zarr2.18.3
zarr2.18.3
Published
An implementation of chunked, compressed, N-dimensional arrays for Python
pip install zarr
Package Downloads
Authors
Project URLs
Requires Python
>=3.10
Dependencies
- asciitree
- numpy
>=1.24
- numcodecs
>=0.10.0
- fasteners
; sys_platform != "emscripten"
- 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]; extra == "docs"
- notebook
; extra == "jupyter"
- ipytree
>=0.2.2; extra == "jupyter"
- ipywidgets
>=8.0.0; extra == "jupyter"
Zarr
Latest Release | |
Package Status | |
License | |
Build Status | |
Pre-commit Status | |
Coverage | |
Downloads | |
Zulip | |
Citation |
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.