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https://github.com/felipenoris/math-server-docker
The ideal multi-user Data Science server with Jupyterhub and RStudio, ready for Python, R and Julia languages.
https://github.com/felipenoris/math-server-docker
data-science docker julia julia-language jupyter jupyter-kernels jupyterhub jupyterlab latex python rstudio-servers shiny-server
Last synced: about 2 months ago
JSON representation
The ideal multi-user Data Science server with Jupyterhub and RStudio, ready for Python, R and Julia languages.
- Host: GitHub
- URL: https://github.com/felipenoris/math-server-docker
- Owner: felipenoris
- License: mit
- Created: 2015-12-10T20:30:45.000Z (about 9 years ago)
- Default Branch: master
- Last Pushed: 2019-12-15T15:41:36.000Z (about 5 years ago)
- Last Synced: 2024-10-13T13:29:30.057Z (2 months ago)
- Topics: data-science, docker, julia, julia-language, jupyter, jupyter-kernels, jupyterhub, jupyterlab, latex, python, rstudio-servers, shiny-server
- Language: Dockerfile
- Homepage:
- Size: 398 KB
- Stars: 74
- Watchers: 8
- Forks: 18
- Open Issues: 3
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# math-server-docker
[](LICENSE)
Dockerfile to build the ideal multi-user Data Science server with Jupyterhub and RStudio, ready for Python, R and Julia languages.
It's based on CentOS 7 image, which is a very stable Linux distribution, compatible with Red Hat (widely used in Corporations),
but often offers outdated packages. In order to provide up-to-date tools, this Dockerfile builds most tools from source.
## List of tools
* [Jupyterhub](https://github.com/jupyter/jupyterhub) and [Jupyterlab](https://github.com/jupyterlab/jupyterlab) with support for the following languages:
* Python 2
* Python 3
* R
* Bash
* [RStudio Server](https://www.rstudio.com/)
* [Shiny Server](https://www.rstudio.com/products/shiny/shiny-server2/)
There's also a number of utilities under the hood:
* [Julia](https://julialang.org/)
* [p7zip](http://p7zip.sourceforge.net)
* [Java SDK](http://openjdk.java.net)
* [Redis](https://redis.io)
* [MongoDB](https://www.mongodb.com)
* [git](https://git-scm.com)
* [svn](https://subversion.apache.org)
* [sqlite3](https://www.sqlite.org)
* [pigz](https://zlib.net/pigz/)
* [Node.js](https://nodejs.org)
* [LaTeX](https://www.latex-project.org)
* [HDF5](https://support.hdfgroup.org/HDF5/)
* [uchardet](https://www.freedesktop.org/wiki/Software/uchardet/)
## Usage
To build the image, run the following comand:
```
# docker build -t math-server .
```
Be patient. It may take up to 8 hours to complete.
After the build is complete, you can start the server with:
```
# docker run -d -p 8787:8787 -p 8000:8000 --name ms1 math-server
```
With a running container, you can go ahead and create users:
```
# docker exec ms1 useradd myuser
# docker exec -it ms1 passwd myuser
```
The default ports are:
* `8787` for RStudio
* `8000` for Jupyter
## Requirements
[Docker](https://www.docker.com/).
## Application specific notes
The last command in the Dockerfile starts Jupyterhub and RStudio:
```shell
CMD /usr/lib/rstudio-server/bin/rserver \
&& jupyterhub --no-ssl -f jupyterhub_config.py
```
### Jupyter
Data files are at `/usr/local/share/jupyter/hub`.
By default, Jupyter will be accessible on the following link: `http://localhost:8000`, and will create state files (`jupyterhub_cookie_secret`, `jupyterhub.sqlite`) on current directory, and use default configuration.
You can generate a sample configuration file with:
```
# jupyterhub --generate-config
```
To start the server using a configuration file, use:
```
# jupyterhub -f jupyterhub_config.py
```
To set IP and port, use:
```
# jupyterhub --ip=192.168.1.2 --port=443
```
You may have to open port for external access:
```
# /sbin/iptables -I INPUT -p tcp -m tcp --dport 8000 -j ACCEPT
# /sbin/service iptables save
```
For `https` support, add the following lines to the config file:
```python
c.JupyterHub.port = 443
c.JupyterHub.ssl_cert = '/root/.ssh/sample-cert.pem'
c.JupyterHub.ssl_key = '/root/.ssh/sample-key.pem'
```
`443` is the default port for https. So the server will be accessible using https://localhost.
`sample-cert.pem` is the signed certificate file, and `sample-key.pem` is the private ssl key.
You can generate self signed certificate file by running the code below, but be aware that your browser will not recognize the certificate as trusted.
```
# mkdir ~/.ssh
# openssl req -x509 -newkey rsa:2048 -keyout ~/.ssh/sample-key.pem -out ~/.ssh/sample-cert.pem -days 9999 -nodes -subj "/C=BR/ST=Rio de Janeiro/L=Rio de Janeiro/O=org/OU=unit/CN=website"
# chmod 400 sample*.pem
```
This project provides a minimal `jupyter_config.py` configuration file that sets
a few important environment variables that should be passed to child spawned processes, namely: `'PATH', 'LD_LIBRARY_PATH', 'JAVA_HOME', 'CPATH', 'CMAKE_ROOT', 'http_proxy', 'https_proxy'`.
### Jupyterlab
Jupyterlab is the default user interface. This behavior is set by the following line in the provided jupyterhub_config.py file:
```
c.Spawner.default_url = '/lab'
```
To revert to old Jupyter user interface, you can either access manually the `/tree` url (as in `http://localhost:8000/user/username/tree`)
or edit `jupyterhub_config.py` deleting the `c.Spawner.default_url` line.
See [Jupyterlab documentation](http://jupyterlab.readthedocs.io/en/latest/user/jupyterhub.html) for more information.
### RStudio
Configuration files are at `/etc/rstudio`. There's also the Server Options file at `/usr/lib/rstudio-server/R/ServerOptions.R`.
Default port is 8787.
Change the default port by editing `rserver.conf`. The following will change to port 80:
```
# echo -e "www-port=80" | tee /etc/rstudio/rserver.conf
# rstudio-server restart
# rstudio-server verify-installation
```
`auth-pam-sessions-profile` directive on /etc/rstudio.rserver.conf may not work. If that happens, RStudio will look at `/etc/pam.d/rstudio`.
Proxy settings are not configured in RStudio by default. If you're running behind proxy, you should update `ServerOptions.R` file.
```
RUN echo "options(download.file.method = 'wget')" >> /usr/lib/rstudio-server/R/ServerOptions.R
RUN echo "Sys.setenv(http_proxy = 'my-proxy-url')" >> /usr/lib/rstudio-server/R/ServerOptions.R
RUN echo "Sys.setenv(https_proxy = 'my-proxy-url')" >> /usr/lib/rstudio-server/R/ServerOptions.R
```
## Packages
**Python**
Users can packages with `conda` or `pip` command line.
With pip, users can install local packages for Python2 using:
```
$ source activate py2
$ pip install --user pkgname
```
And also for Python3 using:
```
$ source activate py3
$ pip install --user pkgname
```
Refer to `conda` documentation to install packages using `conda` utility.
**R**
Check package locations with `$ R -e '.libPaths()'`.
System packages will be installed at `/usr/lib64/R/library`.
Each user can have a local package dir, automatically created under `~/R`.
*root user* will add packages with `R -e 'install.packages("pkg-name")'` command.
**Julia**
Since Julia v1.0, system packages are disabled. Only user-level packages are supported.
To install IJulia kernel, open a terminal and use the following commands:
```shell
julia> using Pkg
julia> pkg"add IJulia"
```
Restart your Jupyter session. After that, a Julia notebook option should show up.
**LaTeX**
The Docker image comes with a LaTeX distribution that is installed using [texlive](http://www.tug.org/texlive/) tool.
TeX packages can me managed using `tlmgr`.
System-wide packages can be installed using:
```
# tlmgr install [pkgname]
```
Users can also install local packages. To do that, a user must initialize a `~/texmf` tree:
```
$ tlmgr init-usertree
```
After that, the user can install local packages using:
```
$ tlmgr --usermode install [pkgname]
```
## References
* [Jupyterhub Docs](https://jupyterhub.readthedocs.org/en/latest/index.html)
* [Jupyterlab Docs](http://jupyterlab.readthedocs.io)
* [Full list of supported kernels for Jupyter](https://github.com/ipython/ipython/wiki/IPython-kernels-for-other-languages)
* [RStudio Server Admin Guide](https://s3.amazonaws.com/rstudio-server/rstudio-server-pro-0.99.879-admin-guide.pdf)
* [Shiny Server Admin Guide](http://rstudio.github.io/shiny-server/latest/)