| Name | zarr JSON |
| Version |
2.18.0
JSON |
| download |
| home_page | None |
| Summary | An implementation of chunked, compressed, N-dimensional arrays for Python |
| upload_time | 2024-05-07 21:33:13 |
| maintainer | None |
| docs_url | None |
| author | None |
| requires_python | >=3.9 |
| license | MIT |
| keywords |
|
| VCS |
 |
| bugtrack_url |
|
| requirements |
No requirements were recorded.
|
| Travis-CI |
No Travis.
|
| coveralls test coverage |
No coveralls.
|
<div align="center">
<img src="https://raw.githubusercontent.com/zarr-developers/community/main/logos/logo2.png"><br>
</div>
# Zarr
<table>
<tr>
<td>Latest Release</td>
<td>
<a href="https://pypi.org/project/zarr/">
<img src="https://badge.fury.io/py/zarr.svg" alt="latest release" />
</a>
</td>
</tr>
<td></td>
<td>
<a href="https://anaconda.org/anaconda/zarr/">
<img src="https://anaconda.org/conda-forge/zarr/badges/version.svg" alt="latest release" />
</a>
</td>
</tr>
<tr>
<td>Package Status</td>
<td>
<a href="https://pypi.org/project/zarr/">
<img src="https://img.shields.io/pypi/status/zarr.svg" alt="status" />
</a>
</td>
</tr>
<tr>
<td>License</td>
<td>
<a href="https://github.com/zarr-developers/zarr-python/blob/main/LICENSE.txt">
<img src="https://img.shields.io/pypi/l/zarr.svg" alt="license" />
</a>
</td>
</tr>
<tr>
<td>Build Status</td>
<td>
<a href="https://github.com/zarr-developers/zarr-python/blob/main/.github/workflows/python-package.yml">
<img src="https://github.com/zarr-developers/zarr-python/actions/workflows/python-package.yml/badge.svg" alt="build status" />
</a>
</td>
</tr>
<tr>
<td>Pre-commit Status</td>
<td>
<a href=""https://github.com/zarr-developers/zarr-python/blob/main/.pre-commit-config.yaml">
<img src="https://results.pre-commit.ci/badge/github/zarr-developers/zarr-python/main.svg" alt="pre-commit status" />
</a>
</td>
</tr>
<tr>
<td>Coverage</td>
<td>
<a href="https://codecov.io/gh/zarr-developers/zarr-python">
<img src="https://codecov.io/gh/zarr-developers/zarr-python/branch/main/graph/badge.svg"/ alt="coverage">
</a>
</td>
</tr>
<tr>
<td>Downloads</td>
<td>
<a href="https://zarr.readthedocs.io">
<img src="https://pepy.tech/badge/zarr" alt="pypi downloads" />
</a>
</td>
</tr>
<tr>
<td>Zulip</td>
<td>
<a href="https://ossci.zulipchat.com/">
<img src="https://img.shields.io/badge/zulip-join_chat-brightgreen.svg" />
</a>
</td>
</tr>
<tr>
<td>Citation</td>
<td>
<a href="https://doi.org/10.5281/zenodo.3773450">
<img src="https://zenodo.org/badge/DOI/10.5281/zenodo.3773450.svg" alt="DOI">
</a>
</td>
</tr>
</table>
## What is it?
Zarr is a Python package providing an implementation of compressed, chunked, N-dimensional arrays, designed for use in parallel computing. See the [documentation](https://zarr.readthedocs.io) for more information.
## Main Features
- [**Create**](https://zarr.readthedocs.io/en/stable/tutorial.html#creating-an-array) N-dimensional arrays with any NumPy `dtype`.
- [**Chunk arrays**](https://zarr.readthedocs.io/en/stable/tutorial.html#chunk-optimizations) along any dimension.
- [**Compress**](https://zarr.readthedocs.io/en/stable/tutorial.html#compressors) and/or filter chunks using any NumCodecs codec.
- [**Store arrays**](https://zarr.readthedocs.io/en/stable/tutorial.html#tutorial-storage) in memory, on disk, inside a zip file, on S3, etc...
- [**Read**](https://zarr.readthedocs.io/en/stable/tutorial.html#reading-and-writing-data) an array [**concurrently**](https://zarr.readthedocs.io/en/stable/tutorial.html#parallel-computing-and-synchronization) from multiple threads or processes.
- Write to an array concurrently from multiple threads or processes.
- Organize arrays into hierarchies via [**groups**](https://zarr.readthedocs.io/en/stable/tutorial.html#groups).
## Where to get it
Zarr can be installed from PyPI using `pip`:
```bash
pip install zarr
```
or via `conda`:
```bash
conda install -c conda-forge zarr
```
For more details, including how to install from source, see the [installation documentation](https://zarr.readthedocs.io/en/stable/index.html#installation).
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