https://github.com/skuschel/generatorpipeline
Parallelize your data-processing pipelines with just a decorator.
https://github.com/skuschel/generatorpipeline
data-processing data-science hacktoberfest python
Last synced: about 1 year ago
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Parallelize your data-processing pipelines with just a decorator.
- Host: GitHub
- URL: https://github.com/skuschel/generatorpipeline
- Owner: skuschel
- License: gpl-3.0
- Created: 2019-11-21T08:01:08.000Z (over 6 years ago)
- Default Branch: master
- Last Pushed: 2024-10-19T20:22:57.000Z (over 1 year ago)
- Last Synced: 2025-04-10T23:14:22.200Z (about 1 year ago)
- Topics: data-processing, data-science, hacktoberfest, python
- Language: Python
- Homepage:
- Size: 222 KB
- Stars: 2
- Watchers: 1
- Forks: 4
- Open Issues: 12
-
Metadata Files:
- Readme: README.md
- Changelog: CHANGELOG.md
- License: LICENSE
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README
# generatorpipeline
Parallelize your data-processing pipelines with just a decorator.
# Tutorial
Please see the [tutorial notebook](generatorpipeline-tutorial.ipynb) for an overview of the functionality.
# Installation
Python 2 is NOT supported. You must use __python version 3.6__ or higher!
1) The recommended way is to create a python venv and install it into the venv. Create a new virtualenv by
```
python -m venv --system-site-packages ~/.venv/defaultpyvenv
```
2) activate the environment using `source ~/.venv/defaultpyvenv/bin/activate`.
3) Install into the venv
```
pip install generatorpipeline[full]@git+https://github.com/skuschel/generatorpipeline.git
```
# Installation for developers
Follow steps 1 and 2 of the normal installation to create and activate a venv.
3) git clone this repository
```
git clone git@github.com:skuschel/generatorpipeline.git
```
4) Install in editable mode using
```
pip install -e .
```
# Contributing
... is always welcome! Development and issue tracker can be found on github. Please report bugs to
https://github.com/skuschel/generatorpipeline/issues