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zarr-python

Guides use of Zarr-Python 3 for storing chunked, compressed N-dimensional arrays and groups, with local, in-memory, ZIP, and fsspec-backed S3/GCS/HTTP stores, plus NumPy, Dask, and Xarray integration. Covers array creation, resizing and appending, attributes, chunk and shard sizing, codecs, consolidated metadata, and v2-to-v3 migration. Use when creating or opening Zarr arrays or groups, choosing chunk sizes or compression for large datasets, reading or writing arrays on S3 or GCS, appending to time-series arrays, or migrating code from Zarr-Python 2 to 3. Use when setting up parallel I/O with Dask or Xarray. For labeled multi-dimensional datasets, use Xarray instead.

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# 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 Kalaris Labs, not an official zarr-developers package.

## Quick Start

### Installation

```bash
uv pip install "zarr==3.2.1"