An implementation of chunked, compressed, N-dimensional arrays for Python
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Author: Alistair Miles
Maintainer: jakirkham, Norman Rzepka, Ryan Abernathey, David Stansby, Deepak Cherian
Requires Python: >=3.12
Classifiers
Development Status
- 6 - Mature
Intended Audience
- Developers
- Information Technology
- Science/Research
Operating System
- Unix
Programming Language
- Python
- Python :: 3
- Python :: 3.12
- Python :: 3.13
- Python :: 3.14
Topic
- Software Development :: Libraries :: Python Modules
Zarr
What is it?
The zarr library is a Python implementation of the Zarr storage format. zarr delivers compressed, chunked, N-dimensional arrays that work well for parallel computing and object storage. See the documentation for more information.
Main Features
- Create N-dimensional arrays with NumPy-compatible
dtypes. - Chunk arrays along any dimension.
- Encode chunks using a variety of useful encodings (e.g., compression).
- Store arrays in memory, on disk, inside a zip file, on S3, etc...
- Read an array concurrently from multiple threads or processes.
- Write to an array concurrently from multiple threads or processes.
- Organize arrays into hierarchies via groups.
Where to get it
Zarr can be installed from PyPI using pip:
pip install zarr
or via conda:
conda install -c conda-forge zarr
For more details, including how to install from source, see the installation documentation.
Repository sub-packages
In addition to the primary zarr implementation, this repository contains other packages that provide specialized functionality with minimal dependencies:
zarr-metadata: Tools for Zarr metadata. Install withpip install zarr-metadata.zarr-indexing: Tools for lazily indexing chunked arrays. Install withpip install zarr-indexing.zarr-http-server: An HTTP server implementation targeting Zarr data. Install withpip install zarr-http-server.
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