https://github.com/zarr-developers/zarr-python

An implementation of chunked, compressed, N-dimensional arrays for Python.
https://github.com/zarr-developers/zarr-python

compressed ndimensional-arrays python zarr

Last synced: about 23 hours ago
JSON representation

An implementation of chunked, compressed, N-dimensional arrays for Python.

• Host: GitHub
• URL: https://github.com/zarr-developers/zarr-python
• Owner: zarr-developers
• License: mit
• Created: 2015-12-15T14:49:40.000Z (about 9 years ago)
• Default Branch: main
• Last Pushed: 2024-10-29T01:33:14.000Z (3 months ago)
• Last Synced: 2024-10-29T11:29:05.476Z (3 months ago)
• Topics: compressed, ndimensional-arrays, python, zarr
• Language: Python
• Homepage: https://zarr.readthedocs.io
• Size: 16.6 MB
• Stars: 1,512
• Watchers: 44
• Forks: 279
• Open Issues: 322
• Metadata Files:
  • Readme: README-v3.md
  • Contributing: .github/CONTRIBUTING.md
  • Funding: FUNDING.yml
  • License: LICENSE.txt
  • Codeowners: .github/CODEOWNERS
  • Roadmap: docs/roadmap.rst

Awesome Lists containing this project

• best-of-python - GitHub - 42% open · ⏱️ 04.06.2024): (Data Containers & Dataframes)
• awesome-scientific-computing - GitHub
• awesome-list - Zarr - An implementation of chunked, compressed, N-dimensional arrays for Python. (Data Processing / Data Representation)
• awesome-python-machine-learning-resources - GitHub - 38% open · ⏱️ 15.08.2022): (数据容器和结构)
• awesome-production-machine-learning - Zarr - developers/zarr-python.svg?style=social) - Python implementation of chunked, compressed, N-dimensional arrays designed for use in parallel computing. (Data Storage Optimisation)

README

        
# V3 Contributor Guide

A bare-bones guide to contributing to V3.

Developed for the Feb. 2024 Zarr Sprint.

## Clone V3 branch

[Fork](https://github.com/zarr-developers/zarr-python/fork) zarr-python and clone it locally.

```

git clone {your remote}

git remote add upstream https://github.com/zarr-developers/zarr-python

git fetch upstream

git checkout --track upstream/v3

```

## Set up your environment

Zarr uses [hatch](https://hatch.pypa.io/) for its build system.

```

mamba install hatch

```

or

```

pip install hatch

```

Then

```

hatch env create test

```

## Run the Tests

```

hatch run test:run 

```

or

```

hatch -e test shell

pytest -v

```