https://github.com/olemussmann/ds_project
Helper scripts to start a Data Science project with Docker containers.
https://github.com/olemussmann/ds_project
data-science datascience docker docker-compose jupyter jupyter-lab jupyter-notebook jupyter-notebooks jupyterlab
Last synced: 3 months ago
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Helper scripts to start a Data Science project with Docker containers.
- Host: GitHub
- URL: https://github.com/olemussmann/ds_project
- Owner: OleMussmann
- License: mit
- Created: 2019-05-08T15:04:25.000Z (about 7 years ago)
- Default Branch: master
- Last Pushed: 2019-05-09T09:37:02.000Z (about 7 years ago)
- Last Synced: 2025-02-26T04:33:28.368Z (over 1 year ago)
- Topics: data-science, datascience, docker, docker-compose, jupyter, jupyter-lab, jupyter-notebook, jupyter-notebooks, jupyterlab
- Language: Shell
- Size: 8.79 KB
- Stars: 0
- Watchers: 2
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# DS_project
You found these great Docker containers for data science, but they are a hassle to use? These scripts make it easy to start, stop and destroy these containers.
This is a companion-repository for either the [Original Jupyter Docker Stacks](https://github.com/jupyter/docker-stacks) or the [GPU-enabled Docker Stacks](https://github.com/OleMussmann/docker-stacks).
## 🎬 Getting started
1. Clone this repository.
```
git clone git@github.com:OleMussmann/DS_project.git
```
2. Rename the folder to your liking, `cd` into folder.
```
mv DS_project MyDataScienceProject && cd MyDataScienceProject
```
3. Edit the `.env` file and choose a docker container for the `NOTEBOOK` variable, for example:
```
NOTEBOOK=isbjornlabs/fastai-notebook-cuda10.1:latest
```
4. For quick testing, just use the `workdir` folder to preserve your scripts and data. For a serious project, please consider a proper project structure like [Cookiecutter Data Science](https://drivendata.github.io/cookiecutter-data-science/#getting-started) within the `workdir`.
5. Use the scripts below to start, stop and destroy your data science environments.
## 📑 Scripts
[`dc`](dc) is a (very thin) wrapper around docker-compose, use it just the same. [`enter_container`](enter_container) starts a `bash`-shell in an existing container, if you prefer to work without Jupyter notebooks.
### Jupyter Notebook
| action | command |
|------------------|------------|
| start container | `./dc up` |
| stop container | `CTRL-C` |
| remove container | `./dc down`|
### Bash Shell
| action | command |
|------------------|-----------------------------------------|
| start container | `./dc -f docker-compose-bash.yml up` |
| enter container | different terminal: `./enter_container` |
| exit container | different terminal: `CTRL-D` |
| stop container | `CTRL-C` |
| remove container | `./dc -f docker-compose-bash.yml down` |
### Customization
Use environment variables to quickly override settings without editing `.env`. Starting a different notebook `jupyter/tensorflow-notebook` on port `1234`:
```
NOTEBOOK=jupyter/tensorflow-notebook PORT=1234 ./dc up
```