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2022-11-24 09:40:21 +01:00
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.circleci/config.yml
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# 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

9
.flake8
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# E: style errors
# W: style warnings
# C: complexity
# F401: module imported but unused
# F403: import *
# F811: redefinition of unused `name` from line `N`
# D: docstring warnings (unused pydocstyle extension)
# F841: local variable assigned but never used
# E402: module level import not at top of file
# I100: Import statements are in the wrong order
# I101: Imported names are in the wrong order. Should be
ignore = E, C, W, F401, F403, F811, F841, E402, I100, I101, D400
ignore = E, C, W, D, F841
builtins = c, get_config
exclude =
.cache,

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.github/ISSUE_TEMPLATE/bug_report.md vendored
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---
name: Bug 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 issue](https://github.com/jupyterhub/jupyterhub/issues) search feature to check if your issue has been asked already. If it has, please add your comments to the existing issue.
**Describe the bug**
A clear and concise description of what the bug is.
**To Reproduce**
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.
**Screenshots**
If applicable, add screenshots to help explain your problem.
**Desktop (please complete the following information):**
- OS: [e.g. iOS]
- Browser [e.g. chrome, safari]
- Version [e.g. 22]
**Additional context**
Add any other context about the problem here.
- Running `jupyter troubleshoot` from the command line, if possible, and posting
its output would also be helpful.
- Running in `--debug` mode can also be helpful for troubleshooting.

7
.github/ISSUE_TEMPLATE/installation-and-configuration-issues.md vendored
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---
name: Installation and configuration issues
about: Installation and configuration assistance
---
If you are having issues with installation or configuration, you may ask for help on the JupyterHub gitter channel or file an issue here.

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

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

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

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

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

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# This is a GitHub workflow defining a set of jobs with a set of steps.
# ref: https://docs.github.com/en/actions/learn-github-actions/workflow-syntax-for-github-actions
#
name: Test
on:
pull_request:
paths-ignore:
- "docs/**"
- "**.md"
- "**.rst"
- ".github/workflows/*"
- "!.github/workflows/test.yml"
push:
paths-ignore:
- "docs/**"
- "**.md"
- "**.rst"
- ".github/workflows/*"
- "!.github/workflows/test.yml"
branches-ignore:
- "dependabot/**"
- "pre-commit-ci-update-config"
tags:
- "**"
workflow_dispatch:
env:
# UTF-8 content may be interpreted as ascii and causes errors without this.
LANG: C.UTF-8
PYTEST_ADDOPTS: "--verbose --color=yes"
permissions:
contents: read
jobs:
# Run "pytest jupyterhub/tests" in various configurations
pytest:
runs-on: ubuntu-20.04
timeout-minutes: 15
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.
#
# legacy_notebook:
# Tests everything when the user instances are started with
# the legacy notebook server instead of jupyter_server.
#
# ssl:
# Tests everything using internal SSL connections instead of
# unencrypted HTTP
#
# main_dependencies:
# Tests everything when the we use the latest available dependencies
# from: traitlets.
#
# NOTE: Since only the value of these parameters are presented in the
# GitHub UI when the workflow run, we avoid using true/false as
# values by instead duplicating the name to signal true.
# Python versions available at:
# https://github.com/actions/python-versions/blob/HEAD/versions-manifest.json
include:
- python: "3.7"
oldest_dependencies: oldest_dependencies
legacy_notebook: legacy_notebook
- python: "3.8"
legacy_notebook: legacy_notebook
- python: "3.9"
db: mysql
- python: "3.10"
db: postgres
- python: "3.11"
subdomain: subdomain
- python: "3.11"
ssl: ssl
- python: "3.11"
selenium: selenium
- python: "3.11"
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@v3
# NOTE: actions/setup-node@v3 make use of a cache within the GitHub base
# environment and setup in a fraction of a second.
- name: Install Node v14
uses: actions/setup-node@v3
with:
node-version: "14"
- name: Install Javascript dependencies
run: |
npm install
npm install -g configurable-http-proxy yarn
npm list
# NOTE: actions/setup-python@v4 make use of a cache within the GitHub base
# environment and setup in a fraction of a second.
- name: Install Python ${{ matrix.python }}
uses: actions/setup-python@v4
with:
python-version: "${{ matrix.python }}"
- name: Install Python dependencies
run: |
pip install --upgrade pip
pip install ".[test]"
if [ "${{ matrix.oldest_dependencies }}" != "" ]; then
# take any dependencies in requirements.txt such as tornado>=5.0
# and transform them to tornado==5.0 so we can run tests with
# the earliest-supported versions
cat requirements.txt | grep '>=' | sed -e 's@>=@==@g' > oldest-requirements.txt
pip install -r oldest-requirements.txt
fi
if [ "${{ matrix.main_dependencies }}" != "" ]; then
pip install git+https://github.com/ipython/traitlets#egg=traitlets --force
fi
if [ "${{ matrix.legacy_notebook }}" != "" ]; then
pip uninstall jupyter_server --yes
pip install 'notebook<7'
fi
if [ "${{ 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
if [[ -z "$(which mysql)" ]]; then
sudo apt-get update
sudo apt-get install -y mysql-client
fi
DB=mysql bash ci/docker-db.sh
DB=mysql bash ci/init-db.sh
fi
if [ "${{ matrix.db }}" == "postgres" ]; then
if [[ -z "$(which psql)" ]]; then
sudo apt-get update
sudo apt-get install -y postgresql-client
fi
DB=postgres bash ci/docker-db.sh
DB=postgres bash ci/init-db.sh
fi
- name: Setup Firefox
if: matrix.selenium
uses: browser-actions/setup-firefox@latest
with:
firefox-version: latest
- name: Setup Geckodriver
if: matrix.selenium
uses: browser-actions/setup-geckodriver@latest
- name: Configure selenium tests
if: matrix.selenium
run: echo "PYTEST_ADDOPTS=$PYTEST_ADDOPTS -m selenium" >> "${GITHUB_ENV}"
- name: Run pytest
run: |
pytest --maxfail=2 --cov=jupyterhub jupyterhub/tests
- uses: codecov/codecov-action@v3
docker-build:
runs-on: ubuntu-20.04
timeout-minutes: 20
steps:
- uses: actions/checkout@v3
- name: build images
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

8
.gitignore vendored
View File

@@ -8,7 +8,9 @@ dist
docs/_build
docs/build
docs/source/_static/rest-api
docs/source/rbac/scope-table.md
.ipynb_checkpoints
jsx/build/
# ignore config file at the top-level of the repo
# but not sub-dirs
/jupyterhub_config.py
@@ -18,11 +20,17 @@ package-lock.json
share/jupyterhub/static/components
share/jupyterhub/static/css/style.min.css
share/jupyterhub/static/css/style.min.css.map
share/jupyterhub/static/js/admin-react.js*
*.egg-info
MANIFEST
.coverage
.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

79
.pre-commit-config.yaml
View File

@@ -1,20 +1,61 @@
# pre-commit is a tool to perform a predefined set of tasks manually and/or
# automatically before git commits are made.
#
# Config reference: https://pre-commit.com/#pre-commit-configyaml---top-level
#
# Common tasks
#
# - Run on all files: pre-commit run --all-files
# - Register git hooks: pre-commit install --install-hooks
#
repos:
- repo: https://github.com/asottile/reorder_python_imports
rev: v1.3.5
hooks:
- id: reorder-python-imports
language_version: python3.6
- repo: https://github.com/ambv/black
rev: 18.9b0
hooks:
- id: black
- repo: https://github.com/pre-commit/pre-commit-hooks
rev: v2.1.0
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
# Autoformat: Python code, syntax patterns are modernized
- repo: https://github.com/asottile/pyupgrade
rev: v3.2.2
hooks:
- id: pyupgrade
args:
- --py36-plus
# Autoformat: Python code
- repo: https://github.com/PyCQA/autoflake
rev: v1.7.7
hooks:
- id: autoflake
# args ref: https://github.com/PyCQA/autoflake#advanced-usage
args:
- --in-place
# Autoformat: Python code
- repo: https://github.com/pycqa/isort
rev: 5.10.1
hooks:
- id: isort
# Autoformat: Python code
- repo: https://github.com/psf/black
rev: 22.10.0
hooks:
- id: black
# Autoformat: markdown, yaml, javascript (see the file .prettierignore)
- repo: https://github.com/pre-commit/mirrors-prettier
rev: v3.0.0-alpha.4
hooks:
- id: prettier
# Autoformat and linting, misc. details
- repo: https://github.com/pre-commit/pre-commit-hooks
rev: v4.3.0
hooks:
- id: end-of-file-fixer
exclude: share/jupyterhub/static/js/admin-react.js
- id: requirements-txt-fixer
- id: check-case-conflict
- id: check-executables-have-shebangs
# Linting: Python code (see the file .flake8)
- repo: https://github.com/PyCQA/flake8
rev: "5.0.4"
hooks:
- id: flake8

2
.prettierignore Normal file
View File

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

25
.readthedocs.yaml Normal file
View File

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

100
.travis.yml
View File

@@ -1,100 +0,0 @@
language: python
sudo: false
cache:
- pip
python:
- 3.6
- 3.5
- nightly
env:
global:
- ASYNC_TEST_TIMEOUT=15
- MYSQL_HOST=127.0.0.1
- MYSQL_TCP_PORT=13306
services:
- postgres
- 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==8.0.15'
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
allow_failures:
- python: nightly

26
CHECKLIST-Release.md
View File

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

2
CODE_OF_CONDUCT.md
View File

@@ -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).

100
CONTRIBUTING.md
View File

@@ -1,102 +1,14 @@
# 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
Please see our documentation on
JupyterHub requires Python >= 3.5 and nodejs.
- [Setting up a development install](https://jupyterhub.readthedocs.io/en/latest/contributing/setup.html)
- [Testing JupyterHub and linting code](https://jupyterhub.readthedocs.io/en/latest/contributing/tests.html)
As a Python project, a development install of JupyterHub follows standard practices for the basics (steps 1-2).
1. clone the repo
```bash
git clone https://github.com/jupyterhub/jupyterhub
```
2. do a development install with pip
```bash
cd jupyterhub
python3 -m pip install --editable .
```
3. install the development requirements,
which include things like testing tools
```bash
python3 -m pip install -r dev-requirements.txt
```
4. install configurable-http-proxy with npm:
```bash
npm install -g configurable-http-proxy
```
5. set up pre-commit hooks for automatic code formatting, etc.
```bash
pre-commit install
```
You can also invoke the pre-commit hook manually at any time with
```bash
pre-commit run
```
## Contributing
JupyterHub has adopted automatic code formatting so you shouldn't
need to worry too much about your code style.
As long as your code is valid,
the pre-commit hook should take care of how it should look.
You can invoke the pre-commit hook by hand at any time with:
```bash
pre-commit run
```
which should run any autoformatting on your code
and tell you about any errors it couldn't fix automatically.
You may also install [black integration](https://github.com/ambv/black#editor-integration)
into your text editor to format code automatically.
If you have already committed files before setting up the pre-commit
hook with `pre-commit install`, you can fix everything up using
`pre-commit run --all-files`. You need to make the fixing commit
yourself after that.
## Testing
It's a good idea to write tests to exercise any new features,
or that trigger any bugs that you have fixed to catch regressions.
You can run the tests with:
```bash
pytest -v
```
in the repo directory. If you want to just run certain tests,
check out the [pytest docs](https://pytest.readthedocs.io/en/latest/usage.html)
for how pytest can be called.
For instance, to test only spawner-related things in the REST API:
```bash
pytest -v -k spawn jupyterhub/tests/test_api.py
```
The tests live in `jupyterhub/tests` and are organized roughly into:
1. `test_api.py` tests the REST API
2. `test_pages.py` tests loading the HTML pages
and other collections of tests for different components.
When writing a new test, there should usually be a test of
similar functionality already written and related tests should
be added nearby.
When in doubt, feel free to ask.
TODO: describe some details about fixtures, etc.
If you need some help, feel free to ask on [Gitter](https://gitter.im/jupyterhub/jupyterhub) or [Discourse](https://discourse.jupyter.org/).

6
COPYING.md
View File

@@ -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.

89
Dockerfile
View File

@@ -21,40 +21,83 @@
# your jupyterhub_config.py will be added automatically
# from your docker directory.
FROM ubuntu:18.04
LABEL maintainer="Jupyter Project <jupyter@googlegroups.com>"
ARG BASE_IMAGE=ubuntu:22.04
FROM $BASE_IMAGE AS builder
USER root
# install nodejs, utf8 locale, set CDN because default httpredir is unreliable
ENV DEBIAN_FRONTEND noninteractive
RUN apt-get -y update && \
apt-get -y upgrade && \
apt-get -y install wget git bzip2 && \
apt-get purge && \
apt-get clean && \
rm -rf /var/lib/apt/lists/*
ENV LANG C.UTF-8
RUN apt-get update \
&& apt-get install -yq --no-install-recommends \
build-essential \
ca-certificates \
locales \
python3-dev \
python3-pip \
python3-pycurl \
python3-venv \
nodejs \
npm \
&& apt-get clean \
&& rm -rf /var/lib/apt/lists/*
# install Python + NodeJS with conda
RUN wget -q https://repo.continuum.io/miniconda/Miniconda3-4.5.11-Linux-x86_64.sh -O /tmp/miniconda.sh && \
echo 'e1045ee415162f944b6aebfe560b8fee */tmp/miniconda.sh' | md5sum -c - && \
bash /tmp/miniconda.sh -f -b -p /opt/conda && \
/opt/conda/bin/conda install --yes -c conda-forge \
python=3.6 sqlalchemy tornado jinja2 traitlets requests pip pycurl \
nodejs configurable-http-proxy && \
/opt/conda/bin/pip install --upgrade pip && \
rm /tmp/miniconda.sh
ENV PATH=/opt/conda/bin:$PATH
RUN python3 -m pip install --upgrade setuptools pip build wheel
RUN npm install --global yarn
ADD . /src/jupyterhub
# copy everything except whats in .dockerignore, its a
# compromise between needing to rebuild and maintaining
# what needs to be part of the build
COPY . /src/jupyterhub/
WORKDIR /src/jupyterhub
RUN pip install . && \
rm -rf $PWD ~/.cache ~/.npm
# Build client component packages (they will be copied into ./share and
# packaged with the built wheel.)
RUN python3 -m build --wheel
RUN python3 -m pip wheel --wheel-dir wheelhouse dist/*.whl
FROM $BASE_IMAGE
USER root
ENV DEBIAN_FRONTEND=noninteractive
RUN apt-get update \
&& apt-get install -yq --no-install-recommends \
ca-certificates \
curl \
gnupg \
locales \
python3-pip \
python3-pycurl \
nodejs \
npm \
&& apt-get clean \
&& rm -rf /var/lib/apt/lists/*
ENV SHELL=/bin/bash \
LC_ALL=en_US.UTF-8 \
LANG=en_US.UTF-8 \
LANGUAGE=en_US.UTF-8
RUN locale-gen $LC_ALL
# always make sure pip is up to date!
RUN python3 -m pip install --no-cache --upgrade setuptools pip
RUN npm install -g configurable-http-proxy@^4.2.0 \
&& rm -rf ~/.npm
# install the wheels we built in the first stage
COPY --from=builder /src/jupyterhub/wheelhouse /tmp/wheelhouse
RUN python3 -m pip install --no-cache /tmp/wheelhouse/*
RUN mkdir -p /srv/jupyterhub/
WORKDIR /srv/jupyterhub/
EXPOSE 8000
LABEL maintainer="Jupyter Project <jupyter@googlegroups.com>"
LABEL org.jupyter.service="jupyterhub"
CMD ["jupyterhub"]

5
MANIFEST.in
View File

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

94
README.md
View File

@@ -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 +50,32 @@ 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][]
for administration of the Hub and its users.
## Installation
[rest api]: https://jupyterhub.readthedocs.io/en/latest/reference/rest-api.html
## Installation
### Check prerequisites
- A Linux/Unix based system
- [Python](https://www.python.org/downloads/) 3.5 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 +89,11 @@ 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 +102,13 @@ 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
@@ -114,13 +117,12 @@ To start the Hub server, run the command:
jupyterhub
Visit `https://localhost:8000` in your browser, and sign in with your unix
PAM credentials.
Visit `http://localhost:8000` in your browser, and sign in with your system username and password.
*Note*: To allow multiple users to sign 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 +141,7 @@ 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 +203,7 @@ 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.
@@ -228,20 +230,20 @@ 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][rest api]
- [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)
JupyterHub follows the Jupyter [Community Guides](https://jupyter.readthedocs.io/en/latest/community/content-community.html).

55
RELEASE.md Normal file
View File

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

5
SECURITY.md Normal file
View File

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

2
bower-lite
View File

@@ -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)

20
ci/check_installed_data.py Executable file
View File

@@ -0,0 +1,20 @@
#!/usr/bin/env python
# Check that installed package contains everything we expect
import os
from jupyterhub._data import DATA_FILES_PATH
print("Checking jupyterhub._data")
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",
"static/js/admin-react.js",
):
path = os.path.join(DATA_FILES_PATH, subpath)
assert os.path.exists(path), path
print("OK")

27
ci/check_sdist.py Executable file
View File

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

99
ci/docker-db.sh
View File

@@ -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

39
ci/init-db.sh
View File

@@ -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 _upgrade_150 _upgrade_211; do
$SQL_CLIENT "DROP DATABASE jupyterhub${SUFFIX};" 2>/dev/null || true
$SQL_CLIENT "CREATE DATABASE jupyterhub${SUFFIX} ${EXTRA_CREATE_DATABASE_ARGS:-};"
done

16
demo-image/Dockerfile Normal file
View File

@@ -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

26
demo-image/README.md Normal file
View File

@@ -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:!

7
demo-image/jupyterhub_config.py Normal file
View File

@@ -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"

17
dev-requirements.txt
View File

@@ -1,17 +0,0 @@
-r requirements.txt
# temporary pin of attrs for jsonschema 0.3.0a1
# seems to be a pip bug
attrs>=17.4.0
beautifulsoup4
codecov
coverage
cryptography
html5lib # needed for beautifulsoup
mock
notebook
pre-commit
pytest-asyncio
pytest-cov
pytest>=3.3
requests-mock
virtualenv

15
dockerfiles/Dockerfile.alpine
View File

@@ -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"]

22
dockerfiles/README.md
View File

@@ -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"

14
dockerfiles/test.py Normal file
View File

@@ -0,0 +1,14 @@
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",
"static/js/admin-react.js",
):
path = os.path.join(DATA_FILES_PATH, sub_path)
assert os.path.exists(path), path

18
docs/Makefile
View File

@@ -48,19 +48,25 @@ 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)/*
node_modules: package.json
npm install && touch node_modules
metrics: source/reference/metrics.rst
rest-api: source/_static/rest-api/index.html
source/reference/metrics.rst: generate-metrics.py
python3 generate-metrics.py
source/_static/rest-api/index.html: rest-api.yml node_modules
npm run rest-api
scopes: source/rbac/scope-table.md
html: rest-api
source/rbac/scope-table.md: source/rbac/generate-scope-table.py
python3 source/rbac/generate-scope-table.py
# If the pre-requisites for the html target is updated, also update the Read The
# Docs section in docs/source/conf.py.
#
html: metrics scopes
$(SPHINXBUILD) -b html $(ALLSPHINXOPTS) $(BUILDDIR)/html
@echo
@echo "Build finished. The HTML pages are in $(BUILDDIR)/html."

26
docs/environment.yml
View File

@@ -1,26 +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
- requests
- sqlalchemy>=1
- tornado>=5.0
- traitlets>=4.1
- sphinx>=1.7
- pip:
- entrypoints
- oauthlib>=2.0
- recommonmark==0.5.0
- async_generator
- prometheus_client
- attrs>=17.4.0
- sphinx-copybutton
- alabaster_jupyterhub

56
docs/generate-metrics.py Normal file
View File

@@ -0,0 +1,56 @@
import os
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()

14
docs/package.json
View File

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

26
docs/requirements.txt
View File

@@ -1,7 +1,21 @@
# ReadTheDocs uses the `environment.yaml` so make sure to update that as well
# if you change this file
-r ../requirements.txt
alabaster_jupyterhub
recommonmark==0.5.0
# We install the jupyterhub package to help autodoc-traits inspect it and
# generate documentation.
#
# FIXME: If there is a way for this requirements.txt file to pass a flag that
# the build system can intercept to not build the javascript artifacts,
# then do so so. That would mean that installing the documentation can
# avoid needing node/npm installed.
#
--editable .
autodoc-traits
myst-parser
pre-commit
pydata-sphinx-theme
pytablewriter>=0.56
ruamel.yaml
sphinx>=4
sphinx-copybutton
sphinx>=1.7
sphinx-jsonschema
sphinxext-opengraph
sphinxext-rediraffe

868
docs/rest-api.yml
View File

@@ -1,868 +0,0 @@
# see me at: http://petstore.swagger.io/?url=https://raw.githubusercontent.com/jupyterhub/jupyterhub/master/docs/rest-api.yml#/default
swagger: '2.0'
info:
title: JupyterHub
description: The REST API for JupyterHub
version: 0.9.0dev
license:
name: BSD-3-Clause
schemes:
[http, https]
securityDefinitions:
token:
type: apiKey
name: Authorization
in: header
security:
- token: []
basePath: /hub/api
produces:
- application/json
consumes:
- application/json
paths:
/:
get:
summary: Get JupyterHub version
description: |
This endpoint is not authenticated for the purpose of clients and user
to identify the JupyterHub version before setting up authentication.
responses:
'200':
description: The JupyterHub version
schema:
type: object
properties:
version:
type: string
description: The version of JupyterHub itself
/info:
get:
summary: Get detailed info about JupyterHub
description: |
Detailed JupyterHub information, including Python version,
JupyterHub's version and executable path,
and which Authenticator and Spawner are active.
responses:
'200':
description: Detailed JupyterHub info
schema:
type: object
properties:
version:
type: string
description: The version of JupyterHub itself
python:
type: string
description: The Python version, as returned by sys.version
sys_executable:
type: string
description: The path to sys.executable running JupyterHub
authenticator:
type: object
properties:
class:
type: string
description: The Python class currently active for JupyterHub Authentication
version:
type: string
description: The version of the currently active Authenticator
spawner:
type: object
properties:
class:
type: string
description: The Python class currently active for spawning single-user notebook servers
version:
type: string
description: The version of the currently active Spawner
/users:
get:
summary: List users
responses:
'200':
description: The Hub's user list
schema:
type: array
items:
$ref: '#/definitions/User'
post:
summary: Create multiple users
parameters:
- name: body
in: body
required: true
schema:
type: object
properties:
usernames:
type: array
description: list of usernames to create on the Hub
items:
type: string
admin:
description: whether the created users should be admins
type: boolean
responses:
'201':
description: The users have been created
schema:
type: array
description: The created users
items:
$ref: '#/definitions/User'
/users/{name}:
get:
summary: Get a user by name
parameters:
- name: name
description: username
in: path
required: true
type: string
responses:
'200':
description: The User model
schema:
$ref: '#/definitions/User'
post:
summary: Create a single user
parameters:
- name: name
description: username
in: path
required: true
type: string
responses:
'201':
description: The user has been created
schema:
$ref: '#/definitions/User'
patch:
summary: Modify a user
description: Change a user's name or admin status
parameters:
- name: name
description: username
in: path
required: true
type: string
- name: body
in: body
required: true
description: Updated user info. At least one key to be updated (name or admin) is required.
schema:
type: object
properties:
name:
type: string
description: the new name (optional, if another key is updated i.e. admin)
admin:
type: boolean
description: update admin (optional, if another key is updated i.e. name)
responses:
'200':
description: The updated user info
schema:
$ref: '#/definitions/User'
delete:
summary: Delete a user
parameters:
- name: name
description: username
in: path
required: true
type: string
responses:
'204':
description: The user has been deleted
/users/{name}/activity:
post:
summary:
Notify Hub of activity for a given user.
description:
Notify the Hub of activity by the user,
e.g. accessing a service or (more likely)
actively using a server.
parameters:
- name: name
description: username
in: path
required: true
type: string
- name: body
in: body
schema:
type: object
properties:
last_activity:
type: string
format: date-time
description: |
Timestamp of last-seen activity for this user.
Only needed if this is not activity associated
with using a given server.
servers:
description: |
Register activity for specific servers by name.
The keys of this dict are the names of servers.
The default server has an empty name ('').
type: object
properties:
'<server name>':
description: |
Activity for a single server.
type: object
required:
- last_activity
properties:
last_activity:
type: string
format: date-time
description: |
Timestamp of last-seen activity on this server.
example:
last_activity: '2019-02-06T12:54:14Z'
servers:
'':
last_activity: '2019-02-06T12:54:14Z'
gpu:
last_activity: '2019-02-06T12:54:14Z'
responses:
'401':
$ref: '#/responses/Unauthorized'
'404':
description: No such user
/users/{name}/server:
post:
summary: Start a user's single-user notebook server
parameters:
- name: name
description: username
in: path
required: true
type: string
- name: options
description: |
Spawn options can be passed as a JSON body
when spawning via the API instead of spawn form.
The structure of the options
will depend on the Spawner's configuration.
in: body
required: false
schema:
type: object
responses:
'201':
description: The user's notebook server has started
'202':
description: The user's notebook server has not yet started, but has been requested
delete:
summary: Stop a user's server
parameters:
- name: name
description: username
in: path
required: true
type: string
responses:
'204':
description: The user's notebook server has stopped
'202':
description: The user's notebook server has not yet stopped as it is taking a while to stop
/users/{name}/servers/{server_name}:
post:
summary: Start a user's single-user named-server notebook server
parameters:
- name: name
description: username
in: path
required: true
type: string
- name: server_name
description: name given to a named-server
in: path
required: true
type: string
- name: options
description: |
Spawn options can be passed as a JSON body
when spawning via the API instead of spawn form.
The structure of the options
will depend on the Spawner's configuration.
in: body
required: false
schema:
type: object
responses:
'201':
description: The user's notebook named-server has started
'202':
description: The user's notebook named-server has not yet started, but has been requested
delete:
summary: Stop a user's named-server
parameters:
- name: name
description: username
in: path
required: true
type: string
- name: server_name
description: name given to a named-server
in: path
required: true
type: string
- name: remove
description: |
Whether to fully remove the server, rather than just stop it.
Removing a server deletes things like the state of the stopped server.
in: body
required: false
schema:
type: boolean
responses:
'204':
description: The user's notebook named-server has stopped
'202':
description: The user's notebook named-server has not yet stopped as it is taking a while to stop
/users/{name}/tokens:
parameters:
- name: name
description: username
in: path
required: true
type: string
get:
summary: List tokens for the user
responses:
'200':
description: The list of tokens
schema:
type: array
items:
$ref: '#/definitions/Token'
'401':
$ref: '#/responses/Unauthorized'
'404':
description: No such user
post:
summary: Create a new token for the user
parameters:
- name: token_params
in: body
required: false
schema:
type: object
properties:
expires_in:
type: number
description: lifetime (in seconds) after which the requested token will expire.
note:
type: string
description: A note attached to the token for future bookkeeping
responses:
'201':
description: The newly created token
schema:
$ref: '#/definitions/Token'
'400':
description: Body must be a JSON dict or empty
/users/{name}/tokens/{token_id}:
parameters:
- name: name
description: username
in: path
required: true
type: string
- name: token_id
in: path
required: true
type: string
get:
summary: Get the model for a token by id
responses:
'200':
description: The info for the new token
schema:
$ref: '#/definitions/Token'
delete:
summary: Delete (revoke) a token by id
responses:
'204':
description: The token has been deleted
/user:
get:
summary: Return authenticated user's model
responses:
'200':
description: The authenticated user's model is returned.
schema:
$ref: '#/definitions/User'
/groups:
get:
summary: List groups
responses:
'200':
description: The list of groups
schema:
type: array
items:
$ref: '#/definitions/Group'
/groups/{name}:
get:
summary: Get a group by name
parameters:
- name: name
description: group name
in: path
required: true
type: string
responses:
'200':
description: The group model
schema:
$ref: '#/definitions/Group'
post:
summary: Create a group
parameters:
- name: name
description: group name
in: path
required: true
type: string
responses:
'201':
description: The group has been created
schema:
$ref: '#/definitions/Group'
delete:
summary: Delete a group
parameters:
- name: name
description: group name
in: path
required: true
type: string
responses:
'204':
description: The group has been deleted
/groups/{name}/users:
post:
summary: Add users to a group
parameters:
- name: name
description: group name
in: path
required: true
type: string
- name: body
in: body
required: true
description: The users to add to the group
schema:
type: object
properties:
users:
type: array
description: List of usernames to add to the group
items:
type: string
responses:
'200':
description: The users have been added to the group
schema:
$ref: '#/definitions/Group'
delete:
summary: Remove users from a group
parameters:
- name: name
description: group name
in: path
required: true
type: string
- name: body
in: body
required: true
description: The users to remove from the group
schema:
type: object
properties:
users:
type: array
description: List of usernames to remove from the group
items:
type: string
responses:
'200':
description: The users have been removed from the group
/services:
get:
summary: List services
responses:
'200':
description: The service list
schema:
type: array
items:
$ref: '#/definitions/Service'
/services/{name}:
get:
summary: Get a service by name
parameters:
- name: name
description: service name
in: path
required: true
type: string
responses:
'200':
description: The Service model
schema:
$ref: '#/definitions/Service'
/proxy:
get:
summary: Get the proxy's routing table
description: A convenience alias for getting the routing table directly from the proxy
responses:
'200':
description: Routing table
schema:
type: object
description: configurable-http-proxy routing table (see configurable-http-proxy docs for details)
post:
summary: Force the Hub to sync with the proxy
responses:
'200':
description: Success
patch:
summary: Notify the Hub about a new proxy
description: Notifies the Hub of a new proxy to use.
parameters:
- name: body
in: body
required: true
description: Any values that have changed for the new proxy. All keys are optional.
schema:
type: object
properties:
ip:
type: string
description: IP address of the new proxy
port:
type: string
description: Port of the new proxy
protocol:
type: string
description: Protocol of new proxy, if changed
auth_token:
type: string
description: CONFIGPROXY_AUTH_TOKEN for the new proxy
responses:
'200':
description: Success
/authorizations/token:
post:
summary: Request a new API token
description: |
Request a new API token to use with the JupyterHub REST API.
If not already authenticated, username and password can be sent
in the JSON request body.
Logging in via this method is only available when the active Authenticator
accepts passwords (e.g. not OAuth).
parameters:
- name: credentials
in: body
schema:
type: object
properties:
username:
type: string
password:
type: string
responses:
'200':
description: The new API token
schema:
type: object
properties:
token:
type: string
description: The new API token.
'403':
description: The user can not be authenticated.
/authorizations/token/{token}:
get:
summary: Identify a user or service from an API token
parameters:
- name: token
in: path
required: true
type: string
responses:
'200':
description: The user or service identified by the API token
'404':
description: A user or service is not found.
/authorizations/cookie/{cookie_name}/{cookie_value}:
get:
summary: Identify a user from a cookie
description: Used by single-user notebook servers to hand off cookie authentication to the Hub
parameters:
- name: cookie_name
in: path
required: true
type: string
- name: cookie_value
in: path
required: true
type: string
responses:
'200':
description: The user identified by the cookie
schema:
$ref: '#/definitions/User'
'404':
description: A user is not found.
/oauth2/authorize:
get:
summary: 'OAuth 2.0 authorize endpoint'
description: |
Redirect users to this URL to begin the OAuth process.
It is not an API endpoint.
parameters:
- name: client_id
description: The client id
in: query
required: true
type: string
- name: response_type
description: The response type (always 'code')
in: query
required: true
type: string
- name: state
description: A state string
in: query
required: false
type: string
- name: redirect_uri
description: The redirect url
in: query
required: true
type: string
responses:
'200':
description: Success
'400':
description: OAuth2Error
/oauth2/token:
post:
summary: Request an OAuth2 token
description: |
Request an OAuth2 token from an authorization code.
This request completes the OAuth process.
consumes:
- application/x-www-form-urlencoded
parameters:
- name: client_id
description: The client id
in: formData
required: true
type: string
- name: client_secret
description: The client secret
in: formData
required: true
type: string
- name: grant_type
description: The grant type (always 'authorization_code')
in: formData
required: true
type: string
- name: code
description: The code provided by the authorization redirect
in: formData
required: true
type: string
- name: redirect_uri
description: The redirect url
in: formData
required: true
type: string
responses:
'200':
description: JSON response including the token
schema:
type: object
properties:
access_token:
type: string
description: The new API token for the user
token_type:
type: string
description: Will always be 'Bearer'
/shutdown:
post:
summary: Shutdown the Hub
parameters:
- name: body
in: body
schema:
type: object
properties:
proxy:
type: boolean
description: Whether the proxy should be shutdown as well (default from Hub config)
servers:
type: boolean
description: Whether users' notebook servers should be shutdown as well (default from Hub config)
responses:
'202':
description: Shutdown successful
'400':
description: Unexpeced value for proxy or servers
# Descriptions of common responses
responses:
NotFound:
description: The specified resource was not found
Unauthorized:
description: Authentication/Authorization error
definitions:
User:
type: object
properties:
name:
type: string
description: The user's name
admin:
type: boolean
description: Whether the user is an admin
groups:
type: array
description: The names of groups where this user is a member
items:
type: string
server:
type: string
description: The user's notebook server's base URL, if running; null if not.
pending:
type: string
enum: ["spawn", "stop", null]
description: The currently pending action, if any
last_activity:
type: string
format: date-time
description: Timestamp of last-seen activity from the user
servers:
type: array
description: The active servers for this user.
items:
$ref: '#/definitions/Server'
Server:
type: object
properties:
name:
type: string
description: The server's name. The user's default server has an empty name ('')
ready:
type: boolean
description: |
Whether the server is ready for traffic.
Will always be false when any transition is pending.
pending:
type: string
enum: ["spawn", "stop", null]
description: |
The currently pending action, if any.
A server is not ready if an action is pending.
url:
type: string
description: |
The URL where the server can be accessed
(typically /user/:name/:server.name/).
progress_url:
type: string
description: |
The URL for an event-stream to retrieve events during a spawn.
started:
type: string
format: date-time
description: UTC timestamp when the server was last started.
last_activity:
type: string
format: date-time
description: UTC timestamp last-seen activity on this server.
state:
type: object
description: Arbitrary internal state from this server's spawner. Only available on the hub's users list or get-user-by-name method, and only if a hub admin. None otherwise.
Group:
type: object
properties:
name:
type: string
description: The group's name
users:
type: array
description: The names of users who are members of this group
items:
type: string
Service:
type: object
properties:
name:
type: string
description: The service's name
admin:
type: boolean
description: Whether the service is an admin
url:
type: string
description: The internal url where the service is running
prefix:
type: string
description: The proxied URL prefix to the service's url
pid:
type: number
description: The PID of the service process (if managed)
command:
type: array
description: The command used to start the service (if managed)
items:
type: string
info:
type: object
description: |
Additional information a deployment can attach to a service.
JupyterHub does not use this field.
Token:
type: object
properties:
token:
type: string
description: The token itself. Only present in responses to requests for a new token.
id:
type: string
description: The id of the API token. Used for modifying or deleting the token.
user:
type: string
description: The user that owns a token (undefined if owned by a service)
service:
type: string
description: The service that owns the token (undefined of owned by a user)
note:
type: string
description: A note about the token, typically describing what it was created for.
created:
type: string
format: date-time
description: Timestamp when this token was created
expires_at:
type: string
format: date-time
description: Timestamp when this token expires. Null if there is no expiry.
last_activity:
type: string
format: date-time
description: |
Timestamp of last-seen activity using this token.
Can be null if token has never been used.

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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;
}
/* hide redundant funky-formatted swagger-ui version */
.swagger-ui .info .title small {
display: none !important;
}

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@@ -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 %}

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{# 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>

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

69
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@@ -1,5 +1,3 @@
.. _admin/upgrading:
====================
Upgrading JupyterHub
====================
@@ -7,35 +5,36 @@ Upgrading JupyterHub
JupyterHub offers easy upgrade pathways between minor versions. This
document describes how to do these upgrades.
If you are using :ref:`a JupyterHub distribution <index/distributions>`, you
If you use :ref:`a JupyterHub distribution <index/distributions>`, you
should consult the distribution's documentation on how to upgrade. This
document is if you have set up your own JupyterHub without using a
document is applicable if you have set up your own JupyterHub without using a
distribution.
It is long because is pretty detailed! Most likely, upgrading
This documentation is lengthy because it is quite detailed. Most likely, upgrading
JupyterHub is painless, quick and with minimal user interruption.
The steps are discussed in detail, so if you get stuck at any step you can always refer to this guide.
Read the Changelog
==================
The `changelog <../changelog.html>`_ contains information on what has
changed with the new JupyterHub release, and any deprecation warnings.
The `changelog <../changelog.md>`_ contains information on what has
changed with the new JupyterHub release and any deprecation warnings.
Read these notes to familiarize yourself with the coming changes. There
might be new releases of authenticators & spawners you are using, so
might be new releases of the authenticators & spawners you use, so
read the changelogs for those too!
Notify your users
=================
If you are using the default configuration where ``configurable-http-proxy``
If you use the default configuration where ``configurable-http-proxy``
is managed by JupyterHub, your users will see service disruption during
the upgrade process. You should notify them, and pick a time to do the
upgrade where they will be least disrupted.
If you are using a different proxy, or running ``configurable-http-proxy``
If you use a different proxy or run ``configurable-http-proxy``
independent of JupyterHub, your users will be able to continue using notebook
servers they had already launched, but will not be able to launch new servers
nor sign in.
servers they had already launched, but will not be able to launch new servers or sign in.
Backup database & config
@@ -43,37 +42,37 @@ Backup database & config
Before doing an upgrade, it is critical to back up:
#. Your JupyterHub database (sqlite by default, or MySQL / Postgres
if you used those). If you are using sqlite (the default), you
should backup the ``jupyterhub.sqlite`` file.
#. Your JupyterHub database (SQLite by default, or MySQL / Postgres if you used those).
If you use SQLite (the default), you should backup the ``jupyterhub.sqlite`` file.
#. Your ``jupyterhub_config.py`` file.
#. Your user's home directories. This is unlikely to be affected directly by
a JupyterHub upgrade, but we recommend a backup since user data is very
critical.
#. Your users' home directories. This is unlikely to be affected directly by
a JupyterHub upgrade, but we recommend a backup since user data is critical.
Shutdown JupyterHub
===================
Shut down JupyterHub
====================
Shutdown the JupyterHub process. This would vary depending on how you
have set up JupyterHub to run. Most likely, it is using a process
Shut down the JupyterHub process. This would vary depending on how you
have set up JupyterHub to run. It is most likely using a process
supervisor of some sort (``systemd`` or ``supervisord`` or even ``docker``).
Use the supervisor specific command to stop the JupyterHub process.
Use the supervisor-specific command to stop the JupyterHub process.
Upgrade JupyterHub packages
===========================
There are two environments where the ``jupyterhub`` package is installed:
#. The *hub environment*, which is where the JupyterHub server process
#. The *hub environment*: where the JupyterHub server process
runs. This is started with the ``jupyterhub`` command, and is what
people generally think of as JupyterHub.
#. The *notebook user environments*. This is where the user notebook
#. The *notebook user environments*: where the user notebook
servers are launched from, and is probably custom to your own
installation. This could be just one environment (different from the
hub environment) that is shared by all users, one environment
per user, or same environment as the hub environment. The hub
per user, or the same environment as the hub environment. The hub
launched the ``jupyterhub-singleuser`` command in this environment,
which in turn starts the notebook server.
@@ -94,10 +93,8 @@ with:
conda install -c conda-forge jupyterhub==<version>
Where ``<version>`` is the version of JupyterHub you are upgrading to.
You should also check for new releases of the authenticator & spawner you
are using. You might wish to upgrade those packages too along with JupyterHub,
are using. You might wish to upgrade those packages, too, along with JupyterHub
or upgrade them separately.
Upgrade JupyterHub database
@@ -111,7 +108,7 @@ database. From the hub environment, in the same directory as your
jupyterhub upgrade-db
This should find the location of your database, and run necessary upgrades
This should find the location of your database, and run the necessary upgrades
for it.
SQLite database disadvantages
@@ -120,11 +117,11 @@ SQLite database disadvantages
SQLite has some disadvantages when it comes to upgrading JupyterHub. These
are:
- ``upgrade-db`` may not work, and you may need delete your database
- ``upgrade-db`` may not work, and you may need to delete your database
and start with a fresh one.
- ``downgrade-db`` **will not** work if you want to rollback to an
earlier version, so backup the ``jupyterhub.sqlite`` file before
upgrading
upgrading.
What happens if I delete my database?
-------------------------------------
@@ -139,10 +136,10 @@ resides only in the Hub database includes:
If the following conditions are true, you should be fine clearing the
Hub database and starting over:
- users specified in config file, or login using an external
- users specified in the config file, or login using an external
authentication provider (Google, GitHub, LDAP, etc)
- user servers are stopped during upgrade
- don't mind causing users to login again after upgrade
- user servers are stopped during the upgrade
- don't mind causing users to log in again after the upgrade
Start JupyterHub
================
@@ -150,7 +147,7 @@ Start JupyterHub
Once the database upgrade is completed, start the ``jupyterhub``
process again.
#. Log-in and start the server to make sure things work as
#. Log in and start the server to make sure things work as
expected.
#. Check the logs for any errors or deprecation warnings. You
might have to update your ``jupyterhub_config.py`` file to

11
docs/source/api/index.rst
View File

@@ -1,8 +1,8 @@
.. _api-index:
##################
The JupyterHub API
##################
##############
JupyterHub API
##############
:Release: |release|
:Date: |today|
@@ -17,11 +17,6 @@ information on:
- making an API request programmatically using the requests library
- learning more about JupyterHub's API
The same JupyterHub API spec, as found here, is available in an interactive form
`here (on swagger's petstore) <http://petstore.swagger.io/?url=https://raw.githubusercontent.com/jupyterhub/jupyterhub/master/docs/rest-api.yml#!/default>`__.
The `OpenAPI Initiative`_ (fka Swagger™) is a project used to describe
and document RESTful APIs.
JupyterHub API Reference:
.. toctree::

1248
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378
docs/source/conf.py
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@@ -1,211 +1,215 @@
# -*- coding: utf-8 -*-
# Configuration file for Sphinx to build our documentation to HTML.
#
# Configuration reference: https://www.sphinx-doc.org/en/master/usage/configuration.html
#
import contextlib
import datetime
import io
import os
import shlex
import sys
import subprocess
# Set paths
sys.path.insert(0, os.path.abspath('.'))
# -- General configuration ------------------------------------------------
# Minimal Sphinx version
needs_sphinx = '1.4'
# Sphinx extension modules
extensions = [
'sphinx.ext.autodoc',
'sphinx.ext.intersphinx',
'sphinx.ext.napoleon',
'autodoc_traits',
'sphinx_copybutton',
]
templates_path = ['_templates']
# The master toctree document.
master_doc = 'index'
# General information about the project.
project = u'JupyterHub'
copyright = u'2016, Project Jupyter team'
author = u'Project Jupyter team'
# Autopopulate version
from os.path import dirname
docs = dirname(dirname(__file__))
root = dirname(docs)
sys.path.insert(0, root)
sys.path.insert(0, os.path.join(docs, 'sphinxext'))
from docutils import nodes
from sphinx.directives.other import SphinxDirective
import jupyterhub
from jupyterhub.app import JupyterHub
# The short X.Y version.
version = '%i.%i' % jupyterhub.version_info[:2]
# The full version, including alpha/beta/rc tags.
# -- Project information -----------------------------------------------------
# ref: https://www.sphinx-doc.org/en/master/usage/configuration.html#project-information
#
project = "JupyterHub"
author = "Project Jupyter Contributors"
copyright = f"{datetime.date.today().year}, {author}"
version = "%i.%i" % jupyterhub.version_info[:2]
release = jupyterhub.__version__
language = None
exclude_patterns = []
pygments_style = 'sphinx'
todo_include_todos = False
# Set the default role so we can use `foo` instead of ``foo``
default_role = 'literal'
# -- General Sphinx configuration --------------------------------------------
# ref: https://www.sphinx-doc.org/en/master/usage/configuration.html#general-configuration
#
extensions = [
"sphinx.ext.autodoc",
"sphinx.ext.intersphinx",
"sphinx.ext.napoleon",
"autodoc_traits",
"sphinx_copybutton",
"sphinx-jsonschema",
"sphinxext.opengraph",
"sphinxext.rediraffe",
"myst_parser",
]
root_doc = "index"
source_suffix = [".md", ".rst"]
# default_role let's use use `foo` instead of ``foo`` in rST
default_role = "literal"
# -- Source -------------------------------------------------------------
import recommonmark
from recommonmark.transform import AutoStructify
# -- MyST configuration ------------------------------------------------------
# ref: https://myst-parser.readthedocs.io/en/latest/configuration.html
#
myst_heading_anchors = 2
myst_enable_extensions = [
"colon_fence",
"deflist",
]
# -- Custom directives to generate documentation -----------------------------
# ref: https://myst-parser.readthedocs.io/en/latest/syntax/roles-and-directives.html
#
# We define custom directives to help us generate documentation using Python on
# demand when referenced from our documentation files.
#
# Create a temp instance of JupyterHub for use by two separate directive classes
# to get the output from using the "--generate-config" and "--help-all" CLI
# flags respectively.
#
jupyterhub_app = JupyterHub()
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, "$HOME", 1)
par = nodes.literal_block(text=generated_config)
return [par]
class HelpAllDirective(SphinxDirective):
"""Print the output of jupyterhub help --all for use in the documentation."""
has_content = False
required_arguments = 0
optional_arguments = 0
final_argument_whitespace = False
option_spec = {}
def run(self):
# The output of the help command for this version
buffer = io.StringIO()
with contextlib.redirect_stdout(buffer):
jupyterhub_app.print_help("--help-all")
all_help = buffer.getvalue()
# post-process output
home_dir = os.environ["HOME"]
all_help = all_help.replace(home_dir, "$HOME", 1)
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.
import alabaster_jupyterhub
html_theme = 'alabaster_jupyterhub'
html_theme_path = [alabaster_jupyterhub.get_html_theme_path()]
html_logo = '_static/images/logo/logo.png'
html_favicon = '_static/images/logo/favicon.ico'
# Paths that contain custom static files (such as style sheets)
html_static_path = ['_static']
html_theme_options = {
'show_related': True,
'description': 'Documentation for JupyterHub',
'github_user': 'jupyterhub',
'github_repo': 'jupyterhub',
'github_banner': False,
'github_button': True,
'github_type': 'star',
'show_powered_by': False,
'extra_nav_links': {
'GitHub Repo': 'http://github.com/jupyterhub/jupyterhub',
'Issue Tracker': 'http://github.com/jupyterhub/jupyterhub/issues',
},
}
html_sidebars = {
'**': [
'about.html',
'searchbox.html',
'navigation.html',
'relations.html',
'sourcelink.html',
]
}
htmlhelp_basename = 'JupyterHubdoc'
# -- Options for LaTeX output ---------------------------------------------
latex_elements = {
# 'papersize': 'letterpaper',
# 'pointsize': '10pt',
# 'preamble': '',
# 'figure_align': 'htbp',
}
# Grouping the document tree into LaTeX files. List of tuples
# (source start file, target name, title,
# author, documentclass [howto, manual, or own class]).
latex_documents = [
(
master_doc,
'JupyterHub.tex',
u'JupyterHub Documentation',
u'Project Jupyter team',
'manual',
)
]
# latex_logo = None
# latex_use_parts = False
# latex_show_pagerefs = False
# latex_show_urls = False
# latex_appendices = []
# latex_domain_indices = True
# -- Read The Docs -----------------------------------------------------------
#
# Since RTD runs sphinx-build directly without running "make html", we run the
# pre-requisite steps for "make html" from here if needed.
#
if os.environ.get("READTHEDOCS"):
docs = os.path.dirname(os.path.dirname(__file__))
subprocess.check_call(["make", "metrics", "scopes"], cwd=docs)
# -- manual page output -------------------------------------------------
# One entry per manual page. List of tuples
# (source start file, name, description, authors, manual section).
man_pages = [(master_doc, 'jupyterhub', u'JupyterHub Documentation', [author], 1)]
# man_show_urls = False
# -- Texinfo output -----------------------------------------------------
# Grouping the document tree into Texinfo files. List of tuples
# (source start file, target name, title, author,
# dir menu entry, description, category)
texinfo_documents = [
(
master_doc,
'JupyterHub',
u'JupyterHub Documentation',
author,
'JupyterHub',
'One line description of project.',
'Miscellaneous',
)
]
# texinfo_appendices = []
# texinfo_domain_indices = True
# texinfo_show_urls = 'footnote'
# texinfo_no_detailmenu = False
# -- Epub output --------------------------------------------------------
# Bibliographic Dublin Core info.
epub_title = project
epub_author = author
epub_publisher = author
epub_copyright = copyright
# A list of files that should not be packed into the epub file.
epub_exclude_files = ['search.html']
# -- Intersphinx ----------------------------------------------------------
intersphinx_mapping = {'https://docs.python.org/3/': None}
# -- Read The Docs --------------------------------------------------------
on_rtd = os.environ.get('READTHEDOCS', None) == 'True'
if on_rtd:
# readthedocs.org uses their theme by default, so no need to specify it
# build rest-api, since RTD doesn't run make
from subprocess import check_call as sh
sh(['make', 'rest-api'], cwd=docs)
# -- Spell checking -------------------------------------------------------
# -- Spell checking ----------------------------------------------------------
# ref: https://sphinxcontrib-spelling.readthedocs.io/en/latest/customize.html#configuration-options
#
# The "sphinxcontrib.spelling" extension is optionally enabled if its available.
#
try:
import sphinxcontrib.spelling
import sphinxcontrib.spelling # noqa
except ImportError:
pass
else:
extensions.append("sphinxcontrib.spelling")
spelling_word_list_filename = "spelling_wordlist.txt"
spelling_word_list_filename = 'spelling_wordlist.txt'
# -- Options for HTML output -------------------------------------------------
# ref: https://www.sphinx-doc.org/en/master/usage/configuration.html#options-for-html-output
#
html_logo = "_static/images/logo/logo.png"
html_favicon = "_static/images/logo/favicon.ico"
html_static_path = ["_static"]
html_theme = "pydata_sphinx_theme"
html_theme_options = {
"icon_links": [
{
"name": "GitHub",
"url": "https://github.com/jupyterhub/jupyterhub",
"icon": "fab fa-github-square",
},
{
"name": "Discourse",
"url": "https://discourse.jupyter.org/c/jupyterhub/10",
"icon": "fab fa-discourse",
},
],
"use_edit_page_button": True,
"navbar_align": "left",
}
html_context = {
"github_user": "jupyterhub",
"github_repo": "jupyterhub",
"github_version": "main",
"doc_path": "docs/source",
}
# -- Options for linkcheck builder -------------------------------------------
# ref: https://www.sphinx-doc.org/en/master/usage/configuration.html#options-for-the-linkcheck-builder
#
linkcheck_ignore = [
r"(.*)github\.com(.*)#", # javascript based anchors
r"(.*)/#%21(.*)/(.*)", # /#!forum/jupyter - encoded anchor edge case
r"https://github.com/[^/]*$", # too many github usernames / searches in changelog
"https://github.com/jupyterhub/jupyterhub/pull/", # too many PRs in changelog
"https://github.com/jupyterhub/jupyterhub/compare/", # too many comparisons in changelog
]
linkcheck_anchors_ignore = [
"/#!",
"/#%21",
]
# -- Intersphinx -------------------------------------------------------------
# ref: https://www.sphinx-doc.org/en/master/usage/extensions/intersphinx.html#configuration
#
intersphinx_mapping = {
"python": ("https://docs.python.org/3/", None),
"tornado": ("https://www.tornadoweb.org/en/stable/", None),
}
# -- Options for the opengraph extension -------------------------------------
# ref: https://github.com/wpilibsuite/sphinxext-opengraph#options
#
# ogp_site_url is set automatically by RTD
ogp_image = "_static/logo.png"
ogp_use_first_image = True
# -- Options for the rediraffe extension -------------------------------------
# ref: https://github.com/wpilibsuite/sphinxext-rediraffe#readme
#
# This extensions help us relocated content without breaking links. If a
# document is moved internally, a redirect like should be configured below to
# help us not break links.
#
rediraffe_branch = "main"
rediraffe_redirects = {
# "old-file": "new-folder/new-file-name",
}

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

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

18
docs/source/contributing/docs.rst
View File

@@ -5,7 +5,7 @@ Contributing Documentation
==========================
Documentation is often more important than code. This page helps
you get set up on how to contribute documentation to JupyterHub.
you get set up on how to contribute to JupyterHub's documentation.
Building documentation locally
==============================
@@ -13,12 +13,12 @@ Building documentation locally
We use `sphinx <http://sphinx-doc.org>`_ to build our documentation. It takes
our documentation source files (written in `markdown
<https://daringfireball.net/projects/markdown/>`_ or `reStructuredText
<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.
#. Make sure you have successfuly completed :ref:`contributing/setup`.
#. Make sure you have successfully completed :ref:`contributing/setup`.
#. Install the packages required to build the docs.
@@ -39,13 +39,17 @@ 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::
On macOS, you can open a file from the terminal with ``open <path-to-file>``.
On Linux, you can do the same with ``xdg-open <path-to-file>``.
**On Windows**, you can open a file from the terminal with ``start <path-to-file>``.
**On macOS**, you can do the same with ``open <path-to-file>``.
**On Linux**, you can do the same with ``xdg-open <path-to-file>``.
After opening index.html in your browser you can just refresh the page whenever
you rebuild the docs via ``make html``

21
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@@ -0,0 +1,21 @@
============
Contributing
============
We want you to contribute to JupyterHub in ways that are most exciting
& useful to you. We value documentation, testing, bug reporting & code equally,
and are glad to have your contributions in whatever form you wish :)
Our `Code of Conduct <https://github.com/jupyter/governance/blob/HEAD/conduct/code_of_conduct.md>`_
(`reporting guidelines <https://github.com/jupyter/governance/blob/HEAD/conduct/reporting_online.md>`_)
helps keep our community welcoming to as many people as possible.
.. toctree::
:maxdepth: 2
community
setup
docs
tests
roadmap
security

71
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@@ -4,10 +4,10 @@ This roadmap collects "next steps" for JupyterHub. It is about creating a
shared understanding of the project's vision and direction amongst
the community of users, contributors, and maintainers.
The goal is to communicate priorities and upcoming release plans.
It is not a aimed at limiting contributions to what is listed here.
It is not aimed at limiting contributions to what is listed here.
## Using the roadmap
### 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.

71
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View File

@@ -7,28 +7,27 @@ Setting up a development install
System requirements
===================
JupyterHub can only run on MacOS or Linux operating systems. If you are
using Windows, we recommend using `VirtualBox <https://virtualbox.org>`_
JupyterHub can only run on macOS or Linux operating systems. If you are
using Windows, we recommend using `VirtualBox <https://virtualbox.org>`_
or a similar system to run `Ubuntu Linux <https://ubuntu.com>`_ for
development.
Install Python
--------------
JupyterHub is written in the `Python <https://python.org>`_ programming language, and
requires you have at least version 3.5 installed locally. If you haven’t
JupyterHub is written in the `Python <https://python.org>`_ programming language and
requires you have at least version 3.6 installed locally. If you haven’t
installed Python before, the recommended way to install it is to use
`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
--------------
``configurable-http-proxy``, the default proxy implementation for
JupyterHub, is written in Javascript to run on `NodeJS
<https://nodejs.org/en/>`_. If you have not installed nodejs before, we
recommend installing it in the ``miniconda`` environment you set up for
Python. You can do so with ``conda install nodejs``.
`NodeJS 12+ <https://nodejs.org/en/>`_ is required for building some JavaScript components.
``configurable-http-proxy``, the default proxy implementation for JupyterHub, is written in Javascript.
If you have not installed NodeJS before, we recommend installing it in the ``miniconda`` environment you set up for Python.
You can do so with ``conda install nodejs``.
Many in the Jupyter community use [``nvm``](https://github.com/nvm-sh/nvm) to
managing node dependencies.
@@ -36,7 +35,7 @@ managing node dependencies.
Install git
-----------
JupyterHub uses `git <https://git-scm.com>`_ & `GitHub <https://github.com>`_
JupyterHub uses `Git <https://git-scm.com>`_ & `GitHub <https://github.com>`_
for development & collaboration. You need to `install git
<https://git-scm.com/book/en/v2/Getting-Started-Installing-Git>`_ to work on
JupyterHub. We also recommend getting a free account on GitHub.com.
@@ -44,11 +43,15 @@ JupyterHub. We also recommend getting a free account on GitHub.com.
Setting up a development install
================================
When developing JupyterHub, you need to make changes to the code & see
their effects quickly. You need to do a developer install to make that
happen.
When developing JupyterHub, you would need to make changes and be able to instantly view the results of the changes. To achieve that, a developer install is required.
1. Clone the `JupyterHub git repository <https://github.com/jupyterhub/jupyterhub>`_
.. note:: This guide does not attempt to dictate *how* development
environments should be isolated since that is a personal preference and can
be achieved in many ways, for example, `tox`, `conda`, `docker`, etc. See this
`forum thread <https://discourse.jupyter.org/t/thoughts-on-using-tox/3497>`_ for
a more detailed discussion.
1. Clone the `JupyterHub git repository <https://github.com/jupyterhub/jupyterhub>`_
to your computer.
.. code:: bash
@@ -63,7 +66,7 @@ happen.
python -V
This should return a version number greater than or equal to 3.5.
This should return a version number greater than or equal to 3.6.
.. code:: bash
@@ -71,12 +74,11 @@ happen.
This should return a version number greater than or equal to 5.0.
3. Install ``configurable-http-proxy``. This is required to run
JupyterHub.
3. Install ``configurable-http-proxy`` (required to run and test the default JupyterHub configuration) and ``yarn`` (required to build some components):
.. code:: bash
npm install -g configurable-http-proxy
npm install -g configurable-http-proxy yarn
If you get an error that says ``Error: EACCES: permission denied``, you might need to prefix the command with ``sudo``.
``sudo`` may be required to perform a system-wide install.
@@ -84,25 +86,31 @@ happen.
.. code:: bash
npm install configurable-http-proxy
npm install configurable-http-proxy yarn
export PATH=$PATH:$(pwd)/node_modules/.bin
The second line needs to be run every time you open a new terminal.
4. Install the python packages required for JupyterHub development.
If you are using conda you can instead run:
.. code:: bash
python3 -m pip install -r dev-requirements.txt
python3 -m pip install -r requirements.txt
conda install configurable-http-proxy yarn
5. 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.
4. Install an editable version of JupyterHub and its requirements for
development and testing. This lets you edit JupyterHub code in a text editor
& restart the JupyterHub process to see your code changes immediately.
.. code:: bash
python3 -m pip install --editable .
python3 -m pip install --editable ".[test]"
5. Set up a database.
The default database engine is ``sqlite`` so if you are just trying
to get up and running quickly for local development that should be
available via `Python <https://docs.python.org/3.5/library/sqlite3.html>`__.
See :doc:`/reference/database` for details on other supported databases.
6. You are now ready to start JupyterHub!
@@ -123,7 +131,7 @@ To simplify testing of JupyterHub, it’s helpful to use
authenticator and SimpleLocalProcessSpawner instead of the default spawner.
There is a sample configuration file that does this in
``testing/jupyterhub_config.py``. To launch jupyterhub with this
``testing/jupyterhub_config.py``. To launch JupyterHub with this
configuration:
.. code:: bash
@@ -139,14 +147,14 @@ JupyterHub as.
DummyAuthenticator allows you to log in with any username & password,
while SimpleLocalProcessSpawner allows you to start servers without having to
create a unix user for each JupyterHub user. Together, these make it
create a Unix user for each JupyterHub user. Together, these make it
much easier to test JupyterHub.
Tip: If you are working on parts of JupyterHub that are common to all
authenticators & spawners, we recommend using both DummyAuthenticator &
SimpleLocalProcessSpawner. If you are working on just authenticator related
SimpleLocalProcessSpawner. If you are working on just authenticator-related
parts, use only SimpleLocalProcessSpawner. Similarly, if you are working on
just spawner related parts, use only DummyAuthenticator.
just spawner-related parts, use only DummyAuthenticator.
Troubleshooting
===============
@@ -176,3 +184,4 @@ development updates, with:
python3 setup.py js # fetch updated client-side js
python3 setup.py css # recompile CSS from LESS sources
python3 setup.py jsx # build React admin app

113
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@@ -1,49 +1,49 @@
.. _contributing/tests:
==================
Testing JupyterHub
==================
===================================
Testing JupyterHub and linting code
===================================
Unit testing helps to validate that JupyterHub works the way we think it does,
and continues to do so when changes occur. They also help communicate
precisely what we expect our code to do.
JupyterHub uses `pytest <https://pytest.org>`_ for all our tests. You
can find them under ``jupyterhub/tests`` directory in the git repository.
JupyterHub uses `pytest <https://pytest.org>`_ for all the tests. You
can find them under the `jupyterhub/tests <https://github.com/jupyterhub/jupyterhub/tree/main/jupyterhub/tests>`_ directory in the git repository.
Running the tests
==================
#. Make sure you have completed :ref:`contributing/setup`. You should be able
to start ``jupyterhub`` from the commandline & access it from your
web browser. This ensures that the dev environment is properly set
#. Make sure you have completed :ref:`contributing/setup`. Once completed, you should be able
to run ``jupyterhub`` on your command line and access JupyterHub from your browser at http://localhost:8000. Being able to run and access `jupyterhub` should mean that the dev environment is properly set
up for tests to run.
#. You can run all tests in JupyterHub
.. code-block:: bash
pytest --async-test-timeout 15 -v jupyterhub/tests
pytest -v jupyterhub/tests
This should display progress as it runs all the tests, printing
information about any test failures as they occur.
If you wish to confirm test coverage the run tests with the `--cov` flag:
The ``--async-test-timeout`` parameter is used by `pytest-tornado
<https://github.com/eugeniy/pytest-tornado#markers>`_ to set the
asynchronous test timeout to 15 seconds rather than the default 5,
since some of our tests take longer than 5s to execute.
.. code-block:: bash
pytest -v --cov=jupyterhub jupyterhub/tests
#. You can also run tests in just a specific file:
.. code-block:: bash
pytest --async-test-timeout 15 -v jupyterhub/tests/<test-file-name>
pytest -v jupyterhub/tests/<test-file-name>
#. To run a specific test only, you can do:
.. code-block:: bash
pytest --async-test-timeout 15 -v jupyterhub/tests/<test-file-name>::<test-name>
pytest -v jupyterhub/tests/<test-file-name>::<test-name>
This runs the test with function name ``<test-name>`` defined in
``<test-file-name>``. This is very useful when you are iteratively
@@ -56,6 +56,49 @@ Running the tests
pytest -v jupyterhub/tests/test_api.py::test_shutdown
For more information, refer to the `pytest usage documentation <https://pytest.readthedocs.io/en/latest/usage.html>`_.
Test organisation
=================
The tests live in ``jupyterhub/tests`` and are organized roughly into:
#. ``test_api.py`` tests the REST API
#. ``test_pages.py`` tests loading the HTML pages
and other collections of tests for different components.
When writing a new test, there should usually be a test of
similar functionality already written and related tests should
be added nearby.
The fixtures live in ``jupyterhub/tests/conftest.py``. There are
fixtures that can be used for JupyterHub components, such as:
- ``app``: an instance of JupyterHub with mocked parts
- ``auth_state_enabled``: enables persisting auth_state (like authentication tokens)
- ``db``: a sqlite in-memory DB session
- ``io_loop```: a Tornado event loop
- ``event_loop``: a new asyncio event loop
- ``user``: creates a new temporary user
- ``admin_user``: creates a new temporary admin user
- single user servers
- ``cleanup_after``: allows cleanup of single user servers between tests
- mocked service
- ``MockServiceSpawner``: a spawner that mocks services for testing with a short poll interval
- ``mockservice```: mocked service with no external service url
- ``mockservice_url``: mocked service with a url to test external services
And fixtures to add functionality or spawning behavior:
- ``admin_access``: grants admin access
- ``no_patience```: sets slow-spawning timeouts to zero
- ``slow_spawn``: enables the SlowSpawner (a spawner that takes a few seconds to start)
- ``never_spawn``: enables the NeverSpawner (a spawner that will never start)
- ``bad_spawn``: enables the BadSpawner (a spawner that fails immediately)
- ``slow_bad_spawn``: enables the SlowBadSpawner (a spawner that fails after a short delay)
For information on using the existing fixtures and creating new ones, refer to the `pytest fixtures documentation <https://pytest.readthedocs.io/en/latest/fixture.html>`_
Troubleshooting Test Failures
=============================
@@ -63,16 +106,34 @@ Troubleshooting Test Failures
All the tests are failing
-------------------------
Make sure you have completed all the steps in :ref:`contributing/setup` sucessfully, and
can launch ``jupyterhub`` from the terminal.
Make sure you have completed all the steps in :ref:`contributing/setup` successfully, and are able to access JupyterHub from your browser at http://localhost:8000 after starting ``jupyterhub`` in your command line.
Tests are timing out
--------------------
The ``--async-test-timeout`` parameter to ``pytest`` is used by
`pytest-tornado <https://github.com/eugeniy/pytest-tornado#markers>`_ to set
the asynchronous test timeout to a higher value than the default of 5s,
since some of our tests take longer than 5s to execute. If the tests
are still timing out, try increasing that value even more. You can
also set an environment variable ``ASYNC_TEST_TIMEOUT`` instead of
passing ``--async-test-timeout`` to each invocation of pytest.
Code formatting and linting
===========================
JupyterHub automatically enforces code formatting. This means that pull requests
with changes breaking this formatting will receive a commit from pre-commit.ci
automatically.
To automatically format code locally, you can install pre-commit and register a
*git hook* to automatically check with pre-commit before you make a commit if
the formatting is okay.
.. code:: bash
pip install pre-commit
pre-commit install --install-hooks
To run pre-commit manually you would do:
.. code:: bash
# check for changes to code not yet committed
pre-commit run
# check for changes also in already committed code
pre-commit run --all-files
You may also install `black integration <https://github.com/psf/black#editor-integration>`_
into your text editor to format code automatically.

1
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@@ -120,3 +120,4 @@ contribution on JupyterHub:
- yuvipanda
- zoltan-fedor
- zonca
- Neeraj Natu

46
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View File

@@ -0,0 +1,46 @@
Event logging and telemetry
===========================
JupyterHub can be configured to record structured events from a running server using Jupyter's `Telemetry System`_. The types of events that JupyterHub emits are defined by `JSON schemas`_ listed at the bottom of this page_.
.. _logging: https://docs.python.org/3/library/logging.html
.. _`Telemetry System`: https://github.com/jupyter/telemetry
.. _`JSON schemas`: https://json-schema.org/
How to emit events
------------------
Event logging is handled by its ``Eventlog`` object. This leverages Python's standing logging_ library to emit, filter, and collect event data.
To begin recording events, you'll need to set two configurations:
1. ``handlers``: tells the EventLog *where* to route your events. This trait is a list of Python logging handlers that route events to the event log file.
2. ``allows_schemas``: tells the EventLog *which* events should be recorded. No events are emitted by default; all recorded events must be listed here.
Here's a basic example:
.. code-block::
import logging
c.EventLog.handlers = [
logging.FileHandler('event.log'),
]
c.EventLog.allowed_schemas = [
'hub.jupyter.org/server-action'
]
The output is a file, ``"event.log"``, with events recorded as JSON data.
.. _page:
Event schemas
-------------
.. toctree::
:maxdepth: 2
server-actions.rst

1
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@@ -0,0 +1 @@
.. jsonschema:: ../../../jupyterhub/event-schemas/server-actions/v1.yaml

85
docs/source/gallery-jhub-deployments.md
View File

@@ -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
@@ -87,7 +97,7 @@ easy to do with RStudio too.
### University of Illinois
- https://datascience.business.illinois.edu (currently down; checked 04/26/19)
- https://datascience.business.illinois.edu (currently down; checked 10/26/22)
### IllustrisTNG Simulation Project
@@ -112,11 +122,11 @@ easy to do with RStudio too.
### Paderborn University
- [Data Science (DICE) group](https://dice.cs.uni-paderborn.de/)
- [nbgraderutils](https://github.com/dice-group/nbgraderutils): Use JupyterHub + nbgrader + iJava kernel for online Java exercises. Used in lecture Statistical Natural Language Processing.
- [nbgraderutils](https://github.com/dice-group/nbgraderutils): Use JupyterHub + nbgrader + iJava kernel for online Java exercises. Used in lecture Statistical Natural Language Processing.
### Penn State University
- [Press release](https://news.psu.edu/story/523093/2018/05/24/new-open-source-web-apps-available-students-and-faculty): "New open-source web apps available for students and faculty" (but Hub is currently down; checked 04/26/19)
- [Press release](https://news.psu.edu/story/523093/2018/05/24/new-open-source-web-apps-available-students-and-faculty): "New open-source web apps available for students and faculty"
### University of Rochester CIRC
@@ -125,33 +135,34 @@ easy to do with RStudio too.
### University of California San Diego
- San Diego Supercomputer Center - Andrea Zonca
- [Deploy JupyterHub on a Supercomputer with SSH](https://zonca.github.io/2017/05/jupyterhub-hpc-batchspawner-ssh.html)
- [Run Jupyterhub on a Supercomputer](https://zonca.github.io/2015/04/jupyterhub-hpc.html)
- [Deploy JupyterHub on a VM for a Workshop](https://zonca.github.io/2016/04/jupyterhub-sdsc-cloud.html)
- [Customize your Python environment in Jupyterhub](https://zonca.github.io/2017/02/customize-python-environment-jupyterhub.html)
- [Jupyterhub deployment on multiple nodes with Docker Swarm](https://zonca.github.io/2016/05/jupyterhub-docker-swarm.html)
- [Sample deployment of Jupyterhub in HPC on SDSC Comet](https://zonca.github.io/2017/02/sample-deployment-jupyterhub-hpc.html)
- [Deploy JupyterHub on a Supercomputer with SSH](https://zonca.github.io/2017/05/jupyterhub-hpc-batchspawner-ssh.html)
- [Run Jupyterhub on a Supercomputer](https://zonca.github.io/2015/04/jupyterhub-hpc.html)
- [Deploy JupyterHub on a VM for a Workshop](https://zonca.github.io/2016/04/jupyterhub-sdsc-cloud.html)
- [Customize your Python environment in Jupyterhub](https://zonca.github.io/2017/02/customize-python-environment-jupyterhub.html)
- [Jupyterhub deployment on multiple nodes with Docker Swarm](https://zonca.github.io/2016/05/jupyterhub-docker-swarm.html)
- [Sample deployment of Jupyterhub in HPC on SDSC Comet](https://zonca.github.io/2017/02/sample-deployment-jupyterhub-hpc.html)
- Educational Technology Services - Paul Jamason
- [jupyterhub.ucsd.edu](https://jupyterhub.ucsd.edu)
- [jupyterhub.ucsd.edu](https://jupyterhub.ucsd.edu)
### TACC University of Texas
### Texas A&M
- Kristen Thyng - Oceanography
- [Teaching with JupyterHub and nbgrader](http://kristenthyng.com/blog/2016/09/07/jupyterhub+nbgrader/)
- [Teaching with JupyterHub and nbgrader](http://kristenthyng.com/blog/2016/09/07/jupyterhub+nbgrader/)
### Elucidata
- What's new in Jupyter Notebooks @[Elucidata](https://elucidata.io/):
- Using Jupyter Notebooks with Jupyterhub on GCP, managed by GKE
- https://medium.com/elucidata/why-you-should-be-using-a-jupyter-notebook-8385a4ccd93d
- What's new in Jupyter Notebooks @[Elucidata](https://elucidata.io/):
- [Using Jupyter Notebooks with Jupyterhub on GCP, managed by GKE](https://medium.com/elucidata/why-you-should-be-using-a-jupyter-notebook-8385a4ccd93d)
## Service Providers
### AWS
- [running-jupyter-notebook-and-jupyterhub-on-amazon-emr](https://aws.amazon.com/blogs/big-data/running-jupyter-notebook-and-jupyterhub-on-amazon-emr/)
- [Run Jupyter Notebook and JupyterHub on Amazon EMR](https://aws.amazon.com/blogs/big-data/running-jupyter-notebook-and-jupyterhub-on-amazon-emr/)
### Google Cloud Platform
@@ -164,28 +175,28 @@ easy to do with RStudio too.
### Microsoft Azure
- https://docs.microsoft.com/en-us/azure/machine-learning/machine-learning-data-science-linux-dsvm-intro
- [Azure Data Science Virtual Machine release notes](https://docs.microsoft.com/en-us/azure/machine-learning/machine-learning-data-science-linux-dsvm-intro)
### Rackspace Carina
- https://getcarina.com/blog/learning-how-to-whale/
- http://carolynvanslyck.com/talk/carina/jupyterhub/#/
- http://carolynvanslyck.com/talk/carina/jupyterhub/#/ (but carolynvanslyck is currently down; checked 10/26/22)
### Hadoop
- [Deploying JupyterHub on Hadoop](https://jupyterhub-on-hadoop.readthedocs.io)
## Miscellaneous
- https://medium.com/@ybarraud/setting-up-jupyterhub-with-sudospawner-and-anaconda-844628c0dbee#.rm3yt87e1
- https://groups.google.com/forum/#!topic/jupyter/nkPSEeMr8c0 Mailing list UT deployment
- JupyterHub setup on Centos https://gist.github.com/johnrc/604971f7d41ebf12370bf5729bf3e0a4
- Deploy JupyterHub to Docker Swarm https://jupyterhub.surge.sh/#/welcome
- [Mailing list UT deployment](https://groups.google.com/forum/#!topic/jupyter/nkPSEeMr8c0)
- [JupyterHub setup on Centos](https://gist.github.com/johnrc/604971f7d41ebf12370bf5729bf3e0a4)
- [Deploy JupyterHub to Docker Swarm](https://jupyterhub.surge.sh/#/welcome)
- http://www.laketide.com/building-your-lab-part-3/
- http://estrellita.hatenablog.com/entry/2015/07/31/083202
- http://www.walkingrandomly.com/?p=5734
- https://wrdrd.com/docs/consulting/education-technology
- https://bitbucket.org/jackhale/fenics-jupyter
- [LinuxCluster blog](https://linuxcluster.wordpress.com/category/application/jupyterhub/)
- [Network Technology](https://arnesund.com/tag/jupyterhub/) [Spark Cluster on OpenStack with Multi-User Jupyter Notebook](https://arnesund.com/2015/09/21/spark-cluster-on-openstack-with-multi-user-jupyter-notebook/)
- [Network Technology](https://arnesund.com/tag/jupyterhub/)
- [Spark Cluster on OpenStack with Multi-User Jupyter Notebook](https://arnesund.com/2015/09/21/spark-cluster-on-openstack-with-multi-user-jupyter-notebook/)

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@@ -1,40 +1,51 @@
# Authentication and User Basics
The default Authenticator uses [PAM][] to authenticate system users with
The default Authenticator uses [PAM][] (Pluggable Authentication Module) 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 (`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.
```{warning}
If this configuration value is not set, then **all authenticated users will be allowed into your hub**.
```
## Configure admins (`admin_users`)
```{note}
As of JupyterHub 2.0, the full permissions of `admin_users`
should not be required.
Instead, you can assign [roles](define-role-target) to users or groups
with only the scopes they require.
```
Admin users of JupyterHub, `admin_users`, can add and remove users from
the user `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:
Each Authenticator may have different ways of determining whether a user is an
administrator. By default, JupyterHub uses the PAMAuthenticator which provides the
`admin_groups` option and can set administrator status based on a user
group. For example, we can let any user in the `wheel` group be an admin:
```python
c.PAMAuthenticator.admin_groups = {'wheel'}
@@ -42,35 +53,35 @@ c.PAMAuthenticator.admin_groups = {'wheel'}
## Give admin access to other users' notebook servers (`admin_access`)
Since the default `JupyterHub.admin_access` setting is False, the admins
Since the default `JupyterHub.admin_access` setting is `False`, the admins
do not have permission to log in to the single user notebook servers
owned by *other users*. If `JupyterHub.admin_access` is set to True,
then admins have permission to log in *as other users* on their
respective machines, for debugging. **As a courtesy, you should make
owned by _other users_. If `JupyterHub.admin_access` is set to `True`,
then admins have permission to log in _as other users_ on their
respective machines for debugging. **As a courtesy, you should make
sure your users know if admin_access is enabled.**
## Add or remove users from the Hub
Users can be added to and removed from the Hub via either the admin
Users can be added to and removed from the Hub via 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.
## Use LocalAuthenticator to create system users
The `LocalAuthenticator` is a special kind of authenticator that has
The `LocalAuthenticator` is a special kind of Authenticator that has
the ability to manage users on the local system. When you try to add a
new user to the Hub, a `LocalAuthenticator` will check if the user
already exists. If you set the configuration value, `create_system_users`,
to `True` in the configuration file, the `LocalAuthenticator` has
the privileges to add users to the system. The setting in the config
the ability to add users to the system. The setting in the config
file is:
```python
@@ -80,7 +91,7 @@ c.LocalAuthenticator.create_system_users = True
Adding a user to the Hub that doesn't already exist on the system will
result in the Hub creating that user via the system `adduser` command
line tool. This option is typically used on hosted deployments of
JupyterHub, to avoid the need to manually create all your users before
JupyterHub to avoid the need to manually create all your users before
launching the service. This approach is not recommended when running
JupyterHub in situations where JupyterHub users map directly onto the
system's UNIX users.
@@ -90,27 +101,25 @@ system's UNIX users.
JupyterHub's [OAuthenticator][] currently supports the following
popular services:
- Auth0
- Bitbucket
- CILogon
- GitHub
- GitLab
- Globus
- Google
- MediaWiki
- Okpy
- OpenShift
- [Auth0](https://oauthenticator.readthedocs.io/en/latest/api/gen/oauthenticator.auth0.html#module-oauthenticator.auth0)
- [Azure AD](https://oauthenticator.readthedocs.io/en/latest/api/gen/oauthenticator.azuread.html#module-oauthenticator.azuread)
- [Bitbucket](https://oauthenticator.readthedocs.io/en/latest/api/gen/oauthenticator.bitbucket.html#module-oauthenticator.bitbucket)
- [CILogon](https://oauthenticator.readthedocs.io/en/latest/api/gen/oauthenticator.cilogon.html#module-oauthenticator.cilogon)
- [GitHub](https://oauthenticator.readthedocs.io/en/latest/api/gen/oauthenticator.github.html#module-oauthenticator.github)
- [GitLab](https://oauthenticator.readthedocs.io/en/latest/api/gen/oauthenticator.gitlab.html#module-oauthenticator.gitlab)
- [Globus](https://oauthenticator.readthedocs.io/en/latest/api/gen/oauthenticator.globus.html#module-oauthenticator.globus)
- [Google](https://oauthenticator.readthedocs.io/en/latest/api/gen/oauthenticator.google.html#module-oauthenticator.google)
- [MediaWiki](https://oauthenticator.readthedocs.io/en/latest/api/gen/oauthenticator.mediawiki.html#module-oauthenticator.mediawiki)
- [Okpy](https://oauthenticator.readthedocs.io/en/latest/api/gen/oauthenticator.okpy.html#module-oauthenticator.okpy)
- [OpenShift](https://oauthenticator.readthedocs.io/en/latest/api/gen/oauthenticator.openshift.html#module-oauthenticator.openshift)
NOTE: Open issue asking for more details on this generic implementation.
It's not clear if this is a different implementation or if the JupyterHub OAuth
_is_ the generic implementation.
A generic implementation, which you can use for OAuth authentication
A [generic implementation](https://oauthenticator.readthedocs.io/en/latest/api/gen/oauthenticator.generic.html#module-oauthenticator.generic), which you can use for OAuth authentication
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 or 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:
@@ -118,5 +127,5 @@ 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

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

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@@ -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.

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@@ -1,5 +1,10 @@
Getting Started
===============
Get Started
===========
This section covers how to configure and customize JupyterHub for your
needs. It contains information about authentication, networking, security, and
other topics that are relevant to individuals or organizations deploying their
own JupyterHub.
.. toctree::
:maxdepth: 2
@@ -10,3 +15,5 @@ Getting Started
authenticators-users-basics
spawners-basics
services-basics
faq
institutional-faq

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@@ -0,0 +1,260 @@
# Institutional FAQ
This page contains common questions from users of JupyterHub,
broken down by their roles within organizations.
## For all
### Is it appropriate for adoption within a larger institutional context?
Yes! JupyterHub has been used at-scale for large pools of users, as well
as complex and high-performance computing. For example, UC Berkeley uses
JupyterHub for its Data Science Education Program courses (serving over
3,000 students). The Pangeo project uses JupyterHub to provide access
to scalable cloud computing with Dask. JupyterHub is stable and customizable
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
narrative text with code cells and their outputs. It is also a graphical interface
that allows users to edit these documents. There are also several other graphical interfaces
that allow users to edit the `.ipynb` format (nteract, Jupyter Lab, Google Colab, Kaggle, etc).
- **JupyterLab** is a flexible and extendible user interface for interactive computing. It
has several extensions that are tailored for using Jupyter Notebooks, as well as extensions
for other parts of the data science stack.
- **JupyterHub** is an application that manages interactive computing sessions for **multiple users**.
It also connects them with infrastructure those users wish to access. It can provide
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,
the R tidyverse, and Jupyter Notebooks) on institutional infrastructure. It also allows administrators
some control over access to resources, security, environments, and authentication.
### Is JupyterHub mature? Why should we trust it?
Yes - the core JupyterHub application recently
reached 1.0 status, and is considered stable and performant for most institutions.
JupyterHub has also been deployed (along with other tools) to work on
scalable infrastructure, large datasets, and high-performance computing.
### Who else uses JupyterHub?
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
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
access to organizational hardware, data, and analytics environments at scale.
Here is a sample of organizations that use JupyterHub:
- **Universities and colleges**: UC Berkeley, UC San Diego, Cal Poly SLO, Harvard University, University of Chicago,
University of Oslo, University of Sheffield, Université Paris Sud, University of Versailles
- **Research laboratories**: NASA, NCAR, NOAA, the Large Synoptic Survey Telescope, Brookhaven National Lab,
Minnesota Supercomputing Institute, ALCF, CERN, Lawrence Livermore National Laboratory
- **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.
### How does JupyterHub compare with hosted products, like Google Colaboratory, RStudio.cloud, or Anaconda Enterprise?
JupyterHub puts you in control of your data, infrastructure, and coding environment.
In addition, it is vendor neutral, which reduces lock-in to a particular vendor or service.
JupyterHub provides access to interactive computing environments in the cloud (similar to each of these services).
Compared with the tools above, it is more flexible, more customizable, free, and
gives administrators more control over their setup and hardware.
Because JupyterHub is an open-source, community-driven tool, it can be extended and
modified to fit an institution's needs. It plays nicely with the open source data science
stack, and can serve a variety of computing environments, user interfaces, and
computational hardware. It can also be deployed anywhere - on enterprise cloud infrastructure, on
High-Performance-Computing machines, on local hardware, or even on a single laptop, which
is not possible with most other tools for shared interactive computing.
## For IT
### How would I set up JupyterHub on institutional hardware?
That depends on what kind of hardware you've got. JupyterHub is flexible enough to be deployed
on a variety of hardware, including in-room hardware, on-prem clusters, cloud infrastructure,
etc.
The most common way to set up a JupyterHub is to use a JupyterHub distribution, these are pre-configured
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
guide that runs on Kubernetes. Better for larger or dynamic user groups (50-10,000) or more complex
compute/data needs.
- [The Littlest JupyterHub](https://tljh.jupyter.org) is a lightweight JupyterHub that runs on a single
single machine (in the cloud or under your desk). Better for smaller user groups (4-80) or more
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.
Depending on the distribution of JupyterHub that you'd like to use, you can also connect your JupyterHub
deployment with a number of other cloud-native services so that users have access to other resources from
their interactive computing sessions.
For example, if you use the [Zero to JupyterHub for Kubernetes](https://z2jh.jupyter.org) distribution,
you'll be able to utilize container-based workflows of other technologies such as the [dask-kubernetes](https://kubernetes.dask.org/en/latest/)
project for distributed computing.
The Z2JH Helm Chart also has some functionality built in for auto-scaling your cluster up and down
as more resources are needed - allowing you to utilize the benefits of a flexible cloud-based deployment.
### Is JupyterHub secure?
The short answer: yes. JupyterHub as a standalone application has been battle-tested at an institutional
level for several years, and makes a number of "default" security decisions that are reasonable for most
users.
- For security considerations in the base JupyterHub application,
[see the JupyterHub security page](https://jupyterhub.readthedocs.io/en/stable/reference/websecurity.html).
- For security considerations when deploying JupyterHub on Kubernetes, see the
[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
in a variety of deployment setups. This often entails connecting your JupyterHub to **other** infrastructure
(such as a [Dask Gateway service](https://gateway.dask.org/)). There are many security decisions to be made
in these cases, and the security of your JupyterHub deployment will often depend on these decisions.
If you are worried about security, don't hesitate to reach out to the JupyterHub community in the
[Jupyter Community Forum](https://discourse.jupyter.org/c/jupyterhub). This community of practice has many
individuals with experience running secure JupyterHub deployments.
### Does JupyterHub provide computing or data infrastructure?
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
kind of **authentication** you'd like to use. For example, you can have users sign up with an institutional
email address, or choose a username / password when they first log-in, or offload authentication onto
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
gives you the abiltiy to stop or restart kernels, inspect user filesystems, and even take over user
sessions to assist them with debugging.
### How do I manage software environments?
A key benefit of JupyterHub is the ability for an administrator to define the environment(s) that users
have access to. There are many ways to do this, depending on what kind of infrastructure you're using for
your JupyterHub.
For example, **The Littlest JupyterHub** runs on a single VM. In this case, the administrator defines
an environment by installing packages to a shared folder that exists on the path of all users. The
**JupyterHub for Kubernetes** deployment uses Docker images to define environments. You can create your
own list of Docker images that users can select from, and can also control things like the amount of
RAM available to users, or the types of machines that their sessions will use in the cloud.
### How does JupyterHub manage computational resources?
For interactive computing sessions, JupyterHub controls computational resources via a **spawner**.
Spawners define how a new user session is created, and are customized for particular kinds of
infrastructure. For example, the KubeSpawner knows how to control a Kubernetes deployment
to create new pods when users log in.
For more sophisticated computational resources (like distributed computing), JupyterHub can
connect with other infrastructure tools (like Dask or Spark). This allows users to control
scalable or high-performance resources from within their JupyterHub sessions. The logic of
how those resources are controlled is taken care of by the non-JupyterHub application.
### Can JupyterHub be used with my high-performance computing resources?
Yes - JupyterHub can provide access to many kinds of computing infrastructure.
Especially when combined with other open-source schedulers such as Dask, you can manage fairly
complex computing infrastructures from the interactive sessions of a JupyterHub. For example
[see the Dask HPC page](https://docs.dask.org/en/latest/setup/hpc.html).
### How much resources do user sessions take?
This is highly configurable by the administrator. If you wish for your users to have simple
data analytics environments for prototyping and light data exploring, you can restrict their
memory and CPU based on the resources that you have available. If you'd like your JupyterHub
to serve as a gateway to high-performance compute or data resources, you may increase the
resources available on user machines, or connect them with computing infrastructures elsewhere.
### Can I customize the look and feel of a JupyterHub?
JupyterHub provides some customization of the graphics displayed to users. The most common
modification is to add custom branding to the JupyterHub login page, loading pages, and
various elements that persist across all pages (such as headers).
## For Technical Leads
### Will JupyterHub “just work” with our team's interactive computing setup?
Depending on the complexity of your setup, you'll have different experiences with "out of the box"
distributions of JupyterHub. If all of the resources you need will fit on a single VM, then
[The Littlest JupyterHub](https://tljh.jupyter.org) should get you up-and-running within
a half day or so. For more complex setups, such as scalable Kubernetes clusters or access
to high-performance computing and data, it will require more time and expertise with
the technologies your JupyterHub will use (e.g., dev-ops knowledge with cloud computing).
In general, the base JupyterHub deployment is not the bottleneck for setup, it is connecting
your JupyterHub with the various services and tools that you wish to provide to your users.
### How well does JupyterHub scale? What are JupyterHub's limitations?
JupyterHub works well at both a small scale (e.g., a single VM or machine) as well as a
high scale (e.g., a scalable Kubernetes cluster). It can be used for teams as small as 2, and
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
possible to configure the JupyterHub to be fairly resistant to failures in the system.
For example, if JupyterHub fails, then user sessions will not be affected (though new
users will not be able to log in). When a JupyterHub process is restarted, it should
seamlessly connect with the user database and the system will return to normal.
Again, the details of your JupyterHub deployment (e.g., whether it's deployed on a scalable cluster)
will affect the resiliency of the deployment.
### What interfaces does JupyterHub support?
Out of the box, JupyterHub supports a variety of popular data science interfaces for user sessions,
such as JupyterLab, Jupyter Notebooks, and RStudio. Any interface that can be served
via a web address can be served with a JupyterHub (with the right setup).
### Does JupyterHub make it easier for our team to collaborate?
JupyterHub provides a standardized environment and access to shared resources for your teams.
This greatly reduces the cost associated with sharing analyses and content with other team
members, and makes it easier to collaborate and build off of one another's ideas. Combined with
access to high-performance computing and data, JupyterHub provides a common resource to
amplify your team's ability to prototype their analyses, scale them to larger data, and then
share their results with one another.
JupyterHub also provides a computational framework to share computational narratives between
different levels of an organization. For example, data scientists can share Jupyter Notebooks
rendered as [Voilà dashboards](https://voila.readthedocs.io/en/stable/) with those who are not
familiar with programming, or create publicly-available interactive analyses to allow others to
interact with your work.
### Can I use JupyterHub with R/RStudio or other languages and environments?
Yes, Jupyter is a polyglot project, and there are over 40 community-provided kernels for a variety
of languages (the most common being Python, Julia, and R). You can also use a JupyterHub to provide
access to other interfaces, such as RStudio, that provide their own access to a language kernel.

14
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@@ -11,8 +11,8 @@ 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;
instead, use of `'0.0.0.0'` is preferred.
(`''`) 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
JupyterHub **command line options**:
@@ -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.

146
docs/source/getting-started/security-basics.rst
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@@ -5,17 +5,17 @@ Security settings
You should not run JupyterHub without SSL encryption on a public network.
Security is the most important aspect of configuring Jupyter. Three
configuration settings are the main aspects of security configuration:
Security is the most important aspect of configuring Jupyter.
Three (3) configuration settings are the main aspects of security configuration:
1. :ref:`SSL encryption <ssl-encryption>` (to enable HTTPS)
2. :ref:`Cookie secret <cookie-secret>` (a key for encrypting browser cookies)
3. Proxy :ref:`authentication token <authentication-token>` (used for the Hub and
other services to authenticate to the Proxy)
The Hub hashes all secrets (e.g., auth tokens) before storing them in its
The Hub hashes all secrets (e.g. auth tokens) before storing them in its
database. A loss of control over read-access to the database should have
minimal impact on your deployment; if your database has been compromised, it
minimal impact on your deployment. If your database has been compromised, it
is still a good idea to revoke existing tokens.
.. _ssl-encryption:
@@ -31,7 +31,7 @@ Using an SSL certificate
This will require you to obtain an official, trusted SSL certificate or create a
self-signed certificate. Once you have obtained and installed a key and
certificate you need to specify their locations in the ``jupyterhub_config.py``
certificate, you need to specify their locations in the ``jupyterhub_config.py``
configuration file as follows:
.. code-block:: python
@@ -72,7 +72,7 @@ would be the needed configuration:
If SSL termination happens outside of the Hub
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
In certain cases, for example if the hub is running behind a reverse proxy, and
In certain cases, for example, if the hub is running behind a reverse proxy, and
`SSL termination is being provided by NGINX <https://www.nginx.com/resources/admin-guide/nginx-ssl-termination/>`_,
it is reasonable to run the hub without SSL.
@@ -80,12 +80,55 @@ To achieve this, remove ``c.JupyterHub.ssl_key`` and ``c.JupyterHub.ssl_cert``
from your configuration (setting them to ``None`` or an empty string does not
have the same effect, and will result in an error).
.. _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 do not set the Proxy authentication token, the Hub will generate a random
key itself. This means that any time you restart the Hub, you **must also
restart the Proxy**. If the proxy is a subprocess of the Hub, this should happen
automatically (this is the default configuration).
.. _cookie-secret:
Cookie secret
-------------
The cookie secret is an encryption key, used to encrypt the browser cookies
The cookie secret is an encryption key, used to encrypt the browser cookies,
which are used for authentication. Three common methods are described for
generating and configuring the cookie secret.
@@ -93,8 +136,8 @@ Generating and storing as a cookie secret file
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
The cookie secret should be 32 random bytes, encoded as hex, and is typically
stored in a ``jupyterhub_cookie_secret`` file. An example command to generate the
``jupyterhub_cookie_secret`` file is:
stored in a ``jupyterhub_cookie_secret`` file. Below, is an example command to generate the
``jupyterhub_cookie_secret`` file:
.. code-block:: bash
@@ -112,7 +155,7 @@ The location of the ``jupyterhub_cookie_secret`` file can be specified in the
If the cookie secret file doesn't exist when the Hub starts, a new cookie
secret is generated and stored in the file. The file must not be readable by
``group`` or ``other`` or the server won't start. The recommended permissions
``group`` or ``other``, otherwise the server won't start. The recommended permissions
for the cookie secret file are ``600`` (owner-only rw).
Generating and storing as an environment variable
@@ -133,54 +176,79 @@ the Hub starts.
Generating and storing as a binary string
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
You can also set the cookie secret in the configuration file
itself, ``jupyterhub_config.py``, as a binary string:
You can also set the cookie secret, as a binary string,
in the configuration file (``jupyterhub_config.py``) itself:
.. code-block:: python
c.JupyterHub.cookie_secret = bytes.fromhex('64 CHAR HEX STRING')
.. _cookies:
.. important::
Cookies used by JupyterHub authentication
-----------------------------------------
If the cookie secret value changes for the Hub, all single-user notebook
servers must also be restarted.
The following cookies are used by the Hub for handling user authentication.
This section was created based on this post_ from Discourse.
.. _authentication-token:
.. _post: https://discourse.jupyter.org/t/how-to-force-re-login-for-users/1998/6
Proxy authentication token
--------------------------
jupyterhub-hub-login
~~~~~~~~~~~~~~~~~~~~
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 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.
Generating and storing token in the configuration file
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
Resetting the Hub cookie secret effectively revokes this cookie.
Or you can set the value in the configuration file, ``jupyterhub_config.py``:
This cookie is restricted to the path ``/hub/``.
.. code-block:: python
jupyterhub-user-<username>
~~~~~~~~~~~~~~~~~~~~~~~~~~
c.JupyterHub.proxy_auth_token = '0bc02bede919e99a26de1e2a7a5aadfaf6228de836ec39a05a6c6942831d8fe5'
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.
Generating and storing as an environment variable
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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.
You can pass this value of the proxy authentication token to the Hub and Proxy
using the ``CONFIGPROXY_AUTH_TOKEN`` environment variable:
Each OAuth access token is associated with a session id (see ``jupyterhub-session-id`` section
below).
.. code-block:: bash
To avoid hitting the Hub on every request, the authentication response is cached.
The cache key is comprised of both the token and session id, to avoid a stale cache.
export CONFIGPROXY_AUTH_TOKEN=$(openssl rand -hex 32)
Resetting the Hub cookie secret effectively revokes this cookie.
This environment variable needs to be visible to the Hub and Proxy.
This cookie is restricted to the path ``/user/<username>``,
to ensure that only the user’s server receives it.
Default if token is not set
~~~~~~~~~~~~~~~~~~~~~~~~~~~
jupyterhub-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).
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, 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 you 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.

78
docs/source/getting-started/services-basics.md
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@@ -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
@@ -15,16 +15,16 @@ 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
### Create an API token
### Step 1: Generate an API token
To run such an external service, an API token must be created and
provided to the service.
@@ -43,12 +43,12 @@ generating an API token is available from the JupyterHub user interface:
![API TOKEN success page](../images/token-request-success.png)
### Pass environment variable with token to the Hub
### Step 2: Pass environment variable with token to the Hub
In the case of `cull_idle_servers`, it is passed as the environment
variable called `JUPYTERHUB_API_TOKEN`.
### Use API tokens for services and tasks that require external access
### Step 3: Use API tokens for services and tasks that require external access
While API tokens are often associated with a specific user, API tokens
can be used by services that require external access for activities
@@ -62,7 +62,7 @@ c.JupyterHub.services = [
]
```
### Restart JupyterHub
### Step 4: Restart JupyterHub
Upon restarting JupyterHub, you should see a message like below in the
logs:
@@ -78,44 +78,72 @@ 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
## How to configure the idle culler 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:
### Step 1: Install the idle culler:
```
pip install jupyterhub-idle-culler
```
### Step 2: In `jupyterhub_config.py`, add the following dictionary for the `idle-culler` Service to the `c.JupyterHub.services` list:
```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.
## Run `cull-idle` manually as a standalone script
```{versionchanged} 2.0
Prior to 2.0, the idle-culler required 'admin' permissions.
It now needs the scopes:
Now you can run your script, i.e. `cull_idle_servers`, by providing it
- `list:users` to access the user list endpoint
- `read:users:activity` to read activity info
- `admin:servers` to start/stop servers
```
## How to run `cull-idle` manually as a standalone script
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

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

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@@ -0,0 +1,15 @@
=====
About
=====
JupyterHub is an open source project and community. It is a part of the
`Jupyter Project <https://jupyter.org>`_. JupyterHub is an open and inclusive
community, and invites contributions from anyone. This section covers information
about our community, as well as ways that you can connect and get involved.
.. toctree::
:maxdepth: 1
contributor-list
changelog
gallery-jhub-deployments

14
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@@ -0,0 +1,14 @@
=====================
Administrator's Guide
=====================
This guide covers best-practices, tips, common questions and operations, as
well as other information relevant to running your own JupyterHub over time.
.. toctree::
:maxdepth: 2
troubleshooting
admin/upgrading
admin/log-messages
changelog

142
docs/source/index.rst
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@@ -3,30 +3,28 @@ 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
Because JupyterHub manages a separate Jupyter environment for each user,
it can be used in a class of students, a corporate data science group, or a scientific
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
take a look at them before continuing with the configuration of the broad
original system of `JupyterHub`_. Today, you can find two main cases:
JupyterHub offers distributions for different use cases. Be sure to
take a look at them before continuing with the configuration of the broad
original system of `JupyterHub`_. As of now, you can find two main cases:
1. If you need a simple case for a small amount of users (0-100) and single server
take a look at
`The Littlest JupyterHub <https://github.com/jupyterhub/the-littlest-jupyterhub>`__ distribution.
2. If you need to allow for even more users, a dynamic amount of servers can be used on a cloud,
take a look at the `Zero to JupyterHub with Kubernetes <https://github.com/jupyterhub/zero-to-jupyterhub-k8s>`__ .
1. `The Littlest JupyterHub <https://github.com/jupyterhub/the-littlest-jupyterhub>`__ distribution is suitable if you need a small number of users (1-100) and a single server with a simple environment.
2. `Zero to JupyterHub with Kubernetes <https://github.com/jupyterhub/zero-to-jupyterhub-k8s>`__ allows you to deploy dynamic servers on the cloud if you need even more users.
Four subsystems make up JupyterHub:
* a **Hub** (tornado process) that is the heart of JupyterHub
* a **configurable http proxy** (node-http-proxy) that receives the requests from the client's browser
* multiple **single-user Jupyter notebook servers** (Python/IPython/tornado) that are monitored by Spawners
* an **authentication class** that manages how users can access the system
* a **Configurable HTTP Proxy** (node-http-proxy) that receives the requests from the client's browser
* multiple **Single-User Jupyter Notebook Servers** (Python/IPython/tornado) that are monitored by Spawners
* an **Authentication Class** that manages how users can access the system
Besides these central pieces, you can add optional configurations through a `config.py` file and manage users kernels on an admin panel. A simplification of the whole system can be seen in the figure below:
Besides these central pieces, you can add optional configurations through a `config.py` file and manage users' environments through an admin panel. A simplification of the whole system can be seen in the figure below:
.. image:: images/jhub-fluxogram.jpeg
:alt: JupyterHub subsystems
@@ -43,7 +41,7 @@ JupyterHub performs the following functions:
notebook servers
For convenient administration of the Hub, its users, and services,
JupyterHub also provides a `REST API`_.
JupyterHub also provides a :doc:`REST API <reference/rest-api>`.
The JupyterHub team and Project Jupyter value our community, and JupyterHub
follows the Jupyter `Community Guides <https://jupyter.readthedocs.io/en/latest/community/content-community.html>`_.
@@ -56,120 +54,89 @@ Contents
Distributions
-------------
A JupyterHub **distribution** is tailored towards a particular set of
Each JupyterHub **distribution** is tailored toward a particular set of
use cases. These are generally easier to set up than setting up
JupyterHub from scratch, assuming they fit your use case.
The two popular ones are:
* `Zero to JupyterHub on Kubernetes <http://z2jh.jupyter.org>`_, for
running JupyterHub on top of `Kubernetes <https://k8s.io>`_. This
can scale to large number of machines & users.
* `The Littlest JupyterHub <http://tljh.jupyter.org>`_, for an easy
to set up & run JupyterHub supporting 1-100 users on a single machine.
* `Zero to JupyterHub on Kubernetes <http://z2jh.jupyter.org>`_, for
running JupyterHub on top of `Kubernetes <https://k8s.io>`_. This
can scale to a large number of machines & users.
Installation Guide
------------------
.. toctree::
:maxdepth: 1
:maxdepth: 2
installation-guide
quickstart
quickstart-docker
installation-basics
Getting Started
---------------
.. toctree::
:maxdepth: 1
:maxdepth: 2
getting-started/index
getting-started/config-basics
getting-started/networking-basics
getting-started/security-basics
getting-started/authenticators-users-basics
getting-started/spawners-basics
getting-started/services-basics
Technical Reference
-------------------
.. toctree::
:maxdepth: 1
:maxdepth: 2
reference/index
reference/technical-overview
reference/websecurity
reference/authenticators
reference/spawners
reference/services
reference/rest
reference/templates
reference/config-user-env
reference/config-examples
reference/config-ghoauth
reference/config-proxy
reference/config-sudo
Contributing
------------
We want you to contribute to JupyterHub in ways that are most exciting
& useful to you. We value documentation, testing, bug reporting & code equally,
and are glad to have your contributions in whatever form you wish :)
Our `Code of Conduct <https://github.com/jupyter/governance/blob/master/conduct/code_of_conduct.md>`_
(`reporting guidelines <https://github.com/jupyter/governance/blob/master/conduct/reporting_online.md>`_)
helps keep our community welcoming to as many people as possible.
.. toctree::
:maxdepth: 1
contributing/community
contributing/setup
contributing/docs
contributing/tests
contributing/roadmap
contributing/security
Upgrading JupyterHub
Administrators guide
--------------------
We try to make upgrades between minor versions as painless as possible.
.. toctree::
:maxdepth: 1
:maxdepth: 2
admin/upgrading
changelog
index-admin
API Reference
-------------
.. toctree::
:maxdepth: 1
:maxdepth: 2
api/index
Troubleshooting
---------------
RBAC Reference
--------------
.. toctree::
:maxdepth: 1
:maxdepth: 2
troubleshooting
rbac/index
Contributing
------------
We welcome you to contribute to JupyterHub in ways that are most exciting
& useful to you. We value documentation, testing, bug reporting & code equally
and are glad to have your contributions in whatever form you wish :)
Our `Code of Conduct <https://github.com/jupyter/governance/blob/HEAD/conduct/code_of_conduct.md>`_
(`reporting guidelines <https://github.com/jupyter/governance/blob/HEAD/conduct/reporting_online.md>`_)
helps keep our community welcoming to as many people as possible.
.. toctree::
:maxdepth: 2
contributing/index
About JupyterHub
----------------
.. toctree::
:maxdepth: 1
:maxdepth: 2
contributor-list
changelog
gallery-jhub-deployments
index-about
Indices and tables
==================
@@ -184,24 +151,5 @@ Questions? Suggestions?
- `Jupyter mailing list <https://groups.google.com/forum/#!forum/jupyter>`_
- `Jupyter website <https://jupyter.org>`_
.. _contents:
Full Table of Contents
======================
.. toctree::
:maxdepth: 2
installation-guide
getting-started/index
reference/index
api/index
troubleshooting
contributor-list
gallery-jhub-deployments
changelog
.. _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

6
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@@ -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

8
docs/source/installation-guide.rst
View File

@@ -1,5 +1,9 @@
Installation Guide
==================
Installation
============
These sections cover how to get up-and-running with JupyterHub. They cover
some basics of the tools needed to deploy JupyterHub as well as how to get it
running on your own infrastructure.
.. toctree::
:maxdepth: 3

72
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View File

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

40
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@@ -5,35 +5,45 @@
Before installing JupyterHub, you will need:
- a Linux/Unix based system
- [Python](https://www.python.org/downloads/) 3.5 or greater. An understanding
of using [`pip`](https://pip.pypa.io/en/stable/) or
- [Python](https://www.python.org/downloads/) 3.6 or greater. An understanding
of using [`pip`](https://pip.pypa.io) or
[`conda`](https://conda.io/docs/get-started.html) for
installing Python packages is helpful.
- [nodejs/npm](https://www.npmjs.com/). [Install nodejs/npm](https://docs.npmjs.com/getting-started/installing-node),
using your operating system's package manager.
* If you are using **`conda`**, the nodejs and npm dependencies will be installed for
- If you are using **`conda`**, the nodejs and npm dependencies will be installed for
you by conda.
* If you are using **`pip`**, install a recent version of
- If you are using **`pip`**, install a recent version of
[nodejs/npm](https://docs.npmjs.com/getting-started/installing-node).
For example, install it on Linux (Debian/Ubuntu) using:
```
sudo apt-get install npm nodejs-legacy
sudo apt-get install nodejs npm
```
The `nodejs-legacy` package installs the `node` executable and is currently
required for npm to work on Debian/Ubuntu.
[nodesource][] is a great resource to get more recent versions of the nodejs runtime,
if your system package manager only has an old version of Node.js (e.g. 10 or older).
- 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
[nodesource]: https://github.com/nodesource/distributions#table-of-contents
Before running the single-user notebook servers (which may be on the same
system as the Hub or not), you will need:
- [Jupyter Notebook](https://jupyter.readthedocs.io/en/latest/install.html)
version 4 or greater
- [JupyterLab][] version 3 or greater,
or [Jupyter Notebook][]
4 or greater.
[jupyterlab]: https://jupyterlab.readthedocs.io
[jupyter notebook]: https://jupyter.readthedocs.io/en/latest/install.html
## Installation
@@ -44,14 +54,14 @@ JupyterHub can be installed with `pip` (and the proxy with `npm`) or `conda`:
```bash
python3 -m pip install jupyterhub
npm install -g configurable-http-proxy
python3 -m pip install notebook # needed if running the notebook servers locally
python3 -m pip install jupyterlab notebook # needed if running the notebook servers in the same environment
```
**conda** (one command installs jupyterhub and proxy):
```bash
conda install -c conda-forge jupyterhub # installs jupyterhub and proxy
conda install notebook # needed if running the notebook servers locally
conda install jupyterlab notebook # needed if running the notebook servers in the same environment
```
Test your installation. If installed, these commands should return the packages'
@@ -70,16 +80,16 @@ To start the Hub server, run the command:
jupyterhub
```
Visit `https://localhost:8000` in your browser, and sign in with your unix
Visit `http://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.

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

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

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

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

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

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

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

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

100
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@@ -1,6 +1,6 @@
# Authenticators
The [Authenticator][] is the mechanism for authorizing users to use the
The {class}`.Authenticator` is the mechanism for authorizing users to use the
Hub and single user notebook servers.
## The default PAM Authenticator
@@ -36,7 +36,7 @@ A [generic implementation](https://github.com/jupyterhub/oauthenticator/blob/mas
## The Dummy Authenticator
When testing, it may be helpful to use the
:class:`~jupyterhub.auth.DummyAuthenticator`. This allows for any username and
{class}`jupyterhub.auth.DummyAuthenticator`. This allows for any username and
password unless if a global password has been set. Once set, any username will
still be accepted but the correct password will need to be provided.
@@ -88,7 +88,6 @@ class DictionaryAuthenticator(Authenticator):
return data['username']
```
#### Normalize usernames
Since the Authenticator and Spawner both use the same username,
@@ -111,11 +110,8 @@ 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
`pam_normalize_username` is on, usernames are _not_ normalized to
lowercase.
NOTE: Earlier it says that usernames are normalized using PAM.
I guess that doesn't normalize them?
#### Validate usernames
@@ -133,7 +129,6 @@ 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
@@ -141,12 +136,11 @@ via other mechanisms. One such example is using [GitHub OAuth][].
Because the username is passed from the Authenticator to the Spawner,
a custom Authenticator and Spawner are often used together.
For example, the Authenticator methods, [pre_spawn_start(user, spawner)][]
and [post_spawn_stop(user, spawner)][], are hooks that can be used to do
For example, the Authenticator methods, {meth}`.Authenticator.pre_spawn_start`
and {meth}`.Authenticator.post_spawn_stop`, 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
@@ -187,7 +181,6 @@ 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,
@@ -221,25 +214,22 @@ To store auth_state, two conditions must be met:
export JUPYTERHUB_CRYPT_KEY=$(openssl rand -hex 32)
```
JupyterHub uses [Fernet](https://cryptography.io/en/latest/fernet/) to encrypt auth_state.
To facilitate key-rotation, `JUPYTERHUB_CRYPT_KEY` may be a semicolon-separated list of encryption keys.
If there are multiple keys present, the **first** key is always used to persist any new auth_state.
#### Using auth_state
Typically, if `auth_state` is persisted it is desirable to affect the Spawner environment in some way.
This may mean defining environment variables, placing certificate in the user's home directory, etc.
The `Authenticator.pre_spawn_start` method can be used to pass information from authenticator state
The {meth}`Authenticator.pre_spawn_start` method can be used to pass information from authenticator state
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': {
@@ -247,21 +237,69 @@ 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
spawner.environment['UPSTREAM_TOKEN'] = auth_state['upstream_token']
```
Note that environment variable names and values are always strings, so passing multiple values means setting multiple environment variables or serializing more complex data into a single variable, e.g. as a JSON string.
auth state can also be used to configure the spawner via _config_ without subclassing
by setting `c.Spawner.auth_state_hook`. This function will be called with `(spawner, auth_state)`,
only when auth_state is defined.
For example:
(for KubeSpawner)
```python
def auth_state_hook(spawner, auth_state):
spawner.volumes = auth_state['user_volumes']
spawner.mounts = auth_state['user_mounts']
c.Spawner.auth_state_hook = auth_state_hook
```
(authenticator-groups)=
## Authenticator-managed group membership
:::{versionadded} 2.2
:::
Some identity providers may have their own concept of group membership that you would like to preserve in JupyterHub.
This is now possible with `Authenticator.managed_groups`.
You can set the config:
```python
c.Authenticator.manage_groups = True
```
to enable this behavior.
The default is False for Authenticators that ship with JupyterHub,
but may be True for custom Authenticators.
Check your Authenticator's documentation for manage_groups support.
If True, {meth}`.Authenticator.authenticate` and {meth}`.Authenticator.refresh_user` may include a field `groups`
which is a list of group names the user should be a member of:
- Membership will be added for any group in the list
- Membership in any groups not in the list will be revoked
- Any groups not already present in the database will be created
- If `None` is returned, no changes are made to the user's group membership
If authenticator-managed groups are enabled,
all group-management via the API is disabled.
## pre_spawn_start and post_spawn_stop hooks
Authenticators uses two hooks, [pre_spawn_start(user, spawner)][] and
[post_spawn_stop(user, spawner)][] to pass additional state information
between the authenticator and a spawner. These hooks are typically used for auth-related
Authenticators use two hooks, {meth}`.Authenticator.pre_spawn_start` and
{meth}`.Authenticator.post_spawn_stop(user, spawner)` to add pass additional state information
between the authenticator and a spawner. These hooks are typically used auth-related
startup, i.e. opening a PAM session, and auth-related cleanup, i.e. closing a
PAM session.
@@ -269,11 +307,7 @@ 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
[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
[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

25
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@@ -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](https://oauthenticator.readthedocs.io/en/latest)) for login
- Using the default spawner (to configure other spawners, uncomment and edit
`spawner_class` as well as follow the instructions for your desired spawner)
* Users exist locally on the server
* Users' notebooks to be served from `~/assignments` to allow users to browse
- Users exist locally on the server
- Users' notebooks to be served from `~/assignments` to allow users to browse
for notebooks within other users' home directories
* You want the landing page for each user to be a `Welcome.ipynb` notebook in
their assignments directory.
* All runtime files are put into `/srv/jupyterhub` and log files in `/var/log`.
- You want the landing page for each user to be a `Welcome.ipynb` notebook in
their assignments directory
- All runtime files are put into `/srv/jupyterhub` and log files in `/var/log`
The `jupyterhub_config.py` file would have these settings:
@@ -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
@@ -70,7 +69,7 @@ c.Spawner.args = ['--NotebookApp.default_url=/notebooks/Welcome.ipynb']
```
Using the GitHub Authenticator requires a few additional
environment variable to be set prior to launching JupyterHub:
environment variables to be set prior to launching JupyterHub:
```bash
export GITHUB_CLIENT_ID=github_id
@@ -80,3 +79,5 @@ export CONFIGPROXY_AUTH_TOKEN=super-secret
# append log output to log file /var/log/jupyterhub.log
jupyterhub -f /etc/jupyterhub/jupyterhub_config.py &>> /var/log/jupyterhub.log
```
Visit the [Github OAuthenticator reference](https://oauthenticator.readthedocs.io/en/latest/api/gen/oauthenticator.github.html) to see the full list of options for configuring Github OAuth with JupyterHub.

93
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@@ -6,15 +6,15 @@ SSL port `443`. This could be useful if the JupyterHub server machine is also
hosting other domains or content on `443`. The goal in this example is to
satisfy the following:
* JupyterHub is running on a server, accessed *only* via `HUB.DOMAIN.TLD:443`
* On the same machine, `NO_HUB.DOMAIN.TLD` strictly serves different content,
- JupyterHub is running on a server, accessed _only_ via `HUB.DOMAIN.TLD:443`
- On the same machine, `NO_HUB.DOMAIN.TLD` strictly serves different content,
also on port `443`
* `nginx` or `apache` is used as the public access point (which means that
only nginx/apache will bind to `443`)
* After testing, the server in question should be able to score at least an A on the
- `nginx` or `apache` is used as the public access point (which means that
only nginx/apache will bind to `443`)
- After testing, the server in question should be able to score at least an A on the
Qualys SSL Labs [SSL Server Test](https://www.ssllabs.com/ssltest/)
Let's start out with needed JupyterHub configuration in `jupyterhub_config.py`:
Let's start out with the needed JupyterHub configuration in `jupyterhub_config.py`:
```python
# Force the proxy to only listen to connections to 127.0.0.1 (on port 8000)
@@ -30,15 +30,15 @@ This can take a few minutes:
openssl dhparam -out /etc/ssl/certs/dhparam.pem 4096
```
## nginx
## Nginx
This **`nginx` config file** is fairly standard fare except for the two
`location` blocks within the main section for HUB.DOMAIN.tld.
To create a new site for jupyterhub in your nginx config, make a new file
To create a new site for jupyterhub in your Nginx config, make a new file
in `sites.enabled`, e.g. `/etc/nginx/sites.enabled/jupyterhub.conf`:
```bash
# top-level http config for websocket headers
# Top-level HTTP config for WebSocket headers
# If Upgrade is defined, Connection = upgrade
# If Upgrade is empty, Connection = close
map $http_upgrade $connection_upgrade {
@@ -51,7 +51,7 @@ server {
listen 80;
server_name HUB.DOMAIN.TLD;
# Tell all requests to port 80 to be 302 redirected to HTTPS
# Redirect the request to HTTPS
return 302 https://$host$request_uri;
}
@@ -75,7 +75,7 @@ server {
ssl_stapling_verify on;
add_header Strict-Transport-Security max-age=15768000;
# Managing literal requests to the JupyterHub front end
# Managing literal requests to the JupyterHub frontend
location / {
proxy_pass http://127.0.0.1:8000;
proxy_set_header X-Real-IP $remote_addr;
@@ -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 $scheme;
proxy_buffering off;
}
# Managing requests to verify letsencrypt host
@@ -97,10 +101,10 @@ server {
If `nginx` is not running on port 443, substitute `$http_host` for `$host` on
the lines setting the `Host` header.
`nginx` will now be the front facing element of JupyterHub on `443` which means
`nginx` will now be the front-facing element of JupyterHub on `443` which means
it is also free to bind other servers, like `NO_HUB.DOMAIN.TLD` to the same port
on the same machine and network interface. In fact, one can simply use the same
server blocks as above for `NO_HUB` and simply add line for the root directory
server blocks as above for `NO_HUB` and simply add a line for the root directory
of the site as well as the applicable location call:
```bash
@@ -108,7 +112,7 @@ server {
listen 80;
server_name NO_HUB.DOMAIN.TLD;
# Tell all requests to port 80 to be 302 redirected to HTTPS
# Redirect the request to HTTPS
return 302 https://$host$request_uri;
}
@@ -139,25 +143,40 @@ 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
As with nginx above, you can use [Apache](https://httpd.apache.org) as the reverse proxy.
First, we will need to enable the apache modules that we are going to need:
As with Nginx above, you can use [Apache](https://httpd.apache.org) as the reverse proxy.
First, we will need to enable the Apache modules that we are going to need:
```bash
a2enmod ssl rewrite proxy proxy_http proxy_wstunnel
a2enmod ssl rewrite proxy headers proxy_http proxy_wstunnel
```
Our Apache configuration is equivalent to the nginx configuration above:
Our Apache configuration is equivalent to the Nginx configuration above:
- Redirect HTTP to HTTPS
- Good SSL Configuration
- Support for websockets on any proxied URL
- Support for WebSocket on any proxied URL
- JupyterHub is running locally at http://127.0.0.1:8000
```bash
# redirect HTTP to HTTPS
# Redirect HTTP to HTTPS
Listen 80
<VirtualHost HUB.DOMAIN.TLD:80>
ServerName HUB.DOMAIN.TLD
@@ -169,15 +188,26 @@ Listen 443
ServerName HUB.DOMAIN.TLD
# configure SSL
# Enable HTTP/2, if available
Protocols h2 http/1.1
# HTTP Strict Transport Security (mod_headers is required) (63072000 seconds)
Header always set Strict-Transport-Security "max-age=63072000"
# Configure SSL
SSLEngine on
SSLCertificateFile /etc/letsencrypt/live/HUB.DOMAIN.TLD/fullchain.pem
SSLCertificateKeyFile /etc/letsencrypt/live/HUB.DOMAIN.TLD/privkey.pem
SSLProtocol All -SSLv2 -SSLv3
SSLOpenSSLConfCmd DHParameters /etc/ssl/certs/dhparam.pem
SSLCipherSuite EECDH+AESGCM:EDH+AESGCM:AES256+EECDH:AES256+EDH
# Use RewriteEngine to handle websocket connection upgrades
# Intermediate configuration from SSL-config.mozilla.org (2022-03-03)
# Please note, that this configuration might be outdated - please update it accordingly using https://ssl-config.mozilla.org/
SSLProtocol all -SSLv3 -TLSv1 -TLSv1.1
SSLCipherSuite ECDHE-ECDSA-AES128-GCM-SHA256:ECDHE-RSA-AES128-GCM-SHA256:ECDHE-ECDSA-AES256-GCM-SHA384:ECDHE-RSA-AES256-GCM-SHA384:ECDHE-ECDSA-CHACHA20-POLY1305:ECDHE-RSA-CHACHA20-POLY1305:DHE-RSA-AES128-GCM-SHA256:DHE-RSA-AES256-GCM-SHA384
SSLHonorCipherOrder off
SSLSessionTickets off
# Use RewriteEngine to handle WebSocket connection upgrades
RewriteEngine On
RewriteCond %{HTTP:Connection} Upgrade [NC]
RewriteCond %{HTTP:Upgrade} websocket [NC]
@@ -189,26 +219,29 @@ Listen 443
# proxy to JupyterHub
ProxyPass http://127.0.0.1:8000/
ProxyPassReverse http://127.0.0.1:8000/
RequestHeader set "X-Forwarded-Proto" expr=%{REQUEST_SCHEME}
</Location>
</VirtualHost>
```
In case of the need to run the jupyterhub under /jhub/ or other location please use the below configurations:
In case of the need to run JupyterHub under /jhub/ or another location please use the below configurations:
- JupyterHub running locally at http://127.0.0.1:8000/jhub/ or other location
httpd.conf amendments:
```bash
RewriteRule /jhub/(.*) ws://127.0.0.1:8000/jhub/$1 [P,L]
RewriteRule /jhub/(.*) http://127.0.0.1:8000/jhub/$1 [P,L]
ProxyPass /jhub/ http://127.0.0.1:8000/jhub/
ProxyPassReverse /jhub/ http://127.0.0.1:8000/jhub/
```
```
jupyterhub_config.py amendments:
```python
# The public facing URL of the whole JupyterHub application.
# This is the address on which the proxy will bind. Sets protocol, ip, base_url
# 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/'
```

30
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@@ -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::

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@@ -6,10 +6,10 @@ Only do this if you are very sure you must.
## Overview
There are many Authenticators and Spawners available for JupyterHub. Some, such
as DockerSpawner or OAuthenticator, do not need any elevated permissions. This
There are many [Authenticators](../getting-started/authenticators-users-basics) and [Spawners](../getting-started/spawners-basics) available for JupyterHub. Some, such
as [DockerSpawner](https://github.com/jupyterhub/dockerspawner) or [OAuthenticator](https://github.com/jupyterhub/oauthenticator), do not need any elevated permissions. This
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
@@ -92,16 +91,16 @@ $ 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
...
```
@@ -121,6 +120,11 @@ the shadow password database.
### Shadow group (Linux)
**Note:** On [Fedora based distributions](https://fedoraproject.org/wiki/List_of_Fedora_remixes) there is no clear way to configure
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
@@ -147,12 +151,13 @@ We want our new user to be able to read the shadow passwords, so add it to the s
$ sudo usermod -a -G shadow rhea
```
If you want jupyterhub to serve pages on a restricted port (such as port 80 for http),
If you want jupyterhub to serve pages on a restricted port (such as port 80 for HTTP),
then you will need to give `node` permission to do so:
```bash
sudo setcap 'cap_net_bind_service=+ep' /usr/bin/node
```
However, you may want to further understand the consequences of this.
([Further reading](http://man7.org/linux/man-pages/man7/capabilities.7.html))
@@ -162,7 +167,6 @@ 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 on FreeBSD and may not work as expected on
@@ -184,7 +188,7 @@ $ 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
@@ -218,15 +222,15 @@ 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.
## Troubleshooting: SELinux
If you still get a generic `Permission denied` `PermissionError`, it's possible SELinux is blocking you.
Here's how you can make a module to allow this.
First, put this in a file named `sudo_exec_selinux.te`:
Here's how you can make a module to resolve this.
First, put this in a file named `sudo_exec_selinux.te`:
```bash
module sudo_exec_selinux 1.1;

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