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https://github.com/darribas/gds_env
A containerised platform for Geographic Data Science
https://github.com/darribas/gds_env
docker geographic-data-science jupyter-lab latex python r
Last synced: 8 days ago
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A containerised platform for Geographic Data Science
- Host: GitHub
- URL: https://github.com/darribas/gds_env
- Owner: darribas
- License: bsd-3-clause
- Created: 2016-08-12T20:44:11.000Z (about 8 years ago)
- Default Branch: master
- Last Pushed: 2024-10-10T15:40:13.000Z (24 days ago)
- Last Synced: 2024-10-13T19:42:17.872Z (21 days ago)
- Topics: docker, geographic-data-science, jupyter-lab, latex, python, r
- Language: Jupyter Notebook
- Homepage: https://darribas.org/gds_env
- Size: 4.88 MB
- Stars: 134
- Watchers: 13
- Forks: 40
- Open Issues: 9
-
Metadata Files:
- Readme: README.md
- Contributing: CONTRIBUTING.md
- License: LICENSE
Awesome Lists containing this project
README
# A containerised platform for Geographic Data Science: `gds_env`
[](https://microbadger.com/images/darribas/gds:10.0 "Get your own image badge on microbadger.com")
[](https://microbadger.com/images/darribas/gds:10.0 "Get your own version badge on microbadger.com")
[](https://mybinder.org/v2/gh/darribas/gds_env/master)
* [Dani Arribas-Bel](http://darribas.org)
[[`@darribas`](http://twitter.com/darribas)]
The `gds_env` (short for "GDS environment") provides a modern platform for Geographic Data Science. The project is a [Jupyter](https://jupyter.org/)-based stack that includes state-of-the-art **geospatial** libraries for **Python** and **R**. The `gds_env` is based on **container** technology to make it a transferrable platform for reproducibility. The source code is released under an [open source license](https://github.com/darribas/gds_env/blob/master/LICENSE) and the build process is transparent.
The `gds_env` extends the official [Jupyter Docker Stack](https://jupyter-docker-stacks.readthedocs.io/en/latest/) to include geospatial functionality in both Python and R. To offer more flexibility, this extension is provided in three different flavours, or stacks (to ): [`gds_py`](stacks/gds_py), [`gds`](stacks/gds) and [`gds_dev`](stacks/gds_dev). Each of them builds on each other and adds further functionality. Please check the [Stacks section](stacks) for more information.
The goal of the `gds_env` is to make using Python and R for geospatial easy to set up in a large variety of contexts. The `gds_env` can support research and teaching activities, but is also suitable for data scientists using Python and R "in the field". The stacks can be used in a range of environments, including: Windows/Mac/Linux laptops and desktops, servers, compute clusters, supercomputers or in the cloud (e.g. you can deploy them on [Binder](https://mybinder.org/)). For more information on how to build or install any of the stacks, check the [Guides section](guides).
## Building blocks
The `gds_env` stands on the shoulders of giants. Here are the core open technologies it is built with:
.vertimg {
vertical-align: middle;
}
[
](https://www.python.org/)
[
](https://www.r-project.org/)
[
](https://jupyter.org/)
[
](https://www.docker.com/)
[
](https://www.virtualbox.org/)
## Community
The `gds_env` is an open-source project. To join the conversation, please read through its [community guidelines](contributing).
## Citation
[](https://zenodo.org/badge/latestdoi/65582539)
```bibtex
@software{gds_env,
author = { Dani Arribas-Bel },
title = {\texttt{gds\_env}: A containerised platform for Geographic Data Science},
url = {https://darribas.org/gds_env},
version = {10.0},
date = {2023-04-11},
doi = {10.5281/zenodo.4642516},
}
```
## License
The code to generate the `gds_env` stacks is released under a BSD License. More details available on the repository's [license document](https://github.com/darribas/gds_env/blob/master/LICENSE).
---
[
](https://www.liverpool.ac.uk/geographic-data-science/)