalue()
+        # post-process output
+        home_dir = os.environ['HOME']
+        all_help = all_help.replace(home_dir, '$HOME', 1)
+        par = nodes.literal_block(text=all_help)
+        return [par]
 
 
 def setup(app):
-    app.add_config_value('recommonmark_config', {'enable_eval_rst': True}, True)
-    app.add_stylesheet('custom.css')
-    app.add_transform(AutoStructify)
+    app.add_css_file('custom.css')
+    app.add_directive('jupyterhub-generate-config', ConfigDirective)
+    app.add_directive('jupyterhub-help-all', HelpAllDirective)
 
 
-source_parsers = {'.md': 'recommonmark.parser.CommonMarkParser'}
-
 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 = 'pandas_sphinx_theme'
+html_theme = 'pydata_sphinx_theme'
 
 html_logo = '_static/images/logo/logo.png'
 html_favicon = '_static/images/logo/favicon.ico'
@@ -100,8 +146,8 @@ latex_documents = [
     (
         master_doc,
         'JupyterHub.tex',
-        u'JupyterHub Documentation',
-        u'Project Jupyter team',
+        'JupyterHub Documentation',
+        'Project Jupyter team',
         'manual',
     )
 ]
@@ -118,7 +164,7 @@ latex_documents = [
 
 # One entry per manual page. List of tuples
 # (source start file, name, description, authors, manual section).
-man_pages = [(master_doc, 'jupyterhub', u'JupyterHub Documentation', [author], 1)]
+man_pages = [(master_doc, 'jupyterhub', 'JupyterHub Documentation', [author], 1)]
 
 # man_show_urls = False
 
@@ -132,7 +178,7 @@ texinfo_documents = [
     (
         master_doc,
         'JupyterHub',
-        u'JupyterHub Documentation',
+        'JupyterHub Documentation',
         author,
         'JupyterHub',
         'One line description of project.',
@@ -166,10 +212,10 @@ intersphinx_mapping = {'https://docs.python.org/3/': None}
 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 rest-api, since RTD doesn't run make
+    # build both metrics and rest-api, since RTD doesn't run make
     from subprocess import check_call as sh
 
-    sh(['make', 'rest-api'], cwd=docs)
+    sh(['make', 'metrics', 'rest-api', 'scopes'], cwd=docs)
 
 # -- Spell checking -------------------------------------------------------
 

docs/source/contributing/docs.rst

@@ -13,7 +13,7 @@ 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
-<http://www.sphinx-doc.org/en/master/usage/restructuredtext/basics.html>`_ &
+<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.
@@ -39,8 +39,8 @@ change renders correctly, it is good practice to test it locally.
    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. 
+#. View the rendered documentation by opening ``build/html/index.html`` in
+   a web browser.
 
    .. tip::
 

docs/source/contributing/index.rst

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

docs/source/contributing/roadmap.md

@@ -6,8 +6,8 @@ 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.
 
-
 ## Using the roadmap
+
 ### Sharing Feedback on the Roadmap
 
 All of the community is encouraged to provide feedback as well as share new
@@ -22,17 +22,17 @@ maintainers will help identify what a good next step is for the issue.
 When submitting an issue, think about what "next step" category best describes
 your issue:
 
-* **now**, concrete/actionable step that is ready for someone to start work on.
-These might be items that have a link to an issue or more abstract like
-"decrease typos and dead links in the documentation"
-* **soon**, less concrete/actionable step that is going to happen soon,
-discussions around the topic are coming close to an end at which point it can
-move into the "now" category
-* **later**, abstract ideas or tasks, need a lot of discussion or
-experimentation to shape the idea so that it can be executed. Can also
-contain concrete/actionable steps that have been postponed on purpose
-(these are steps that could be in "now" but the decision was taken to work on
-them later)
+- **now**, concrete/actionable step that is ready for someone to start work on.
+  These might be items that have a link to an issue or more abstract like
+  "decrease typos and dead links in the documentation"
+- **soon**, less concrete/actionable step that is going to happen soon,
+  discussions around the topic are coming close to an end at which point it can
+  move into the "now" category
+- **later**, abstract ideas or tasks, need a lot of discussion or
+  experimentation to shape the idea so that it can be executed. Can also
+  contain concrete/actionable steps that have been postponed on purpose
+  (these are steps that could be in "now" but the decision was taken to work on
+  them later)
 
 ### Reviewing and Updating the Roadmap
 
@@ -47,8 +47,8 @@ For those please create a
 The roadmap should give the reader an idea of what is happening next, what needs
 input and discussion before it can happen and what has been postponed.
 
-
 ## The roadmap proper
+
 ### Project vision
 
 JupyterHub is a dependable tool used by humans that reduces the complexity of
@@ -58,20 +58,19 @@ creating the environment in which a piece of software can be executed.
 
 These "Now" items are considered active areas of focus for the project:
 
-* HubShare - a sharing service for use with JupyterHub.
-    * Users should be able to:
-        - Push a project to other users.
-        - Get a checkout of a project from other users.
-        - Push updates to a published project.
-        - Pull updates from a published project.
-        - Manage conflicts/merges by simply picking a version (our/theirs)
-        - Get a checkout of a project from the internet. These steps are completely different from saving notebooks/files.
-        - Have directories that are managed by git completely separately from our stuff.
-        - Look at pushed content that they have access to without an explicit pull.
-        - Define and manage teams of users.
-            - Adding/removing a user to/from a team gives/removes them access to all projects that team has access to.
-        - Build other services, such as static HTML publishing and dashboarding on top of these things.
-
+- HubShare - a sharing service for use with JupyterHub.
+  - Users should be able to:
+    - Push a project to other users.
+    - Get a checkout of a project from other users.
+    - Push updates to a published project.
+    - Pull updates from a published project.
+    - Manage conflicts/merges by simply picking a version (our/theirs)
+    - Get a checkout of a project from the internet. These steps are completely different from saving notebooks/files.
+    - Have directories that are managed by git completely separately from our stuff.
+    - Look at pushed content that they have access to without an explicit pull.
+    - Define and manage teams of users.
+      - Adding/removing a user to/from a team gives/removes them access to all projects that team has access to.
+    - Build other services, such as static HTML publishing and dashboarding on top of these things.
 
 ### Soon
 
@@ -79,12 +78,10 @@ These "Soon" items are under discussion. Once an item reaches the point of an
 actionable plan, the item will be moved to the "Now" section. Typically,
 these will be moved at a future review of the roadmap.
 
-* resource monitoring and management:
-    - (prometheus?) API for resource monitoring
-    - tracking activity on single-user servers instead of the proxy
-    - notes and activity tracking per API token
-    - UI for managing named servers
-
+- resource monitoring and management:
+  - (prometheus?) API for resource monitoring
+  - tracking activity on single-user servers instead of the proxy
+  - notes and activity tracking per API token
 
 ### Later
 
@@ -93,6 +90,6 @@ time there is no active plan for an item. The project would like to find the
 resources and time to discuss these ideas.
 
 - real-time collaboration
-    - Enter into real-time collaboration mode for a project that starts a shared execution context.
-    - Once the single-user notebook package supports realtime collaboration,
-      implement sharing mechanism integrated into the Hub.
+  - Enter into real-time collaboration mode for a project that starts a shared execution context.
+  - Once the single-user notebook package supports realtime collaboration,
+    implement sharing mechanism integrated into the Hub.

docs/source/contributing/setup.rst

@@ -8,7 +8,7 @@ System requirements
 ===================
 
 JupyterHub can only run on MacOS or Linux operating systems. If you are
-using Windows, we recommend using `VirtualBox <https://virtualbox.org>`_ 
+using Windows, we recommend using `VirtualBox <https://virtualbox.org>`_
 or a similar system to run `Ubuntu Linux <https://ubuntu.com>`_ for
 development.
 
@@ -18,7 +18,7 @@ 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, 
+`miniconda <https://conda.io/miniconda.html>`_. Remember to get the ‘Python 3’ version,
 and **not** the ‘Python 2’ version!
 
 Install nodejs
@@ -45,7 +45,13 @@ 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.
 
-1. Clone the `JupyterHub git repository <https://github.com/jupyterhub/jupyterhub>`_ 
+.. 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
@@ -93,7 +99,14 @@ happen.
       python3 -m pip install -r dev-requirements.txt
       python3 -m pip install -r requirements.txt
 
-5. Install the development version of JupyterHub. This lets you edit
+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.
 
@@ -101,13 +114,13 @@ happen.
 
       python3 -m pip install --editable .
 
-6. You are now ready to start JupyterHub!
+7. You are now ready to start JupyterHub!
 
    .. code:: bash
 
       jupyterhub
 
-7. You can access JupyterHub from your browser at
+8. You can access JupyterHub from your browser at
    ``http://localhost:8000`` now.
 
 Happy developing!

docs/source/contributing/tests.rst

@@ -64,5 +64,5 @@ Troubleshooting Test Failures
 All the tests are failing
 -------------------------
 
-Make sure you have completed all the steps in :ref:`contributing/setup` sucessfully, and
+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

@@ -1,10 +1,7 @@
 Eventlogging and Telemetry
 ==========================
 
-JupyterHub can be configured to record structured events from a running server using Jupyter's `Telemetry System`_. The types of events that JupyterHub emits are defined by `JSON schemas`_ listed below_
-
- emitted as JSON data, defined and validated by the JSON schemas listed below.
-
+JupyterHub can be configured to record structured events from a running server using Jupyter's `Telemetry System`_. The types of events that JupyterHub emits are defined by `JSON schemas`_ listed at the bottom of this page_.
 
 .. _logging: https://docs.python.org/3/library/logging.html
 .. _`Telemetry System`: https://github.com/jupyter/telemetry
@@ -38,13 +35,12 @@ Here's a basic example:
 The output is a file, ``"event.log"``, with events recorded as JSON data.
 
 
-
-.. _below:
+.. _page:
 
 Event schemas
 -------------
 
 .. toctree::
-   :maxdepth: 2
+    :maxdepth: 2
 
-   server-actions.rst
+    server-actions.rst

docs/source/gallery-jhub-deployments.md

@@ -8,27 +8,29 @@ high performance computing.
 
 Please submit pull requests to update information or to add new institutions or uses.
 
-
 ## Academic Institutions, Research Labs, and Supercomputer Centers
 
 ### University of California Berkeley
 
 - [BIDS - Berkeley Institute for Data Science](https://bids.berkeley.edu/)
-    - [Teaching with Jupyter notebooks and JupyterHub](https://bids.berkeley.edu/resources/videos/teaching-ipythonjupyter-notebooks-and-jupyterhub)
+
+  - [Teaching with Jupyter notebooks and JupyterHub](https://bids.berkeley.edu/resources/videos/teaching-ipythonjupyter-notebooks-and-jupyterhub)
 
 - [Data 8](http://data8.org/)
-    - [GitHub organization](https://github.com/data-8)
+
+  - [GitHub organization](https://github.com/data-8)
 
 - [NERSC](http://www.nersc.gov/)
-    - [Press release on Jupyter and Cori](http://www.nersc.gov/news-publications/nersc-news/nersc-center-news/2016/jupyter-notebooks-will-open-up-new-possibilities-on-nerscs-cori-supercomputer/)
-    - [Moving and sharing data](https://www.nersc.gov/assets/Uploads/03-MovingAndSharingData-Cholia.pdf)
+
+  - [Press release on Jupyter and Cori](http://www.nersc.gov/news-publications/nersc-news/nersc-center-news/2016/jupyter-notebooks-will-open-up-new-possibilities-on-nerscs-cori-supercomputer/)
+  - [Moving and sharing data](https://www.nersc.gov/assets/Uploads/03-MovingAndSharingData-Cholia.pdf)
 
 - [Research IT](http://research-it.berkeley.edu)
-    - [JupyterHub server supports campus research computation](http://research-it.berkeley.edu/blog/17/01/24/free-fully-loaded-jupyterhub-server-supports-campus-research-computation)
+  - [JupyterHub server supports campus research computation](http://research-it.berkeley.edu/blog/17/01/24/free-fully-loaded-jupyterhub-server-supports-campus-research-computation)
 
 ### University of California Davis
 
-- [Spinning up multiple Jupyter Notebooks on AWS for a tutorial](https://github.com/mblmicdiv/course2017/blob/master/exercises/sourmash-setup.md)
+- [Spinning up multiple Jupyter Notebooks on AWS for a tutorial](https://github.com/mblmicdiv/course2017/blob/HEAD/exercises/sourmash-setup.md)
 
 Although not technically a JupyterHub deployment, this tutorial setup
 may be helpful to others in the Jupyter community.
@@ -59,23 +61,31 @@ easy to do with RStudio too.
 
 - [jupyterhub-deploy-teaching](https://github.com/jupyterhub/jupyterhub-deploy-teaching) based on work by Brian Granger for Cal Poly's Data Science 301 Course
 
+### Chameleon
+
+[Chameleon](https://www.chameleoncloud.org) is a NSF-funded configurable experimental environment for large-scale computer science systems research with [bare metal reconfigurability](https://chameleoncloud.readthedocs.io/en/latest/technical/baremetal.html). Chameleon users utilize JupyterHub to document and reproduce their complex CISE and networking experiments.
+
+- [Shared JupyterHub](https://jupyter.chameleoncloud.org): provides a common "workbench" environment for any Chameleon user.
+- [Trovi](https://www.chameleoncloud.org/experiment/share): a sharing portal of experiments, tutorials, and examples, which users can launch as a dedicated isolated environments on Chameleon's JupyterHub.
+
 ### Clemson University
 
 - Advanced Computing
-    - [Palmetto cluster and JupyterHub](http://citi.sites.clemson.edu/2016/08/18/JupyterHub-for-Palmetto-Cluster.html)
+  - [Palmetto cluster and JupyterHub](http://citi.sites.clemson.edu/2016/08/18/JupyterHub-for-Palmetto-Cluster.html)
 
 ### University of Colorado Boulder
 
 - (CU Research Computing) CURC
-    - [JupyterHub User Guide](https://www.rc.colorado.edu/support/user-guide/jupyterhub.html)
-        - Slurm job dispatched on Crestone compute cluster
-        - log troubleshooting
-        - Profiles in IPython Clusters tab
-    - [Parallel Processing with JupyterHub tutorial](https://www.rc.colorado.edu/support/examples-and-tutorials/parallel-processing-with-jupyterhub.html)
-    - [Parallel Programming with JupyterHub document](https://www.rc.colorado.edu/book/export/html/833)
+
+  - [JupyterHub User Guide](https://www.rc.colorado.edu/support/user-guide/jupyterhub.html)
+    - Slurm job dispatched on Crestone compute cluster
+    - log troubleshooting
+    - Profiles in IPython Clusters tab
+  - [Parallel Processing with JupyterHub tutorial](https://www.rc.colorado.edu/support/examples-and-tutorials/parallel-processing-with-jupyterhub.html)
+  - [Parallel Programming with JupyterHub document](https://www.rc.colorado.edu/book/export/html/833)
 
 - Earth Lab at CU
-    - [Tutorial on Parallel R on JupyterHub](https://earthdatascience.org/tutorials/parallel-r-on-jupyterhub/)
+  - [Tutorial on Parallel R on JupyterHub](https://earthdatascience.org/tutorials/parallel-r-on-jupyterhub/)
 
 ### George Washington University
 
@@ -112,7 +122,7 @@ easy to do with RStudio too.
 ### Paderborn University
 
 - [Data Science (DICE) group](https://dice.cs.uni-paderborn.de/)
-    - [nbgraderutils](https://github.com/dice-group/nbgraderutils): Use JupyterHub + nbgrader + iJava kernel for online Java exercises. Used in lecture Statistical Natural Language Processing.
+  - [nbgraderutils](https://github.com/dice-group/nbgraderutils): Use JupyterHub + nbgrader + iJava kernel for online Java exercises. Used in lecture Statistical Natural Language Processing.
 
 ### Penn State University
 
@@ -125,27 +135,28 @@ easy to do with RStudio too.
 ### University of California San Diego
 
 - San Diego Supercomputer Center - Andrea Zonca
-    - [Deploy JupyterHub on a Supercomputer with SSH](https://zonca.github.io/2017/05/jupyterhub-hpc-batchspawner-ssh.html)
-    - [Run Jupyterhub on a Supercomputer](https://zonca.github.io/2015/04/jupyterhub-hpc.html)
-    - [Deploy JupyterHub on a VM for a Workshop](https://zonca.github.io/2016/04/jupyterhub-sdsc-cloud.html)
-    - [Customize your Python environment in Jupyterhub](https://zonca.github.io/2017/02/customize-python-environment-jupyterhub.html)
-    - [Jupyterhub deployment on multiple nodes with Docker Swarm](https://zonca.github.io/2016/05/jupyterhub-docker-swarm.html)
-    - [Sample deployment of Jupyterhub in HPC on SDSC Comet](https://zonca.github.io/2017/02/sample-deployment-jupyterhub-hpc.html)
+
+  - [Deploy JupyterHub on a Supercomputer with SSH](https://zonca.github.io/2017/05/jupyterhub-hpc-batchspawner-ssh.html)
+  - [Run Jupyterhub on a Supercomputer](https://zonca.github.io/2015/04/jupyterhub-hpc.html)
+  - [Deploy JupyterHub on a VM for a Workshop](https://zonca.github.io/2016/04/jupyterhub-sdsc-cloud.html)
+  - [Customize your Python environment in Jupyterhub](https://zonca.github.io/2017/02/customize-python-environment-jupyterhub.html)
+  - [Jupyterhub deployment on multiple nodes with Docker Swarm](https://zonca.github.io/2016/05/jupyterhub-docker-swarm.html)
+  - [Sample deployment of Jupyterhub in HPC on SDSC Comet](https://zonca.github.io/2017/02/sample-deployment-jupyterhub-hpc.html)
 
 - Educational Technology Services - Paul Jamason
-    - [jupyterhub.ucsd.edu](https://jupyterhub.ucsd.edu)
+  - [jupyterhub.ucsd.edu](https://jupyterhub.ucsd.edu)
 
 ### TACC University of Texas
 
 ### Texas A&M
 
 - Kristen Thyng - Oceanography
-    - [Teaching with JupyterHub and nbgrader](http://kristenthyng.com/blog/2016/09/07/jupyterhub+nbgrader/)
+  - [Teaching with JupyterHub and nbgrader](http://kristenthyng.com/blog/2016/09/07/jupyterhub+nbgrader/)
 
 ### Elucidata
-  - What's new in Jupyter Notebooks @[Elucidata](https://elucidata.io/):
-      - Using Jupyter Notebooks with Jupyterhub on GCP, managed by GKE
-            - https://medium.com/elucidata/why-you-should-be-using-a-jupyter-notebook-8385a4ccd93d
+
+- What's new in Jupyter Notebooks @[Elucidata](https://elucidata.io/):
+  - Using Jupyter Notebooks with Jupyterhub on GCP, managed by GKE - https://medium.com/elucidata/why-you-should-be-using-a-jupyter-notebook-8385a4ccd93d
 
 ## Service Providers
 
@@ -175,7 +186,6 @@ easy to do with RStudio too.
 
 - [Deploying JupyterHub on Hadoop](https://jupyterhub-on-hadoop.readthedocs.io)
 
-
 ## Miscellaneous
 
 - https://medium.com/@ybarraud/setting-up-jupyterhub-with-sudospawner-and-anaconda-844628c0dbee#.rm3yt87e1

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

@@ -4,37 +4,44 @@ The default Authenticator uses [PAM][] to authenticate system users with
 their username and password. With the default Authenticator, any user
 with an account and password on the system will be allowed to login.
 
-## Create a whitelist of users
-
-You can restrict which users are allowed to login with a whitelist,
-`Authenticator.whitelist`:
+## Create a set of allowed users
 
+You can restrict which users are allowed to login with a set,
+`Authenticator.allowed_users`:
 
 ```python
-c.Authenticator.whitelist = {'mal', 'zoe', 'inara', 'kaylee'}
+c.Authenticator.allowed_users = {'mal', 'zoe', 'inara', 'kaylee'}
 ```
 
-Users in the whitelist are added to the Hub database when the Hub is
+Users in the `allowed_users` set are added to the Hub database when the Hub is
 started.
 
 ## Configure admins (`admin_users`)
 
+```{note}
+As of JupyterHub 2.0, the full permissions of `admin_users`
+should not be required.
+Instead, you can assign [roles][] to users or groups
+with only the scopes they require.
+```
+
 Admin users of JupyterHub, `admin_users`, can add and remove users from
-the user `whitelist`. `admin_users` can take actions on other users'
+the user `allowed_users` set. `admin_users` can take actions on other users'
 behalf, such as stopping and restarting their servers.
 
-A set of initial admin users, `admin_users` can configured be as follows:
+A set of initial admin users, `admin_users` can be configured as follows:
 
 ```python
 c.Authenticator.admin_users = {'mal', 'zoe'}
 ```
-Users in the admin list are automatically added to the user `whitelist`,
+
+Users in the admin set are automatically added to the user `allowed_users` set,
 if they are not already present.
 
 Each authenticator may have different ways of determining whether a user is an
-administrator. By default JupyterHub use the PAMAuthenticator which provide the
-`admin_groups` option and can determine administrator status base on a user
-groups. For example we can let any users in the `wheel` group be admin:
+administrator. By default JupyterHub uses the PAMAuthenticator which provides the
+`admin_groups` option and can set administrator status based on a user
+group. For example we can let any user in the `wheel` group be admin:
 
 ```python
 c.PAMAuthenticator.admin_groups = {'wheel'}
@@ -42,10 +49,10 @@ c.PAMAuthenticator.admin_groups = {'wheel'}
 
 ## Give admin access to other users' notebook servers (`admin_access`)
 
-Since the default `JupyterHub.admin_access` setting is False, the admins
+Since the default `JupyterHub.admin_access` setting is `False`, the admins
 do not have permission to log in to the single user notebook servers
-owned by *other users*. If `JupyterHub.admin_access` is set to True,
-then admins have permission to log in *as other users* on their
+owned by _other users_. If `JupyterHub.admin_access` is set to `True`,
+then admins have permission to log in _as other users_ on their
 respective machines, for debugging. **As a courtesy, you should make
 sure your users know if admin_access is enabled.**
 
@@ -53,12 +60,12 @@ sure your users know if admin_access is enabled.**
 
 Users can be added to and removed from the Hub via either the admin
 panel or the REST API. When a user is **added**, the user will be
-automatically added to the whitelist and database. Restarting the Hub
-will not require manually updating the whitelist in your config file,
+automatically added to the `allowed_users` set and database. Restarting the Hub
+will not require manually updating the `allowed_users` set in your config file,
 as the users will be loaded from the database.
 
 After starting the Hub once, it is not sufficient to **remove** a user
-from the whitelist in your config file. You must also remove the user
+from the allowed users set in your config file. You must also remove the user
 from the Hub's database, either by deleting the user from JupyterHub's
 admin page, or you can clear the `jupyterhub.sqlite` database and start
 fresh.
@@ -91,6 +98,7 @@ JupyterHub's [OAuthenticator][] currently supports the following
 popular services:
 
 - Auth0
+- Azure AD
 - Bitbucket
 - CILogon
 - GitHub
@@ -106,8 +114,8 @@ with any provider, is also available.
 
 ## Use DummyAuthenticator for testing
 
-The :class:`~jupyterhub.auth.DummyAuthenticator` is a simple authenticator that
-allows for any username/password unless if a global password has been set. If
+The `DummyAuthenticator` is a simple authenticator that
+allows for any username/password unless a global password has been set. If
 set, it will allow for any username as long as the correct password is provided.
 To set a global password, add this to the config file:
 
@@ -115,5 +123,5 @@ To set a global password, add this to the config file:
 c.DummyAuthenticator.password = "some_password"
 ```
 
-[PAM]: https://en.wikipedia.org/wiki/Pluggable_authentication_module
-[OAuthenticator]: https://github.com/jupyterhub/oauthenticator
+[pam]: https://en.wikipedia.org/wiki/Pluggable_authentication_module
+[oauthenticator]: https://github.com/jupyterhub/oauthenticator

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

@@ -44,7 +44,7 @@ jupyterhub -f /etc/jupyterhub/jupyterhub_config.py
 ```
 
 The IPython documentation provides additional information on the
-[config system](http://ipython.readthedocs.io/en/stable/development/config)
+[config system](http://ipython.readthedocs.io/en/stable/development/config.html)
 that Jupyter uses.
 
 ## Configure using command line options
@@ -56,18 +56,18 @@ To display all command line options that are available for configuration:
 ```
 
 Configuration using the command line options is done when launching JupyterHub.
-For example, to start JupyterHub on ``10.0.1.2:443`` with https, you
+For example, to start JupyterHub on `10.0.1.2:443` with https, you
 would enter:
 
 ```bash
     jupyterhub --ip 10.0.1.2 --port 443 --ssl-key my_ssl.key --ssl-cert my_ssl.cert
 ```
 
-All configurable options may technically be set on the command-line,
+All configurable options may technically be set on the command line,
 though some are inconvenient to type. To set a particular configuration
 parameter, `c.Class.trait`, you would use the command line option,
 `--Class.trait`, when starting JupyterHub. For example, to configure the
-`c.Spawner.notebook_dir` trait from the command-line, use the
+`c.Spawner.notebook_dir` trait from the command line, use the
 `--Spawner.notebook_dir` option:
 
 ```bash
@@ -88,13 +88,13 @@ meant as illustration, are:
 
 ## Run the proxy separately
 
-This is *not* strictly necessary, but useful in many cases.  If you
-use a custom proxy (e.g. Traefik), this also not needed.
+This is _not_ strictly necessary, but useful in many cases. If you
+use a custom proxy (e.g. Traefik), this is also not needed.
 
-Connections to user servers go through the proxy, and *not* the hub
-itself.  If the proxy stays running when the hub restarts (for
-maintenance, re-configuration, etc.), then use connections are not
-interrupted.  For simplicity, by default the hub starts the proxy
+Connections to user servers go through the proxy, and _not_ the hub
+itself. If the proxy stays running when the hub restarts (for
+maintenance, re-configuration, etc.), then user connections are not
+interrupted. For simplicity, by default the hub starts the proxy
 automatically, so if the hub restarts, the proxy restarts, and user
-connections are interrupted.  It is easy to run the proxy separately,
+connections are interrupted. It is easy to run the proxy separately,
 for information see [the separate proxy page](../reference/separate-proxy).

docs/source/getting-started/faq.md

@@ -0,0 +1,35 @@
+# 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

@@ -15,4 +15,5 @@ own JupyterHub.
    authenticators-users-basics
    spawners-basics
    services-basics
+   faq
    institutional-faq

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

@@ -11,30 +11,30 @@ 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 customizable
+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?
 
 Here is a quick breakdown of these three tools:
 
-* **The Jupyter Notebook** is a document specification (the `.ipynb`) file that interweaves
+- **The Jupyter Notebook** is a document specification (the `.ipynb`) file that interweaves
   narrative text with code cells and their outputs. It is also a graphical interface
   that allows users to edit these documents. There are also several other graphical interfaces
-  that allow users to edit the `.ipynb` format (nteract, Jupyer Lab, Google Colab, Kaggle, etc).
-* **JupyterLab** is a flexible and extendible user interface for interactive computing. It
+  that allow users to edit the `.ipynb` format (nteract, Jupyter Lab, Google Colab, Kaggle, etc).
+- **JupyterLab** is a flexible and extendible user interface for interactive computing. It
   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**.
+- **JupyterHub** is an application that manages interactive computing sessions for **multiple users**.
   It also connects them with infrastructure those users wish to access. It can provide
-  remote access to Jupyter Notebooks and Jupyter Lab for many people.
+  remote access to Jupyter Notebooks and JupyterLab for many people.
 
 ## For management
 
 ### Briefly, what problem does JupyterHub solve for us?
 
 JupyterHub provides a shared platform for data science and collaboration.
-It allows users to utilize familiar data science workflows (such as the scientific python stack,
+It allows users to utilize familiar data science workflows (such as the scientific Python stack,
 the R tidyverse, and Jupyter Notebooks) on institutional infrastructure. It also allows administrators
 some control over access to resources, security, environments, and authentication.
 
@@ -50,20 +50,20 @@ scalable infrastructure, large datasets, and high-performance computing.
 JupyterHub is used at a variety of institutions in academia,
 industry, and government research labs. It is most-commonly used by two kinds of groups:
 
-* Small teams (e.g., data science teams, research labs, or collaborative projects) to provide a
+- Small teams (e.g., data science teams, research labs, or collaborative projects) to provide a
   shared resource for interactive computing, collaboration, and analytics.
-* Large teams (e.g., a department, a large class, or a large group of remote users) to provide
+- Large teams (e.g., a department, a large class, or a large group of remote users) to provide
   access to organizational hardware, data, and analytics environments at scale.
 
-Here are a sample of organizations that use JupyterHub:
+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,
+- **Universities and colleges**: UC Berkeley, UC San Diego, Cal Poly SLO, Harvard University, University of Chicago,
   University of Oslo, University of Sheffield, Université Paris Sud, University of Versailles
-* **Research laboratories**: NASA, NCAR, NOAA, the Large Synoptic Survey Telescope, Brookhaven National Lab,
+- **Research laboratories**: NASA, NCAR, NOAA, the Large Synoptic Survey Telescope, Brookhaven National Lab,
   Minnesota Supercomputing Institute, ALCF, CERN, Lawrence Livermore National Laboratory
-* **Online communities**: Pangeo, Quantopian, mybinder.org, MathHub, Open Humans
-* **Computing infrastructure providers**: NERSC, San Diego Supercomputing Center, Compute Canada
-* **Companies**: Capital One, SANDVIK code, Globus
+- **Online communities**: Pangeo, Quantopian, mybinder.org, MathHub, Open Humans
+- **Computing infrastructure providers**: NERSC, San Diego Supercomputing Center, Compute Canada
+- **Companies**: Capital One, SANDVIK code, Globus
 
 See the [Gallery of JupyterHub deployments](../gallery-jhub-deployments.md) for
 a more complete list of JupyterHub deployments at institutions.
@@ -95,14 +95,13 @@ The most common way to set up a JupyterHub is to use a JupyterHub distribution,
 and opinionated ways to set up a JupyterHub on particular kinds of infrastructure. The two distributions
 that we currently suggest are:
 
-* [Zero to JupyterHub for Kubernetes](https://z2jh.jupyter.org) is a scalable JupyterHub deployment and
+- [Zero to JupyterHub for Kubernetes](https://z2jh.jupyter.org) is a scalable JupyterHub deployment and
   guide that runs on Kubernetes. Better for larger or dynamic user groups (50-10,000) or more complex
   compute/data needs.
-* [The Littlest JupyterHub](https://tljh.jupyter.org) is a lightweight JupyterHub that runs on a single
-  single machine (in the cloud or under your desk). Better for smaller usergroups (4-80) or more
+- [The Littlest JupyterHub](https://tljh.jupyter.org) is a lightweight JupyterHub that runs on a single
+  single machine (in the cloud or under your desk). Better for smaller 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.
@@ -123,9 +122,9 @@ The short answer: yes. JupyterHub as a standalone application has been battle-te
 level for several years, and makes a number of "default" security decisions that are reasonable for most
 users.
 
-* For security considerations in the base JupyterHub application,
-  [see the JupyterHub security page](https://jupyterhub.readthedocs.io/en/stable/reference/websecurity.html)
-* For security considerations when deploying JupyterHub on Kubernetes, see the
+- For security considerations in the base JupyterHub application,
+  [see the JupyterHub security page](https://jupyterhub.readthedocs.io/en/stable/reference/websecurity.html).
+- For security considerations when deploying JupyterHub on Kubernetes, see the
   [JupyterHub on Kubernetes security page](https://zero-to-jupyterhub.readthedocs.io/en/latest/security.html).
 
 The longer answer: it depends on your deployment. Because JupyterHub is very flexible, it can be used
@@ -137,15 +136,13 @@ If you are worried about security, don't hesitate to reach out to the JupyterHub
 [Jupyter Community Forum](https://discourse.jupyter.org/c/jupyterhub). This community of practice has many
 individuals with experience running secure JupyterHub deployments.
 
-
 ### Does JupyterHub provide computing or data infrastructure?
 
-No - JupyterHub manages user sessions and can *control* computing infrastructure, but it does not provide these
+No - JupyterHub manages user sessions and can _control_ computing infrastructure, but it does not provide these
 things itself. You are expected to run JupyterHub on your own infrastructure (local or in the cloud). Moreover,
 JupyterHub has no internal concept of "data", but is designed to be able to communicate with data repositories
 (again, either locally or remotely) for use within interactive computing sessions.
 
-
 ### How do I manage users?
 
 JupyterHub offers a few options for managing your users. Upon setting up a JupyterHub, you can choose what
@@ -154,7 +151,7 @@ email address, or choose a username / password when they first log-in, or offloa
 another service such as an organization's OAuth.
 
 The users of a JupyterHub are stored locally, and can be modified manually by an administrator of the JupyterHub.
-Moreover, the *active* users on a JupyterHub can be found on the administrator's page. This page
+Moreover, the _active_ users on a JupyterHub can be found on the administrator's page. This page
 gives you the abiltiy to stop or restart kernels, inspect user filesystems, and even take over user
 sessions to assist them with debugging.
 
@@ -182,12 +179,11 @@ connect with other infrastructure tools (like Dask or Spark). This allows users
 scalable or high-performance resources from within their JupyterHub sessions. The logic of
 how those resources are controlled is taken care of by the non-JupyterHub application.
 
-
 ### Can JupyterHub be used with my high-performance computing resources?
 
 Yes - JupyterHub can provide access to many kinds of computing infrastructure.
 Especially when combined with other open-source schedulers such as Dask, you can manage fairly
-complex computing infrastructure from the interactive sessions of a JupyterHub. For example
+complex computing infrastructures from the interactive sessions of a JupyterHub. For example
 [see the Dask HPC page](https://docs.dask.org/en/latest/setup/hpc.html).
 
 ### How much resources do user sessions take?
@@ -196,7 +192,7 @@ This is highly configurable by the administrator. If you wish for your users to
 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
-resources available on user machines, or connect them with computing infrastructure elsewhere.
+resources available on user machines, or connect them with computing infrastructures elsewhere.
 
 ### Can I customize the look and feel of a JupyterHub?
 
@@ -218,16 +214,14 @@ the technologies your JupyterHub will use (e.g., dev-ops knowledge with cloud co
 In general, the base JupyterHub deployment is not the bottleneck for setup, it is connecting
 your JupyterHub with the various services and tools that you wish to provide to your users.
 
-
 ### How well does JupyterHub scale? What are JupyterHub's limitations?
 
 JupyterHub works well at both a small scale (e.g., a single VM or machine) as well as a
-high scale (e.g., a scalable Kubernetes cluster). It can be used for teams as small a 2, and
+high scale (e.g., a scalable Kubernetes cluster). It can be used for teams as small as 2, and
 for user bases as large as 10,000. The scalability of JupyterHub largely depends on the
 infrastructure on which it is deployed. JupyterHub has been designed to be lightweight and
 flexible, so you can tailor your JupyterHub deployment to your needs.
 
-
 ### Is JupyterHub resilient? What happens when a machine goes down?
 
 For JupyterHubs that are deployed in a containerized environment (e.g., Kubernetes), it is
@@ -255,7 +249,7 @@ share their results with one another.
 
 JupyterHub also provides a computational framework to share computational narratives between
 different levels of an organization. For example, data scientists can share Jupyter Notebooks
-rendered as [voila dashboards](https://voila.readthedocs.io/en/stable/) with those who are not
+rendered as [Voilà dashboards](https://voila.readthedocs.io/en/stable/) with those who are not
 familiar with programming, or create publicly-available interactive analyses to allow others to
 interact with your work.
 

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

@@ -11,7 +11,7 @@ This section will help you with basic proxy and network configuration to:
 
 The Proxy's main IP address setting determines where JupyterHub is available to users.
 By default, JupyterHub is configured to be available on all network interfaces
-(`''`) on port 8000. *Note*: Use of `'*'` is discouraged for IP configuration;
+(`''`) on port 8000. _Note_: Use of `'*'` is discouraged for IP configuration;
 instead, use of `'0.0.0.0'` is preferred.
 
 Changing the Proxy's main IP address and port can be done with the following
@@ -43,7 +43,7 @@ port.
 
 By default, this REST API listens on port 8001 of `localhost` only.
 The Hub service talks to the proxy via a REST API on a secondary port. The
-API URL can be configured separately and override the default settings.
+API URL can be configured separately to override the default settings.
 
 ### Set api_url
 
@@ -74,7 +74,7 @@ The Hub service listens only on `localhost` (port 8081) by default.
 The Hub needs to be accessible from both the proxy and all Spawners.
 When spawning local servers, an IP address setting of `localhost` is fine.
 
-If *either* the Proxy *or* (more likely) the Spawners will be remote or
+If _either_ the Proxy _or_ (more likely) the Spawners will be remote or
 isolated in containers, the Hub must listen on an IP that is accessible.
 
 ```python
@@ -82,20 +82,20 @@ c.JupyterHub.hub_ip = '10.0.1.4'
 c.JupyterHub.hub_port = 54321
 ```
 
-**Added in 0.8:** The `c.JupyterHub.hub_connect_ip` setting is the ip address or
+**Added in 0.8:** The `c.JupyterHub.hub_connect_ip` setting is the IP address or
 hostname that other services should use to connect to the Hub. A common
 configuration for, e.g. docker, is:
 
 ```python
 c.JupyterHub.hub_ip = '0.0.0.0'  # listen on all interfaces
-c.JupyterHub.hub_connect_ip = '10.0.1.4'  # ip as seen on the docker network. Can also be a hostname.
+c.JupyterHub.hub_connect_ip = '10.0.1.4'  # IP as seen on the docker network. Can also be a hostname.
 ```
 
 ## Adjusting the hub's URL
 
-The hub will most commonly be running on a hostname of its own.  If it
+The hub will most commonly be running on a hostname of its own. If it
 is not – for example, if the hub is being reverse-proxied and being
 exposed at a URL such as `https://proxy.example.org/jupyter/` – then
-you will need to tell JupyterHub the base URL of the service.  In such
+you will need to tell JupyterHub the base URL of the service. In such
 a case, it is both necessary and sufficient to set
 `c.JupyterHub.base_url = '/jupyter/'` in the configuration.

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

@@ -80,6 +80,49 @@ 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
@@ -146,41 +189,73 @@ itself, ``jupyterhub_config.py``, as a binary string:
    If the cookie secret value changes for the Hub, all single-user notebook
    servers must also be restarted.
 
+.. _cookies:
 
-.. _authentication-token:
+Cookies used by JupyterHub authentication
+-----------------------------------------
 
-Proxy authentication token
---------------------------
+The following cookies are used by the Hub for handling user authentication.
 
-The Hub authenticates its requests to the Proxy using a secret token that
-the Hub and Proxy agree upon. The value of this string should be a random
-string (for example, generated by ``openssl rand -hex 32``).
+This section was created based on this post_ from Discourse.
 
-Generating and storing token in the configuration file
-~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+.. _post: https://discourse.jupyter.org/t/how-to-force-re-login-for-users/1998/6
 
-Or you can set the value in the configuration file, ``jupyterhub_config.py``:
+jupyterhub-hub-login
+~~~~~~~~~~~~~~~~~~~~
 
-.. code-block:: python
+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.
 
-    c.JupyterHub.proxy_auth_token = '0bc02bede919e99a26de1e2a7a5aadfaf6228de836ec39a05a6c6942831d8fe5'
+Resetting the Hub cookie secret effectively revokes this cookie.
 
-Generating and storing as an environment variable
-~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+This cookie is restricted to the path ``/hub/``.
 
-You can pass this value of the proxy authentication token to the Hub and Proxy
-using the ``CONFIGPROXY_AUTH_TOKEN`` environment variable:
+jupyterhub-user-<username>
+~~~~~~~~~~~~~~~~~~~~~~~~~~
 
-.. code-block:: bash
+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.
 
-    export CONFIGPROXY_AUTH_TOKEN=$(openssl rand -hex 32)
+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.
 
-This environment variable needs to be visible to the Hub and Proxy.
+Each OAuth access token is associated with a session id (see ``jupyterhub-session-id`` section
+below).
 
-Default if token is not set
-~~~~~~~~~~~~~~~~~~~~~~~~~~~
+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.
 
-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).
+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/getting-started/services-basics.md

@@ -2,10 +2,10 @@
 
 When working with JupyterHub, a **Service** is defined as a process
 that interacts with the Hub's REST API. A Service may perform a specific
-or action or task. For example, shutting down individuals' single user
+action or task. For example, shutting down individuals' single user
 notebook servers that have been idle for some time is a good example of
 a task that could be automated by a Service. Let's look at how the
-[cull_idle_servers][] script can be used as a Service.
+[jupyterhub_idle_culler][] script can be used as a Service.
 
 ## Real-world example to cull idle servers
 
@@ -15,11 +15,11 @@ document will:
 - explain some basic information about API tokens
 - clarify that API tokens can be used to authenticate to
   single-user servers as of [version 0.8.0](../changelog)
-- show how the [cull_idle_servers][] script can be:
-    - used in a Hub-managed service
-    - run as a standalone script
+- show how the [jupyterhub_idle_culler][] script can be:
+  - used in a Hub-managed service
+  - run as a standalone script
 
-Both examples for `cull_idle_servers` will communicate tasks to the
+Both examples for `jupyterhub_idle_culler` will communicate tasks to the
 Hub via the REST API.
 
 ## API Token basics
@@ -78,44 +78,73 @@ single-user servers, and only cookies can be used for authentication.
 0.8 supports using JupyterHub API tokens to authenticate to single-user
 servers.
 
-## Configure `cull-idle` to run as a Hub-Managed Service
+## Configure the idle culler to run as a Hub-Managed Service
+
+Install the idle culler:
+
+```
+pip install jupyterhub-idle-culler
+```
 
 In `jupyterhub_config.py`, add the following dictionary for the
-`cull-idle` Service to the `c.JupyterHub.services` list:
+`idle-culler` Service to the `c.JupyterHub.services` list:
 
 ```python
 c.JupyterHub.services = [
     {
-        'name': 'cull-idle',
-        'admin': True,
-        'command': [sys.executable, 'cull_idle_servers.py', '--timeout=3600'],
+        'name': 'idle-culler',
+        'command': [sys.executable, '-m', 'jupyterhub_idle_culler', '--timeout=3600'],
+    }
+]
+
+c.JupyterHub.load_roles = [
+    {
+        "name": "list-and-cull", # name the role
+        "services": [
+            "idle-culler", # assign the service to this role
+        ],
+        "scopes": [
+            # declare what permissions the service should have
+            "list:users", # list users
+            "read:users:activity", # read user last-activity
+            "admin:servers", # start/stop servers
+        ],
     }
 ]
 ```
 
 where:
 
-- `'admin': True` indicates that the Service has 'admin' permissions, and
-- `'command'` indicates that the Service will be launched as a
+- `command` indicates that the Service will be launched as a
   subprocess, managed by the Hub.
 
+```{versionchanged} 2.0
+Prior to 2.0, the idle-culler required 'admin' permissions.
+It now needs the scopes:
+
+- `list:users` to access the user list endpoint
+- `read:users:activity` to read activity info
+- `admin:servers` to start/stop servers
+```
+
 ## Run `cull-idle` manually as a standalone script
 
-Now you can run your script, i.e. `cull_idle_servers`, by providing it
+Now you can run your script by providing it
 the API token and it will authenticate through the REST API to
 interact with it.
 
-This will run `cull-idle` manually. `cull-idle` can be run as a standalone
+This will run the idle culler service manually. It can be run as a standalone
 script anywhere with access to the Hub, and will periodically check for idle
 servers and shut them down via the Hub's REST API. In order to shutdown the
-servers, the token given to cull-idle must have admin privileges.
+servers, the token given to `cull-idle` must have permission to list users
+and admin their servers.
 
 Generate an API token and store it in the `JUPYTERHUB_API_TOKEN` environment
-variable. Run `cull_idle_servers.py` manually.
+variable. Run `jupyterhub_idle_culler` manually.
 
 ```bash
     export JUPYTERHUB_API_TOKEN='token'
-    python3 cull_idle_servers.py [--timeout=900] [--url=http://127.0.0.1:8081/hub/api]
+    python -m jupyterhub_idle_culler [--timeout=900] [--url=http://127.0.0.1:8081/hub/api]
 ```
 
-[cull_idle_servers]: https://github.com/jupyterhub/jupyterhub/blob/master/examples/cull-idle/cull_idle_servers.py
+[jupyterhub_idle_culler]: https://github.com/jupyterhub/jupyterhub-idle-culler

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

@@ -1,8 +1,8 @@
 # Spawners and single-user notebook servers
 
 Since the single-user server is an instance of `jupyter notebook`, an entire separate
-multi-process application, there are many aspect of that server can configure, and a lot of ways
-to express that configuration.
+multi-process application, there are many aspects of that server that can be configured, and a lot
+of ways to express that configuration.
 
 At the JupyterHub level, you can set some values on the Spawner. The simplest of these is
 `Spawner.notebook_dir`, which lets you set the root directory for a user's server. This root
@@ -14,7 +14,7 @@ expanded to the user's home directory.
 c.Spawner.notebook_dir = '~/notebooks'
 ```
 
-You can also specify extra command-line arguments to the notebook server with:
+You can also specify extra command line arguments to the notebook server with:
 
 ```python
 c.Spawner.args = ['--debug', '--profile=PHYS131']

docs/source/index.rst

@@ -3,11 +3,11 @@ JupyterHub
 ==========
 
 `JupyterHub`_ is the best way to serve `Jupyter notebook`_ for multiple users.
-It can be used in a classes of students, a corporate data science group or scientific
+It can be used in a class of students, a corporate data science group or scientific
 research group. It is a multi-user **Hub** that spawns, manages, and proxies multiple
 instances of the single-user `Jupyter notebook`_ server.
 
-To make life easier, JupyterHub have distributions. Be sure to
+To make life easier, JupyterHub has distributions. Be sure to
 take a look at them before continuing with the configuration of the broad
 original system of `JupyterHub`_. Today, you can find two main cases:
 
@@ -108,6 +108,14 @@ API Reference
 
    api/index
 
+RBAC Reference
+--------------
+
+.. toctree::
+   :maxdepth: 2
+
+   rbac/index
+
 Contributing
 ------------
 
@@ -115,8 +123,8 @@ We want you to contribute to JupyterHub in ways that are most exciting
 & useful to you. We value documentation, testing, bug reporting & code equally,
 and are glad to have your contributions in whatever form you wish :)
 
-Our `Code of Conduct <https://github.com/jupyter/governance/blob/master/conduct/code_of_conduct.md>`_
-(`reporting guidelines <https://github.com/jupyter/governance/blob/master/conduct/reporting_online.md>`_)
+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::
@@ -147,4 +155,4 @@ Questions? Suggestions?
 
 .. _JupyterHub: https://github.com/jupyterhub/jupyterhub
 .. _Jupyter notebook: https://jupyter-notebook.readthedocs.io/en/latest/
-.. _REST API: http://petstore.swagger.io/?url=https://raw.githubusercontent.com/jupyterhub/jupyterhub/master/docs/rest-api.yml#!/default
+.. _REST API: https://petstore3.swagger.io/?url=https://raw.githubusercontent.com/jupyterhub/jupyterhub/HEAD/docs/rest-api.yml#!/default

docs/source/installation-guide-hard.rst

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

docs/source/quickstart.md

@@ -12,20 +12,24 @@ Before installing JupyterHub, you will need:
 - [nodejs/npm](https://www.npmjs.com/). [Install nodejs/npm](https://docs.npmjs.com/getting-started/installing-node),
   using your operating system's package manager.
 
-  * If you are using **`conda`**, the nodejs and npm dependencies will be installed for
+  - If you are using **`conda`**, the nodejs and npm dependencies will be installed for
     you by conda.
 
-  * If you are using **`pip`**, install a recent version of
+  - If you are using **`pip`**, install a recent version of
     [nodejs/npm](https://docs.npmjs.com/getting-started/installing-node).
     For example, install it on Linux (Debian/Ubuntu) using:
 
     ```
     sudo apt-get install npm nodejs-legacy
     ```
-          
+
     The `nodejs-legacy` package installs the `node` executable and is currently
     required for npm to work on Debian/Ubuntu.
 
+- A [pluggable authentication module (PAM)](https://en.wikipedia.org/wiki/Pluggable_authentication_module)
+  to use the [default Authenticator](./getting-started/authenticators-users-basics.md).
+  PAM is often available by default on most distributions, if this is not the case it can be installed by
+  using the operating system's package manager.
 - TLS certificate and key for HTTPS communication
 - Domain name
 
@@ -74,12 +78,12 @@ Visit `https://localhost:8000` in your browser, and sign in with your unix
 credentials.
 
 To **allow multiple users to sign in** to the Hub server, you must start
-`jupyterhub` as a *privileged user*, such as root:
+`jupyterhub` as a _privileged user_, such as root:
 
 ```bash
 sudo jupyterhub
 ```
 
 The [wiki](https://github.com/jupyterhub/jupyterhub/wiki/Using-sudo-to-run-JupyterHub-without-root-privileges)
-describes how to run the server as a *less privileged user*. This requires
+describes how to run the server as a _less privileged user_. This requires
 additional configuration of the system.

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

@@ -0,0 +1,126 @@
+import os
+from collections import defaultdict
+from pathlib import Path
+
+from pytablewriter import MarkdownTableWriter
+from ruamel.yaml import YAML
+
+from jupyterhub.scopes import scope_definitions
+
+HERE = os.path.abspath(os.path.dirname(__file__))
+PARENT = Path(HERE).parent.parent.absolute()
+
+
+class ScopeTableGenerator:
+    def __init__(self):
+        self.scopes = scope_definitions
+
+    @classmethod
+    def create_writer(cls, table_name, headers, values):
+        writer = MarkdownTableWriter()
+        writer.table_name = table_name
+        writer.headers = headers
+        writer.value_matrix = values
+        writer.margin = 1
+        return writer
+
+    def _get_scope_relationships(self):
+        """Returns a tuple of dictionary of all scope-subscope pairs and a list of just subscopes:
+
+        ({scope: subscope}, [subscopes])
+
+        used for creating hierarchical scope table in _parse_scopes()
+        """
+        pairs = []
+        for scope, data in self.scopes.items():
+            subscopes = data.get('subscopes')
+            if subscopes is not None:
+                for subscope in subscopes:
+                    pairs.append((scope, subscope))
+            else:
+                pairs.append((scope, None))
+        subscopes = [pair[1] for pair in pairs]
+        pairs_dict = defaultdict(list)
+        for scope, subscope in pairs:
+            pairs_dict[scope].append(subscope)
+        return pairs_dict, subscopes
+
+    def _get_top_scopes(self, subscopes):
+        """Returns a list of highest level scopes
+        (not a subscope of any other scopes)"""
+        top_scopes = []
+        for scope in self.scopes.keys():
+            if scope not in subscopes:
+                top_scopes.append(scope)
+        return top_scopes
+
+    def _parse_scopes(self):
+        """Returns a list of table rows where row:
+        [indented scopename string, scope description string]"""
+        scope_pairs, subscopes = self._get_scope_relationships()
+        top_scopes = self._get_top_scopes(subscopes)
+
+        table_rows = []
+        md_indent = "   "
+
+        def _add_subscopes(table_rows, scopename, depth=0):
+            description = self.scopes[scopename]['description']
+            doc_description = self.scopes[scopename].get('doc_description', '')
+            if doc_description:
+                description = doc_description
+            table_row = [f"{md_indent * depth}`{scopename}`", description]
+            table_rows.append(table_row)
+            for subscope in scope_pairs[scopename]:
+                if subscope:
+                    _add_subscopes(table_rows, subscope, depth + 1)
+
+        for scope in top_scopes:
+            _add_subscopes(table_rows, scope)
+
+        return table_rows
+
+    def write_table(self):
+        """Generates the scope table in markdown format and writes it into `scope-table.md`"""
+        filename = f"{HERE}/scope-table.md"
+        table_name = ""
+        headers = ["Scope", "Grants permission to:"]
+        values = self._parse_scopes()
+        writer = self.create_writer(table_name, headers, values)
+
+        title = "Table 1. Available scopes and their hierarchy"
+        content = f"{title}\n{writer.dumps()}"
+        with open(filename, 'w') as f:
+            f.write(content)
+        print(f"Generated {filename}.")
+        print(
+            "Run 'make clean' before 'make html' to ensure the built scopes.html contains latest scope table changes."
+        )
+
+    def write_api(self):
+        """Generates the API description in markdown format and writes it into `rest-api.yml`"""
+        filename = f"{PARENT}/rest-api.yml"
+        yaml = YAML(typ='rt')
+        yaml.preserve_quotes = True
+        scope_dict = {}
+        with open(filename, 'r+') as f:
+            content = yaml.load(f.read())
+            f.seek(0)
+            for scope in self.scopes:
+                description = self.scopes[scope]['description']
+                doc_description = self.scopes[scope].get('doc_description', '')
+                if doc_description:
+                    description = doc_description
+                scope_dict[scope] = description
+            content['securityDefinitions']['oauth2']['scopes'] = scope_dict
+            yaml.dump(content, f)
+            f.truncate()
+
+
+def main():
+    table_generator = ScopeTableGenerator()
+    table_generator.write_table()
+    table_generator.write_api()
+
+
+if __name__ == "__main__":
+    main()

docs/source/rbac/index.md

@@ -0,0 +1,37 @@
+# JupyterHub RBAC
+
+Role Based Access Control (RBAC) in JupyterHub serves to provide fine grained control of access to Jupyterhub's API resources.
+
+RBAC is new in JupyterHub 2.0.
+
+## Motivation
+
+The JupyterHub API requires authorization to access its APIs.
+This ensures that an arbitrary user, or even an unauthenticated third party, are not allowed to perform such actions.
+For instance, the behaviour prior to adoption of RBAC is that creating or deleting users requires _admin rights_.
+
+The prior system is functional, but lacks flexibility. If your Hub serves a number of users in different groups, you might want to delegate permissions to other users or automate certain processes.
+Prior to RBAC, appointing a 'group-only admin' or a bot that culls idle servers, requires granting full admin rights to all actions. This poses a risk of the user or service intentionally or unintentionally accessing and modifying any data within the Hub and violates the [principle of least privilege](https://en.wikipedia.org/wiki/Principle_of_least_privilege).
+
+To remedy situations like this, JupyterHub is transitioning to an RBAC system. By equipping users, groups and services with _roles_ that supply them with a collection of permissions (_scopes_), administrators are able to fine-tune which parties are granted access to which resources.
+
+## Definitions
+
+**Scopes** are specific permissions used to evaluate API requests. For example: the API endpoint `users/servers`, which enables starting or stopping user servers, is guarded by the scope `servers`.
+
+Scopes are not directly assigned to requesters. Rather, when a client performs an API call, their access will be evaluated based on their assigned roles.
+
+**Roles** are collections of scopes that specify the level of what a client is allowed to do. For example, a group administrator may be granted permission to control the servers of group members, but not to create, modify or delete group members themselves.
+Within the RBAC framework, this is achieved by assigning a role to the administrator that covers exactly those privileges.
+
+## Technical Overview
+
+```{toctree}
+:maxdepth: 2
+
+roles
+scopes
+use-cases
+tech-implementation
+upgrade
+```

docs/source/rbac/roles.md

@@ -0,0 +1,162 @@
+(roles)=
+
+# Roles
+
+JupyterHub provides four roles that are available by default:
+
+```{admonition} **Default roles**
+- `user` role provides a {ref}`default user scope <default-user-scope-target>` `self` that grants access to the user's own resources.
+- `admin` role contains all available scopes and grants full rights to all actions. This role **cannot be edited**.
+- `token` role provides a {ref}`default token scope <default-token-scope-target>` `all` that resolves to the same permissions as the owner of the token has.
+- `server` role allows for posting activity of "itself" only.
+
+**These roles cannot be deleted.**
+```
+
+These default roles have a default collection of scopes,
+but you can define the scopes associated with each role (excluding admin) to suit your needs,
+as seen [below](overriding-default-roles).
+
+The `user`, `admin`, and `token` roles by default all preserve the permissions prior to RBAC.
+Only the `server` role is changed from pre-2.0, to reduce its permissions to activity-only
+instead of the default of a full access token.
+
+Additional custom roles can also be defined (see {ref}`define-role-target`).
+Roles can be assigned to the following entities:
+
+- Users
+- Services
+- Groups
+- Tokens
+
+An entity can have zero, one, or multiple roles, and there are no restrictions on which roles can be assigned to which entity. Roles can be added to or removed from entities at any time.
+
+**Users** \
+When a new user gets created, they are assigned their default role `user`. Additionaly, if the user is created with admin privileges (via `c.Authenticator.admin_users` in `jupyterhub_config.py` or `admin: true` via API), they will be also granted `admin` role. If existing user's admin status changes via API or `jupyterhub_config.py`, their default role will be updated accordingly (after next startup for the latter).
+
+**Services** \
+Services do not have a default role. Services without roles have no access to the guarded API end-points, so most services will require assignment of a role in order to function.
+
+**Groups** \
+A group does not require any role, and has no roles by default. If a user is a member of a group, they automatically inherit any of the group's permissions (see {ref}`resolving-roles-scopes-target` for more details). This is useful for assigning a set of common permissions to several users.
+
+**Tokens** \
+A token’s permissions are evaluated based on their owning entity. Since a token is always issued for a user or service, it can never have more permissions than its owner. If no specific role is requested for a new token, the token is assigned the `token` role.
+
+(define-role-target)=
+
+## Defining Roles
+
+Roles can be defined or modified in the configuration file as a list of dictionaries. An example:
+
+% TODO: think about loading users into roles if membership has been changed via API.
+% What should be the result?
+
+```python
+# in jupyterhub_config.py
+
+c.JupyterHub.load_roles = [
+ {
+   'name': 'server-rights',
+   'description': 'Allows parties to start and stop user servers',
+   'scopes': ['servers'],
+   'users': ['alice', 'bob'],
+   'services': ['idle-culler'],
+   'groups': ['admin-group'],
+ }
+]
+```
+
+The role `server-rights` now allows the starting and stopping of servers by any of the following:
+
+- users `alice` and `bob`
+- the service `idle-culler`
+- any member of the `admin-group`.
+
+```{attention}
+Tokens cannot be assigned roles through role definition but may be assigned specific roles when requested via API (see {ref}`requesting-api-token-target`).
+```
+
+Another example:
+
+```python
+# in jupyterhub_config.py
+
+c.JupyterHub.load_roles = [
+ {
+   'description': 'Read-only user models',
+   'name': 'reader',
+   'scopes': ['read:users'],
+   'services': ['external'],
+   'users': ['maria', 'joe']
+ }
+]
+```
+
+The role `reader` allows users `maria` and `joe` and service `external` to read (but not modify) any user’s model.
+
+```{admonition} Requirements
+:class: warning
+In a role definition, the `name` field is required, while all other fields are optional.\
+**Role names must:**
+- be 3 - 255 characters
+- use ascii lowercase, numbers, 'unreserved' URL punctuation `-_.~`
+- start with a letter
+- end with letter or number.
+
+`users`, `services`, and `groups` only accept objects that already exist in the database or are defined previously in the file.
+It is not possible to implicitly add a new user to the database by defining a new role.
+```
+
+If no scopes are defined for _new role_, JupyterHub will raise a warning. Providing non-existing scopes will result in an error.
+
+In case the role with a certain name already exists in the database, its definition and scopes will be overwritten. This holds true for all roles except the `admin` role, which cannot be overwritten; an error will be raised if trying to do so. All the role bearers permissions present in the definition will change accordingly.
+
+(overriding-default-roles)=
+
+### Overriding default roles
+
+Role definitions can include those of the "default" roles listed above (admin excluded),
+if the default scopes associated with those roles do not suit your deployment.
+For example, to specify what permissions the $JUPYTERHUB_API_TOKEN issued to all single-user servers
+has,
+define the `server` role.
+
+To restore the JupyterHub 1.x behavior of servers being able to do anything their owners can do,
+use the scope `all`:
+
+```python
+c.JupyterHub.load_roles = [
+ {
+   'name': 'server',
+   'scopes': ['all'],
+ }
+]
+```
+
+or, better yet, identify the specific [scopes][] you want server environments to have access to.
+
+[scopes]: available-scopes-target
+
+If you don't want to get too detailed,
+one option is the `self` scope,
+which will have no effect on non-admin users,
+but will restrict the token issued to admin user servers to only have access to their own resources,
+instead of being able to take actions on behalf of all other users.
+
+```python
+c.JupyterHub.load_roles = [
+ {
+   'name': 'server',
+   'scopes': ['self'],
+ }
+]
+```
+
+(removing-roles-target)=
+
+## Removing roles
+
+Only the entities present in the role definition in the `jupyterhub_config.py` remain the role bearers. If a user, service or group is removed from the role definition, they will lose the role on the next startup.
+
+Once a role is loaded, it remains in the database until removing it from the `jupyterhub_config.py` and restarting the Hub. All previously defined role bearers will lose the role and associated permissions. Default roles, even if previously redefined through the config file and removed, will not be deleted from the database.

docs/source/rbac/scopes.md

@@ -0,0 +1,126 @@
+# Scopes in JupyterHub
+
+A scope has a syntax-based design that reveals which resources it provides access to. Resources are objects with a type, associated data, relationships to other resources, and a set of methods that operate on them (see [RESTful API](https://restful-api-design.readthedocs.io/en/latest/resources.html) documentation for more information).
+
+`<resource>` in the RBAC scope design refers to the resource name in the [JupyterHub's API](../reference/rest-api.rst) endpoints in most cases. For instance, `<resource>` equal to `users` corresponds to JupyterHub's API endpoints beginning with _/users_.
+
+(scope-conventions-target)=
+
+## Scope conventions
+
+- `<resource>` \
+  The top-level `<resource>` scopes, such as `users` or `groups`, grant read, write, and list permissions to the resource itself as well as its sub-resources. For example, the scope `users:activity` is included in the scope `users`.
+
+- `read:<resource>` \
+  Limits permissions to read-only operations on single resources.
+
+- `list:<resource>` \
+  Read-only access to listing endpoints.
+  Use `read:<resource>:<subresource>` to control what fields are returned.
+
+- `admin:<resource>` \
+  Grants additional permissions such as create/delete on the corresponding resource in addition to read and write permissions.
+
+- `access:<resource>` \
+  Grants access permissions to the `<resource>` via API or browser.
+
+- `<resource>:<subresource>` \
+  The {ref}`vertically filtered <vertical-filtering-target>` scopes provide access to a subset of the information granted by the `<resource>` scope. E.g., the scope `users:activity` only provides permission to post user activity.
+
+- `<resource>!<object>=<objectname>` \
+  {ref}`horizontal-filtering-target` is implemented by the `!<object>=<objectname>`scope structure. A resource (or sub-resource) can be filtered based on `user`, `server`, `group` or `service` name. For instance, `<resource>!user=charlie` limits access to only return resources of user `charlie`. \
+  Only one filter per scope is allowed, but filters for the same scope have an additive effect; a larger filter can be used by supplying the scope multiple times with different filters.
+
+By adding a scope to an existing role, all role bearers will gain the associated permissions.
+
+## Metascopes
+
+Metascopes do not follow the general scope syntax. Instead, a metascope resolves to a set of scopes, which can refer to different resources, based on their owning entity. In JupyterHub, there are currently two metascopes:
+
+1. default user scope `self`, and
+2. default token scope `all`.
+
+(default-user-scope-target)=
+
+### Default user scope
+
+Access to the user's own resources and subresources is covered by metascope `self`. This metascope includes the user's model, activity, servers and tokens. For example, `self` for a user named "gerard" includes:
+
+- `users!user=gerard` where the `users` scope provides access to the full user model and activity. The filter restricts this access to the user's own resources.
+- `servers!user=gerard` which grants the user access to their own servers without being able to create/delete any.
+- `tokens!user=gerard` which allows the user to access, request and delete their own tokens.
+- `access:servers!user=gerard` which allows the user to access their own servers via API or browser.
+
+The `self` scope is only valid for user entities. In other cases (e.g., for services) it resolves to an empty set of scopes.
+
+(default-token-scope-target)=
+
+### Default token scope
+
+The token metascope `all` covers the same scopes as the token owner's scopes during requests. For example, if a token owner has roles containing the scopes `read:groups` and `read:users`, the `all` scope resolves to the set of scopes `{read:groups, read:users}`.
+
+If the token owner has default `user` role, the `all` scope resolves to `self`, which will subsequently be expanded to include all the user-specific scopes (or empty set in the case of services).
+
+If the token owner is a member of any group with roles, the group scopes will also be included in resolving the `all` scope.
+
+(horizontal-filtering-target)=
+
+## Horizontal filtering
+
+Horizontal filtering, also called _resource filtering_, is the concept of reducing the payload of an API call to cover only the subset of the _resources_ that the scopes of the client provides them access to.
+Requested resources are filtered based on the filter of the corresponding scope. For instance, if a service requests a user list (guarded with scope `read:users`) with a role that only contains scopes `read:users!user=hannah` and `read:users!user=ivan`, the returned list of user models will be an intersection of all users and the collection `{hannah, ivan}`. In case this intersection is empty, the API call returns an HTTP 404 error, regardless if any users exist outside of the clients scope filter collection.
+
+In case a user resource is being accessed, any scopes with _group_ filters will be expanded to filters for each _user_ in those groups.
+
+### `!user` filter
+
+The `!user` filter is a special horizontal filter that strictly refers to the **"owner only"** scopes, where _owner_ is a user entity. The filter resolves internally into `!user=<ownerusername>` ensuring that only the owner's resources may be accessed through the associated scopes.
+
+For example, the `server` role assigned by default to server tokens contains `access:servers!user` and `users:activity!user` scopes. This allows the token to access and post activity of only the servers owned by the token owner.
+
+The filter can be applied to any scope.
+
+(vertical-filtering-target)=
+
+## Vertical filtering
+
+Vertical filtering, also called _attribute filtering_, is the concept of reducing the payload of an API call to cover only the _attributes_ of the resources that the scopes of the client provides them access to. This occurs when the client scopes are subscopes of the API endpoint that is called.
+For instance, if a client requests a user list with the only scope being `read:users:groups`, the returned list of user models will contain only a list of groups per user.
+In case the client has multiple subscopes, the call returns the union of the data the client has access to.
+
+The payload of an API call can be filtered both horizontally and vertically simultaneously. For instance, performing an API call to the endpoint `/users/` with the scope `users:name!user=juliette` returns a payload of `[{name: 'juliette'}]` (provided that this name is present in the database).
+
+(available-scopes-target)=
+
+## Available scopes
+
+Table below lists all available scopes and illustrates their hierarchy. Indented scopes indicate subscopes of the scope(s) above them.
+
+There are four exceptions to the general {ref}`scope conventions <scope-conventions-target>`:
+
+- `read:users:name` is a subscope of both `read:users` and `read:servers`. \
+  The `read:servers` scope requires access to the user name (server owner) due to named servers distinguished internally in the form `!server=username/servername`.
+
+- `read:users:activity` is a subscope of both `read:users` and `users:activity`. \
+  Posting activity via the `users:activity`, which is not included in `users` scope, needs to check the last valid activity of the user.
+
+- `read:roles:users` is a subscope of both `read:roles` and `admin:users`. \
+  Admin privileges to the _users_ resource include the information about user roles.
+
+- `read:roles:groups` is a subscope of both `read:roles` and `admin:groups`. \
+  Similar to the `read:roles:users` above.
+
+```{include} scope-table.md
+
+```
+
+```{Caution}
+Note that only the {ref}`horizontal filtering <horizontal-filtering-target>` can be added to scopes to customize them. \
+Metascopes `self` and `all`, `<resource>`, `<resource>:<subresource>`, `read:<resource>`, `admin:<resource>`, and `access:<resource>` scopes are predefined and cannot be changed otherwise.
+```
+
+### Scopes and APIs
+
+The scopes are also listed in the [](../reference/rest-api.rst) documentation. Each API endpoint has a list of scopes which can be used to access the API; if no scopes are listed, the API is not authenticated and can be accessed without any permissions (i.e., no scopes).
+
+Listed scopes by each API endpoint reflect the "lowest" permissions required to gain any access to the corresponding API. For example, posting user's activity (_POST /users/:name/activity_) needs `users:activity` scope. If scope `users` is passed during the request, the access will be granted as the required scope is a subscope of the `users` scope. If, on the other hand, `read:users:activity` scope is passed, the access will be denied.

docs/source/rbac/tech-implementation.md

@@ -0,0 +1,80 @@
+# Technical Implementation
+
+Roles are stored in the database, where they are associated with users, services, etc., and can be added or modified as explained in {ref}`define-role-target` section. Users, services, groups, and tokens can gain, change, and lose roles. This is currently achieved via `jupyterhub_config.py` (see {ref}`define-role-target`) and will be made available via API in future. The latter will allow for changing a token's role, and thereby its permissions, without the need to issue a new token.
+
+Roles and scopes utilities can be found in `roles.py` and `scopes.py` modules. Scope variables take on five different formats which is reflected throughout the utilities via specific nomenclature:
+
+```{admonition} **Scope variable nomenclature**
+:class: tip
+- _scopes_ \
+  List of scopes with abbreviations (used in role definitions). E.g., `["users:activity!user"]`.
+- _expanded scopes_ \
+  Set of expanded scopes without abbreviations (i.e., resolved metascopes, filters and subscopes). E.g., `{"users:activity!user=charlie", "read:users:activity!user=charlie"}`.
+- _parsed scopes_ \
+  Dictionary JSON like format of expanded scopes. E.g., `{"users:activity": {"user": ["charlie"]}, "read:users:activity": {"users": ["charlie"]}}`.
+- _intersection_ \
+  Set of expanded scopes as intersection of 2 expanded scope sets.
+- _identify scopes_ \
+  Set of expanded scopes needed for identify (whoami) endpoints.
+```
+
+(resolving-roles-scopes-target)=
+
+## Resolving roles and scopes
+
+**Resolving roles** refers to determining which roles a user, service, token, or group has, extracting the list of scopes from each role and combining them into a single set of scopes.
+
+**Resolving scopes** involves expanding scopes into all their possible subscopes (_expanded scopes_), parsing them into format used for access evaluation (_parsed scopes_) and, if applicable, comparing two sets of scopes (_intersection_). All procedures take into account the scope hierarchy, {ref}`vertical <vertical-filtering-target>` and {ref}`horizontal filtering <horizontal-filtering-target>`, limiting or elevated permissions (`read:<resource>` or `admin:<resource>`, respectively), and metascopes.
+
+Roles and scopes are resolved on several occasions, for example when requesting an API token with specific roles or making an API request. The following sections provide more details.
+
+(requesting-api-token-target)=
+
+### Requesting API token with specific roles
+
+API tokens grant access to JupyterHub's APIs. The RBAC framework allows for requesting tokens with specific existing roles. To date, it is only possible to add roles to a token through the _POST /users/:name/tokens_ API where the roles can be specified in the token parameters body (see [](../reference/rest-api.rst)).
+
+RBAC adds several steps into the token issue flow.
+
+If no roles are requested, the token is issued with the default `token` role (providing the requester is allowed to create the token).
+
+If the token is requested with any roles, the permissions of requesting entity are checked against the requested permissions to ensure the token would not grant its owner additional privileges.
+
+If, due to modifications of roles or entities, at API request time a token has any scopes that its owner does not, those scopes are removed. The API request is resolved without additional errors using the scopes _intersection_, but the Hub logs a warning (see {ref}`Figure 2 <api-request-chart>`).
+
+Resolving a token's roles (yellow box in {ref}`Figure 1 <token-request-chart>`) corresponds to resolving all the token's owner roles (including the roles associated with their groups) and the token's requested roles into a set of scopes. The two sets are compared (Resolve the scopes box in orange in {ref}`Figure 1 <token-request-chart>`), taking into account the scope hierarchy but, solely for role assignment, omitting any {ref}`horizontal filter <horizontal-filtering-target>` comparison. If the token's scopes are a subset of the token owner's scopes, the token is issued with the requested roles; if not, JupyterHub will raise an error.
+
+{ref}`Figure 1 <token-request-chart>` below illustrates the steps involved. The orange rectangles highlight where in the process the roles and scopes are resolved.
+
+```{figure} ../images/rbac-token-request-chart.png
+:align: center
+:name: token-request-chart
+
+Figure 1. Resolving roles and scopes during API token request
+```
+
+### Making an API request
+
+With the RBAC framework each authenticated JupyterHub API request is guarded by a scope decorator that specifies which scopes are required to gain the access to the API.
+
+When an API request is performed, the requesting API token's roles are again resolved (yellow box in {ref}`Figure 2 <api-request-chart>`) to ensure the token does not grant more permissions than its owner has at the request time (e.g., due to changing/losing roles).
+If the owner's roles do not include some scopes of the token's scopes, only the _intersection_ of the token's and owner's scopes will be used. For example, using a token with scope `users` whose owner's role scope is `read:users:name` will result in only the `read:users:name` scope being passed on. In the case of no _intersection_, an empty set of scopes will be used.
+
+The passed scopes are compared to the scopes required to access the API as follows:
+
+- if the API scopes are present within the set of passed scopes, the access is granted and the API returns its "full" response
+
+- if that is not the case, another check is utilized to determine if subscopes of the required API scopes can be found in the passed scope set:
+
+  - if found, the RBAC framework employs the {ref}`filtering <vertical-filtering-target>` procedures to refine the API response to access only resource attributes corresponding to the passed scopes. For example, providing a scope `read:users:activity!group=class-C` for the _GET /users_ API will return a list of user models from group `class-C` containing only the `last_activity` attribute for each user model
+
+  - if not found, the access to API is denied
+
+{ref}`Figure 2 <api-request-chart>` illustrates this process highlighting the steps where the role and scope resolutions as well as filtering occur in orange.
+
+```{figure} ../images/rbac-api-request-chart.png
+:align: center
+:name: api-request-chart
+
+Figure 2. Resolving roles and scopes when an API request is made
+```

docs/source/rbac/upgrade.md

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

docs/source/rbac/use-cases.md

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

docs/source/reference/authenticators.md

@@ -37,7 +37,7 @@ with any provider, is also available.
 ## The Dummy Authenticator
 
 When testing, it may be helpful to use the
-:class:`~jupyterhub.auth.DummyAuthenticator`. This allows for any username and
+{class}`jupyterhub.auth.DummyAuthenticator`. This allows for any username and
 password unless if a global password has been set. Once set, any username will
 still be accepted but the correct password will need to be provided.
 
@@ -89,7 +89,6 @@ class DictionaryAuthenticator(Authenticator):
             return data['username']
 ```
 
-
 #### Normalize usernames
 
 Since the Authenticator and Spawner both use the same username,
@@ -111,11 +110,10 @@ When using `PAMAuthenticator`, you can set
 normalize usernames using PAM (basically round-tripping them: username
 to uid to username), which is useful in case you use some external
 service that allows multiple usernames mapping to the same user (such
-as ActiveDirectory, yes, this really happens).  When
-`pam_normalize_username` is on, usernames are *not* normalized to
+as ActiveDirectory, yes, this really happens). When
+`pam_normalize_username` is on, usernames are _not_ normalized to
 lowercase.
 
-
 #### Validate usernames
 
 In most cases, there is a very limited set of acceptable usernames.
@@ -132,7 +130,6 @@ To only allow usernames that start with 'w':
 c.Authenticator.username_pattern = r'w.*'
 ```
 
-
 ### How to write a custom authenticator
 
 You can use custom Authenticator subclasses to enable authentication
@@ -145,7 +142,6 @@ and [post_spawn_stop(user, spawner)][], are hooks that can be used to do
 auth-related startup (e.g. opening PAM sessions) and cleanup
 (e.g. closing PAM sessions).
 
-
 See a list of custom Authenticators [on the wiki](https://github.com/jupyterhub/jupyterhub/wiki/Authenticators).
 
 If you are interested in writing a custom authenticator, you can read
@@ -186,7 +182,6 @@ Additionally, configurable attributes for your authenticator will
 appear in jupyterhub help output and auto-generated configuration files
 via `jupyterhub --generate-config`.
 
-
 ### Authentication state
 
 JupyterHub 0.8 adds the ability to persist state related to authentication,
@@ -220,12 +215,10 @@ To store auth_state, two conditions must be met:
    export JUPYTERHUB_CRYPT_KEY=$(openssl rand -hex 32)
    ```
 
-
 JupyterHub uses [Fernet](https://cryptography.io/en/latest/fernet/) to encrypt auth_state.
 To facilitate key-rotation, `JUPYTERHUB_CRYPT_KEY` may be a semicolon-separated list of encryption keys.
 If there are multiple keys present, the **first** key is always used to persist any new auth_state.
 
-
 #### Using auth_state
 
 Typically, if `auth_state` is persisted it is desirable to affect the Spawner environment in some way.
@@ -235,10 +228,9 @@ to Spawner environment:
 
 ```python
 class MyAuthenticator(Authenticator):
-    @gen.coroutine
-    def authenticate(self, handler, data=None):
-        username = yield identify_user(handler, data)
-        upstream_token = yield token_for_user(username)
+    async def authenticate(self, handler, data=None):
+        username = await identify_user(handler, data)
+        upstream_token = await token_for_user(username)
         return {
             'name': username,
             'auth_state': {
@@ -246,10 +238,9 @@ class MyAuthenticator(Authenticator):
             },
         }
 
-    @gen.coroutine
-    def pre_spawn_start(self, user, spawner):
+    async def pre_spawn_start(self, user, spawner):
         """Pass upstream_token to spawner via environment variable"""
-        auth_state = yield user.get_auth_state()
+        auth_state = await user.get_auth_state()
         if not auth_state:
             # auth_state not enabled
             return
@@ -268,11 +259,10 @@ PAM session.
 
 Beginning with version 0.8, JupyterHub is an OAuth provider.
 
-
-[Authenticator]: https://github.com/jupyterhub/jupyterhub/blob/master/jupyterhub/auth.py
-[PAM]: https://en.wikipedia.org/wiki/Pluggable_authentication_module
-[OAuth]: https://en.wikipedia.org/wiki/OAuth
-[GitHub OAuth]: https://developer.github.com/v3/oauth/
-[OAuthenticator]: https://github.com/jupyterhub/oauthenticator
+[authenticator]: https://github.com/jupyterhub/jupyterhub/blob/HEAD/jupyterhub/auth.py
+[pam]: https://en.wikipedia.org/wiki/Pluggable_authentication_module
+[oauth]: https://en.wikipedia.org/wiki/OAuth
+[github oauth]: https://developer.github.com/v3/oauth/
+[oauthenticator]: https://github.com/jupyterhub/oauthenticator
 [pre_spawn_start(user, spawner)]: https://jupyterhub.readthedocs.io/en/latest/api/auth.html#jupyterhub.auth.Authenticator.pre_spawn_start
 [post_spawn_stop(user, spawner)]: https://jupyterhub.readthedocs.io/en/latest/api/auth.html#jupyterhub.auth.Authenticator.post_spawn_stop

docs/source/reference/config-ghoauth.md

@@ -3,18 +3,17 @@
 In this example, we show a configuration file for a fairly standard JupyterHub
 deployment with the following assumptions:
 
-* Running JupyterHub on a single cloud server
-* Using SSL on the standard HTTPS port 443
-* Using GitHub OAuth (using oauthenticator) for login
-* Using the default spawner (to configure other spawners, uncomment and edit
+- Running JupyterHub on a single cloud server
+- Using SSL on the standard HTTPS port 443
+- Using GitHub OAuth (using oauthenticator) for login
+- Using the default spawner (to configure other spawners, uncomment and edit
   `spawner_class` as well as follow the instructions for your desired spawner)
-* Users exist locally on the server
-* Users' notebooks to be served from `~/assignments` to allow users to browse
+- Users exist locally on the server
+- Users' notebooks to be served from `~/assignments` to allow users to browse
   for notebooks within other users' home directories
-* You want the landing page for each user to be a `Welcome.ipynb` notebook in
+- 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`.
-
+- All runtime files are put into `/srv/jupyterhub` and log files in `/var/log`.
 
 The `jupyterhub_config.py` file would have these settings:
 
@@ -52,7 +51,7 @@ c.GitHubOAuthenticator.oauth_callback_url = os.environ['OAUTH_CALLBACK_URL']
 c.LocalAuthenticator.create_system_users = True
 
 # specify users and admin
-c.Authenticator.whitelist = {'rgbkrk', 'minrk', 'jhamrick'}
+c.Authenticator.allowed_users = {'rgbkrk', 'minrk', 'jhamrick'}
 c.Authenticator.admin_users = {'jhamrick', 'rgbkrk'}
 
 # uses the default spawner

docs/source/reference/config-proxy.md

@@ -6,12 +6,12 @@ SSL port `443`. This could be useful if the JupyterHub server machine is also
 hosting other domains or content on `443`. The goal in this example is to
 satisfy the following:
 
-* JupyterHub is running on a server, accessed *only* via `HUB.DOMAIN.TLD:443`
-* On the same machine, `NO_HUB.DOMAIN.TLD` strictly serves different content,
+- JupyterHub is running on a server, accessed _only_ via `HUB.DOMAIN.TLD:443`
+- On the same machine, `NO_HUB.DOMAIN.TLD` strictly serves different content,
   also on port `443`
-* `nginx` or `apache` is used as the public access point (which means that
-  only nginx/apache will bind  to `443`)
-* After testing, the server in question should be able to score at least an A on the
+- `nginx` or `apache` is used as the public access point (which means that
+  only nginx/apache will bind to `443`)
+- After testing, the server in question should be able to score at least an A on the
   Qualys SSL Labs [SSL Server Test](https://www.ssllabs.com/ssltest/)
 
 Let's start out with needed JupyterHub configuration in `jupyterhub_config.py`:
@@ -83,8 +83,12 @@ server {
         proxy_set_header X-Forwarded-For $proxy_add_x_forwarded_for;
 
         # websocket headers
+        proxy_http_version 1.1;
         proxy_set_header Upgrade $http_upgrade;
         proxy_set_header Connection $connection_upgrade;
+        proxy_set_header X-Scheme $scheme;
+
+        proxy_buffering off;
     }
 
     # Managing requests to verify letsencrypt host
@@ -139,6 +143,21 @@ 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
+
+On distributions with SELinux enabled (e.g. Fedora), one may encounter permission errors
+when the nginx service is started.
+
+We need to allow nginx to perform network relay and connect to the jupyterhub port. The
+following commands do that:
+
+```bash
+semanage port -a -t http_port_t -p tcp 8000
+setsebool -P httpd_can_network_relay 1
+setsebool -P httpd_can_network_connect 1
+```
+
+Replace 8000 with the port the jupyterhub server is running from.
 
 ## Apache
 
@@ -193,22 +212,24 @@ Listen 443
 </VirtualHost>
 ```
 
- 
 In case of the need to run the jupyterhub under /jhub/ or other location please use the below configurations:
+
 - JupyterHub running locally at http://127.0.0.1:8000/jhub/ or other location
 
 httpd.conf amendments:
+
 ```bash
- RewriteRule /jhub/(.*) ws://127.0.0.1:8000/jhub/$1 [P,L]
- RewriteRule /jhub/(.*) http://127.0.0.1:8000/jhub/$1 [P,L]
- 
+ RewriteRule /jhub/(.*) ws://127.0.0.1:8000/jhub/$1 [NE.P,L]
+ RewriteRule /jhub/(.*) http://127.0.0.1:8000/jhub/$1 [NE,P,L]
+
  ProxyPass /jhub/ http://127.0.0.1:8000/jhub/
  ProxyPassReverse /jhub/  http://127.0.0.1:8000/jhub/
- ```
- 
+```
+
 jupyterhub_config.py amendments:
- ```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/'
-  ```
+
+```bash
+ --The public facing URL of the whole JupyterHub application.
+ --This is the address on which the proxy will bind. Sets protocol, ip, base_url
+ c.JupyterHub.bind_url = 'http://127.0.0.1:8000/jhub/'
+```

docs/source/reference/config-reference.rst

@@ -0,0 +1,30 @@
+==============================
+Configuration Reference
+==============================
+
+.. important::
+
+    Make sure the version of JupyterHub for this documentation matches your
+    installation version, as the output of this command may change between versions.
+
+JupyterHub configuration
+------------------------
+
+As explained in the `Configuration Basics <../getting-started/config-basics.html#generate-a-default-config-file>`_
+section, the ``jupyterhub_config.py`` can be automatically generated via
+
+    .. code-block:: bash
+
+        jupyterhub --generate-config
+
+
+The following contains the output of that command for reference.
+
+.. jupyterhub-generate-config::
+
+JupyterHub help command output
+------------------------------
+
+This section contains the output of the command ``jupyterhub --help-all``.
+
+.. jupyterhub-help-all::

docs/source/reference/config-sudo.md

@@ -9,7 +9,7 @@ Only do this if you are very sure you must.
 There are many Authenticators and Spawners available for JupyterHub. Some, such
 as DockerSpawner or OAuthenticator, do not need any elevated permissions. This
 document describes how to get the full default behavior of JupyterHub while
-running notebook servers as real system users on a shared system without 
+running notebook servers as real system users on a shared system without
 running the Hub itself as root.
 
 Since JupyterHub needs to spawn processes as other users, the simplest way
@@ -50,14 +50,13 @@ To do this we add to `/etc/sudoers` (use `visudo` for safe editing of sudoers):
 
 - specify the list of users `JUPYTER_USERS` for whom `rhea` can spawn servers
 - set the command `JUPYTER_CMD` that `rhea` can execute on behalf of users
-- give `rhea` permission to run `JUPYTER_CMD` on behalf of `JUPYTER_USERS` 
+- give `rhea` permission to run `JUPYTER_CMD` on behalf of `JUPYTER_USERS`
   without entering a password
 
-
 For example:
 
 ```bash
-# comma-separated whitelist of users that can spawn single-user servers
+# comma-separated list of users that can spawn single-user servers
 # this should include all of your Hub users
 Runas_Alias JUPYTER_USERS = rhea, zoe, wash
 
@@ -91,16 +90,16 @@ $ 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:
 
 ```bash
 $ sudo -u rhea sudo -n -u $USER /usr/local/bin/sudospawner --help
 Usage: /usr/local/bin/sudospawner [OPTIONS]
-    
+
 Options:
-    
+
 --help          show this help information
 ...
 ```
@@ -120,6 +119,11 @@ the shadow password database.
 
 ### Shadow group (Linux)
 
+**Note:** On Fedora based distributions there is no clear way to configure
+the PAM database to allow sufficient access for authenticating with the target user's password
+from JupyterHub. As a workaround we recommend use an
+[alternative authentication method](https://github.com/jupyterhub/jupyterhub/wiki/Authenticators).
+
 ```bash
 $ ls -l /etc/shadow
 -rw-r-----  1 root shadow   2197 Jul 21 13:41 shadow
@@ -146,12 +150,13 @@ We want our new user to be able to read the shadow passwords, so add it to the s
     $ sudo usermod -a -G shadow rhea
 ```
 
-If you want jupyterhub to serve pages on a restricted port (such as port 80 for http), 
+If you want jupyterhub to serve pages on a restricted port (such as port 80 for http),
 then you will need to give `node` permission to do so:
 
 ```bash
 sudo setcap 'cap_net_bind_service=+ep' /usr/bin/node
 ```
+
 However, you may want to further understand the consequences of this.
 
 You may also be interested in limiting the amount of CPU any process can use
@@ -160,7 +165,6 @@ distributions' packaging system. This can be used to keep any user's process
 from using too much CPU cycles. You can configure it accoring to [these
 instructions](http://ubuntuforums.org/showthread.php?t=992706).
 
-
 ### Shadow group (FreeBSD)
 
 **NOTE:** This has not been tested and may not work as expected.
@@ -181,7 +185,7 @@ $ sudo chgrp shadow /etc/master.passwd
 $ sudo chmod g+r /etc/master.passwd
 ```
 
-We want our new user to be able to read the shadow passwords, so add it to the 
+We want our new user to be able to read the shadow passwords, so add it to the
 shadow group:
 
 ```bash
@@ -215,7 +219,7 @@ Finally, start the server as our newly configured user, `rhea`:
 ```bash
 $ cd /etc/jupyterhub
 $ sudo -u rhea jupyterhub --JupyterHub.spawner_class=sudospawner.SudoSpawner
-```                                                                             
+```
 
 And try logging in.
 
@@ -223,7 +227,7 @@ And try logging in.
 
 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.
-First, put this in a file  named `sudo_exec_selinux.te`:
+First, put this in a file named `sudo_exec_selinux.te`:
 
 ```bash
 module sudo_exec_selinux 1.1;

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

@@ -22,20 +22,18 @@ This section will focus on user environments, including:
 - Installing kernelspecs
 - Using containers vs. multi-user hosts
 
-
 ## Installing packages
 
 To make packages available to users, you generally will install packages
 system-wide or in a shared environment.
 
 This installation location should always be in the same environment that
-`jupyterhub-singleuser` itself is installed in, and must be *readable and
-executable* by your users. If you want users to be able to install additional
-packages, it must also be *writable* by your users.
+`jupyterhub-singleuser` itself is installed in, and must be _readable and
+executable_ by your users. If you want users to be able to install additional
+packages, it must also be _writable_ by your users.
 
 If you are using a standard system Python install, you would use:
 
-
 ```bash
 sudo python3 -m pip install numpy
 ```
@@ -47,7 +45,6 @@ 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.
 
-
 ## Configuring Jupyter and IPython
 
 [Jupyter](https://jupyter-notebook.readthedocs.io/en/stable/config_overview.html)
@@ -64,6 +61,7 @@ users. It's generally more efficient to configure user environments "system-wide
 and it's a good idea to avoid creating files in users' home directories.
 
 The typical locations for these config files are:
+
 - **system-wide** in `/etc/{jupyter|ipython}`
 - **env-wide** (environment wide) in `{sys.prefix}/etc/{jupyter|ipython}`.
 
@@ -91,7 +89,6 @@ c.MappingKernelManager.cull_idle_timeout = 20 * 60
 c.MappingKernelManager.cull_interval = 2 * 60
 ```
 
-
 ## Installing kernelspecs
 
 You may have multiple Jupyter kernels installed and want to make sure that
@@ -119,7 +116,6 @@ sure are available, I can install their specs system-wide (in /usr/local) with:
 /path/to/python2 -m IPython kernel install --prefix=/usr/local
 ```
 
-
 ## Multi-user hosts vs. Containers
 
 There are two broad categories of user environments that depend on what
@@ -141,8 +137,8 @@ When JupyterHub uses **container-based** Spawners (e.g. KubeSpawner or
 DockerSpawner), the 'system-wide' environment is really the container image
 which you are using for users.
 
-In both cases, you want to *avoid putting configuration in user home
-directories* because users can change those configuration settings. Also,
+In both cases, you want to _avoid putting configuration in user home
+directories_ because users can change those configuration settings. Also,
 home directories typically persist once they are created, so they are
 difficult for admins to update later.
 
@@ -179,3 +175,13 @@ The number of named servers per user can be limited by setting
 ```python
 c.JupyterHub.named_server_limit_per_user = 5
 ```
+
+## Switching to Jupyter Server
+
+[Jupyter Server](https://jupyter-server.readthedocs.io/en/latest/) is a new Tornado Server backend for Jupyter web applications (e.g. JupyterLab 3.0 uses this package as its default backend).
+
+By default, the single-user notebook server uses the (old) `NotebookApp` from the [notebook](https://github.com/jupyter/notebook) package. You can switch to using Jupyter Server's `ServerApp` backend (this will likely become the default in future releases) by setting the `JUPYTERHUB_SINGLEUSER_APP` environment variable to:
+
+```bash
+export JUPYTERHUB_SINGLEUSER_APP='jupyter_server.serverapp.ServerApp'
+```

docs/source/reference/database.md

@@ -46,8 +46,8 @@ additional configuration required for MySQL that is not needed for PostgreSQL.
 
 - You should use the `pymysql` sqlalchemy provider (the other one, MySQLdb,
   isn't available for py3).
-- You also need to set `pool_recycle` to some value (typically 60 - 300) 
-  which depends on your  MySQL setup. This is necessary since MySQL kills
+- You also need to set `pool_recycle` to some value (typically 60 - 300)
+  which depends on your MySQL setup. This is necessary since MySQL kills
   connections serverside if they've been idle for a while, and the connection
   from the hub will be idle for longer than most connections. This behavior
   will lead to frustrating 'the connection has gone away' errors from

docs/source/reference/index.rst

@@ -16,6 +16,8 @@ what happens under-the-hood when you deploy and configure your JupyterHub.
    proxy
    separate-proxy
    rest
+   server-api
+   monitoring
    database
    templates
    ../events/index
@@ -24,3 +26,5 @@ what happens under-the-hood when you deploy and configure your JupyterHub.
    config-ghoauth
    config-proxy
    config-sudo
+   config-reference
+   oauth

docs/source/reference/monitoring.rst

@@ -0,0 +1,20 @@
+Monitoring
+==========
+
+This section covers details on monitoring the state of your JupyterHub installation.
+
+JupyterHub expose the ``/metrics`` endpoint that returns text describing its current
+operational state formatted in a way `Prometheus <https://prometheus.io/docs/introduction/overview/>`_ understands.
+
+Prometheus is a separate open source tool that can be configured to repeatedly poll
+JupyterHub's ``/metrics`` endpoint to parse and save its current state.
+
+By doing so, Prometheus can describe JupyterHub's evolving state over time.
+This evolving state can then be accessed through Prometheus that expose its underlying
+storage to those allowed to access it, and be presented with dashboards by a
+tool like `Grafana <https://grafana.com/docs/grafana/latest/getting-started/what-is-grafana/>`_.
+
+.. toctree::
+   :maxdepth: 2
+
+   metrics

docs/source/reference/oauth.md

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

docs/source/reference/proxy.md

@@ -54,7 +54,7 @@ class MyProxy(Proxy):
         """Stop the proxy"""
 ```
 
-These methods **may** be  coroutines.
+These methods **may** be coroutines.
 
 `c.Proxy.should_start` is a configurable flag that determines whether the
 Hub should call these methods when the Hub itself starts and stops.
@@ -103,7 +103,7 @@ route to be proxied, such as `/user/name/`. A routespec will:
 
 When adding a route, JupyterHub may pass a JSON-serializable dict as a `data`
 argument that should be attached to the proxy route. When that route is
-retrieved, the `data` argument should be returned as well. If your  proxy
+retrieved, the `data` argument should be returned as well. If your proxy
 implementation doesn't support storing data attached to routes, then your
 Python wrapper may have to handle storing the `data` piece itself, e.g in a
 simple file or database.
@@ -136,7 +136,7 @@ async def delete_route(self, routespec):
 
 ### Retrieving routes
 
-For retrieval, you only *need* to implement a single method that retrieves all
+For retrieval, you only _need_ to implement a single method that retrieves all
 routes. The return value for this function should be a dictionary, keyed by
 `routespect`, of dicts whose keys are the same three arguments passed to
 `add_route` (`routespec`, `target`, `data`)
@@ -220,3 +220,11 @@ previously required.
 Additionally, configurable attributes for your proxy will
 appear in jupyterhub help output and auto-generated configuration files
 via `jupyterhub --generate-config`.
+
+### Index of proxies
+
+A list of the proxies that are currently available for JupyterHub (that we know about).
+
+1. [`jupyterhub/configurable-http-proxy`](https://github.com/jupyterhub/configurable-http-proxy) The default proxy which uses node-http-proxy
+2. [`jupyterhub/traefik-proxy`](https://github.com/jupyterhub/traefik-proxy) The proxy which configures traefik proxy server for jupyterhub
+3. [`AbdealiJK/configurable-http-proxy`](https://github.com/AbdealiJK/configurable-http-proxy) A pure python implementation of the configurable-http-proxy

docs/source/reference/rest.md

@@ -17,6 +17,7 @@ such as:
 - 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)
 API provides a standard way for users to get and send information to the
@@ -27,8 +28,7 @@ Hub.
 To send requests using JupyterHub API, you must pass an API token with
 the request.
 
-As of [version 0.6.0](../changelog.md), the preferred way of
-generating an API token is:
+The preferred way of generating an API token is:
 
 ```bash
 openssl rand -hex 32
@@ -48,25 +48,85 @@ jupyterhub token <username>
 This command generates a random string to use as a token and registers
 it for the given user with the Hub's database.
 
-In [version 0.8.0](../changelog.md), a TOKEN request page for
+In [version 0.8.0](../changelog.md), a token request page for
 generating an API token is available from the JupyterHub user interface:
 
-![Request API TOKEN page](../images/token-request.png)
+![Request API token page](../images/token-request.png)
 
-![API TOKEN success page](../images/token-request-success.png)
+![API token success page](../images/token-request-success.png)
 
-## Add API tokens to the config file
+## Assigning permissions to a token
 
-You may also add a dictionary of API tokens and usernames to the hub's
-configuration file, `jupyterhub_config.py` (note that
-the **key** is the 'secret-token' while the **value** is the 'username'):
+Prior to JupyterHub 2.0, there were two levels of permissions:
+
+1. user, and
+2. admin
+
+where a token would always have full permissions to do whatever its owner could do.
+
+In JupyterHub 2.0,
+specific permissions are now defined as 'scopes',
+and can be assigned both at the user/service level,
+and at the individual token level.
+
+This allows e.g. a user with full admin permissions to request a token with limited permissions.
+
+### Updating to admin services
+
+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:
 
 ```python
+c.JupyterHub.admin_users = {"service-admin",}
 c.JupyterHub.api_tokens = {
-    'secret-token': 'username',
+    "secret-token": "service-admin",
 }
 ```
 
+This can be updated to create a service, with the following configuration:
+
+```python
+c.JupyterHub.services = [
+    {
+        # give the token a name
+        "name": "service-admin",
+        "api_token": "secret-token",
+        # "admin": True, # if using JupyterHub 1.x
+    },
+]
+
+# roles are new in JupyterHub 2.0
+# prior to 2.0, only 'admin': True or False
+# was available
+
+c.JupyterHub.load_roles = [
+    {
+        "name": "service-role",
+        "scopes": [
+            # specify the permissions the token should have
+            "admin:users",
+            "admin:services",
+        ],
+        "services": [
+            # assign the service the above permissions
+            "service-admin",
+        ],
+    }
+]
+```
+
+The token will have the permissions listed in the role
+(see [scopes][] for a list of available permissions),
+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
+and the service will not show up in the various user list pages and APIs.
+
 ## Make an API request
 
 To authenticate your requests, pass the API token in the request's
@@ -74,7 +134,7 @@ Authorization header.
 
 ### Use requests
 
-Using the popular Python [requests](http://docs.python-requests.org/en/master/)
+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:
@@ -86,9 +146,9 @@ api_url = 'http://127.0.0.1:8081/hub/api'
 
 r = requests.get(api_url + '/users',
     headers={
-             'Authorization': 'token %s' % token,
-            }
-    )
+        'Authorization': f'token {token}',
+    }
+)
 
 r.raise_for_status()
 users = r.json()
@@ -106,19 +166,95 @@ data = {'name': 'mygroup', 'users': ['user1', 'user2']}
 
 r = requests.post(api_url + '/groups/formgrade-data301/users',
     headers={
-             'Authorization': 'token %s' % token,
-            },
-    json=data
+        'Authorization': f'token {token}',
+    },
+    json=data,
 )
 r.raise_for_status()
 r.json()
 ```
 
 The same API token can also authorize access to the [Jupyter Notebook REST API][]
-provided by notebook servers managed by JupyterHub if one of the following is true:
+provided by notebook servers managed by JupyterHub if it has the necessary `access:users:servers` scope:
 
-1. The token is for the same user as the owner of the notebook
-2. The token is tied to an admin user or service **and** `c.JupyterHub.admin_access` is set to `True`
+(api-pagination)=
+
+## Paginating API requests
+
+```{versionadded} 2.0
+
+```
+
+Pagination is available through the `offset` and `limit` query parameters on
+list endpoints, which can be used to return ideally sized windows of results.
+Here's example code demonstrating pagination on the `GET /users`
+endpoint to fetch the first 20 records.
+
+```python
+import os
+import requests
+
+api_url = 'http://127.0.0.1:8081/hub/api'
+
+r = requests.get(
+    api_url + '/users?offset=0&limit=20',
+    headers={
+        "Accept": "application/jupyterhub-pagination+json",
+        "Authorization": f"token {token}",
+    },
+)
+r.raise_for_status()
+r.json()
+```
+
+For backward-compatibility, the default structure of list responses is unchanged.
+However, this lacks pagination information (e.g. is there a next page),
+so if you have enough users that they won't fit in the first response,
+it is a good idea to opt-in to the new paginated list format.
+There is a new schema for list responses which include pagination information.
+You can request this by including the header:
+
+```
+Accept: application/jupyterhub-pagination+json
+```
+
+with your request, in which case a response will look like:
+
+```python
+{
+  "items": [
+    {
+      "name": "username",
+      "kind": "user",
+      ...
+    },
+  ],
+  "_pagination": {
+    "offset": 0,
+    "limit": 20,
+    "total": 50,
+    "next": {
+      "offset": 20,
+      "limit": 20,
+      "url": "http://127.0.0.1:8081/hub/api/users?limit=20&offset=20"
+    }
+  }
+}
+```
+
+where the list results (same as pre-2.0) will be in `items`,
+and pagination info will be in `_pagination`.
+The `next` field will include the offset, limit, and URL for requesting the next page.
+`next` will be `null` if there is no next page.
+
+Pagination is governed by two configuration options:
+
+- `JupyterHub.api_page_default_limit` - the page size, if `limit` is unspecified in the request
+  and the new pagination API is requested
+  (default: 50)
+- `JupyterHub.api_page_max_limit` - the maximum page size a request can ask for (default: 200)
+
+Pagination is enabled on the `GET /users`, `GET /groups`, and `GET /proxy` REST endpoints.
 
 ## Enabling users to spawn multiple named-servers via the API
 
@@ -131,7 +267,7 @@ curl -X POST -H "Authorization: token <token>" "http://127.0.0.1:8081/hub/api/us
 ```
 
 With the named-server functionality, it's now possible to launch more than one
-specifically named servers against a given user.  This could be used, for instance,
+specifically named servers against a given user. This could be used, for instance,
 to launch each server based on a different image.
 
 First you must enable named-servers by including the following setting in the `jupyterhub_config.py` file.
@@ -149,6 +285,7 @@ hub:
 ```
 
 With that setting in place, a new named-server is activated like this:
+
 ```bash
 curl -X POST -H "Authorization: token <token>" "http://127.0.0.1:8081/hub/api/users/<user>/servers/<serverA>"
 curl -X POST -H "Authorization: token <token>" "http://127.0.0.1:8081/hub/api/users/<user>/servers/<serverB>"
@@ -163,7 +300,6 @@ will need to be able to handle the case of multiple servers per user and ensure
 uniqueness of names, particularly if servers are spawned via docker containers
 or kubernetes pods.
 
-
 ## Learn more about the API
 
 You can see the full [JupyterHub REST API][] for details. This REST API Spec can
@@ -171,7 +307,7 @@ 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][].
 
-[interactive style on swagger's petstore]: http://petstore.swagger.io/?url=https://raw.githubusercontent.com/jupyterhub/jupyterhub/master/docs/rest-api.yml#!/default
-[OpenAPI Initiative]: https://www.openapis.org/
-[JupyterHub REST API]: ./rest-api
-[Jupyter Notebook REST API]: http://petstore.swagger.io/?url=https://raw.githubusercontent.com/jupyter/notebook/master/notebook/services/api/api.yaml
+[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
+[jupyter notebook rest api]: https://petstore3.swagger.io/?url=https://raw.githubusercontent.com/jupyter/notebook/HEAD/notebook/services/api/api.yaml

docs/source/reference/separate-proxy.md

@@ -1,28 +1,26 @@
 # Running proxy separately from the hub
 
-
 ## Background
 
 The thing which users directly connect to is the proxy, by default
-`configurable-http-proxy`.  The proxy either redirects users to the
+`configurable-http-proxy`. The proxy either redirects users to the
 hub (for login and managing servers), or to their own single-user
-servers.  Thus, as long as the proxy stays running, access to existing
+servers. Thus, as long as the proxy stays running, access to existing
 servers continues, even if the hub itself restarts or goes down.
 
 When you first configure the hub, you may not even realize this
-because the proxy is automatically managed by the hub.  This is great
+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
+hub, all user connections also get restarted. But it's also simple to
 run the proxy as a service separate from the hub, so that you are free
 to reconfigure the hub while only interrupting users who are currently
 actively starting the hub.
 
 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
+and that page has some docs. If you are using a different proxy, such
 as Traefik, these instructions are probably not relevant to you.
 
-
 ## Configuration options
 
 `c.JupyterHub.cleanup_servers = False` should be set, which tells the
@@ -37,24 +35,20 @@ it yourself).
 token for authenticating communication with the proxy.
 
 `c.ConfigurableHTTPProxy.api_url = 'http://localhost:8001'` should be
-set to the URL which the hub uses to connect *to the proxy's API*.
-
+set to the URL which the hub uses to connect _to the proxy's API_.
 
 ## Proxy configuration
 
-You need to configure a service to start the proxy.  An example
-command line 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
+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
+systemd service on within another docker cotainer). The proxy has no
 configuration files, all configuration is via the command line and
 environment variables.
 
 `--api-ip` and `--api-port` (which tells the proxy where to listen) should match the hub's `ConfigurableHTTPProxy.api_url`.
 
-`--ip`, `-port`, and other options configure the *user* connections to the proxy.
+`--ip`, `-port`, and other options configure the _user_ connections to the proxy.
 
 `--default-target` and `--error-target` should point to the hub, and used when users navigate to the proxy originally.
 
@@ -63,18 +57,16 @@ 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
+what other options are needed, for example SSL options. Note that
 these are configured in the hub if the hub is starting the proxy - you
 need to move the options to here.
 
-
 ## Docker image
 
 You can use [jupyterhub configurable-http-proxy docker
 image](https://hub.docker.com/r/jupyterhub/configurable-http-proxy/)
 to run the proxy.
 
-
 ## See also
 
-* [jupyterhub configurable-http-proxy](https://github.com/jupyterhub/configurable-http-proxy)
+- [jupyterhub configurable-http-proxy](https://github.com/jupyterhub/configurable-http-proxy)

docs/source/reference/server-api.md

@@ -0,0 +1,369 @@
+# Starting servers with the JupyterHub API
+
+JupyterHub's [REST API][] allows launching servers on behalf of users
+without ever interacting with the JupyterHub UI.
+This allows you to build services launching Jupyter-based services for users
+without relying on the JupyterHub UI at all,
+enabling a variety of user/launch/lifecycle patterns not natively supported by JupyterHub,
+without needing to develop all the server management features of JupyterHub Spawners and/or Authenticators.
+[BinderHub][] is an example of such an application.
+
+[binderhub]: https://binderhub.readthedocs.io
+[rest api]: ../reference/rest.md
+
+This document provides an example of working with the JupyterHub API to
+manage servers for users.
+In particular, we will cover how to:
+
+1. [check status of servers](checking)
+2. [start servers](starting)
+3. [wait for servers to be ready](waiting)
+4. [communicate with servers](communicating)
+5. [stop servers](stopping)
+
+(checking)=
+
+## Checking server status
+
+Requesting information about a user includes a `servers` field,
+which is a dictionary.
+
+```
+GET /hub/api/users/:username
+```
+
+**Required scope: `read:servers`**
+
+```json
+{
+  "admin": false,
+  "groups": [],
+  "pending": null,
+  "server": null,
+  "name": "test-1",
+  "kind": "user",
+  "last_activity": "2021-08-03T18:12:46.026411Z",
+  "created": "2021-08-03T18:09:59.767600Z",
+  "roles": ["user"],
+  "servers": {}
+}
+```
+
+If the `servers` dict is empty, the user has no running servers.
+The keys of the `servers` dict are server names as strings.
+Many JupyterHub deployments only use the 'default' server,
+which has the empty string `''` for a name.
+In this case, the servers dict will always have either zero or one elements.
+
+This is the servers dict when the user's default server is fully running and ready:
+
+```json
+  "servers": {
+    "": {
+      "name": "",
+      "last_activity": "2021-08-03T18:48:35.934000Z",
+      "started": "2021-08-03T18:48:29.093885Z",
+      "pending": null,
+      "ready": true,
+      "url": "/user/test-1/",
+      "user_options": {},
+      "progress_url": "/hub/api/users/test-1/server/progress"
+    }
+  }
+```
+
+Key properties of a server:
+
+name
+: the server's name. Always the same as the key in `servers`
+
+ready
+: boolean. If true, the server can be expected to respond to requests at `url`.
+
+pending
+: `null` or a string indicating a transitional state (such as `start` or `stop`).
+Will always be `null` if `ready` is true,
+and will always be a string if `ready` is false.
+
+url
+: The server's url (just the path, e.g. `/users/:name/:servername/`)
+where the server can be accessed if `ready` is true.
+
+progress_url
+: The API url path (starting with `/hub/api`)
+where the progress API can be used to wait for the server to be ready.
+See below for more details on the progress API.
+
+last_activity
+: ISO8601 timestamp indicating when activity was last observed on the server
+
+started
+: ISO801 timestamp indicating when the server was last started
+
+We've seen the `servers` model with no servers and with one `ready` server.
+Here is what it looks like immediately after requesting a server launch,
+while the server is not ready yet:
+
+```json
+  "servers": {
+    "": {
+      "name": "",
+      "last_activity": "2021-08-03T18:48:29.093885Z",
+      "started": "2021-08-03T18:48:29.093885Z",
+      "pending": "spawn",
+      "ready": false,
+      "url": "/user/test-1/",
+      "user_options": {},
+      "progress_url": "/hub/api/users/test-1/server/progress"
+    }
+  }
+```
+
+Note that `ready` is false and `pending` is `spawn`.
+This means that the server is not ready
+(attempting to access it may not work)
+because it isn't finished spawning yet.
+We'll get more into that below in [waiting for a server][].
+
+[waiting for a server]: waiting
+
+(starting)=
+
+## Starting servers
+
+To start a server, make the request
+
+```
+POST /hub/api/users/:username/servers/[:servername]
+```
+
+**Required scope: `servers`**
+
+(omit servername for the default server)
+
+Assuming the request was valid,
+there are two possible responses:
+
+201 Created
+: This status code means the launch completed and the server is ready.
+It should be available at the server's URL immediately.
+
+202 Accepted
+: This is the more likely response,
+and means that the server has begun launching,
+but isn't immediately ready.
+The server has `pending: 'spawn'` at this point.
+
+_Aside: how quickly JupyterHub responds with `202 Accepted` is governed by the `slow_spawn_timeout` tornado setting._
+
+(waiting)=
+
+## Waiting for a server
+
+If you are starting a server via the API,
+there's a good change you want to know when it's ready.
+There are two ways to do with:
+
+1. {ref}`Polling the server model <polling>`
+2. the {ref}`progress API <progress>`
+
+(polling)=
+
+### Polling the server model
+
+The simplest way to check if a server is ready
+is to request the user model.
+
+If:
+
+1. the server name is in the user's `servers` model, and
+2. `servers['servername']['ready']` is true
+
+A Python example, checking if a server is ready:
+
+```python
+def server_ready(hub_url, user, server_name="", token):
+    r = requests.get(
+        f"{hub_url}/hub/api/users/{user}/servers/{server_name}",
+        headers={"Authorization": f"token {token}"},
+    )
+    r.raise_for_status()
+    user_model = r.json()
+    servers = user_model.get("servers", {})
+    if server_name not in servers:
+        return False
+
+    server = servers[server_name]
+    if server['ready']:
+        print(f"Server {user}/{server_name} ready at {server['url']}")
+        return True
+    else:
+        print(f"Server {user}/{server_name} not ready, pending {server['pending']}")
+        return False
+```
+
+You can keep making this check until `ready` is true.
+
+(progress)=
+
+### Progress API
+
+The most _efficient_ way to wait for a server to start is the progress API.
+
+The progress URL is available in the server model under `progress_url`,
+and has the form `/hub/api/users/:user/servers/:servername/progress`.
+
+_the default server progress can be accessed at `:user/servers//progress` or `:user/server/progress`_
+
+```
+GET /hub/api/users/:user/servers/:servername/progress
+```
+
+**Required scope: `read:servers`**
+
+This is an [EventStream][] API.
+In an event stream, messages are _streamed_ and delivered on lines of the form:
+
+```
+data: {"progress": 10, "message": "...", ...}
+```
+
+where the line after `data:` contains a JSON-serialized dictionary.
+Lines that do not start with `data:` should be ignored.
+
+[eventstream]: https://developer.mozilla.org/en-US/docs/Web/API/Server-sent_events/Using_server-sent_events#examples
+
+progress events have the form:
+
+```python
+{
+    "progress": 0-100,
+    "message": "",
+    "ready": True, # or False
+
+}
+```
+
+progress
+: integer, 0-100
+
+message
+: string message describing progress stages
+
+ready
+: present and true only for the last event when the server is ready
+
+url
+: only present if `ready` is true; will be the server's url
+
+the progress API can be used even with fully ready servers.
+If the server is ready,
+there will only be one event that looks like:
+
+```json
+{
+  "progress": 100,
+  "ready": true,
+  "message": "Server ready at /user/test-1/",
+  "html_message": "Server ready at <a href=\"/user/test-1/\">/user/test-1/</a>",
+  "url": "/user/test-1/"
+}
+```
+
+where `ready` and `url` are the same as in the server model (`ready` will always be true).
+
+A typical complete stream from the event-stream API:
+
+```
+
+data: {"progress": 0, "message": "Server requested"}
+
+data: {"progress": 50, "message": "Spawning server..."}
+
+data: {"progress": 100, "ready": true, "message": "Server ready at /user/test-user/", "html_message": "Server ready at <a href=\"/user/test-user/\">/user/test-user/</a>", "url": "/user/test-user/"}
+```
+
+Here is a Python example for consuming an event stream:
+
+```{literalinclude} ../../../examples/server-api/start-stop-server.py
+:language: python
+:pyobject: event_stream
+```
+
+(stopping)=
+
+## Stopping servers
+
+Servers can be stopped with a DELETE request:
+
+```
+DELETE /hub/api/users/:user/servers/[:servername]
+```
+
+**Required scope: `servers`**
+
+Like start, delete may not complete immediately.
+The DELETE request has two possible response codes:
+
+204 Deleted
+: This status code means the delete completed and the server is fully stopped.
+It will now be absent from the user `servers` model.
+
+202 Accepted
+: Like start, `202` means your request was accepted,
+but is not yet complete.
+The server has `pending: 'stop'` at this point.
+
+Unlike start, there is no progress API for stop.
+To wait for stop to finish, you must poll the user model
+and wait for the server to disappear from the user `servers` model.
+
+```{literalinclude} ../../../examples/server-api/start-stop-server.py
+:language: python
+:pyobject: stop_server
+```
+
+(communicating)=
+
+## Communicating with servers
+
+JupyterHub tokens with the the `access:servers` scope
+can be used to communicate with servers themselves.
+This can be the same token you used to launch your service.
+
+```{note}
+Access scopes are new in JupyterHub 2.0.
+To access servers in JupyterHub 1.x,
+a token must be owned by the same user as the server,
+*or* be an admin token if admin_access is enabled.
+```
+
+The URL returned from a server model is the url path suffix,
+e.g. `/user/:name/` to append to the jupyterhub base URL.
+
+For instance, `{hub_url}{server_url}`,
+where `hub_url` would be e.g. `http://127.0.0.1:8000` by default,
+and `server_url` `/user/myname`,
+for a full url of `http://127.0.0.1:8000/user/myname`.
+
+## Python example
+
+The JupyterHub repo includes a complete example in {file}`examples/server-api`
+tying all this together.
+
+To summarize the steps:
+
+1. get user info from `/user/:name`
+2. the server model includes a `ready` state to tell you if it's ready
+3. if it's not ready, you can follow up with `progress_url` to wait for it
+4. if it is ready, you can use the `url` field to link directly to the running server
+
+The example demonstrates starting and stopping servers via the JupyterHub API,
+including waiting for them to start via the progress API,
+as well as waiting for them to stop via polling the user model.
+
+```{literalinclude} ../../../examples/server-api/start-stop-server.py
+:language: python
+:start-at: def event_stream
+:end-before: def main
+```

docs/source/reference/services.md

@@ -45,17 +45,14 @@ A Service may have the following properties:
 - `url: str (default - None)` - The URL where the service is/should be. If a
   url is specified for where the Service runs its own web server,
   the service will be added to the proxy at `/services/:name`
-- `api_token: str (default - None)` - For Externally-Managed Services you need to specify 
+- `api_token: str (default - None)` - For Externally-Managed Services you need to specify
   an API token to perform API requests to the Hub
 
 If a service is also to be managed by the Hub, it has a few extra options:
 
-- `command: (str/Popen list`) - Command for JupyterHub to spawn the service.
-      - Only use this if the service should be a subprocess.
-      - If command is not specified, the Service is assumed to be managed
-        externally.
-      - If a command is specified for launching the Service, the Service will
-        be started and managed by the Hub.
+- `command: (str/Popen list)` - Command for JupyterHub to spawn the service. - Only use this if the service should be a subprocess. - If command is not specified, the Service is assumed to be managed
+  externally. - If a command is specified for launching the Service, the Service will
+  be started and managed by the Hub.
 - `environment: dict` - additional environment variables for the Service.
 - `user: str` - the name of a system user to manage the Service. If
   unspecified, run as the same user as the Hub.
@@ -89,11 +86,20 @@ Hub-Managed Service would include:
 This example would be configured as follows in `jupyterhub_config.py`:
 
 ```python
+c.JupyterHub.load_roles = [
+    {
+        "name": "idle-culler",
+        "scopes": [
+            "read:users:activity", # read user last_activity
+            "servers", # start and stop servers
+            # 'admin:users' # needed if culling idle users as well
+        ]
+    }
+
 c.JupyterHub.services = [
     {
-        'name': 'cull-idle',
-        'admin': True,
-        'command': [sys.executable, '/path/to/cull-idle.py', '--timeout']
+        'name': 'idle-culler',
+        'command': [sys.executable, '-m', 'jupyterhub_idle_culler', '--timeout=3600']
     }
 ]
 ```
@@ -103,9 +109,9 @@ parameters, which describe the environment needed to start the Service process:
 
 - `environment: dict` - additional environment variables for the Service.
 - `user: str` - name of the user to run the server if different from the Hub.
-   Requires Hub to be root.
+  Requires Hub to be root.
 - `cwd: path` directory in which to run the Service, if different from the
-   Hub directory.
+  Hub directory.
 
 The Hub will pass the following environment variables to launch the Service:
 
@@ -117,21 +123,21 @@ JUPYTERHUB_BASE_URL:       Base URL of the Hub (https://mydomain[:port]/)
 JUPYTERHUB_SERVICE_PREFIX: URL path prefix of this service (/services/:service-name/)
 JUPYTERHUB_SERVICE_URL:    Local URL where the service is expected to be listening.
                            Only for proxied web services.
+JUPYTERHUB_OAUTH_SCOPES:   JSON-serialized list of scopes to use for allowing access to the service.
 ```
 
 For the previous 'cull idle' Service example, these environment variables
 would be passed to the Service when the Hub starts the 'cull idle' Service:
 
 ```bash
-JUPYTERHUB_SERVICE_NAME: 'cull-idle'
+JUPYTERHUB_SERVICE_NAME: 'idle-culler'
 JUPYTERHUB_API_TOKEN: API token assigned to the service
 JUPYTERHUB_API_URL: http://127.0.0.1:8080/hub/api
 JUPYTERHUB_BASE_URL: https://mydomain[:port]
-JUPYTERHUB_SERVICE_PREFIX: /services/cull-idle/
+JUPYTERHUB_SERVICE_PREFIX: /services/idle-culler/
 ```
 
-See the JupyterHub GitHub repo for additional information about the
-[`cull-idle` example](https://github.com/jupyterhub/jupyterhub/tree/master/examples/cull-idle).
+See the GitHub repo for additional information about the [jupyterhub_idle_culler][].
 
 ## Externally-Managed Services
 
@@ -151,6 +157,8 @@ c.JupyterHub.services = [
     {
         'name': 'my-web-service',
         'url': 'https://10.0.1.1:1984',
+        # any secret >8 characters, you'll use api_token to
+        # authenticate api requests to the hub from your service
         'api_token': 'super-secret',
     }
 ]
@@ -198,16 +206,14 @@ can be used by services. You may go beyond this reference implementation and
 create custom hub-authenticating clients and services. We describe the process
 below.
 
-The reference, or base, implementation is the [`HubAuth`][HubAuth] class,
+The reference, or base, implementation is the [`HubAuth`][hubauth] class,
 which implements the requests to the Hub.
 
 To use HubAuth, you must set the `.api_token`, either programmatically when constructing the class,
 or via the `JUPYTERHUB_API_TOKEN` environment variable.
 
-Most of the logic for authentication implementation is found in the 
-[`HubAuth.user_for_cookie`][HubAuth.user_for_cookie] 
-and in the 
-[`HubAuth.user_for_token`][HubAuth.user_for_token]
+Most of the logic for authentication implementation is found in the
+[`HubAuth.user_for_token`][hubauth.user_for_token]
 methods, which makes a request of the Hub, and returns:
 
 - None, if no user could be identified, or
@@ -217,7 +223,9 @@ methods, which makes a request of the Hub, and returns:
   {
     "name": "username",
     "groups": ["list", "of", "groups"],
-    "admin": False, # or True
+    "scopes": [
+        "access:users:servers!server=username/",
+    ],
   }
   ```
 
@@ -232,63 +240,17 @@ configurable by the `cookie_cache_max_age` setting (default: five minutes).
 For example, you have a Flask service that returns information about a user.
 JupyterHub's HubAuth class can be used to authenticate requests to the Flask
 service. See the `service-whoami-flask` example in the
-[JupyterHub GitHub repo](https://github.com/jupyterhub/jupyterhub/tree/master/examples/service-whoami-flask)
+[JupyterHub GitHub repo](https://github.com/jupyterhub/jupyterhub/tree/HEAD/examples/service-whoami-flask)
 for more details.
 
-```python
-from functools import wraps
-import json
-import os
-from urllib.parse import quote
-
-from flask import Flask, redirect, request, Response
-
-from jupyterhub.services.auth import HubAuth
-
-prefix = os.environ.get('JUPYTERHUB_SERVICE_PREFIX', '/')
-
-auth = HubAuth(
-    api_token=os.environ['JUPYTERHUB_API_TOKEN'],
-    cache_max_age=60,
-)
-
-app = Flask(__name__)
-
-
-def authenticated(f):
-    """Decorator for authenticating with the Hub"""
-    @wraps(f)
-    def decorated(*args, **kwargs):
-        cookie = request.cookies.get(auth.cookie_name)
-        token = request.headers.get(auth.auth_header_name)
-        if cookie:
-            user = auth.user_for_cookie(cookie)
-        elif token:
-            user = auth.user_for_token(token)
-        else:
-            user = None
-        if user:
-            return f(user, *args, **kwargs)
-        else:
-            # redirect to login url on failed auth
-            return redirect(auth.login_url + '?next=%s' % quote(request.path))
-    return decorated
-
-
-@app.route(prefix)
-@authenticated
-def whoami(user):
-    return Response(
-        json.dumps(user, indent=1, sort_keys=True),
-        mimetype='application/json',
-        )
+```{literalinclude} ../../../examples/service-whoami-flask/whoami-flask.py
+:language: python
 ```
 
-
 ### Authenticating tornado services with JupyterHub
 
 Since most Jupyter services are written with tornado,
-we include a mixin class, [`HubAuthenticated`][HubAuthenticated],
+we include a mixin class, [`HubAuthenticated`][hubauthenticated],
 for quickly authenticating your own tornado services with JupyterHub.
 
 Tornado's `@web.authenticated` method calls a Handler's `.get_current_user`
@@ -309,66 +271,93 @@ class MyHandler(HubAuthenticated, web.RequestHandler):
         ...
 ```
 
-
 The HubAuth will automatically load the desired configuration from the Service
 environment variables.
 
-If you want to limit user access, you can whitelist users through either the
+If you want to limit user access, you can specify allowed users through either the
 `.hub_users` attribute or `.hub_groups`. These are sets that check against the
 username and user group list, respectively. If a user matches neither the user
 list nor the group list, they will not be allowed access. If both are left
 undefined, then any user will be allowed.
 
-
 ### Implementing your own Authentication with JupyterHub
 
 If you don't want to use the reference implementation
 (e.g. you find the implementation a poor fit for your Flask app),
 you can implement authentication via the Hub yourself.
-We recommend looking at the [`HubAuth`][HubAuth] class implementation for reference,
+JupyterHub is a standard OAuth2 provider,
+so you can use any OAuth 2 client implementation appropriate for your toolkit.
+See the [FastAPI example][] for an example of using JupyterHub as an OAuth provider with [FastAPI][],
+without using any code imported from JupyterHub.
+
+On completion of OAuth, you will have an access token for JupyterHub,
+which can be used to identify the user and the permissions (scopes)
+the user has authorized for your service.
+
+You will only get to this stage if the user has the required `access:services!service=$service-name` scope.
+
+To retrieve the user model for the token, make a request to `GET /hub/api/user` with the token in the Authorization header.
+For example, using flask:
+
+```{literalinclude} ../../../examples/service-whoami-flask/whoami-flask.py
+:language: python
+```
+
+We recommend looking at the [`HubOAuth`][huboauth] class implementation for reference,
 and taking note of the following process:
 
-1. retrieve the cookie `jupyterhub-services` from the request.
-2. Make an API request `GET /hub/api/authorizations/cookie/jupyterhub-services/cookie-value`,
-    where cookie-value is the url-encoded value of the `jupyterhub-services` cookie.
-    This request must be authenticated with a Hub API token in the `Authorization` header.
-    For example, with [requests][]:
+1. retrieve the token from the request.
+2. Make an API request `GET /hub/api/user`,
+   with the token in the `Authorization` header.
 
-    ```python
-    r = requests.get(
-        '/'.join((["http://127.0.0.1:8081/hub/api",
-                   "authorizations/cookie/jupyterhub-services",
-                   quote(encrypted_cookie, safe=''),
-        ]),
-        headers = {
-            'Authorization' : 'token %s' % api_token,
-        },
-    )
-    r.raise_for_status()
-    user = r.json()
-    ```
+   For example, with [requests][]:
+
+   ```python
+   r = requests.get(
+       "http://127.0.0.1:8081/hub/api/user",
+       headers = {
+           'Authorization' : f'token {api_token}',
+       },
+   )
+   r.raise_for_status()
+   user = r.json()
+   ```
 
 3. On success, the reply will be a JSON model describing the user:
 
-   ```json
+   ```python
    {
      "name": "inara",
+     # groups  may be omitted, depending on permissions
      "groups": ["serenity", "guild"],
-
+     # scopes is new in JupyterHub 2.0
+     "scopes": [
+       "access:services",
+       "read:users:name",
+       "read:users!user=inara",
+       "..."
+     ]
    }
    ```
 
+The `scopes` field can be used to manage access.
+Note: a user will have access to a service to complete oauth access to the service for the first time.
+Individual permissions may be revoked at any later point without revoking the token,
+in which case the `scopes` field in this model should be checked on each access.
+The default required scopes for access are available from `hub_auth.oauth_scopes` or `$JUPYTERHUB_OAUTH_SCOPES`.
+
 An example of using an Externally-Managed Service and authentication is
 in [nbviewer README][nbviewer example] section on securing the notebook viewer,
-and an example of its configuration is found [here](https://github.com/jupyter/nbviewer/blob/master/nbviewer/providers/base.py#L94).
+and an example of its configuration is found [here](https://github.com/jupyter/nbviewer/blob/ed942b10a52b6259099e2dd687930871dc8aac22/nbviewer/providers/base.py#L95).
 nbviewer can also be run as a Hub-Managed Service as described [nbviewer README][nbviewer example]
 section on securing the notebook viewer.
 
-
 [requests]: http://docs.python-requests.org/en/master/
 [services_auth]: ../api/services.auth.html
-[HubAuth]: ../api/services.auth.html#jupyterhub.services.auth.HubAuth
-[HubAuth.user_for_cookie]: ../api/services.auth.html#jupyterhub.services.auth.HubAuth.user_for_cookie
-[HubAuth.user_for_token]: ../api/services.auth.html#jupyterhub.services.auth.HubAuth.user_for_token
-[HubAuthenticated]: ../api/services.auth.html#jupyterhub.services.auth.HubAuthenticated
+[huboauth]: ../api/services.auth.html#jupyterhub.services.auth.HubOAuth
+[hubauth.user_for_token]: ../api/services.auth.html#jupyterhub.services.auth.HubAuth.user_for_token
+[hubauthenticated]: ../api/services.auth.html#jupyterhub.services.auth.HubAuthenticated
 [nbviewer example]: https://github.com/jupyter/nbviewer#securing-the-notebook-viewer
+[fastapi example]: https://github.com/jupyterhub/jupyterhub/tree/HEAD/examples/service-fastapi
+[fastapi]: https://fastapi.tiangolo.com
+[jupyterhub_idle_culler]: https://github.com/jupyterhub/jupyterhub-idle-culler

docs/source/reference/spawners.md

@@ -8,18 +8,17 @@ and a custom Spawner needs to be able to take three actions:
 - poll whether the process is still running
 - stop the process
 
-
 ## Examples
 
 Custom Spawners for JupyterHub can be found on the [JupyterHub wiki](https://github.com/jupyterhub/jupyterhub/wiki/Spawners).
 Some examples include:
 
 - [DockerSpawner](https://github.com/jupyterhub/dockerspawner) for spawning user servers in Docker containers
-  * `dockerspawner.DockerSpawner` for spawning identical Docker containers for
+  - `dockerspawner.DockerSpawner` for spawning identical Docker containers for
     each users
-  * `dockerspawner.SystemUserSpawner` for spawning Docker containers with an
+  - `dockerspawner.SystemUserSpawner` for spawning Docker containers with an
     environment and home directory for each users
-  * both `DockerSpawner` and `SystemUserSpawner` also work with Docker Swarm for
+  - both `DockerSpawner` and `SystemUserSpawner` also work with Docker Swarm for
     launching containers on remote machines
 - [SudoSpawner](https://github.com/jupyterhub/sudospawner) enables JupyterHub to
   run without being root, by spawning an intermediate process via `sudo`
@@ -27,9 +26,8 @@ Some examples include:
   servers using batch systems
 - [YarnSpawner](https://github.com/jupyterhub/yarnspawner) for spawning notebook
   servers in YARN containers on a Hadoop cluster
-- [RemoteSpawner](https://github.com/zonca/remotespawner) to spawn notebooks
-  and a remote server and tunnel the port via SSH
-
+- [SSHSpawner](https://github.com/NERSC/sshspawner) to spawn notebooks
+  on a remote server using SSH
 
 ## Spawner control methods
 
@@ -39,14 +37,13 @@ Some examples include:
 Information about the user can be retrieved from `self.user`,
 an object encapsulating the user's name, authentication, and server info.
 
-The return value of `Spawner.start` should be the (ip, port) of the running server.
-
-**NOTE:** When writing coroutines, *never* `yield` in between a database change and a commit.
+The return value of `Spawner.start` should be the `(ip, port)` of the running server,
+or a full URL as a string.
 
 Most `Spawner.start` functions will look similar to this example:
 
 ```python
-def start(self):
+async def start(self):
     self.ip = '127.0.0.1'
     self.port = random_port()
     # get environment variables,
@@ -58,8 +55,10 @@ def start(self):
     cmd.extend(self.cmd)
     cmd.extend(self.get_args())
 
-    yield self._actually_start_server_somehow(cmd, env)
-    return (self.ip, self.port)
+    await self._actually_start_server_somehow(cmd, env)
+    # url may not match self.ip:self.port, but it could!
+    url = self._get_connectable_url()
+    return url
 ```
 
 When `Spawner.start` returns, the single-user server process should actually be running,
@@ -67,6 +66,48 @@ not just requested. JupyterHub can handle `Spawner.start` being very slow
 (such as PBS-style batch queues, or instantiating whole AWS instances)
 via relaxing the `Spawner.start_timeout` config value.
 
+#### Note on IPs and ports
+
+`Spawner.ip` and `Spawner.port` attributes set the _bind_ url,
+which the single-user server should listen on
+(passed to the single-user process via the `JUPYTERHUB_SERVICE_URL` environment variable).
+The _return_ value is the ip and port (or full url) the Hub should _connect to_.
+These are not necessarily the same, and usually won't be in any Spawner that works with remote resources or containers.
+
+The default for Spawner.ip, and Spawner.port is `127.0.0.1:{random}`,
+which is appropriate for Spawners that launch local processes,
+where everything is on localhost and each server needs its own port.
+For remote or container Spawners, it will often make sense to use a different value,
+such as `ip = '0.0.0.0'` and a fixed port, e.g. `8888`.
+The defaults can be changed in the class,
+preserving configuration with traitlets:
+
+```python
+from traitlets import default
+from jupyterhub.spawner import Spawner
+
+class MySpawner(Spawner):
+    @default("ip")
+    def _default_ip(self):
+        return '0.0.0.0'
+
+    @default("port")
+    def _default_port(self):
+        return 8888
+
+    async def start(self):
+        env = self.get_env()
+        cmd = []
+        # get jupyterhub command to run,
+        # typically ['jupyterhub-singleuser']
+        cmd.extend(self.cmd)
+        cmd.extend(self.get_args())
+
+        remote_server_info = await self._actually_start_server_somehow(cmd, env)
+        url = self.get_public_url_from(remote_server_info)
+        return url
+```
+
 ### Spawner.poll
 
 `Spawner.poll` should check if the spawner is still running.
@@ -74,13 +115,12 @@ It should return `None` if it is still running,
 and an integer exit status, otherwise.
 
 For the local process case, `Spawner.poll` uses `os.kill(PID, 0)`
-to check if the local process is still running.
+to check if the local process is still running. On Windows, it uses `psutil.pid_exists`.
 
 ### Spawner.stop
 
 `Spawner.stop` should stop the process. It must be a tornado coroutine, which should return when the process has finished exiting.
 
-
 ## Spawner state
 
 JupyterHub should be able to stop and restart without tearing down
@@ -112,7 +152,6 @@ def clear_state(self):
     self.pid = 0
 ```
 
-
 ## Spawner options form
 
 (new in 0.4)
@@ -129,7 +168,7 @@ If the `Spawner.options_form` is defined, when a user tries to start their serve
 
 If `Spawner.options_form` is undefined, the user's server is spawned directly, and no spawn page is rendered.
 
-See [this example](https://github.com/jupyterhub/jupyterhub/blob/master/examples/spawn-form/jupyterhub_config.py) for a form that allows custom CLI args for the local spawner.
+See [this example](https://github.com/jupyterhub/jupyterhub/blob/HEAD/examples/spawn-form/jupyterhub_config.py) for a form that allows custom CLI args for the local spawner.
 
 ### `Spawner.options_from_form`
 
@@ -170,8 +209,7 @@ which would return:
 
 When `Spawner.start` is called, this dictionary is accessible as `self.user_options`.
 
-
-[Spawner]: https://github.com/jupyterhub/jupyterhub/blob/master/jupyterhub/spawner.py
+[spawner]: https://github.com/jupyterhub/jupyterhub/blob/HEAD/jupyterhub/spawner.py
 
 ## Writing a custom spawner
 
@@ -212,6 +250,72 @@ Additionally, configurable attributes for your spawner will
 appear in jupyterhub help output and auto-generated configuration files
 via `jupyterhub --generate-config`.
 
+## Environment variables and command-line arguments
+
+Spawners mainly do one thing: launch a command in an environment.
+
+The command-line is constructed from user configuration:
+
+- Spawner.cmd (default: `['jupterhub-singleuser']`)
+- Spawner.args (cli args to pass to the cmd, default: empty)
+
+where the configuration:
+
+```python
+c.Spawner.cmd = ["my-singleuser-wrapper"]
+c.Spawner.args = ["--debug", "--flag"]
+```
+
+would result in spawning the command:
+
+```bash
+my-singleuser-wrapper --debug --flag
+```
+
+The `Spawner.get_args()` method is how Spawner.args is accessed,
+and can be used by Spawners to customize/extend user-provided arguments.
+
+Prior to 2.0, JupyterHub unconditionally added certain options _if specified_ to the command-line,
+such as `--ip={Spawner.ip}` and `--port={Spawner.port}`.
+These have now all been moved to environment variables,
+and from JupyterHub 2.0,
+the command-line launched by JupyterHub is fully specified by overridable configuration `Spawner.cmd + Spawner.args`.
+
+Most process configuration is passed via environment variables.
+Additional variables can be specified via the `Spawner.environment` configuration.
+
+The process environment is returned by `Spawner.get_env`, which specifies the following environment variables:
+
+- JUPYTERHUB*SERVICE_URL - the \_bind* url where the server should launch its http server (`http://127.0.0.1:12345`).
+  This includes Spawner.ip and Spawner.port; _new in 2.0, prior to 2.0 ip,port were on the command-line and only if specified_
+- JUPYTERHUB_SERVICE_PREFIX - the URL prefix the service will run on (e.g. `/user/name/`)
+- JUPYTERHUB_USER - the JupyterHub user's username
+- JUPYTERHUB_SERVER_NAME - the server's name, if using named servers (default server has an empty name)
+- JUPYTERHUB_API_URL - the full url for the JupyterHub API (http://17.0.0.1:8001/hub/api)
+- JUPYTERHUB_BASE_URL - the base url of the whole jupyterhub deployment, i.e. the bit before `hub/` or `user/`,
+  as set by c.JupyterHub.base_url (default: `/`)
+- JUPYTERHUB_API_TOKEN - the API token the server can use to make requests to the Hub.
+  This is also the OAuth client secret.
+- JUPYTERHUB_CLIENT_ID - the OAuth client ID for authenticating visitors.
+- JUPYTERHUB_OAUTH_CALLBACK_URL - the callback URL to use in oauth, typically `/user/:name/oauth_callback`
+
+Optional environment variables, depending on configuration:
+
+- JUPYTERHUB*SSL*[KEYFILE|CERTFILE|CLIENT_CI] - SSL configuration, when internal_ssl is enabled
+- JUPYTERHUB_ROOT_DIR - the root directory of the server (notebook directory), when Spawner.notebook_dir is defined (new in 2.0)
+- JUPYTERHUB_DEFAULT_URL - the default URL for the server (for redirects from /user/:name/),
+  if Spawner.default_url is defined
+  (new in 2.0, previously passed via cli)
+- JUPYTERHUB_DEBUG=1 - generic debug flag, sets maximum log level when Spawner.debug is True
+  (new in 2.0, previously passed via cli)
+- JUPYTERHUB_DISABLE_USER_CONFIG=1 - disable loading user config,
+  sets maximum log level when Spawner.debug is True (new in 2.0,
+  previously passed via cli)
+
+- JUPYTERHUB*[MEM|CPU]*[LIMIT_GUARANTEE] - the values of cpu and memory limits and guarantees.
+  These are not expected to be enforced by the process,
+  but are made available as a hint,
+  e.g. for resource monitoring extensions.
 
 ## Spawners, resource limits, and guarantees (Optional)
 
@@ -224,10 +328,9 @@ support for them**. For example, LocalProcessSpawner, the default
 spawner, does not support limits and guarantees. One of the spawners
 that supports limits and guarantees is the `systemdspawner`.
 
-
 ### Memory Limits & Guarantees
 
-`c.Spawner.mem_limit`: A **limit** specifies the *maximum amount of memory*
+`c.Spawner.mem_limit`: A **limit** specifies the _maximum amount of memory_
 that may be allocated, though there is no promise that the maximum amount will
 be available. In supported spawners, you can set `c.Spawner.mem_limit` to
 limit the total amount of memory that a single-user notebook server can
@@ -235,8 +338,8 @@ allocate. Attempting to use more memory than this limit will cause errors. The
 single-user notebook server can discover its own memory limit by looking at
 the environment variable `MEM_LIMIT`, which is specified in absolute bytes.
 
-`c.Spawner.mem_guarantee`: Sometimes, a **guarantee** of a *minimum amount of
-memory* is desirable. In this case, you can set `c.Spawner.mem_guarantee` to
+`c.Spawner.mem_guarantee`: Sometimes, a **guarantee** of a _minimum amount of
+memory_ is desirable. In this case, you can set `c.Spawner.mem_guarantee` to
 to provide a guarantee that at minimum this much memory will always be
 available for the single-user notebook server to use. The environment variable
 `MEM_GUARANTEE` will also be set in the single-user notebook server.
@@ -271,7 +374,7 @@ utilize these certs, there are two methods of interest on the base `Spawner`
 class: `.create_certs` and `.move_certs`.
 
 The first method, `.create_certs` will sign a key-cert pair using an internally
-trusted authority for notebooks.  During this process, `.create_certs` can
+trusted authority for notebooks. During this process, `.create_certs` can
 apply `ip` and `dns` name information to the cert via an `alt_names` `kwarg`.
 This is used for certificate authentication (verification). Without proper
 verification, the `Notebook` will be unable to communicate with the `Hub` and

docs/source/reference/templates.md

@@ -1,8 +1,8 @@
 # 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
-example, to be defined once and incorporated into all pages.  By providing
+[Jinja](http://jinja.pocoo.org/) 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
 appearance.
 
@@ -10,7 +10,7 @@ appearance.
 
 JupyterHub will look for custom templates in all of the paths in the
 `JupyterHub.template_paths` configuration option, falling back on the
-[default templates](https://github.com/jupyterhub/jupyterhub/tree/master/share/jupyterhub/templates)
+[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
 explicitly included in `template_paths`. You may override as many
@@ -20,8 +20,8 @@ or as few templates as you desire.
 
 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/master/share/jupyterhub/templates)
+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
 interface easily.
 
@@ -32,8 +32,8 @@ In general, a child template can extend a base template, `page.html`, by beginni
 ```
 
 This works, unless you are trying to extend the default template for the same
-file name.  Starting in version 0.9, you may refer to the base file with a
-`templates/` prefix.  Thus, if you are writing a custom `page.html`, start the
+file name. Starting in version 0.9, you may refer to the base file with a
+`templates/` prefix. Thus, if you are writing a custom `page.html`, start the
 file with this block:
 
 ```html
@@ -41,7 +41,7 @@ file with this block:
 ```
 
 By defining `block`s with same name as in the base template, child templates
-can replace those sections with custom content.  The content from the base
+can replace those sections with custom content. The content from the base
 template can be included with the `{{ super() }}` directive.
 
 ### Example
@@ -52,10 +52,7 @@ text about the server starting up, place this content in a file named
 `JupyterHub.template_paths` configuration option.
 
 ```html
-{% extends "templates/spawn_pending.html" %}
-
-{% block message %}
-{{ super() }}
+{% extends "templates/spawn_pending.html" %} {% block message %} {{ super() }}
 <p>Patience is a virtue.</p>
 {% endblock %}
 ```
@@ -69,9 +66,8 @@ To add announcements to be displayed on a page, you have two options:
 
 ### Announcement Configuration Variables
 
-If you set the configuration variable `JupyterHub.template_vars =
-{'announcement': 'some_text'}`, the given `some_text` will be placed on
-the top of all pages.  The more specific variables
+If you set the configuration variable `JupyterHub.template_vars = {'announcement': 'some_text'}`, the given `some_text` will be placed on
+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).
@@ -79,13 +75,12 @@ Note that changing these variables require a restart, unlike direct
 template extension.
 
 You can get the same effect by extending templates, which allows you
-to update the messages without restarting.  Set
+to update the messages without restarting. Set
 `c.JupyterHub.template_paths` as mentioned above, and then create a
 template (for example, `login.html`) with:
 
 ```html
-{% extends "templates/login.html" %}
-{% set announcement = 'some message' %}
+{% extends "templates/login.html" %} {% set announcement = 'some message' %}
 ```
 
 Extending `page.html` puts the message on all pages, but note that

docs/source/reference/urls.md

@@ -11,8 +11,6 @@ All authenticated handlers redirect to `/hub/login` to login users
 prior to being redirected back to the originating page.
 The returned request should preserve all query parameters.
 
-
-
 ## `/`
 
 The top-level request is always a simple redirect to `/hub/`,
@@ -61,7 +59,7 @@ for starting and stopping the user's server.
 If named servers are enabled, there will be some additional
 tools for management of named servers.
 
-*Version added: 1.0* named server UI is new in 1.0.
+_Version added: 1.0_ named server UI is new in 1.0.
 
 ## `/hub/login`
 
@@ -111,7 +109,7 @@ not the Hub.
 The username is the first part and, if using named servers,
 the server name is the second part.
 
-If the user's server is *not* running, this will be redirected to `/hub/user/:username/...`
+If the user's server is _not_ running, this will be redirected to `/hub/user/:username/...`
 
 ## `/hub/user/:username[/:servername]`
 
@@ -123,8 +121,8 @@ Handling this URL is the most complicated condition in JupyterHub,
 because there can be many states:
 
 1. server is not active
-  a. user matches
-  b. user doesn't match
+   a. user matches
+   b. user doesn't match
 2. server is ready
 3. server is pending, but not ready
 
@@ -146,7 +144,7 @@ without additional user action (i.e. clicking the link on the page)
 
 ![Visiting a URL for a server that's not running](../images/not-running.png)
 
-*Version changed: 1.0*
+_Version changed: 1.0_
 
 Prior to 1.0, this URL itself was responsible for spawning servers,
 and served the progress page if it was pending,
@@ -165,7 +163,7 @@ indicating how to spawn the server.
 This is meant to help applications such as JupyterLab
 that are connected to a server that has stopped.
 
-*Version changed: 1.0*
+_Version changed: 1.0_
 
 JupyterHub 0.9 failed these API requests with status 404,
 but 1.0 uses 503.
@@ -207,12 +205,12 @@ and a POST request will trigger the actual spawn and redirect.
 
 ![The spawn form](../images/spawn-form.png)
 
-*Version added: 1.0*
+_Version added: 1.0_
 
 1.0 adds the ability to specify username and servername.
 Prior to 1.0, only `/hub/spawn` was recognized for the default server.
 
-*Version changed: 1.0*
+_Version changed: 1.0_
 
 Prior to 1.0, this page redirected back to `/hub/user/:username`,
 which was responsible for triggering spawn and rendering progress, etc.
@@ -221,7 +219,7 @@ which was responsible for triggering spawn and rendering progress, etc.
 
 ![The spawn pending page](../images/spawn-pending.png)
 
-*Version added: 1.0* this URL is new in JupyterHub 1.0.
+_Version added: 1.0_ this URL is new in JupyterHub 1.0.
 
 This page renders the progress view for the given spawn request.
 Once the server is ready,

docs/source/reference/websecurity.md

@@ -12,17 +12,17 @@ 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
+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 is not necessarily unsuitable for serving **untrusted** users.
 
 Using JupyterHub with **untrusted** users does mean more work by the
 administrator. Much care is required to secure a Hub, with extra caution on
 protecting users from each other as the Hub is serving untrusted users.
 
-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
+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
@@ -40,7 +40,7 @@ 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,
+- A user **does not have permission** to modify their single-user notebook server,
   including:
   - A user **may not** install new packages in the Python environment that runs
     their single-user server.
@@ -49,11 +49,11 @@ ensure that:
     directory that precedes the directory containing `jupyterhub-singleuser`.
   - A user may not modify environment variables (e.g. PATH, PYTHONPATH) for
     their single-user server.
-* A user **may not** modify the configuration of the notebook server
+- A user **may not** modify the configuration of the notebook server
   (the `~/.jupyter` or `JUPYTER_CONFIG_DIR` directory).
 
 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*
+**must never** display user-authored HTML that is neither _sanitized_ nor _sandboxed_
 (e.g. IFramed) to any user that lacks authentication as the author of a file.
 
 ## Mitigate security issues
@@ -85,7 +85,7 @@ admin must enforce.
 ### Prevent spawners from evaluating shell configuration files
 
 For most Spawners, `PATH` is not something users can influence, but care should
-be taken to ensure that the Spawner does *not* evaluate shell configuration
+be taken to ensure that the Spawner does _not_ evaluate shell configuration
 files prior to launching the server.
 
 ### Isolate packages using virtualenv
@@ -125,13 +125,12 @@ versions 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’ve found a security vulnerability in JupyterHub, or any
 Jupyter project, please report it to
-[security@ipython.org](mailto:security@iypthon.org). If you prefer to encrypt
+[security@ipython.org](mailto: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/ipython_security.asc).

docs/source/troubleshooting.md

@@ -4,17 +4,20 @@ When troubleshooting, you may see unexpected behaviors or receive an error
 message. This section provide links for identifying the cause of the
 problem and how to resolve it.
 
-[*Behavior*](#behavior)
+[_Behavior_](#behavior)
+
 - JupyterHub proxy fails to start
 - sudospawner fails to run
-- What is the default behavior when none of the lists (admin, whitelist,
-  group whitelist) are set?
+- 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)
+[_Errors_](#errors)
+
 - 500 error after spawning my single-user server
 
-[*How do I...?*](#how-do-i)
+[_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
@@ -25,7 +28,7 @@ problem and how to resolve it.
 - Toree integration with HDFS rack awareness script
 - Where do I find Docker images and Dockerfiles related to JupyterHub?
 
-[*Troubleshooting commands*](#troubleshooting-commands)
+[_Troubleshooting commands_](#troubleshooting-commands)
 
 ## Behavior
 
@@ -34,8 +37,8 @@ problem and how to resolve it.
 If you have tried to start the JupyterHub proxy and it fails to start:
 
 - check if the JupyterHub IP configuration setting is
-  ``c.JupyterHub.ip = '*'``; if it is, try ``c.JupyterHub.ip = ''``
-- Try starting with ``jupyterhub --ip=0.0.0.0``
+  `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
@@ -55,26 +58,70 @@ or add:
 
 to the config file, `jupyterhub_config.py`.
 
-### What is the default behavior when none of the lists (admin, whitelist, group whitelist) are set?
+### 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
-a password) will be allowed to start a server. The whitelist lets you limit
-this to a particular set of users, and the admin_users lets you specify who
+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 userlist at runtime).
+things like inspect other users' servers, or modify the user list at runtime).
 
 ### JupyterHub Docker container 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 
-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: 
+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
+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`
 
+### 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.
+
+How can I kill the processes that are using these ports?
+
+Run the following command:
+
+    sudo kill -9 $(sudo lsof -t -i:<service_port>)
+
+Where `<service_port>` is the port used by the nbgrader course service. This configuration is specified in `jupyterhub_config.py`.
+
+### 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>`.
+
+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?
+
+When launching JupyterHub with `sudo jupyterhub` I get import errors and my environment variables don't work.
+
+When launching services with `sudo ...` the shell won't have the same environment variables or `PATH`s in place. The most direct way to solve this issue is to use the full path to your python environment and add environment variables. For example:
+
+```bash
+sudo MY_ENV=abc123 \
+  /home/foo/venv/bin/python3 \
+  /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
 
@@ -88,11 +135,11 @@ There are two likely reasons for this:
 
 1. The single-user server cannot connect to the Hub's API (networking
    configuration problems)
-2. The single-user server cannot *authenticate* its requests (invalid token)
+2. The single-user server cannot _authenticate_ its requests (invalid token)
 
 #### Symptoms
 
-The main symptom is a failure to load *any* page served by the single-user
+The main symptom is a failure to load _any_ page served by the single-user
 server, met with a 500 error. This is typically the first page at `/user/<your_name>`
 after logging in or clicking "Start my server". When a single-user notebook server
 receives a request, the notebook server makes an API request to the Hub to
@@ -108,7 +155,7 @@ 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.
 
-If you see 403 (forbidden) like this, it's a token problem:
+If you see 403 (forbidden) like this, it's likely a token problem:
 
 ```
 403 GET /hub/api/authorizations/cookie/jupyterhub-token-name/[secret] (@10.0.1.4) 4.14ms
@@ -152,6 +199,42 @@ After this, when you start your server via JupyterHub, it will build a
 new container. If this was the underlying cause of the issue, you should see
 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`.
+
+### 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:
+
+- **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.
+- **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:
+
+```
+    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:
+
+    export JUPYTERHUB_API_TOKEN=my_secret_token
+    jupyterhub-singleuser
+
+With a docker container, pass in the environment variable with the run command:
+
+    docker run -d \
+      -p 8888:8888 \
+      -e JUPYTERHUB_API_TOKEN=my_secret_token \
+      jupyter/datascience-notebook:latest
+
+[This example](https://github.com/jupyterhub/jupyterhub/tree/HEAD/examples/service-notebook/external) demonstrates how to combine the use of the `jupyterhub-singleuser` environment variables when launching a Notebook as an externally managed service.
 
 ## How do I...?
 
@@ -170,7 +253,6 @@ You would then set in your `jupyterhub_config.py` file the `ssl_key` and
     c.JupyterHub.ssl_cert = your_host-chained.crt
     c.JupyterHub.ssl_key = your_host.key
 
-
 #### Example
 
 Your certificate provider gives you the following files: `example_host.crt`,
@@ -193,7 +275,7 @@ where `ssl_cert` is example-chained.crt and ssl_key to your private key.
 
 Then restart JupyterHub.
 
-See also [JupyterHub SSL encryption](getting-started.md#ssl-encryption).
+See also [JupyterHub SSL encryption](./getting-started/security-basics.html#ssl-encryption).
 
 ### Install JupyterHub without a network connection
 
@@ -252,8 +334,7 @@ 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 whitelist to be an empty list in` jupyterhub_config.py`
-3. Configure admin list to have workshop leaders be listed with administrator privileges.
+2. Configure admin list to have workshop leaders be listed with administrator privileges.
 
 Users will need a GitHub account to login and be authenticated by the Hub.
 
@@ -281,7 +362,6 @@ Or use syslog:
 
     jupyterhub | logger -t jupyterhub
 
-
 ## Troubleshooting commands
 
 The following commands provide additional detail about installed packages,
@@ -324,8 +404,8 @@ SyntaxError: Missing parentheses in call to 'print'
 In order to resolve this issue, there are two potential options.
 
 1. Update HDFS core-site.xml, so the parameter "net.topology.script.file.name" points to a custom
-script (e.g. /etc/hadoop/conf/custom_topology_script.py). Copy the original script and change the first line point
-to a python two installation (e.g. /usr/bin/python).
+   script (e.g. /etc/hadoop/conf/custom_topology_script.py). Copy the original script and change the first line point
+   to a python two installation (e.g. /usr/bin/python).
 2. In spark-env.sh add a Python 2 installation to your path (e.g. export PATH=/opt/anaconda2/bin:$PATH).
 
 ### Where do I find Docker images and Dockerfiles related to JupyterHub?

examples/bootstrap-script/README.md

@@ -1,34 +1,34 @@
 # Bootstrapping your users
 
-Before spawning a notebook to the user, it could be useful to 
+Before spawning a notebook to the user, it could be useful to
 do some preparation work in a bootstrapping process.
 
 Common use cases are:
 
-*Providing writeable storage for LDAP users*
+_Providing writeable storage for LDAP users_
 
 Your Jupyterhub is configured to use the LDAPAuthenticator and DockerSpawer.
 
-* The user has no file directory on the host since your are using LDAP.
-* When a user has no directory and DockerSpawner wants to mount a volume,
-the spawner will use docker to create a directory.
-Since the docker daemon is running as root, the generated directory for the volume 
-mount will not be writeable by the `jovyan` user inside of the container. 
-For the directory to be useful to the user, the permissions on the directory 
-need to be modified for the user to have write access.
+- The user has no file directory on the host since your are using LDAP.
+- When a user has no directory and DockerSpawner wants to mount a volume,
+  the spawner will use docker to create a directory.
+  Since the docker daemon is running as root, the generated directory for the volume
+  mount will not be writeable by the `jovyan` user inside of the container.
+  For the directory to be useful to the user, the permissions on the directory
+  need to be modified for the user to have write access.
 
-*Prepopulating Content*
+_Prepopulating Content_
 
 Another use would be to copy initial content, such as tutorial files or reference
- material, into the user's space when a notebook server is newly spawned.
+material, into the user's space when a notebook server is newly spawned.
 
 You can define your own bootstrap process by implementing a `pre_spawn_hook` on any spawner.
-The Spawner itself is passed as parameter to your hook and you can easily get the contextual information out of the spawning process. 
+The Spawner itself is passed as parameter to your hook and you can easily get the contextual information out of the spawning process.
 
 Similarly, there may be cases where you would like to clean up after a spawner stops.
 You may implement a `post_stop_hook` that is always executed after the spawner stops.
 
-If you implement a hook, make sure that it is *idempotent*. It will be executed every time
+If you implement a hook, make sure that it is _idempotent_. It will be executed every time
 a notebook server is spawned to the user. That means you should somehow
 ensure that things which should run only once are not running again and again.
 For example, before you create a directory, check if it exists.
@@ -41,13 +41,13 @@ Create a directory for the user, if none exists
 
 ```python
 
-# in jupyterhub_config.py  
+# in jupyterhub_config.py
 import os
 def create_dir_hook(spawner):
     username = spawner.user.name # get the username
     volume_path = os.path.join('/volumes/jupyterhub', username)
     if not os.path.exists(volume_path):
-        # create a directory with umask 0755 
+        # create a directory with umask 0755
         # hub and container user must have the same UID to be writeable
         # still readable by other users on the system
         os.mkdir(volume_path, 0o755)
@@ -83,17 +83,17 @@ in a new file in `/etc/sudoers.d`, or simply in `/etc/sudoers`.
 
 All new home directories will be created from `/etc/skel`, so make sure to place any custom homedir-contents in there.
 
-### Example #3 - Run a shell script 
+### Example #3 - Run a shell script
 
-You can specify a plain ole' shell script (or any other executable) to be run 
+You can specify a plain ole' shell script (or any other executable) to be run
 by the bootstrap process.
 
-For example, you can execute a shell script and as first parameter pass the name 
+For example, you can execute a shell script and as first parameter pass the name
 of the user:
 
 ```python
 
-# in jupyterhub_config.py    
+# in jupyterhub_config.py
 from subprocess import check_call
 import os
 def my_script_hook(spawner):
@@ -106,7 +106,7 @@ c.Spawner.pre_spawn_hook = my_script_hook
 
 ```
 
-Here's an example on what you could do in your shell script. See also 
+Here's an example on what you could do in your shell script. See also
 `/examples/bootstrap-script/`
 
 ```bash
@@ -126,7 +126,7 @@ fi
 
 # This example script will do the following:
 # - create one directory for the user $USER in a BASE_DIRECTORY (see below)
-# - create a "tutorials" directory within and download and unzip 
+# - create a "tutorials" directory within and download and unzip
 #   the PythonDataScienceHandbook from GitHub
 
 # Start the Bootstrap Process
@@ -148,9 +148,9 @@ else
     echo "...initial content loading for user ..."
     mkdir $USER_DIRECTORY/tutorials
     cd $USER_DIRECTORY/tutorials
-    wget https://github.com/jakevdp/PythonDataScienceHandbook/archive/master.zip
-    unzip -o master.zip
-    rm master.zip
+    wget https://github.com/jakevdp/PythonDataScienceHandbook/archive/HEAD.zip
+    unzip -o HEAD.zip
+    rm HEAD.zip
 fi
 
 exit 0

examples/bootstrap-script/bootstrap.sh

@@ -40,9 +40,9 @@ else
     echo "...initial content loading for user ..."
     mkdir $USER_DIRECTORY/tutorials
     cd $USER_DIRECTORY/tutorials
-    wget https://github.com/jakevdp/PythonDataScienceHandbook/archive/master.zip
-    unzip -o master.zip
-    rm master.zip
+    wget https://github.com/jakevdp/PythonDataScienceHandbook/archive/HEAD.zip
+    unzip -o HEAD.zip
+    rm HEAD.zip
 fi
 
 exit 0

examples/bootstrap-script/jupyterhub_config.py

@@ -10,7 +10,7 @@ from jupyter_client.localinterfaces import public_ips
 
 
 def create_dir_hook(spawner):
-    """ Create directory """
+    """Create directory"""
     username = spawner.user.name  # get the username
     volume_path = os.path.join('/volumes/jupyterhub', username)
     if not os.path.exists(volume_path):
@@ -20,7 +20,7 @@ def create_dir_hook(spawner):
 
 
 def clean_dir_hook(spawner):
-    """ Delete directory """
+    """Delete directory"""
     username = spawner.user.name  # get the username
     temp_path = os.path.join('/volumes/jupyterhub', username, 'temp')
     if os.path.exists(temp_path) and os.path.isdir(temp_path):

examples/cull-idle/README.md

@@ -1,41 +1,4 @@
-# `cull-idle` Example
+# idle-culler example
 
-The `cull_idle_servers.py` file provides a script to cull and shut down idle
-single-user notebook servers. This script is used when `cull-idle` is run as
-a Service or when it is run manually as a standalone script.
-
-
-## Configure `cull-idle` to run as a Hub-Managed Service
-
-In `jupyterhub_config.py`, add the following dictionary for the `cull-idle`
-Service to the `c.JupyterHub.services` list:
-
-```python
-c.JupyterHub.services = [
-    {
-        'name': 'cull-idle',
-        'admin': True,
-        'command': [sys.executable, 'cull_idle_servers.py', '--timeout=3600'],
-    }
-]
-```
-
-where:
-
-- `'admin': True` indicates that the Service has 'admin' permissions, and
-- `'command'` indicates that the Service will be managed by the Hub.
-
-## Run `cull-idle` manually as a standalone script
-
-This will run `cull-idle` manually. `cull-idle` can be run as a standalone
-script anywhere with access to the Hub, and will periodically check for idle
-servers and shut them down via the Hub's REST API. In order to shutdown the
-servers, the token given to cull-idle must have admin privileges.
-
-Generate an API token and store it in the `JUPYTERHUB_API_TOKEN` environment
-variable. Run `cull_idle_servers.py` manually. 
-
-```bash
-    export JUPYTERHUB_API_TOKEN=$(jupyterhub token)
-    python3 cull_idle_servers.py [--timeout=900] [--url=http://127.0.0.1:8081/hub/api]
-```
+The idle culler has been moved to its own repository at
+[jupyterhub/jupyterhub-idle-culler](https://github.com/jupyterhub/jupyterhub-idle-culler).

examples/cull-idle/cull_idle_servers.py

@@ -1,401 +0,0 @@
-#!/usr/bin/env python3
-"""script to monitor and cull idle single-user servers
-
-Caveats:
-
-last_activity is not updated with high frequency,
-so cull timeout should be greater than the sum of:
-
-- single-user websocket ping interval (default: 30s)
-- JupyterHub.last_activity_interval (default: 5 minutes)
-
-You can run this as a service managed by JupyterHub with this in your config::
-
-
-    c.JupyterHub.services = [
-        {
-            'name': 'cull-idle',
-            'admin': True,
-            'command': [sys.executable, 'cull_idle_servers.py', '--timeout=3600'],
-        }
-    ]
-
-Or run it manually by generating an API token and storing it in `JUPYTERHUB_API_TOKEN`:
-
-    export JUPYTERHUB_API_TOKEN=$(jupyterhub token)
-    python3 cull_idle_servers.py [--timeout=900] [--url=http://127.0.0.1:8081/hub/api]
-
-This script uses the same ``--timeout`` and ``--max-age`` values for
-culling users and users' servers.  If you want a different value for
-users and servers, you should add this script to the services list
-twice, just with different ``name``s, different values, and one with
-the ``--cull-users`` option.
-"""
-import json
-import os
-from datetime import datetime
-from datetime import timezone
-from functools import partial
-
-try:
-    from urllib.parse import quote
-except ImportError:
-    from urllib import quote
-
-import dateutil.parser
-
-from tornado.gen import coroutine, multi
-from tornado.locks import Semaphore
-from tornado.log import app_log
-from tornado.httpclient import AsyncHTTPClient, HTTPRequest
-from tornado.ioloop import IOLoop, PeriodicCallback
-from tornado.options import define, options, parse_command_line
-
-
-def parse_date(date_string):
-    """Parse a timestamp
-
-    If it doesn't have a timezone, assume utc
-
-    Returned datetime object will always be timezone-aware
-    """
-    dt = dateutil.parser.parse(date_string)
-    if not dt.tzinfo:
-        # assume naïve timestamps are UTC
-        dt = dt.replace(tzinfo=timezone.utc)
-    return dt
-
-
-def format_td(td):
-    """
-    Nicely format a timedelta object
-
-    as HH:MM:SS
-    """
-    if td is None:
-        return "unknown"
-    if isinstance(td, str):
-        return td
-    seconds = int(td.total_seconds())
-    h = seconds // 3600
-    seconds = seconds % 3600
-    m = seconds // 60
-    seconds = seconds % 60
-    return "{h:02}:{m:02}:{seconds:02}".format(h=h, m=m, seconds=seconds)
-
-
-@coroutine
-def cull_idle(
-    url, api_token, inactive_limit, cull_users=False, max_age=0, concurrency=10
-):
-    """Shutdown idle single-user servers
-
-    If cull_users, inactive *users* will be deleted as well.
-    """
-    auth_header = {'Authorization': 'token %s' % api_token}
-    req = HTTPRequest(url=url + '/users', headers=auth_header)
-    now = datetime.now(timezone.utc)
-    client = AsyncHTTPClient()
-
-    if concurrency:
-        semaphore = Semaphore(concurrency)
-
-        @coroutine
-        def fetch(req):
-            """client.fetch wrapped in a semaphore to limit concurrency"""
-            yield semaphore.acquire()
-            try:
-                return (yield client.fetch(req))
-            finally:
-                yield semaphore.release()
-
-    else:
-        fetch = client.fetch
-
-    resp = yield fetch(req)
-    users = json.loads(resp.body.decode('utf8', 'replace'))
-    futures = []
-
-    @coroutine
-    def handle_server(user, server_name, server, max_age, inactive_limit):
-        """Handle (maybe) culling a single server
-
-        "server" is the entire server model from the API.
-
-        Returns True if server is now stopped (user removable),
-        False otherwise.
-        """
-        log_name = user['name']
-        if server_name:
-            log_name = '%s/%s' % (user['name'], server_name)
-        if server.get('pending'):
-            app_log.warning(
-                "Not culling server %s with pending %s", log_name, server['pending']
-            )
-            return False
-
-        # jupyterhub < 0.9 defined 'server.url' once the server was ready
-        # as an *implicit* signal that the server was ready.
-        # 0.9 adds a dedicated, explicit 'ready' field.
-        # By current (0.9) definitions, servers that have no pending
-        # events and are not ready shouldn't be in the model,
-        # but let's check just to be safe.
-
-        if not server.get('ready', bool(server['url'])):
-            app_log.warning(
-                "Not culling not-ready not-pending server %s: %s", log_name, server
-            )
-            return False
-
-        if server.get('started'):
-            age = now - parse_date(server['started'])
-        else:
-            # started may be undefined on jupyterhub < 0.9
-            age = None
-
-        # check last activity
-        # last_activity can be None in 0.9
-        if server['last_activity']:
-            inactive = now - parse_date(server['last_activity'])
-        else:
-            # no activity yet, use start date
-            # last_activity may be None with jupyterhub 0.9,
-            # which introduces the 'started' field which is never None
-            # for running servers
-            inactive = age
-
-        # CUSTOM CULLING TEST CODE HERE
-        # Add in additional server tests here.  Return False to mean "don't
-        # cull", True means "cull immediately", or, for example, update some
-        # other variables like inactive_limit.
-        #
-        # Here, server['state'] is the result of the get_state method
-        # on the spawner.  This does *not* contain the below by
-        # default, you may have to modify your spawner to make this
-        # work.  The `user` variable is the user model from the API.
-        #
-        # if server['state']['profile_name'] == 'unlimited'
-        #     return False
-        # inactive_limit = server['state']['culltime']
-
-        should_cull = (
-            inactive is not None and inactive.total_seconds() >= inactive_limit
-        )
-        if should_cull:
-            app_log.info(
-                "Culling server %s (inactive for %s)", log_name, format_td(inactive)
-            )
-
-        if max_age and not should_cull:
-            # only check started if max_age is specified
-            # so that we can still be compatible with jupyterhub 0.8
-            # which doesn't define the 'started' field
-            if age is not None and age.total_seconds() >= max_age:
-                app_log.info(
-                    "Culling server %s (age: %s, inactive for %s)",
-                    log_name,
-                    format_td(age),
-                    format_td(inactive),
-                )
-                should_cull = True
-
-        if not should_cull:
-            app_log.debug(
-                "Not culling server %s (age: %s, inactive for %s)",
-                log_name,
-                format_td(age),
-                format_td(inactive),
-            )
-            return False
-
-        if server_name:
-            # culling a named server
-            delete_url = url + "/users/%s/servers/%s" % (
-                quote(user['name']),
-                quote(server['name']),
-            )
-        else:
-            delete_url = url + '/users/%s/server' % quote(user['name'])
-
-        req = HTTPRequest(url=delete_url, method='DELETE', headers=auth_header)
-        resp = yield fetch(req)
-        if resp.code == 202:
-            app_log.warning("Server %s is slow to stop", log_name)
-            # return False to prevent culling user with pending shutdowns
-            return False
-        return True
-
-    @coroutine
-    def handle_user(user):
-        """Handle one user.
-
-        Create a list of their servers, and async exec them.  Wait for
-        that to be done, and if all servers are stopped, possibly cull
-        the user.
-        """
-        # shutdown servers first.
-        # Hub doesn't allow deleting users with running servers.
-        # jupyterhub 0.9 always provides a 'servers' model.
-        # 0.8 only does this when named servers are enabled.
-        if 'servers' in user:
-            servers = user['servers']
-        else:
-            # jupyterhub < 0.9 without named servers enabled.
-            # create servers dict with one entry for the default server
-            # from the user model.
-            # only if the server is running.
-            servers = {}
-            if user['server']:
-                servers[''] = {
-                    'last_activity': user['last_activity'],
-                    'pending': user['pending'],
-                    'url': user['server'],
-                }
-        server_futures = [
-            handle_server(user, server_name, server, max_age, inactive_limit)
-            for server_name, server in servers.items()
-        ]
-        results = yield multi(server_futures)
-        if not cull_users:
-            return
-        # some servers are still running, cannot cull users
-        still_alive = len(results) - sum(results)
-        if still_alive:
-            app_log.debug(
-                "Not culling user %s with %i servers still alive",
-                user['name'],
-                still_alive,
-            )
-            return False
-
-        should_cull = False
-        if user.get('created'):
-            age = now - parse_date(user['created'])
-        else:
-            # created may be undefined on jupyterhub < 0.9
-            age = None
-
-        # check last activity
-        # last_activity can be None in 0.9
-        if user['last_activity']:
-            inactive = now - parse_date(user['last_activity'])
-        else:
-            # no activity yet, use start date
-            # last_activity may be None with jupyterhub 0.9,
-            # which introduces the 'created' field which is never None
-            inactive = age
-
-        should_cull = (
-            inactive is not None and inactive.total_seconds() >= inactive_limit
-        )
-        if should_cull:
-            app_log.info("Culling user %s (inactive for %s)", user['name'], inactive)
-
-        if max_age and not should_cull:
-            # only check created if max_age is specified
-            # so that we can still be compatible with jupyterhub 0.8
-            # which doesn't define the 'started' field
-            if age is not None and age.total_seconds() >= max_age:
-                app_log.info(
-                    "Culling user %s (age: %s, inactive for %s)",
-                    user['name'],
-                    format_td(age),
-                    format_td(inactive),
-                )
-                should_cull = True
-
-        if not should_cull:
-            app_log.debug(
-                "Not culling user %s (created: %s, last active: %s)",
-                user['name'],
-                format_td(age),
-                format_td(inactive),
-            )
-            return False
-
-        req = HTTPRequest(
-            url=url + '/users/%s' % user['name'], method='DELETE', headers=auth_header
-        )
-        yield fetch(req)
-        return True
-
-    for user in users:
-        futures.append((user['name'], handle_user(user)))
-
-    for (name, f) in futures:
-        try:
-            result = yield f
-        except Exception:
-            app_log.exception("Error processing %s", name)
-        else:
-            if result:
-                app_log.debug("Finished culling %s", name)
-
-
-if __name__ == '__main__':
-    define(
-        'url',
-        default=os.environ.get('JUPYTERHUB_API_URL'),
-        help="The JupyterHub API URL",
-    )
-    define('timeout', default=600, help="The idle timeout (in seconds)")
-    define(
-        'cull_every',
-        default=0,
-        help="The interval (in seconds) for checking for idle servers to cull",
-    )
-    define(
-        'max_age',
-        default=0,
-        help="The maximum age (in seconds) of servers that should be culled even if they are active",
-    )
-    define(
-        'cull_users',
-        default=False,
-        help="""Cull users in addition to servers.
-                This is for use in temporary-user cases such as tmpnb.""",
-    )
-    define(
-        'concurrency',
-        default=10,
-        help="""Limit the number of concurrent requests made to the Hub.
-
-                Deleting a lot of users at the same time can slow down the Hub,
-                so limit the number of API requests we have outstanding at any given time.
-                """,
-    )
-
-    parse_command_line()
-    if not options.cull_every:
-        options.cull_every = options.timeout // 2
-    api_token = os.environ['JUPYTERHUB_API_TOKEN']
-
-    try:
-        AsyncHTTPClient.configure("tornado.curl_httpclient.CurlAsyncHTTPClient")
-    except ImportError as e:
-        app_log.warning(
-            "Could not load pycurl: %s\n"
-            "pycurl is recommended if you have a large number of users.",
-            e,
-        )
-
-    loop = IOLoop.current()
-    cull = partial(
-        cull_idle,
-        url=options.url,
-        api_token=api_token,
-        inactive_limit=options.timeout,
-        cull_users=options.cull_users,
-        max_age=options.max_age,
-        concurrency=options.concurrency,
-    )
-    # schedule first cull immediately
-    # because PeriodicCallback doesn't start until the end of the first interval
-    loop.add_callback(cull)
-    # schedule periodic cull
-    pc = PeriodicCallback(cull, 1e3 * options.cull_every)
-    pc.start()
-    try:
-        loop.start()
-    except KeyboardInterrupt:
-        pass

examples/cull-idle/jupyterhub_config.py

@@ -1,11 +0,0 @@
-import sys
-
-# run cull-idle as a service
-
-c.JupyterHub.services = [
-    {
-        'name': 'cull-idle',
-        'admin': True,
-        'command': [sys.executable, 'cull_idle_servers.py', '--timeout=3600'],
-    }
-]

examples/external-oauth/README.md

@@ -16,63 +16,62 @@ implementations in other web servers or languages.
 
 ## Run the example
 
-1. generate an API token:
+1.  generate an API token:
 
         export JUPYTERHUB_API_TOKEN=$(openssl rand -hex 32)
 
-2. launch a version of the the whoami service.
-   For `whoami-oauth`:
+2.  launch a version of the the whoami service.
+    For `whoami-oauth`:
 
-        bash launch-service.sh &
+         bash launch-service.sh &
 
     or for `whoami-oauth-basic`:
 
-        bash launch-service-basic.sh &
+         bash launch-service-basic.sh &
 
-3. Launch JupyterHub:
+3.  Launch JupyterHub:
 
         jupyterhub
 
-4. Visit http://127.0.0.1:5555/
+4.  Visit http://127.0.0.1:5555/
 
 After logging in with your local-system credentials, you should see a JSON dump of your user info:
 
 ```json
 {
- "admin": false,
- "last_activity": "2016-05-27T14:05:18.016372",
- "name": "queequeg",
- "pending": null,
- "server": "/user/queequeg"
+  "admin": false,
+  "last_activity": "2016-05-27T14:05:18.016372",
+  "name": "queequeg",
+  "pending": null,
+  "server": "/user/queequeg"
 }
 ```
 
-
 The essential pieces for using JupyterHub as an OAuth provider are:
 
 1. registering your service with jupyterhub:
 
-    ```python
-    c.JupyterHub.services = [
-        {
-            # the name of your service
-            # should be simple and unique.
-            # mostly used to identify your service in logging
-            "name": "my-service",
-            # the oauth client id of your service
-            # must be unique but isn't private
-            # can be randomly generated or hand-written
-            "oauth_client_id": "abc123",
-            # the API token and client secret of the service
-            # should be generated securely,
-            # e.g. via `openssl rand -hex 32`
-            "api_token": "abc123...",
-            # the redirect target for jupyterhub to send users
-            # after successful authentication
-            "oauth_redirect_uri": "https://service-host/oauth_callback"
-        }
-    ]
-    ```
+   ```python
+   c.JupyterHub.services = [
+       {
+           # the name of your service
+           # should be simple and unique.
+           # mostly used to identify your service in logging
+           "name": "my-service",
+           # the oauth client id of your service
+           # must be unique but isn't private
+           # can be randomly generated or hand-written
+           "oauth_client_id": "abc123",
+           # the API token and client secret of the service
+           # should be generated securely,
+           # e.g. via `openssl rand -hex 32`
+           "api_token": "abc123...",
+           # the redirect target for jupyterhub to send users
+           # after successful authentication
+           "oauth_redirect_uri": "https://service-host/oauth_callback"
+       }
+   ]
+   ```
 
 2. Telling your service how to authenticate with JupyterHub.
 

examples/external-oauth/jupyterhub_config.py

@@ -13,7 +13,7 @@ if not api_token:
 c.JupyterHub.services = [
     {
         'name': 'external-oauth',
-        'oauth_client_id': "whoami-oauth-client-test",
+        'oauth_client_id': "service-oauth-client-test",
         'api_token': api_token,
         'oauth_redirect_uri': 'http://127.0.0.1:5555/oauth_callback',
     }

examples/external-oauth/launch-service-basic.sh

@@ -9,7 +9,7 @@ if [[ -z "${JUPYTERHUB_API_TOKEN}" ]]; then
 fi
 
 # 2. oauth client ID
-export JUPYTERHUB_CLIENT_ID='whoami-oauth-client-test'
+export JUPYTERHUB_CLIENT_ID='service-oauth-client-test'
 # 3. where the Hub is
 export JUPYTERHUB_URL='http://127.0.0.1:8000'
 

examples/external-oauth/launch-service.sh

@@ -9,7 +9,7 @@ if [[ -z "${JUPYTERHUB_API_TOKEN}" ]]; then
 fi
 
 # 2. oauth client ID
-export JUPYTERHUB_CLIENT_ID="whoami-oauth-client-test"
+export JUPYTERHUB_CLIENT_ID="service-oauth-client-test"
 # 3. what URL to run on
 export JUPYTERHUB_SERVICE_PREFIX='/'
 export JUPYTERHUB_SERVICE_URL='http://127.0.0.1:5555'

examples/external-oauth/whoami-oauth-basic.py

@@ -5,13 +5,11 @@ so all URLs and requests necessary for OAuth with JupyterHub should be in one pl
 """
 import json
 import os
-import sys
 from urllib.parse import urlencode
 from urllib.parse import urlparse
 
 from tornado import log
 from tornado import web
-from tornado.auth import OAuth2Mixin
 from tornado.httpclient import AsyncHTTPClient
 from tornado.httpclient import HTTPRequest
 from tornado.httputil import url_concat

examples/postgres/README.md

@@ -4,14 +4,14 @@ This example shows how you can connect Jupyterhub to a Postgres database
 instead of the default SQLite backend.
 
 ### Running Postgres with Jupyterhub on the host.
+
 0. Uncomment and replace `ENV JPY_PSQL_PASSWORD arglebargle` with your own
    password in the Dockerfile for `examples/postgres/db`. (Alternatively, pass
    -e `JPY_PSQL_PASSWORD=<password>` when you start the db container.)
 
 1. `cd` to the root of your jupyterhub repo.
 
-2. Build the postgres image with `docker build -t jupyterhub-postgres-db
-   examples/postgres/db`.  This may take a minute or two the first time it's
+2. Build the postgres image with `docker build -t jupyterhub-postgres-db examples/postgres/db`. This may take a minute or two the first time it's
    run.
 
 3. Run the db image with `docker run -d -p 5433:5432 jupyterhub-postgres-db`.
@@ -24,24 +24,22 @@ instead of the default SQLite backend.
 5. Log in as the user running jupyterhub on your host machine.
 
 ### Running Postgres with Containerized Jupyterhub.
+
 0. Do steps 0-2 in from the above section, ensuring that the values set/passed
    for `JPY_PSQL_PASSWORD` match for the hub and db containers.
 
-1. Build the hub image with `docker build -t jupyterhub-postgres-hub
-   examples/postgres/hub`.  This may take a minute or two the first time it's
+1. Build the hub image with `docker build -t jupyterhub-postgres-hub examples/postgres/hub`. This may take a minute or two the first time it's
    run.
 
-2. Run the db image with `docker run -d --name=jpy-db
-   jupyterhub-postgres`. Note that, unlike when connecting to a host machine
+2. Run the db image with `docker run -d --name=jpy-db jupyterhub-postgres`. Note that, unlike when connecting to a host machine
    jupyterhub, we don't specify a port-forwarding scheme here, but we do need
    to specify a name for the container.
 
-3. Run the containerized hub with `docker run -it --link jpy-db:postgres
-   jupyterhub-postgres-hub`.  This instructs docker to run the hub container
+3. Run the containerized hub with `docker run -it --link jpy-db:postgres jupyterhub-postgres-hub`. This instructs docker to run the hub container
    with a link to the already-running db container, which will forward
    environment and connection information from the DB to the hub.
 
 4. Log in as one of the users defined in the `examples/postgres/hub/`
-   Dockerfile.  By default `rhea` is the server's admin user, `io` and
+   Dockerfile. By default `rhea` is the server's admin user, `io` and
    `ganymede` are non-admin users, and all users' passwords are their
    usernames.

examples/postgres/hub/jupyterhub_config.py

@@ -1,10 +1,23 @@
 # Configuration file for jupyterhub (postgres example).
 
-c = get_config()
+c = get_config()  # noqa
 
-# Add some users.
-c.JupyterHub.admin_users = {'rhea'}
-c.Authenticator.whitelist = {'ganymede', 'io', 'rhea'}
+# Add some users
+c.Authenticator.allowed_users = {'ganymede', 'io', 'rhea'}
+
+c.JupyterHub.load_roles = [
+    {
+        "name": "user-admin",
+        "scopes": [
+            "admin:groups",
+            "admin:users",
+            "admin:servers",
+        ],
+        "users": [
+            "rhea",
+        ],
+    }
+]
 
 # These environment variables are automatically supplied by the linked postgres
 # container.

examples/server-api/jupyterhub_config.py

@@ -0,0 +1,55 @@
+# create a role with permissions to:
+# 1. start/stop servers, and
+# 2. access the server API
+
+c.JupyterHub.load_roles = [
+    {
+        "name": "launcher",
+        "scopes": [
+            "servers",  # manage servers
+            "access:servers",  # access servers themselves
+        ],
+        # assign role to our 'launcher' service
+        "services": ["launcher"],
+    }
+]
+
+
+# persist token to a file, to share it with the launch-server.py script
+import pathlib
+import secrets
+
+here = pathlib.Path(__file__).parent
+token_file = here.joinpath("service-token")
+if token_file.exists():
+    with token_file.open("r") as f:
+        token = f.read()
+else:
+    token = secrets.token_hex(16)
+    with token_file.open("w") as f:
+        f.write(token)
+
+# define our service
+c.JupyterHub.services = [
+    {
+        "name": "launcher",
+        "api_token": token,
+    }
+]
+
+# ensure spawn requests return immediately,
+# rather than waiting up to 10 seconds for spawn to complete
+# this ensures that we use the progress API
+
+c.JupyterHub.tornado_settings = {"slow_spawn_timeout": 0}
+
+# create our test-user
+c.Authenticator.allowed_users = {
+    'test-user',
+}
+
+
+# testing boilerplate: fake auth/spawner, localhost. Don't use this for real!
+c.JupyterHub.authenticator_class = 'dummy'
+c.JupyterHub.spawner_class = 'simple'
+c.JupyterHub.ip = '127.0.0.1'

examples/server-api/start-stop-server.py

@@ -0,0 +1,173 @@
+#!/usr/bin/env python3
+"""
+Example of starting/stopping a server via the JupyterHub API
+
+1. get user status
+2. start server
+3. wait for server to be ready via progress api
+4. make a request to the server itself
+5. stop server via API
+6. wait for server to finish stopping
+"""
+import json
+import logging
+import pathlib
+import time
+
+import requests
+
+
+log = logging.getLogger(__name__)
+
+
+def get_token():
+    """boilerplate: get token from share file.
+
+    Make sure to start jupyterhub in this directory first
+    """
+    here = pathlib.Path(__file__).parent
+    token_file = here.joinpath("service-token")
+    log.info(f"Loading token from {token_file}")
+    with token_file.open("r") as f:
+        token = f.read()
+    return token
+
+
+def make_session(token):
+    """Create a requests.Session with our service token in the Authorization header"""
+    session = requests.Session()
+    session.headers = {"Authorization": f"token {token}"}
+    return session
+
+
+def event_stream(session, url):
+    """Generator yielding events from a JSON event stream
+
+    For use with the server progress API
+    """
+    r = session.get(url, stream=True)
+    r.raise_for_status()
+    for line in r.iter_lines():
+        line = line.decode('utf8', 'replace')
+        # event lines all start with `data:`
+        # all other lines should be ignored (they will be empty)
+        if line.startswith('data:'):
+            yield json.loads(line.split(':', 1)[1])
+
+
+def start_server(session, hub_url, user, server_name=""):
+    """Start a server for a jupyterhub user
+
+    Returns the full URL for accessing the server
+    """
+    user_url = f"{hub_url}/hub/api/users/{user}"
+    log_name = f"{user}/{server_name}".rstrip("/")
+
+    # step 1: get user status
+    r = session.get(user_url)
+    r.raise_for_status()
+    user_model = r.json()
+
+    # if server is not 'active', request launch
+    if server_name not in user_model.get('servers', {}):
+        log.info(f"Starting server {log_name}")
+        r = session.post(f"{user_url}/servers/{server_name}")
+        r.raise_for_status()
+        if r.status_code == 201:
+            log.info(f"Server {log_name} is launched and ready")
+        elif r.status_code == 202:
+            log.info(f"Server {log_name} is launching...")
+        else:
+            log.warning(f"Unexpected status: {r.status_code}")
+        r = session.get(user_url)
+        r.raise_for_status()
+        user_model = r.json()
+
+    # report server status
+    server = user_model['servers'][server_name]
+    if server['pending']:
+        status = f"pending {server['pending']}"
+    elif server['ready']:
+        status = "ready"
+    else:
+        # shouldn't be possible!
+        raise ValueError(f"Unexpected server state: {server}")
+
+    log.info(f"Server {log_name} is {status}")
+
+    # wait for server to be ready using progress API
+    progress_url = user_model['servers'][server_name]['progress_url']
+    for event in event_stream(session, f"{hub_url}{progress_url}"):
+        log.info(f"Progress {event['progress']}%: {event['message']}")
+        if event.get("ready"):
+            server_url = event['url']
+            break
+    else:
+        # server never ready
+        raise ValueError(f"{log_name} never started!")
+
+    # at this point, we know the server is ready and waiting to receive requests
+    # return the full URL where the server can be accessed
+    return f"{hub_url}{server_url}"
+
+
+def stop_server(session, hub_url, user, server_name=""):
+    """Stop a server via the JupyterHub API
+
+    Returns when the server has finished stopping
+    """
+    # step 1: get user status
+    user_url = f"{hub_url}/hub/api/users/{user}"
+    server_url = f"{user_url}/servers/{server_name}"
+    log_name = f"{user}/{server_name}".rstrip("/")
+
+    log.info(f"Stopping server {log_name}")
+    r = session.delete(server_url)
+    if r.status_code == 404:
+        log.info(f"Server {log_name} already stopped")
+
+    r.raise_for_status()
+    if r.status_code == 204:
+        log.info(f"Server {log_name} stopped")
+        return
+
+    # else: 202, stop requested, but not complete
+    # wait for stop to finish
+    log.info(f"Server {log_name} stopping...")
+
+    # wait for server to be done stopping
+    while True:
+        r = session.get(user_url)
+        r.raise_for_status()
+        user_model = r.json()
+        if server_name not in user_model.get("servers", {}):
+            log.info(f"Server {log_name} stopped")
+            return
+        server = user_model["servers"][server_name]
+        if not server['pending']:
+            raise ValueError(f"Waiting for {log_name}, but no longer pending.")
+        log.info(f"Server {log_name} pending: {server['pending']}")
+        # wait to poll again
+        time.sleep(1)
+
+
+def main():
+    """Start and stop one server
+
+    Uses test-user and hub from jupyterhub_config.py in this directory
+    """
+    user = "test-user"
+    hub_url = "http://127.0.0.1:8000"
+
+    session = make_session(get_token())
+    server_url = start_server(session, hub_url, user)
+    r = session.get(f"{server_url}/api/status")
+    r.raise_for_status()
+    log.info(f"Server status: {r.text}")
+
+    stop_server(session, hub_url, user)
+
+
+if __name__ == "__main__":
+    logging.basicConfig(level=logging.INFO)
+    main()

examples/service-announcement/README.md

@@ -1,4 +1,3 @@
-
 # Simple Announcement Service Example
 
 This is a simple service that allows administrators to manage announcements
@@ -7,32 +6,47 @@ that appear when JupyterHub renders pages.
 To run the service as a hub-managed service simply include in your JupyterHub
 configuration file something like:
 
-    c.JupyterHub.services = [
-            {
-                'name': 'announcement',
-                'url': 'http://127.0.0.1:8888',
-                'command': [sys.executable, "-m", "announcement"],
-            }
-    ]
+```python
+c.JupyterHub.services = [
+        {
+            'name': 'announcement',
+            'url': 'http://127.0.0.1:8888',
+            'command': [sys.executable, "-m", "announcement", "--port", "8888"],
+        }
+]
+```
 
-This starts the announcements service up at `/services/announcement` when
-JupyterHub launches.  By default the announcement text is empty.
+This starts the announcements service up at `/services/announcement/` when
+JupyterHub launches. By default the announcement text is empty.
 
 The `announcement` module has a configurable port (default 8888) and an API
-prefix setting.  By default the API prefix is `JUPYTERHUB_SERVICE_PREFIX` if
+prefix setting. By default the API prefix is `JUPYTERHUB_SERVICE_PREFIX` if
 that environment variable is set or `/` if it is not.
 
 ## Managing the Announcement
 
-Admin users can set the announcement text with an API token:
+Users with permission can set the announcement text with an API token:
 
     $ curl -X POST -H "Authorization: token <token>"                        \
-        -d "{'announcement':'JupyterHub will be upgraded on August 14!'}"   \
-        https://.../services/announcement
+        -d '{"announcement":"JupyterHub will be upgraded on August 14!"}'   \
+        https://.../services/announcement/
+
+To grant permission, add a role (JupyterHub 2.0) with access to the announcement service:
+
+```python
+# grant the 'announcer' permission to access the announcement service
+c.JupyterHub.load_roles = [
+    {
+        "name": "announcers",
+        "users": ["announcer"], # or groups
+        "scopes": ["access:services!service=announcement"],
+    }
+]
+```
 
 Anyone can read the announcement:
 
-    $ curl https://.../services/announcement | python -m json.tool
+    $ curl https://.../services/announcement/ | python -m json.tool
     {
         announcement: "JupyterHub will be upgraded on August 14!",
         timestamp: "...",
@@ -42,19 +56,20 @@ Anyone can read the announcement:
 The time the announcement was posted is recorded in the `timestamp` field and
 the user who posted the announcement is recorded in the `user` field.
 
-To clear the announcement text, just DELETE.  Only admin users can do this.
+To clear the announcement text, send a DELETE request.
+This has the same permission requirement.
 
-    $ curl -X POST -H "Authorization: token <token>"                        \
-        https://.../services/announcement
+    $ curl -X DELETE -H "Authorization: token <token>"                        \
+        https://.../services/announcement/
 
 ## Seeing the Announcement in JupyterHub
 
 To be able to render the announcement, include the provide `page.html` template
-that extends the base `page.html` template.  Set `c.JupyterHub.template_paths`
+that extends the base `page.html` template. Set `c.JupyterHub.template_paths`
 in JupyterHub's configuration to include the path to the extending template.
 The template changes the `announcement` element and does a JQuery `$.get()` call
 to retrieve the announcement text.
 
 JupyterHub's configurable announcement template variables can be set for various
-pages like login, logout, spawn, and home.  Including the template provided in
+pages like login, logout, spawn, and home. Including the template provided in
 this example overrides all of those.