https://github.com/firefly-cpp/alpine-container-data-science
https://github.com/firefly-cpp/alpine-container-data-science
alpine-linux container data-science docker reproducibility reproducible-research
Last synced: 6 months ago
JSON representation
- Host: GitHub
- URL: https://github.com/firefly-cpp/alpine-container-data-science
- Owner: firefly-cpp
- Created: 2022-12-27T20:03:13.000Z (over 2 years ago)
- Default Branch: main
- Last Pushed: 2024-11-27T08:30:30.000Z (7 months ago)
- Last Synced: 2024-11-27T09:28:47.335Z (7 months ago)
- Topics: alpine-linux, container, data-science, docker, reproducibility, reproducible-research
- Language: Dockerfile
- Homepage:
- Size: 16.6 KB
- Stars: 1
- Watchers: 3
- Forks: 2
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
A basic container image for performing data science reproducibility studies based on Alpine Linux
🚀 Build & run •
🔍 Why Alpine Linux for data science?
The repository is devoted to a sample container image built on the top of Alpine Linux that installs some data science dependencies using the "apk" package manager and runs a python script.
## 🚀 Build & run
### 🐳 Docker
The image can be built using the following command:
```sh
$ docker build --tag ds .
```
Run the image using
#### Linux $PWD
```sh
docker run -it --name ds-container -v "$PWD:/var/ds" ds
```
#### Windows {$PWD}
Run the image using Powershell and {$PWD} due to $PWD not being avaliable in command prompt on Windows.
```sh
docker run -it --name ds-container -v "{$PWD}:/var/ds" ds
```
### 🦦 Podman
The image can be built using the following command:
```sh
$ podman build --tag ds .
```
Run the image using
#### Linux $PWD
```sh
podman run -it --name ds-container -v "$PWD:/var/ds" ds
```
#### Windows ($PWD)
Run the image using Powershell and {$PWD} due to $PWD not being avaliable in command prompt on Windows.
```sh
podman run -it --name ds-container -v "{$PWD}:/var/ds" ds
```
## 🔍 Why Alpine Linux for data science?
Some interesting facts:
- Small container image.
- Alpine Linux allows a lot of customization.
- Excellent package manager.
- Many data science tools already exist in the Alpine ecosystem. They can be easily installed using the "apk" command ( e.g., Python tools: NumPy, scipy, scikit-learn, seaborn, matplotlib, niapy, deap, pyswarms, jupyter, etc.) NOTE: if you are installing a Python package using "apk" that is not pure CLI (Command Line Interface), you should prepend "py3-" before the name of the package.
- Excellent community.
## Disclaimer
This software is provided as-is, and there are no guarantees that it fits your purposes or that it is bug-free. Use it at your own risk!