Commit 2b33e23b authored by Peter Parente's avatar Peter Parente Committed by Peter Parente

Make RTD the doc source of truth

parent 6fd049e1
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...@@ -2,134 +2,7 @@ ...@@ -2,134 +2,7 @@
# Base Jupyter Notebook Stack # Base Jupyter Notebook Stack
Small base image for defining your own stack Please visit the documentation site for help using and contributing to this image and others.
## What it Gives You
* Minimally-functional Jupyter Notebook 5.2.x (e.g., no pandoc for document conversion)
* Miniconda Python 3.x
* No preinstalled scientific computing packages
* Unprivileged user `jovyan` (uid=1000, configurable, see options) in group `users` (gid=100) with ownership over `/home/jovyan` and `/opt/conda`
* [tini](https://github.com/krallin/tini) as the container entrypoint and [start-notebook.sh](./start-notebook.sh) as the default command
* A [start-singleuser.sh](./start-singleuser.sh) script useful for running a single-user instance of the Notebook server, as required by JupyterHub
* A [start.sh](./start.sh) script useful for running alternative commands in the container (e.g. `ipython`, `jupyter kernelgateway`, `jupyter lab`)
* Options for a self-signed HTTPS certificate and passwordless `sudo`
## Basic Use
The following command starts a container with the Notebook server listening for HTTP connections on port 8888 with a randomly generated authentication token configured.
```
docker run -it --rm -p 8888:8888 jupyter/base-notebook
```
Take note of the authentication token included in the notebook startup log messages. Include it in the URL you visit to access the Notebook server or enter it in the Notebook login form.
## Notebook Options
The Docker container executes a [`start-notebook.sh` script](./start-notebook.sh) script by default. The `start-notebook.sh` script handles the `NB_UID`, `NB_GID` and `GRANT_SUDO` features documented in the next section, and then executes the `jupyter notebook`.
You can launch [JupyterLab](https://github.com/jupyterlab/jupyterlab) by setting `JUPYTER_ENABLE_LAB`:
```
docker run -it --rm -e JUPYTER_ENABLE_LAB=1 --rm -p 8888:8888 jupyter/base-notebook
```
You can pass [Jupyter command line options](https://jupyter.readthedocs.io/en/latest/projects/jupyter-command.html) through the `start-notebook.sh` script when launching the container. For example, to secure the Notebook server with a custom password hashed using `IPython.lib.passwd()` instead of the default token, run the following:
```
docker run -d -p 8888:8888 jupyter/base-notebook start-notebook.sh --NotebookApp.password='sha1:74ba40f8a388:c913541b7ee99d15d5ed31d4226bf7838f83a50e'
```
For example, to set the base URL of the notebook server, run the following:
```
docker run -d -p 8888:8888 jupyter/base-notebook start-notebook.sh --NotebookApp.base_url=/some/path
```
For example, to disable all authentication mechanisms (not a recommended practice):
```
docker run -d -p 8888:8888 jupyter/base-notebook start-notebook.sh --NotebookApp.token=''
```
You can sidestep the `start-notebook.sh` script and run your own commands in the container. See the *Alternative Commands* section later in this document for more information.
## Docker Options
You may customize the execution of the Docker container and the command it is running with the following optional arguments.
* `-e GEN_CERT=yes` - Generates a self-signed SSL certificate and configures Jupyter Notebook to use it to accept encrypted HTTPS connections.
* `-e NB_UID=1000` - Specify the uid of the `jovyan` user. Useful to mount host volumes with specific file ownership. For this option to take effect, you must run the container with `--user root`. (The `start-notebook.sh` script will `su jovyan` after adjusting the user id.)
* `-e NB_GID=100` - Specify the gid of the `jovyan` user. Useful to mount host volumes with specific file ownership. For this option to take effect, you must run the container with `--user root`. (The `start-notebook.sh` script will `su jovyan` after adjusting the group id.)
* `-e GRANT_SUDO=yes` - Gives the `jovyan` user passwordless `sudo` capability. Useful for installing OS packages. For this option to take effect, you must run the container with `--user root`. (The `start-notebook.sh` script will `su jovyan` after adding `jovyan` to sudoers.) **You should only enable `sudo` if you trust the user or if the container is running on an isolated host.**
* `-v /some/host/folder/for/work:/home/jovyan/work` - Mounts a host machine directory as folder in the container. Useful when you want to preserve notebooks and other work even after the container is destroyed. **You must grant the within-container notebook user or group (`NB_UID` or `NB_GID`) write access to the host directory (e.g., `sudo chown 1000 /some/host/folder/for/work`).**
* `--group-add users` - use this argument if you are also specifying
a specific user id to launch the container (`-u 5000`), rather than launching the container as root and relying on NB_UID and NB_GID to set the user and group.
## SSL Certificates
You may mount SSL key and certificate files into a container and configure Jupyter Notebook to use them to accept HTTPS connections. For example, to mount a host folder containing a `notebook.key` and `notebook.crt`:
```
docker run -d -p 8888:8888 \
-v /some/host/folder:/etc/ssl/notebook \
jupyter/base-notebook start-notebook.sh \
--NotebookApp.keyfile=/etc/ssl/notebook/notebook.key
--NotebookApp.certfile=/etc/ssl/notebook/notebook.crt
```
Alternatively, you may mount a single PEM file containing both the key and certificate. For example:
```
docker run -d -p 8888:8888 \
-v /some/host/folder/notebook.pem:/etc/ssl/notebook.pem \
jupyter/base-notebook start-notebook.sh \
--NotebookApp.certfile=/etc/ssl/notebook.pem
```
In either case, Jupyter Notebook expects the key and certificate to be a base64 encoded text file. The certificate file or PEM may contain one or more certificates (e.g., server, intermediate, and root).
For additional information about using SSL, see the following:
* The [docker-stacks/examples](https://github.com/jupyter/docker-stacks/tree/master/examples) for information about how to use [Let's Encrypt](https://letsencrypt.org/) certificates when you run these stacks on a publicly visible domain.
* The [jupyter_notebook_config.py](jupyter_notebook_config.py) file for how this Docker image generates a self-signed certificate.
* The [Jupyter Notebook documentation](https://jupyter-notebook.readthedocs.io/en/latest/public_server.html#using-ssl-for-encrypted-communication) for best practices about running a public notebook server in general, most of which are encoded in this image.
## Conda Environments
The default Python 3.x [Conda environment](http://conda.pydata.org/docs/using/envs.html) resides in `/opt/conda`.
The commands `jupyter`, `ipython`, `python`, `pip`, and `conda` (among others) are available in both environments. For convenience, you can install packages into either environment regardless of what environment is currently active using commands like the following:
```
# install a package into the default (python 3.x) environment
pip install some-package
conda install some-package
```
## Alternative Commands
### start.sh
The `start.sh` script supports the same features as the default `start-notebook.sh` script (e.g., `GRANT_SUDO`), but allows you to specify an arbitrary command to execute. For example, to run the text-based `ipython` console in a container, do the following:
```
docker run -it --rm jupyter/base-notebook start.sh ipython
```
Or, to run JupyterLab instead of the classic notebook, run the following:
```
docker run -it --rm -p 8888:8888 jupyter/base-notebook start.sh jupyter lab
```
This script is particularly useful when you derive a new Dockerfile from this image and install additional Jupyter applications with subcommands like `jupyter console`, `jupyter kernelgateway`, etc.
### Others
You can bypass the provided scripts and specify your an arbitrary start command. If you do, keep in mind that certain features documented above will not function (e.g., `GRANT_SUDO`).
* [Jupyter Docker Stacks on ReadTheDocs](http://jupyter-docker-stacks.readthedocs.io/en/latest/index.html)
* [Selecting an Image :: Core Stacks :: jupyter/base-notebook](http://jupyter-docker-stacks.readthedocs.io/en/latest/using/selecting.html#jupyter-base-notebook)
...@@ -2,128 +2,7 @@ ...@@ -2,128 +2,7 @@
# Jupyter Notebook Data Science Stack # Jupyter Notebook Data Science Stack
## What it Gives You Please visit the documentation site for help using and contributing to this image and others.
* Jupyter Notebook 5.2.x * [Jupyter Docker Stacks on ReadTheDocs](http://jupyter-docker-stacks.readthedocs.io/en/latest/index.html)
* Conda Python 3.x environment * [Selecting an Image :: Core Stacks :: jupyter/datascience-notebook](http://jupyter-docker-stacks.readthedocs.io/en/latest/using/selecting.html#jupyter-datascience-notebook)
* pandas, matplotlib, scipy, seaborn, scikit-learn, scikit-image, sympy, cython, patsy, statsmodel, cloudpickle, dill, numba, bokeh pre-installed
* Conda R v3.3.x and channel
* plyr, devtools, shiny, rmarkdown, forecast, rsqlite, reshape2, nycflights13, caret, rcurl, and randomforest pre-installed
* The [tidyverse](https://github.com/tidyverse/tidyverse) R packages are also installed, including ggplot2, dplyr, tidyr, readr, purrr, tibble, stringr, lubridate, and broom
* Julia v0.6.x with Gadfly, RDatasets and HDF5 pre-installed
* Unprivileged user `jovyan` (uid=1000, configurable, see options) in group `users` (gid=100) with ownership over `/home/jovyan` and `/opt/conda`
* [tini](https://github.com/krallin/tini) as the container entrypoint and [start-notebook.sh](../base-notebook/start-notebook.sh) as the default command
* `/usr/local/bin/start-notebook.d` directory for custom init scripts that you can add in derived images
* A [start-singleuser.sh](../base-notebook/start-singleuser.sh) script useful for running a single-user instance of the Notebook server, as required by JupyterHub
* A [start.sh](../base-notebook/start.sh) script useful for running alternative commands in the container (e.g. `ipython`, `jupyter kernelgateway`, `jupyter lab`)
* Options for a self-signed HTTPS certificate and passwordless `sudo`
## Basic Use
The following command starts a container with the Notebook server listening for HTTP connections on port 8888 with a randomly generated authentication token configured.
```
docker run -it --rm -p 8888:8888 jupyter/datascience-notebook
```
Take note of the authentication token included in the notebook startup log messages. Include it in the URL you visit to access the Notebook server or enter it in the Notebook login form.
## Notebook Options
The Docker container executes a [`start-notebook.sh` script](../base-notebook/start-notebook.sh) script by default. The `start-notebook.sh` script handles the `NB_UID`, `NB_GID` and `GRANT_SUDO` features documented in the next section, and then executes the `jupyter notebook`.
You can pass [Jupyter command line options](https://jupyter.readthedocs.io/en/latest/projects/jupyter-command.html) through the `start-notebook.sh` script when launching the container. For example, to secure the Notebook server with a custom password hashed using `IPython.lib.passwd()` instead of the default token, run the following:
```
docker run -d -p 8888:8888 jupyter/datascience-notebook start-notebook.sh --NotebookApp.password='sha1:74ba40f8a388:c913541b7ee99d15d5ed31d4226bf7838f83a50e'
```
For example, to set the base URL of the notebook server, run the following:
```
docker run -d -p 8888:8888 jupyter/datascience-notebook start-notebook.sh --NotebookApp.base_url=/some/path
```
For example, to disable all authentication mechanisms (not a recommended practice):
```
docker run -d -p 8888:8888 jupyter/datascience-notebook start-notebook.sh --NotebookApp.token=''
```
You can sidestep the `start-notebook.sh` script and run your own commands in the container. See the *Alternative Commands* section later in this document for more information.
## Docker Options
You may customize the execution of the Docker container and the command it is running with the following optional arguments.
* `-e GEN_CERT=yes` - Generates a self-signed SSL certificate and configures Jupyter Notebook to use it to accept encrypted HTTPS connections.
* `-e NB_UID=1000` - Specify the uid of the `jovyan` user. Useful to mount host volumes with specific file ownership. For this option to take effect, you must run the container with `--user root`. (The `start-notebook.sh` script will `su jovyan` after adjusting the user id.)
* `-e NB_GID=100` - Specify the gid of the `jovyan` user. Useful to mount host volumes with specific file ownership. For this option to take effect, you must run the container with `--user root`. (The `start-notebook.sh` script will `su jovyan` after adjusting the group id.)
* `-e GRANT_SUDO=yes` - Gives the `jovyan` user passwordless `sudo` capability. Useful for installing OS packages. For this option to take effect, you must run the container with `--user root`. (The `start-notebook.sh` script will `su jovyan` after adding `jovyan` to sudoers.) **You should only enable `sudo` if you trust the user or if the container is running on an isolated host.**
* `-v /some/host/folder/for/work:/home/jovyan/work` - Mounts a host machine directory as folder in the container. Useful when you want to preserve notebooks and other work even after the container is destroyed. **You must grant the within-container notebook user or group (`NB_UID` or `NB_GID`) write access to the host directory (e.g., `sudo chown 1000 /some/host/folder/for/work`).**
## SSL Certificates
You may mount SSL key and certificate files into a container and configure Jupyter Notebook to use them to accept HTTPS connections. For example, to mount a host folder containing a `notebook.key` and `notebook.crt`:
```
docker run -d -p 8888:8888 \
-v /some/host/folder:/etc/ssl/notebook \
jupyter/datascience-notebook start-notebook.sh \
--NotebookApp.keyfile=/etc/ssl/notebook/notebook.key
--NotebookApp.certfile=/etc/ssl/notebook/notebook.crt
```
Alternatively, you may mount a single PEM file containing both the key and certificate. For example:
```
docker run -d -p 8888:8888 \
-v /some/host/folder/notebook.pem:/etc/ssl/notebook.pem \
jupyter/datascience-notebook start-notebook.sh \
--NotebookApp.certfile=/etc/ssl/notebook.pem
```
In either case, Jupyter Notebook expects the key and certificate to be a base64 encoded text file. The certificate file or PEM may contain one or more certificates (e.g., server, intermediate, and root).
For additional information about using SSL, see the following:
* The [docker-stacks/examples](https://github.com/jupyter/docker-stacks/tree/master/examples) for information about how to use [Let's Encrypt](https://letsencrypt.org/) certificates when you run these stacks on a publicly visible domain.
* The [jupyter_notebook_config.py](jupyter_notebook_config.py) file for how this Docker image generates a self-signed certificate.
* The [Jupyter Notebook documentation](https://jupyter-notebook.readthedocs.io/en/latest/public_server.html#using-ssl-for-encrypted-communication) for best practices about running a public notebook server in general, most of which are encoded in this image.
## Conda Environments
The default Python 3.x [Conda environment](http://conda.pydata.org/docs/using/envs.html) resides in `/opt/conda`.
The commands `jupyter`, `ipython`, `python`, `pip`, and `conda` (among others) are available in both environments. For convenience, you can install packages into either environment regardless of what environment is currently active using commands like the following:
```
# install a package into the default (python 3.x) environment
pip install some-package
conda install some-package
```
## Alternative Commands
### start.sh
The `start.sh` script supports the same features as the default `start-notebook.sh` script (e.g., `GRANT_SUDO`), but allows you to specify an arbitrary command to execute. For example, to run the text-based `ipython` console in a container, do the following:
```
docker run -it --rm jupyter/datascience-notebook start.sh ipython
```
Or, to run JupyterLab instead of the classic notebook, run the following:
```
docker run -it --rm -p 8888:8888 jupyter/datascience-notebook start.sh jupyter lab
```
This script is particularly useful when you derive a new Dockerfile from this image and install additional Jupyter applications with subcommands like `jupyter console`, `jupyter kernelgateway`, etc.
### Others
You can bypass the provided scripts and specify your an arbitrary start command. If you do, keep in mind that certain features documented above will not function (e.g., `GRANT_SUDO`).
...@@ -43,6 +43,12 @@ Table of Contents ...@@ -43,6 +43,12 @@ Table of Contents
contributing/tests contributing/tests
contributing/stacks contributing/stacks
.. toctree::
:maxdepth: 2
:caption: Maintainer Guide
maintaining/tasks
.. toctree:: .. toctree::
:maxdepth: 2 :maxdepth: 2
:caption: Getting Help :caption: Getting Help
......
# Maintainer Playbook
## Merging Pull Requests
To build new images on Docker Cloud and publish them to the Docker Hub registry, do the following:
1. Make sure Travis is green for a PR.
2. Merge the PR.
3. Monitor the Docker Cloud build status for each of the stacks, starting with [jupyter/base-notebook](https://cloud.docker.com/app/jupyter/repository/docker/jupyter/base-notebook/general) and ending with [jupyter/all-spark-notebook](https://cloud.docker.com/app/jupyter/repository/docker/jupyter/all-spark-notebook/general). See the [stack hierarchy diagram](../using/selecting.html#image-relationships) for the current, complete build order.
4. Manually click the retry button next to any build that fails to resume that build and any dependent builds.
5. Try to avoid merging another PR to master until all outstanding builds complete. There's no way at present to propagate the git SHA to build through the Docker Cloud build trigger API. Every build trigger works off of master HEAD.
## Updating the Ubuntu Base Image
When there's a security fix in the Ubuntu base image or after some time passes, it's a good idea to update the pinned SHA in the [jupyter/base-notebook Dockerfile](https://github.com/jupyter/docker-stacks/blob/master/base-notebook/Dockerfile). Submit it as a regular PR and go through the build process. Expect the build to take a while to complete: every image layer will rebuild.
## Adding a New Core Image to Docker Cloud
When there's a new stack definition, do the following before merging the PR with the new stack:
1. Ensure the PR includes an update to the stack overview diagram [in the documentation](https://github.com/jupyter/docker-stacks/blob/master/docs/using/selecting.md#image-relationships). The image links to the [blockdiag source](http://interactive.blockdiag.com/) used to create it.
2. Ensure the PR updates the Makefile which is used to build the stacks in order on Travis CI.
3. Create a new repository in the `jupyter` org on Docker Cloud named after the stack folder in the git repo.
4. Grant the `stacks` team permission to write to the repo.
5. Click *Builds* and then *Configure Automated Builds* for the repository.
6. Select `jupyter/docker-stacks` as the source repository.
7. Choose *Build on Docker Cloud's infrastructure using a Small node* unless you have reason to believe a bigger host is required.
8. Update the *Build Context* in the default build rule to be `/<name-of-the-stack>`.
9. Toggle *Autobuild* to disabled unless the stack is a new root stack (e.g., like `jupyter/base-notebook`).
10. If the new stack depends on the build of another stack in the hierarchy:
1. Hit *Save* and then click *Configure Automated Builds*.
2. At the very bottom, add a build trigger named *Stack hierarchy trigger*.
3. Copy the build trigger URL.
4. Visit the parent repository *Builds* page and click *Configure Automated Builds*.
5. Add the URL you copied to the *NEXT_BUILD_TRIGGERS* environment variable comma separated list of URLs, creating that environment variable if it does not already exist.
6. Hit *Save*.
11. If the new stack should trigger other dependent builds:
1. Add an environment variable named *NEXT_BUILD_TRIGGERS*.
2. Copy the build trigger URLs from the dependent builds into the *NEXT_BUILD_TRIGGERS* comma separated list of URLs.
3. Hit *Save*.
12. Adjust other *NEXT_BUILD_TRIGGERS* values as needed so that the build order matches that in the stack hierarchy diagram.
## Adding a New Maintainer Account
1. Visit https://cloud.docker.com/app/jupyter/team/stacks/users
2. Add the maintainer's Docker Cloud username.
3. Visit https://github.com/orgs/jupyter/teams/docker-image-maintainers/members
4. Add the maintainer's GitHub username.
## Pushing a Build Manually
If automated builds on Docker Cloud have got you down, do the following to push a build manually:
1. Clone this repository.
2. Check out the git SHA you want to build and publish.
3. `docker login` with your Docker Hub/Cloud credentials.
4. Run `make retry/release-all`.
...@@ -2,127 +2,7 @@ ...@@ -2,127 +2,7 @@
# Minimal Jupyter Notebook Stack # Minimal Jupyter Notebook Stack
Small image for working in the notebook and installing your own libraries Please visit the documentation site for help using and contributing to this image and others.
## What it Gives You * [Jupyter Docker Stacks on ReadTheDocs](http://jupyter-docker-stacks.readthedocs.io/en/latest/index.html)
* [Selecting an Image :: Core Stacks :: jupyter/minimal-notebook](http://jupyter-docker-stacks.readthedocs.io/en/latest/using/selecting.html#jupyter-minimal-notebook)
* Fully-functional Jupyter Notebook 5.2.x
* Miniconda Python 3.x
* No preinstalled scientific computing packages
* Unprivileged user `jovyan` (uid=1000, configurable, see options) in group `users` (gid=100) with ownership over `/home/jovyan` and `/opt/conda`
* [tini](https://github.com/krallin/tini) as the container entrypoint and [start-notebook.sh](../base-notebook/start-notebook.sh) as the default command
* A [start-singleuser.sh](../base-notebook/start-singleuser.sh) script useful for running a single-user instance of the Notebook server, as required by JupyterHub
* `/usr/local/bin/start-notebook.d` directory for custom init scripts that you can add in derived images
* A [start.sh](../base-notebook/start.sh) script useful for running alternative commands in the container (e.g. `ipython`, `jupyter kernelgateway`, `jupyter lab`)
* Options for a self-signed HTTPS certificate and passwordless `sudo`
## Basic Use
The following command starts a container with the Notebook server listening for HTTP connections on port 8888 with a randomly generated authentication token configured.
```
docker run -it --rm -p 8888:8888 jupyter/minimal-notebook
```
Take note of the authentication token included in the notebook startup log messages. Include it in the URL you visit to access the Notebook server or enter it in the Notebook login form.
## Notebook Options
The Docker container executes a [`start-notebook.sh` script](../base-notebook/start-notebook.sh) script by default. The `start-notebook.sh` script handles the `NB_UID`, `NB_GID` and `GRANT_SUDO` features documented in the next section, and then executes the `jupyter notebook`.
You can pass [Jupyter command line options](https://jupyter.readthedocs.io/en/latest/projects/jupyter-command.html) through the `start-notebook.sh` script when launching the container. For example, to secure the Notebook server with a custom password hashed using `IPython.lib.passwd()` instead of the default token, run the following:
```
docker run -d -p 8888:8888 jupyter/minimal-notebook start-notebook.sh --NotebookApp.password='sha1:74ba40f8a388:c913541b7ee99d15d5ed31d4226bf7838f83a50e'
```
For example, to set the base URL of the notebook server, run the following:
```
docker run -d -p 8888:8888 jupyter/minimal-notebook start-notebook.sh --NotebookApp.base_url=/some/path
```
For example, to disable all authentication mechanisms (not a recommended practice):
```
docker run -d -p 8888:8888 jupyter/minimal-notebook start-notebook.sh --NotebookApp.token=''
```
You can sidestep the `start-notebook.sh` script and run your own commands in the container. See the *Alternative Commands* section later in this document for more information.
## Docker Options
You may customize the execution of the Docker container and the Notebook server it contains with the following optional arguments.
* `-e GEN_CERT=yes` - Generates a self-signed SSL certificate and configures Jupyter Notebook to use it to accept encrypted HTTPS connections.
* `-e NB_UID=1000` - Specify the uid of the `jovyan` user. Useful to mount host volumes with specific file ownership. For this option to take effect, you must run the container with `--user root`. (The `start-notebook.sh` script will `su jovyan` after adjusting the user id.)
* `-e NB_GID=100` - Specify the gid of the `jovyan` user. Useful to mount host volumes with specific file ownership. For this option to take effect, you must run the container with `--user root`. (The `start-notebook.sh` script will `su jovyan` after adjusting the group id.)
* `-e GRANT_SUDO=yes` - Gives the `jovyan` user passwordless `sudo` capability. Useful for installing OS packages. For this option to take effect, you must run the container with `--user root`. (The `start-notebook.sh` script will `su jovyan` after adding `jovyan` to sudoers.) **You should only enable `sudo` if you trust the user or if the container is running on an isolated host.**
* `-v /some/host/folder/for/work:/home/jovyan/work` - Mounts a host machine directory as folder in the container. Useful when you want to preserve notebooks and other work even after the container is destroyed. **You must grant the within-container notebook user or group (`NB_UID` or `NB_GID`) write access to the host directory (e.g., `sudo chown 1000 /some/host/folder/for/work`).**
## SSL Certificates
You may mount SSL key and certificate files into a container and configure Jupyter Notebook to use them to accept HTTPS connections. For example, to mount a host folder containing a `notebook.key` and `notebook.crt`:
```
docker run -d -p 8888:8888 \
-v /some/host/folder:/etc/ssl/notebook \
jupyter/minimal-notebook start-notebook.sh \
--NotebookApp.keyfile=/etc/ssl/notebook/notebook.key
--NotebookApp.certfile=/etc/ssl/notebook/notebook.crt
```
Alternatively, you may mount a single PEM file containing both the key and certificate. For example:
```
docker run -d -p 8888:8888 \
-v /some/host/folder/notebook.pem:/etc/ssl/notebook.pem \
jupyter/minimal-notebook start-notebook.sh \
--NotebookApp.certfile=/etc/ssl/notebook.pem
```
In either case, Jupyter Notebook expects the key and certificate to be a base64 encoded text file. The certificate file or PEM may contain one or more certificates (e.g., server, intermediate, and root).
For additional information about using SSL, see the following:
* The [docker-stacks/examples](https://github.com/jupyter/docker-stacks/tree/master/examples) for information about how to use [Let's Encrypt](https://letsencrypt.org/) certificates when you run these stacks on a publicly visible domain.
* The [jupyter_notebook_config.py](jupyter_notebook_config.py) file for how this Docker image generates a self-signed certificate.
* The [Jupyter Notebook documentation](https://jupyter-notebook.readthedocs.io/en/latest/public_server.html#using-ssl-for-encrypted-communication) for best practices about running a public notebook server in general, most of which are encoded in this image.
## Conda Environments
The default Python 3.x [Conda environment](http://conda.pydata.org/docs/using/envs.html) resides in `/opt/conda`.
The commands `jupyter`, `ipython`, `python`, `pip`, and `conda` (among others) are available in both environments. For convenience, you can install packages into either environment regardless of what environment is currently active using commands like the following:
```
# install a package into the default (python 3.x) environment
pip install some-package
conda install some-package
```
## Alternative Commands
### start.sh
The `start.sh` script supports the same features as the default `start-notebook.sh` script (e.g., `GRANT_SUDO`), but allows you to specify an arbitrary command to execute. For example, to run the text-based `ipython` console in a container, do the following:
```
docker run -it --rm jupyter/minimal-notebook start.sh ipython
```
Or, to run JupyterLab instead of the classic notebook, run the following:
```
docker run -it --rm -p 8888:8888 jupyter/minimal-notebook start.sh jupyter lab
```
This script is particularly useful when you derive a new Dockerfile from this image and install additional Jupyter applications with subcommands like `jupyter console`, `jupyter kernelgateway`, etc.
### Others
You can bypass the provided scripts and specify your an arbitrary start command. If you do, keep in mind that certain features documented above will not function (e.g., `GRANT_SUDO`).
This diff is collapsed.
...@@ -2,112 +2,5 @@ ...@@ -2,112 +2,5 @@
# Jupyter Notebook R Stack # Jupyter Notebook R Stack
## What it Gives You * [Jupyter Docker Stacks on ReadTheDocs](http://jupyter-docker-stacks.readthedocs.io/en/latest/index.html)
* [Selecting an Image :: Core Stacks :: jupyter/r-notebook](http://jupyter-docker-stacks.readthedocs.io/en/latest/using/selecting.html#jupyter-r-notebook)
* Jupyter Notebook 5.2.x
* Conda R v3.3.x and channel
* plyr, devtools, shiny, rmarkdown, forecast, rsqlite, reshape2, nycflights13, caret, rcurl, and randomforest pre-installed
* The [tidyverse](https://github.com/tidyverse/tidyverse) R packages are also installed, including ggplot2, dplyr, tidyr, readr, purrr, tibble, stringr, lubridate, and broom
* Unprivileged user `jovyan` (uid=1000, configurable, see options) in group `users` (gid=100) with ownership over `/home/jovyan` and `/opt/conda`
* [tini](https://github.com/krallin/tini) as the container entrypoint and [start-notebook.sh](../base-notebook/start-notebook.sh) as the default command
* `/usr/local/bin/start-notebook.d` directory for custom init scripts that you can add in derived images
* A [start-singleuser.sh](../base-notebook/start-singleuser.sh) script useful for running a single-user instance of the Notebook server, as required by JupyterHub
* A [start.sh](../base-notebook/start.sh) script useful for running alternative commands in the container (e.g. `ipython`, `jupyter kernelgateway`, `jupyter lab`)
* Options for a self-signed HTTPS certificate and passwordless `sudo`
## Basic Use
The following command starts a container with the Notebook server listening for HTTP connections on port 8888 with a randomly generated authentication token configured.
```
docker run -it --rm -p 8888:8888 jupyter/r-notebook
```
Take note of the authentication token included in the notebook startup log messages. Include it in the URL you visit to access the Notebook server or enter it in the Notebook login form.
## Notebook Options
The Docker container executes a [`start-notebook.sh` script](../base-notebook/start-notebook.sh) script by default. The `start-notebook.sh` script handles the `NB_UID`, `NB_GID` and `GRANT_SUDO` features documented in the next section, and then executes the `jupyter notebook`.
You can pass [Jupyter command line options](https://jupyter.readthedocs.io/en/latest/projects/jupyter-command.html) through the `start-notebook.sh` script when launching the container. For example, to secure the Notebook server with a custom password hashed using `IPython.lib.passwd()` instead of the default token, run the following:
```
docker run -d -p 8888:8888 jupyter/r-notebook start-notebook.sh --NotebookApp.password='sha1:74ba40f8a388:c913541b7ee99d15d5ed31d4226bf7838f83a50e'
```
For example, to set the base URL of the notebook server, run the following:
```
docker run -d -p 8888:8888 jupyter/r-notebook start-notebook.sh --NotebookApp.base_url=/some/path
```
For example, to disable all authentication mechanisms (not a recommended practice):
```
docker run -d -p 8888:8888 jupyter/r-notebook start-notebook.sh --NotebookApp.token=''
```
You can sidestep the `start-notebook.sh` script and run your own commands in the container. See the *Alternative Commands* section later in this document for more information.
## Docker Options
You may customize the execution of the Docker container and the command it is running with the following optional arguments.
* `-e GEN_CERT=yes` - Generates a self-signed SSL certificate and configures Jupyter Notebook to use it to accept encrypted HTTPS connections.
* `-e NB_UID=1000` - Specify the uid of the `jovyan` user. Useful to mount host volumes with specific file ownership. For this option to take effect, you must run the container with `--user root`. (The `start-notebook.sh` script will `su jovyan` after adjusting the user id.)
* `-e NB_GID=100` - Specify the gid of the `jovyan` user. Useful to mount host volumes with specific file ownership. For this option to take effect, you must run the container with `--user root`. (The `start-notebook.sh` script will `su jovyan` after adjusting the group id.)
* `-e GRANT_SUDO=yes` - Gives the `jovyan` user passwordless `sudo` capability. Useful for installing OS packages. For this option to take effect, you must run the container with `--user root`. (The `start-notebook.sh` script will `su jovyan` after adding `jovyan` to sudoers.) **You should only enable `sudo` if you trust the user or if the container is running on an isolated host.**
* `-v /some/host/folder/for/work:/home/jovyan/work` - Mounts a host machine directory as folder in the container. Useful when you want to preserve notebooks and other work even after the container is destroyed. **You must grant the within-container notebook user or group (`NB_UID` or `NB_GID`) write access to the host directory (e.g., `sudo chown 1000 /some/host/folder/for/work`).**
## SSL Certificates
You may mount SSL key and certificate files into a container and configure Jupyter Notebook to use them to accept HTTPS connections. For example, to mount a host folder containing a `notebook.key` and `notebook.crt`:
```
docker run -d -p 8888:8888 \
-v /some/host/folder:/etc/ssl/notebook \
jupyter/r-notebook start-notebook.sh \
--NotebookApp.keyfile=/etc/ssl/notebook/notebook.key
--NotebookApp.certfile=/etc/ssl/notebook/notebook.crt
```
Alternatively, you may mount a single PEM file containing both the key and certificate. For example:
```
docker run -d -p 8888:8888 \
-v /some/host/folder/notebook.pem:/etc/ssl/notebook.pem \
jupyter/r-notebook start-notebook.sh \
--NotebookApp.certfile=/etc/ssl/notebook.pem
```
In either case, Jupyter Notebook expects the key and certificate to be a base64 encoded text file. The certificate file or PEM may contain one or more certificates (e.g., server, intermediate, and root).
For additional information about using SSL, see the following:
* The [docker-stacks/examples](https://github.com/jupyter/docker-stacks/tree/master/examples) for information about how to use [Let's Encrypt](https://letsencrypt.org/) certificates when you run these stacks on a publicly visible domain.
* The [jupyter_notebook_config.py](jupyter_notebook_config.py) file for how this Docker image generates a self-signed certificate.
* The [Jupyter Notebook documentation](https://jupyter-notebook.readthedocs.io/en/latest/public_server.html#using-ssl-for-encrypted-communication) for best practices about running a public notebook server in general, most of which are encoded in this image.
## Alternative Commands
### start.sh
The `start.sh` script supports the same features as the default `start-notebook.sh` script (e.g., `GRANT_SUDO`), but allows you to specify an arbitrary command to execute. For example, to run the text-based `ipython` console in a container, do the following:
```
docker run -it --rm jupyter/r-notebook start.sh ipython
```
Or, to run JupyterLab instead of the classic notebook, run the following:
```
docker run -it --rm -p 8888:8888 jupyter/r-notebook start.sh jupyter lab
```
This script is particularly useful when you derive a new Dockerfile from this image and install additional Jupyter applications with subcommands like `jupyter console`, `jupyter kernelgateway`, etc.
### Others
You can bypass the provided scripts and specify your an arbitrary start command. If you do, keep in mind that certain features documented above will not function (e.g., `GRANT_SUDO`).
...@@ -2,125 +2,7 @@ ...@@ -2,125 +2,7 @@
# Jupyter Notebook Scientific Python Stack # Jupyter Notebook Scientific Python Stack
## What it Gives You Please visit the documentation site for help using and contributing to this image and others.
* Jupyter Notebook 5.2.x * [Jupyter Docker Stacks on ReadTheDocs](http://jupyter-docker-stacks.readthedocs.io/en/latest/index.html)
* Conda Python 3.x environment * [Selecting an Image :: Core Stacks :: jupyter/scipy-notebook](http://jupyter-docker-stacks.readthedocs.io/en/latest/using/selecting.html#jupyter-scipy-notebook)
* pandas, matplotlib, scipy, seaborn, scikit-learn, scikit-image, sympy, cython, patsy, statsmodel, cloudpickle, dill, numba, bokeh, vincent, beautifulsoup, xlrd pre-installed
* Unprivileged user `jovyan` (uid=1000, configurable, see options) in group `users` (gid=100) with ownership over `/home/jovyan` and `/opt/conda`
* [tini](https://github.com/krallin/tini) as the container entrypoint and [start-notebook.sh](../base-notebook/start-notebook.sh) as the default command
* `/usr/local/bin/start-notebook.d` directory for custom init scripts that you can add in derived images
* A [start-singleuser.sh](../base-notebook/start-singleuser.sh) script useful for running a single-user instance of the Notebook server, as required by JupyterHub
* A [start.sh](../base-notebook/start.sh) script useful for running alternative commands in the container (e.g. `ipython`, `jupyter kernelgateway`, `jupyter lab`)
* Options for HTTPS, password auth, and passwordless `sudo`
## Basic Use
The following command starts a container with the Notebook server listening for HTTP connections on port 8888 with a randomly generated authentication token configured.
```
docker run -it --rm -p 8888:8888 jupyter/scipy-notebook
```
Take note of the authentication token included in the notebook startup log messages. Include it in the URL you visit to access the Notebook server or enter it in the Notebook login form.
## Notebook Options
The Docker container executes a [`start-notebook.sh` script](../base-notebook/start-notebook.sh) script by default. The `start-notebook.sh` script handles the `NB_UID`, `NB_GID` and `GRANT_SUDO` features documented in the next section, and then executes the `jupyter notebook`.
You can pass [Jupyter command line options](https://jupyter.readthedocs.io/en/latest/projects/jupyter-command.html) through the `start-notebook.sh` script when launching the container. For example, to secure the Notebook server with a custom password hashed using `IPython.lib.passwd()` instead of the default token, run the following:
```
docker run -d -p 8888:8888 jupyter/scipy-notebook start-notebook.sh --NotebookApp.password='sha1:74ba40f8a388:c913541b7ee99d15d5ed31d4226bf7838f83a50e'
```
For example, to set the base URL of the notebook server, run the following:
```
docker run -d -p 8888:8888 jupyter/scipy-notebook start-notebook.sh --NotebookApp.base_url=/some/path
```
For example, to disable all authentication mechanisms (not a recommended practice):
```
docker run -d -p 8888:8888 jupyter/scipy-notebook start-notebook.sh --NotebookApp.token=''
```
You can sidestep the `start-notebook.sh` script and run your own commands in the container. See the *Alternative Commands* section later in this document for more information.
## Docker Options
You may customize the execution of the Docker container and the Notebook server it contains with the following optional arguments.
* `-e GEN_CERT=yes` - Generates a self-signed SSL certificate and configures Jupyter Notebook to use it to accept encrypted HTTPS connections.
* `-e NB_UID=1000` - Specify the uid of the `jovyan` user. Useful to mount host volumes with specific file ownership. For this option to take effect, you must run the container with `--user root`. (The `start-notebook.sh` script will `su jovyan` after adjusting the user id.)
* `-e NB_GID=100` - Specify the gid of the `jovyan` user. Useful to mount host volumes with specific file ownership. For this option to take effect, you must run the container with `--user root`. (The `start-notebook.sh` script will `su jovyan` after adjusting the group id.)
* `-e GRANT_SUDO=yes` - Gives the `jovyan` user passwordless `sudo` capability. Useful for installing OS packages. For this option to take effect, you must run the container with `--user root`. (The `start-notebook.sh` script will `su jovyan` after adding `jovyan` to sudoers.) **You should only enable `sudo` if you trust the user or if the container is running on an isolated host.**
* `-v /some/host/folder/for/work:/home/jovyan/work` - Mounts a host machine directory as folder in the container. Useful when you want to preserve notebooks and other work even after the container is destroyed. **You must grant the within-container notebook user or group (`NB_UID` or `NB_GID`) write access to the host directory (e.g., `sudo chown 1000 /some/host/folder/for/work`).**
## SSL Certificates
You may mount SSL key and certificate files into a container and configure Jupyter Notebook to use them to accept HTTPS connections. For example, to mount a host folder containing a `notebook.key` and `notebook.crt`:
```
docker run -d -p 8888:8888 \
-v /some/host/folder:/etc/ssl/notebook \
jupyter/scipy-notebook start-notebook.sh \
--NotebookApp.keyfile=/etc/ssl/notebook/notebook.key
--NotebookApp.certfile=/etc/ssl/notebook/notebook.crt
```
Alternatively, you may mount a single PEM file containing both the key and certificate. For example:
```
docker run -d -p 8888:8888 \
-v /some/host/folder/notebook.pem:/etc/ssl/notebook.pem \
jupyter/scipy-notebook start-notebook.sh \
--NotebookApp.certfile=/etc/ssl/notebook.pem
```
In either case, Jupyter Notebook expects the key and certificate to be a base64 encoded text file. The certificate file or PEM may contain one or more certificates (e.g., server, intermediate, and root).
For additional information about using SSL, see the following:
* The [docker-stacks/examples](https://github.com/jupyter/docker-stacks/tree/master/examples) for information about how to use [Let's Encrypt](https://letsencrypt.org/) certificates when you run these stacks on a publicly visible domain.
* The [jupyter_notebook_config.py](jupyter_notebook_config.py) file for how this Docker image generates a self-signed certificate.
* The [Jupyter Notebook documentation](https://jupyter-notebook.readthedocs.io/en/latest/public_server.html#using-ssl-for-encrypted-communication) for best practices about running a public notebook server in general, most of which are encoded in this image.
## Conda Environments
The default Python 3.x [Conda environment](http://conda.pydata.org/docs/using/envs.html) resides in `/opt/conda`.
The commands `jupyter`, `ipython`, `python`, `pip`, and `conda` (among others) are available in both environments. For convenience, you can install packages into either environment regardless of what environment is currently active using commands like the following:
```
# install a package into the default (python 3.x) environment
pip install some-package
conda install some-package
```
## Alternative Commands
### start.sh
The `start.sh` script supports the same features as the default `start-notebook.sh` script (e.g., `GRANT_SUDO`), but allows you to specify an arbitrary command to execute. For example, to run the text-based `ipython` console in a container, do the following:
```
docker run -it --rm jupyter/scipy-notebook start.sh ipython
```
Or, to run JupyterLab instead of the classic notebook, run the following:
```
docker run -it --rm -p 8888:8888 jupyter/scipy-notebook start.sh jupyter lab
```
This script is particularly useful when you derive a new Dockerfile from this image and install additional Jupyter applications with subcommands like `jupyter console`, `jupyter kernelgateway`, etc.
### Others
You can bypass the provided scripts and specify your an arbitrary start command. If you do, keep in mind that certain features documented above will not function (e.g., `GRANT_SUDO`).
![docker pulls](https://img.shields.io/docker/pulls/jupyter/tensorflow-notebook.svg) ![docker stars](https://img.shields.io/docker/stars/jupyter/tensorflow-notebook.svg) [![](https://images.microbadger.com/badges/image/jupyter/tensorflow-notebook.svg)](https://microbadger.com/images/jupyter/tensorflow-notebook "jupyter/tensorflow-notebook image metadata") ![docker pulls](https://img.shields.io/docker/pulls/jupyter/tensorflow-notebook.svg) ![docker stars](https://img.shields.io/docker/stars/jupyter/tensorflow-notebook.svg) [![](https://images.microbadger.com/badges/image/jupyter/tensorflow-notebook.svg)](https://microbadger.com/images/jupyter/tensorflow-notebook "jupyter/tensorflow-notebook image metadata")
# Jupyter Notebook Scientific Python Stack + Tensorflow # Jupyter Notebook Deep Learning Stack
## What it Gives You Please visit the documentation site for help using and contributing to this image and others.
* Everything in [Scipy Notebook](https://github.com/jupyter/docker-stacks/tree/master/scipy-notebook) * [Jupyter Docker Stacks on ReadTheDocs](http://jupyter-docker-stacks.readthedocs.io/en/latest/index.html)
* Tensorflow and Keras for Python 3.x (without GPU support) * [Selecting an Image :: Core Stacks :: jupyter/tensorflow-notebook](http://jupyter-docker-stacks.readthedocs.io/en/latest/using/selecting.html#jupyter-tensorflow-notebook)
* [Image Specifics :: Tensorflow](http://jupyter-docker-stacks.readthedocs.io/en/latest/using/specifics.html#tensorflow)
## Basic Use
The following command starts a container with the Notebook server listening for HTTP connections on port 8888 with a randomly generated authentication token configured.
```
docker run -it --rm -p 8888:8888 jupyter/tensorflow-notebook
```
Take note of the authentication token included in the notebook startup log messages. Include it in the URL you visit to access the Notebook server or enter it in the Notebook login form.
## Tensorflow Machine Mode
Tensorflow can use single machine, or distributed mode.
Single machine mode:
```
import tensorflow as tf
hello = tf.Variable('Hello World!')
sess = tf.Session()
init = tf.global_variables_initializer()
sess.run(init)
sess.run(hello)
```
Distributed mode:
```
import tensorflow as tf
hello = tf.Variable('Hello Distributed World!')
server = tf.train.Server.create_local_server()
sess = tf.Session(server.target)
init = tf.global_variables_initializer()
sess.run(init)
sess.run(hello)
```
## Notebook Options
The Docker container executes a [`start-notebook.sh` script](../base-notebook/start-notebook.sh) script by default. The `start-notebook.sh` script handles the `NB_UID`, `NB_GID` and `GRANT_SUDO` features documented in the next section, and then executes the `jupyter notebook`.
You can pass [Jupyter command line options](https://jupyter.readthedocs.io/en/latest/projects/jupyter-command.html) through the `start-notebook.sh` script when launching the container. For example, to secure the Notebook server with a custom password hashed using `IPython.lib.passwd()` instead of the default token, run the following:
```
docker run -d -p 8888:8888 jupyter/tensorflow-notebook start-notebook.sh --NotebookApp.password='sha1:74ba40f8a388:c913541b7ee99d15d5ed31d4226bf7838f83a50e'
```
For example, to set the base URL of the notebook server, run the following:
```
docker run -d -p 8888:8888 jupyter/tensorflow-notebook start-notebook.sh --NotebookApp.base_url=/some/path
```
For example, to disable all authentication mechanisms (not a recommended practice):
```
docker run -d -p 8888:8888 jupyter/tensorflow-notebook start-notebook.sh --NotebookApp.token=''
```
You can sidestep the `start-notebook.sh` script and run your own commands in the container. See the *Alternative Commands* section later in this document for more information.
## Docker Options
You may customize the execution of the Docker container and the command it is running with the following optional arguments.
* `-e GEN_CERT=yes` - Generates a self-signed SSL certificate and configures Jupyter Notebook to use it to accept encrypted HTTPS connections.
* `-e NB_UID=1000` - Specify the uid of the `jovyan` user. Useful to mount host volumes with specific file ownership. For this option to take effect, you must run the container with `--user root`. (The `start-notebook.sh` script will `su jovyan` after adjusting the user id.)
* `-e NB_GID=100` - Specify the gid of the `jovyan` user. Useful to mount host volumes with specific file ownership. For this option to take effect, you must run the container with `--user root`. (The `start-notebook.sh` script will `su jovyan` after adjusting the group id.)
* `-e GRANT_SUDO=yes` - Gives the `jovyan` user passwordless `sudo` capability. Useful for installing OS packages. For this option to take effect, you must run the container with `--user root`. (The `start-notebook.sh` script will `su jovyan` after adding `jovyan` to sudoers.) **You should only enable `sudo` if you trust the user or if the container is running on an isolated host.**
* `-v /some/host/folder/for/work:/home/jovyan/work` - Mounts a host machine directory as folder in the container. Useful when you want to preserve notebooks and other work even after the container is destroyed. **You must grant the within-container notebook user or group (`NB_UID` or `NB_GID`) write access to the host directory (e.g., `sudo chown 1000 /some/host/folder/for/work`).**
## SSL Certificates
You may mount SSL key and certificate files into a container and configure Jupyter Notebook to use them to accept HTTPS connections. For example, to mount a host folder containing a `notebook.key` and `notebook.crt`:
```
docker run -d -p 8888:8888 \
-v /some/host/folder:/etc/ssl/notebook \
jupyter/tensorflow-notebook start-notebook.sh \
--NotebookApp.keyfile=/etc/ssl/notebook/notebook.key
--NotebookApp.certfile=/etc/ssl/notebook/notebook.crt
```
Alternatively, you may mount a single PEM file containing both the key and certificate. For example:
```
docker run -d -p 8888:8888 \
-v /some/host/folder/notebook.pem:/etc/ssl/notebook.pem \
jupyter/tensorflow-notebook start-notebook.sh \
--NotebookApp.certfile=/etc/ssl/notebook.pem
```
In either case, Jupyter Notebook expects the key and certificate to be a base64 encoded text file. The certificate file or PEM may contain one or more certificates (e.g., server, intermediate, and root).
For additional information about using SSL, see the following:
* The [docker-stacks/examples](https://github.com/jupyter/docker-stacks/tree/master/examples) for information about how to use [Let's Encrypt](https://letsencrypt.org/) certificates when you run these stacks on a publicly visible domain.
* The [jupyter_notebook_config.py](jupyter_notebook_config.py) file for how this Docker image generates a self-signed certificate.
* The [Jupyter Notebook documentation](https://jupyter-notebook.readthedocs.io/en/latest/public_server.html#using-ssl-for-encrypted-communication) for best practices about running a public notebook server in general, most of which are encoded in this image.
## Conda Environments
The default Python 3.x [Conda environment](http://conda.pydata.org/docs/using/envs.html) resides in `/opt/conda`.
The commands `jupyter`, `ipython`, `python`, `pip`, and `conda` (among others) are available in both environments. For convenience, you can install packages into either environment regardless of what environment is currently active using commands like the following:
```
# install a package into the default (python 3.x) environment
pip install some-package
conda install some-package
```
## Alternative Commands
### start.sh
The `start.sh` script supports the same features as the default `start-notebook.sh` script (e.g., `GRANT_SUDO`), but allows you to specify an arbitrary command to execute. For example, to run the text-based `ipython` console in a container, do the following:
```
docker run -it --rm jupyter/tensorflow-notebook start.sh ipython
```
Or, to run JupyterLab instead of the classic notebook, run the following:
```
docker run -it --rm -p 8888:8888 jupyter/tensorflow-notebook start.sh jupyter lab
```
This script is particularly useful when you derive a new Dockerfile from this image and install additional Jupyter applications with subcommands like `jupyter console`, `jupyter kernelgateway`, etc.
### Others
You can bypass the provided scripts and specify your an arbitrary start command. If you do, keep in mind that certain features documented above will not function (e.g., `GRANT_SUDO`).
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