base on Ready-to-run Docker images containing Jupyter applications # Jupyter Docker Stacks [](https://github.com/jupyter/docker-stacks/actions/workflows/docker.yml?query=branch%3Amain "Docker images build status") [](https://jupyter-docker-stacks.readthedocs.io/en/latest/ "Documentation build status") [](https://results.pre-commit.ci/latest/github/jupyter/docker-stacks/main "pre-commit.ci build status") [](https://discourse.jupyter.org/ "Jupyter Discourse Forum") [](https://mybinder.org/v2/gh/jupyter/docker-stacks/main?urlpath=lab/tree/README.ipynb "Launch a quay.io/jupyter/base-notebook container on mybinder.org") Jupyter Docker Stacks are a set of ready-to-run [Docker images](https://quay.io/organization/jupyter) containing Jupyter applications and interactive computing tools. You can use a stack image to do any of the following (and more): - Start a personal Jupyter Server with the JupyterLab frontend (default) - Run JupyterLab for a team using JupyterHub - Start a personal Jupyter Server with the Jupyter Notebook frontend in a local Docker container - Write your own project Dockerfile ## Quick Start You can [try a relatively recent build of the quay.io/jupyter/base-notebook image on mybinder.org](https://mybinder.org/v2/gh/jupyter/docker-stacks/main?urlpath=lab/tree/README.ipynb). Otherwise, the examples below may help you get started if you [have Docker installed](https://docs.docker.com/get-started/get-docker/), know [which Docker image](https://jupyter-docker-stacks.readthedocs.io/en/latest/using/selecting.html) you want to use, and want to launch a single Jupyter Application in a container. The [User Guide on ReadTheDocs](https://jupyter-docker-stacks.readthedocs.io/en/latest/) describes additional uses and features in detail. ```{note} Since `2023-10-20` our images are only pushed to `Quay.io` registry. Older images are available on Docker Hub, but they will no longer be updated. ``` ### Example 1 This command pulls the `jupyter/scipy-notebook` image tagged `2024-11-19` from Quay.io if it is not already present on the local host. It then starts a container running a Jupyter Server with the JupyterLab frontend and exposes the container's internal port `8888` to port `10000` of the host machine: ```bash docker run -p 10000:8888 quay.io/jupyter/scipy-notebook:2024-11-19 ``` You can modify the port on which the container's port is exposed by [changing the value of the `-p` option](https://docs.docker.com/engine/containers/run/#exposed-ports) to `-p 8888:8888`. Visiting `http://<hostname>:10000/?token=<token>` in a browser loads JupyterLab, where: - The `hostname` is the name of the computer running Docker - The `token` is the secret token printed in the console. The container remains intact for restart after the Server exits. ### Example 2 This command pulls the `jupyter/datascience-notebook` image tagged `2024-11-19` from Quay.io if it is not already present on the local host. It then starts an _ephemeral_ container running a Jupyter Server with the JupyterLab frontend and exposes the server on host port 10000. ```bash docker run -it --rm -p 10000:8888 -v "${PWD}":/home/jovyan/work quay.io/jupyter/datascience-notebook:2024-11-19 ``` The use of the `-v` flag in the command mounts the current working directory on the host (`${PWD}` in the example command) as `/home/jovyan/work` in the container. The server logs appear in the terminal. Visiting `http://<hostname>:10000/?token=<token>` in a browser loads JupyterLab. Due to the usage of [the `--rm` flag](https://docs.docker.com/reference/cli/docker/container/run/#rm) Docker automatically cleans up the container and removes the file system when the container exits, but any changes made to the `~/work` directory and its files in the container will remain intact on the host. [The `-i` flag](https://docs.docker.com/reference/cli/docker/container/run/#interactive) keeps the container's `STDIN` open, and lets you send input to the container through standard input. [The `-t` flag](https://docs.docker.com/reference/cli/docker/container/run/#tty) attaches a pseudo-TTY to the container. ```{note} By default, [jupyter's root_dir](https://jupyter-server.readthedocs.io/en/latest/other/full-config.html) is `/home/jovyan`. So, new notebooks will be saved there, unless you change the directory in the file browser. To change the default directory, you must specify `ServerApp.root_dir` by adding this line to the previous command: `start-notebook.py --ServerApp.root_dir=/home/jovyan/work`. ``` ## Choosing Jupyter frontend JupyterLab is the default for all the Jupyter Docker Stacks images. It is still possible to switch back to Jupyter Notebook (or to launch a different startup command). You can achieve this by passing the environment variable `DOCKER_STACKS_JUPYTER_CMD=notebook` (or any other valid `jupyter` subcommand) at container startup; more information is available in the [documentation](https://jupyter-docker-stacks.readthedocs.io/en/latest/using/common.html#alternative-commands). ## Resources - [Documentation on ReadTheDocs](https://jupyter-docker-stacks.readthedocs.io/en/latest/) - [Issue Tracker on GitHub](https://github.com/jupyter/docker-stacks/issues) - [Jupyter Discourse Forum](https://discourse.jupyter.org/) - [Jupyter Website](https://jupyter.org) - [Images on Quay.io](https://quay.io/organization/jupyter) ## Acknowledgments - Starting from `2022-07-05`, `aarch64` self-hosted runners were sponsored by [`@mathbunnyru`](https://github.com/mathbunnyru/). Please, consider [sponsoring his work](https://github.com/sponsors/mathbunnyru) on GitHub - Starting from `2023-10-31`, `aarch64` self-hosted runners are sponsored by an amazing [`2i2c non-profit organization`](https://2i2c.org) ## CPU Architectures - We publish containers for both `x86_64` and `aarch64` platforms - Single-platform images have either `aarch64-` or `x86_64-` tag prefixes, for example, `quay.io/jupyter/base-notebook:aarch64-python-3.11.6` - Starting from `2022-09-21`, we create multi-platform images (except `tensorflow-notebook`) - Starting from `2023-06-01`, we create a multi-platform `tensorflow-notebook` image as well - Starting from `2024-02-24`, we create CUDA enabled variants of `pytorch-notebook` image for `x86_64` platform - Starting from `2024-03-26`, we create CUDA enabled variant of `tensorflow-notebook` image for `x86_64` platform ## Using old images This project only builds one set of images at a time. If you want to use the older `Ubuntu` and/or `Python` version, you can use the following images: | Build Date | Ubuntu | Python | Tag | | ------------ | ------ | ------ | -------------- | | 2022-10-09 | 20.04 | 3.7 | `1aac87eb7fa5` | | 2022-10-09 | 20.04 | 3.8 | `a374cab4fcb6` | | 2022-10-09 | 20.04 | 3.9 | `5ae537728c69` | | 2022-10-09 | 20.04 | 3.10 | `f3079808ca8c` | | 2022-10-09 | 22.04 | 3.7 | `b86753318aa1` | | 2022-10-09 | 22.04 | 3.8 | `7285848c0a11` | | 2022-10-09 | 22.04 | 3.9 | `ed2908bbb62e` | | 2023-05-30 | 22.04 | 3.10 | `4d70cf8da953` | | 2024-08-26 | 22.04 | 3.11 | `00987883e58d` | | 2024-10-22 | 24.04 | 3.11 | `b74418220768` | | weekly build | 24.04 | 3.12 | `latest` | ## Contributing Please see the [Contributor Guide on ReadTheDocs](https://jupyter-docker-stacks.readthedocs.io/en/latest/) for information about how to contribute recipes, features, tests, and community-maintained stacks. ## Alternatives - [rocker/binder](https://rocker-project.org/images/versioned/binder.html) - From the R focused [rocker-project](https://rocker-project.org), lets you run both RStudio and Jupyter either standalone or in a JupyterHub - [jupyter/repo2docker](https://github.com/jupyterhub/repo2docker) - Turn git repositories into Jupyter-enabled Docker Images - [openshift/source-to-image](https://github.com/openshift/source-to-image) - A tool for building artifacts from source code and injecting them into docker images - [jupyter-on-openshift/jupyter-notebooks](https://github.com/jupyter-on-openshift/jupyter-notebooks) - OpenShift compatible S2I builder for basic notebook images ", Assign "at most 3 tags" to the expected json: {"id":"6675","tags":[]} "only from the tags list I provide: [{"id":77,"name":"3d"},{"id":89,"name":"agent"},{"id":17,"name":"ai"},{"id":54,"name":"algorithm"},{"id":24,"name":"api"},{"id":44,"name":"authentication"},{"id":3,"name":"aws"},{"id":27,"name":"backend"},{"id":60,"name":"benchmark"},{"id":72,"name":"best-practices"},{"id":39,"name":"bitcoin"},{"id":37,"name":"blockchain"},{"id":1,"name":"blog"},{"id":45,"name":"bundler"},{"id":58,"name":"cache"},{"id":21,"name":"chat"},{"id":49,"name":"cicd"},{"id":4,"name":"cli"},{"id":64,"name":"cloud-native"},{"id":48,"name":"cms"},{"id":61,"name":"compiler"},{"id":68,"name":"containerization"},{"id":92,"name":"crm"},{"id":34,"name":"data"},{"id":47,"name":"database"},{"id":8,"name":"declarative-gui "},{"id":9,"name":"deploy-tool"},{"id":53,"name":"desktop-app"},{"id":6,"name":"dev-exp-lib"},{"id":59,"name":"dev-tool"},{"id":13,"name":"ecommerce"},{"id":26,"name":"editor"},{"id":66,"name":"emulator"},{"id":62,"name":"filesystem"},{"id":80,"name":"finance"},{"id":15,"name":"firmware"},{"id":73,"name":"for-fun"},{"id":2,"name":"framework"},{"id":11,"name":"frontend"},{"id":22,"name":"game"},{"id":81,"name":"game-engine "},{"id":23,"name":"graphql"},{"id":84,"name":"gui"},{"id":91,"name":"http"},{"id":5,"name":"http-client"},{"id":51,"name":"iac"},{"id":30,"name":"ide"},{"id":78,"name":"iot"},{"id":40,"name":"json"},{"id":83,"name":"julian"},{"id":38,"name":"k8s"},{"id":31,"name":"language"},{"id":10,"name":"learning-resource"},{"id":33,"name":"lib"},{"id":41,"name":"linter"},{"id":28,"name":"lms"},{"id":16,"name":"logging"},{"id":76,"name":"low-code"},{"id":90,"name":"message-queue"},{"id":42,"name":"mobile-app"},{"id":18,"name":"monitoring"},{"id":36,"name":"networking"},{"id":7,"name":"node-version"},{"id":55,"name":"nosql"},{"id":57,"name":"observability"},{"id":46,"name":"orm"},{"id":52,"name":"os"},{"id":14,"name":"parser"},{"id":74,"name":"react"},{"id":82,"name":"real-time"},{"id":56,"name":"robot"},{"id":65,"name":"runtime"},{"id":32,"name":"sdk"},{"id":71,"name":"search"},{"id":63,"name":"secrets"},{"id":25,"name":"security"},{"id":85,"name":"server"},{"id":86,"name":"serverless"},{"id":70,"name":"storage"},{"id":75,"name":"system-design"},{"id":79,"name":"terminal"},{"id":29,"name":"testing"},{"id":12,"name":"ui"},{"id":50,"name":"ux"},{"id":88,"name":"video"},{"id":20,"name":"web-app"},{"id":35,"name":"web-server"},{"id":43,"name":"webassembly"},{"id":69,"name":"workflow"},{"id":87,"name":"yaml"}]" returns me the "expected json"