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align=\"center\"\u003e\n  \u003cimg src=\"https://raw.githubusercontent.com/zarr-developers/community/main/logos/logo2.png\"\u003e\u003cbr\u003e\n\u003c/div\u003e\n\n# Zarr\n\n\u003ctable\u003e\n\u003ctr\u003e\n  \u003ctd\u003eLatest Release\u003c/td\u003e\n  \u003ctd\u003e\n    \u003ca href=\"https://pypi.org/project/zarr/\"\u003e\n    \u003cimg src=\"https://badge.fury.io/py/zarr.svg\" alt=\"latest release\" /\u003e\n    \u003c/a\u003e\n  \u003c/td\u003e\n\u003c/tr\u003e\n  \u003ctd\u003e\u003c/td\u003e\n  \u003ctd\u003e\n    \u003ca href=\"https://anaconda.org/anaconda/zarr/\"\u003e\n    \u003cimg src=\"https://anaconda.org/conda-forge/zarr/badges/version.svg\" alt=\"latest release\" /\u003e\n    \u003c/a\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n  \u003ctd\u003ePackage Status\u003c/td\u003e\n  \u003ctd\u003e\n\t\t\u003ca href=\"https://pypi.org/project/zarr/\"\u003e\n\t\t\u003cimg src=\"https://img.shields.io/pypi/status/zarr.svg\" alt=\"status\" /\u003e\n\t\t\u003c/a\u003e\n  \u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n  \u003ctd\u003eLicense\u003c/td\u003e\n  \u003ctd\u003e\n    \u003ca href=\"https://github.com/zarr-developers/zarr-python/blob/main/LICENSE.txt\"\u003e\n    \u003cimg src=\"https://img.shields.io/pypi/l/zarr.svg\" alt=\"license\" /\u003e\n    \u003c/a\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n  \u003ctd\u003eBuild Status\u003c/td\u003e\n  \u003ctd\u003e\n    \u003ca href=\"https://github.com/zarr-developers/zarr-python/blob/main/.github/workflows/python-package.yml\"\u003e\n    \u003cimg src=\"https://github.com/zarr-developers/zarr-python/actions/workflows/python-package.yml/badge.svg\" alt=\"build status\" /\u003e\n    \u003c/a\u003e\n  \u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n  \u003ctd\u003ePre-commit Status\u003c/td\u003e\n  \u003ctd\u003e\n    \u003ca href=\"\"https://github.com/zarr-developers/zarr-python/blob/main/.pre-commit-config.yaml\"\u003e\n    \u003cimg 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alt=\"CZI's Essential Open Source Software for Science\"\u003e\n\t\t\u003c/a\u003e\n\t\u003c/td\u003e\n\u003c/tr\u003e\n\t\u003ctd\u003eCitation\u003c/td\u003e\n\t\u003ctd\u003e\n\t\t\u003ca href=\"https://doi.org/10.5281/zenodo.3773450\"\u003e\n\t\t\t\u003cimg src=\"https://zenodo.org/badge/DOI/10.5281/zenodo.3773450.svg\" alt=\"DOI\"\u003e\n\t\t\u003c/a\u003e\n\t\u003c/td\u003e\n\u003c/tr\u003e\n\n\u003c/table\u003e\n\n## What is it?\n\nZarr 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.\n\n## Main Features\n\n- [**Create**](https://zarr.readthedocs.io/en/stable/user-guide/arrays.html#creating-an-array) N-dimensional arrays with any NumPy `dtype`.\n- [**Chunk arrays**](https://zarr.readthedocs.io/en/stable/user-guide/performance.html#chunk-optimizations) along any dimension.\n- [**Compress**](https://zarr.readthedocs.io/en/stable/user-guide/arrays.html#compressors) and/or filter chunks using any NumCodecs codec.\n- [**Store arrays**](https://zarr.readthedocs.io/en/stable/user-guide/storage.html) in memory, on disk, inside a zip file, on S3, etc...\n- [**Read**](https://zarr.readthedocs.io/en/stable/user-guide/arrays.html#reading-and-writing-data) an array [**concurrently**](https://zarr.readthedocs.io/en/stable/user-guide/performance.html#parallel-computing-and-synchronization) from multiple threads or processes.\n- [**Write**](https://zarr.readthedocs.io/en/stable/user-guide/arrays.html#reading-and-writing-data) to an array concurrently from multiple threads or processes.\n- Organize arrays into hierarchies via [**groups**](https://zarr.readthedocs.io/en/stable/quickstart.html#hierarchical-groups).\n\n## Where to get it\n\nZarr can be installed from PyPI using `pip`:\n\n```bash\npip install zarr\n```\n\nor via `conda`:\n\n```bash\nconda install -c conda-forge zarr\n```\n\nFor more details, including how to install from source, see the [installation documentation](https://zarr.readthedocs.io/en/stable/index.html#installation).\n","funding_links":["https://github.com/sponsors/numfocus","https://numfocus.org/donate-to-zarr"],"categories":["Data Processing","数据容器和结构","Python","Data Storage Optimisation","Data formats","Climate Change","📋 Contents","Data Containers \u0026 Dataframes"],"sub_categories":["Data Representation","Mesh tools","Climate Data Standards","🧬 1. 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