zarr2.18.4
zarr2.18.4
Published
An implementation of chunked, compressed, N-dimensional arrays for Python
pip install zarr
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Requires Python
>=3.11
Dependencies
- asciitree
- numpy
>=1.24 - fasteners
; sys_platform != "emscripten" - numcodecs
!=0.14.0,!=0.14.1,>=0.10.0 - notebook
; extra == "jupyter" - ipytree
>=0.2.2; extra == "jupyter" - ipywidgets
>=8.0.0; extra == "jupyter" - sphinx
; extra == "docs" - sphinx-automodapi
; extra == "docs" - sphinx_design
; extra == "docs" - sphinx-issues
; extra == "docs" - sphinx-copybutton
; extra == "docs" - pydata-sphinx-theme
; extra == "docs" - numpydoc
; extra == "docs" - numcodecs
[msgpack]!=0.14.0,!=0.14.1; extra == "docs" - pytest-doctestplus
; extra == "docs"
Zarr
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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 for more information.
Main Features
- Create N-dimensional arrays with any NumPy
dtype. - Chunk arrays along any dimension.
- Compress and/or filter chunks using any NumCodecs codec.
- 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.