Chunked N-D arrays for cloud storage (Zarr-Python 3). Compressed arrays, parallel I/O, S3/GCS via fsspec, NumPy/Dask/Xarray compatible, for large-scale scientific computing pipelines.
---
name: zarr-python
description: Chunked N-D arrays for cloud storage (Zarr-Python 3). Compressed arrays, parallel I/O, S3/GCS via fsspec, NumPy/Dask/Xarray compatible, for large-scale scientific computing pipelines.
allowed-tools: Read Write Edit Bash
license: MIT license
compatibility: Requires Python 3.12+ and zarr 3.x. Cloud I/O needs zarr[remote] plus pinned s3fs or gcsfs. Legacy Zarr v2 workflows need exact 2.x pins on older Python.
metadata: {"version": "1.1", "skill-author": "K-Dense Inc."}
---
# Zarr Python
## Overview
Zarr is a Python library for storing large N-dimensional arrays with chunking and compression. Apply this skill for efficient parallel I/O, cloud-native workflows, and seamless integration with NumPy, Dask, and Xarray.
**Current upstream:** zarr **3.2.1** (released 2026-05-05). Docs: [zarr.readthedocs.io](https://zarr.readthedocs.io/en/stable/). New arrays default to **Zarr format 3**; set `zarr_format=2` for legacy interop. Zarr 3.2 adds rectilinear chunks and continues to refine the v3 codec pipeline. This skill is a **community guide** maintained by K-Dense Inc., not an official zarr-developers package.
## Quick Start
### Installation
```bash
uv pip install "zarr==3.2.1"
```
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