%global _empty_manifest_terminate_build 0
Name: python-zarr
Version: 2.14.2
Release: 1
Summary: An implementation of chunked, compressed, N-dimensional arrays for Python
License: MIT
URL: https://github.com/zarr-developers/zarr-python
Source0: https://mirrors.nju.edu.cn/pypi/web/packages/bd/12/cf2edf7da7a9bcd3c204d2723ec615dc3dc7ef1533bd4c84a165d20f0980/zarr-2.14.2.tar.gz
BuildArch: noarch
Requires: python3-asciitree
Requires: python3-numpy
Requires: python3-fasteners
Requires: python3-numcodecs
Requires: python3-notebook
Requires: python3-ipytree
Requires: python3-ipywidgets
%description
# 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](https://zarr.readthedocs.io) for more information.
## Main Features
- [**Create**](https://zarr.readthedocs.io/en/stable/tutorial.html#creating-an-array) N-dimensional arrays with any NumPy `dtype`.
- [**Chunk arrays**](https://zarr.readthedocs.io/en/stable/tutorial.html#chunk-optimizations) along any dimension.
- [**Compress**](https://zarr.readthedocs.io/en/stable/tutorial.html#compressors) and/or filter chunks using any NumCodecs codec.
- [**Store arrays**](https://zarr.readthedocs.io/en/stable/tutorial.html#tutorial-storage) in memory, on disk, inside a zip file, on S3, etc...
- [**Read**](https://zarr.readthedocs.io/en/stable/tutorial.html#reading-and-writing-data) an array [**concurrently**](https://zarr.readthedocs.io/en/stable/tutorial.html#parallel-computing-and-synchronization) from multiple threads or processes.
- Write to an array concurrently from multiple threads or processes.
- Organize arrays into hierarchies via [**groups**](https://zarr.readthedocs.io/en/stable/tutorial.html#groups).
## Where to get it
Zarr can be installed from PyPI using `pip`:
```bash
pip install zarr
```
or via `conda`:
```bash
conda install -c conda-forge zarr
```
For more details, including how to install from source, see the [installation documentation](https://zarr.readthedocs.io/en/stable/index.html#installation).
%package -n python3-zarr
Summary: An implementation of chunked, compressed, N-dimensional arrays for Python
Provides: python-zarr
BuildRequires: python3-devel
BuildRequires: python3-setuptools
BuildRequires: python3-pip
%description -n python3-zarr
# Zarr
Latest Release |
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Build Status |
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Pre-commit Status |
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Coverage |
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Downloads |
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Gitter |
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Citation |
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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](https://zarr.readthedocs.io) for more information.
## Main Features
- [**Create**](https://zarr.readthedocs.io/en/stable/tutorial.html#creating-an-array) N-dimensional arrays with any NumPy `dtype`.
- [**Chunk arrays**](https://zarr.readthedocs.io/en/stable/tutorial.html#chunk-optimizations) along any dimension.
- [**Compress**](https://zarr.readthedocs.io/en/stable/tutorial.html#compressors) and/or filter chunks using any NumCodecs codec.
- [**Store arrays**](https://zarr.readthedocs.io/en/stable/tutorial.html#tutorial-storage) in memory, on disk, inside a zip file, on S3, etc...
- [**Read**](https://zarr.readthedocs.io/en/stable/tutorial.html#reading-and-writing-data) an array [**concurrently**](https://zarr.readthedocs.io/en/stable/tutorial.html#parallel-computing-and-synchronization) from multiple threads or processes.
- Write to an array concurrently from multiple threads or processes.
- Organize arrays into hierarchies via [**groups**](https://zarr.readthedocs.io/en/stable/tutorial.html#groups).
## Where to get it
Zarr can be installed from PyPI using `pip`:
```bash
pip install zarr
```
or via `conda`:
```bash
conda install -c conda-forge zarr
```
For more details, including how to install from source, see the [installation documentation](https://zarr.readthedocs.io/en/stable/index.html#installation).
%package help
Summary: Development documents and examples for zarr
Provides: python3-zarr-doc
%description help
# Zarr
Latest Release |
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Package Status |
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License |
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Build Status |
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Pre-commit Status |
|
Coverage |
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Downloads |
|
Gitter |
|
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](https://zarr.readthedocs.io) for more information.
## Main Features
- [**Create**](https://zarr.readthedocs.io/en/stable/tutorial.html#creating-an-array) N-dimensional arrays with any NumPy `dtype`.
- [**Chunk arrays**](https://zarr.readthedocs.io/en/stable/tutorial.html#chunk-optimizations) along any dimension.
- [**Compress**](https://zarr.readthedocs.io/en/stable/tutorial.html#compressors) and/or filter chunks using any NumCodecs codec.
- [**Store arrays**](https://zarr.readthedocs.io/en/stable/tutorial.html#tutorial-storage) in memory, on disk, inside a zip file, on S3, etc...
- [**Read**](https://zarr.readthedocs.io/en/stable/tutorial.html#reading-and-writing-data) an array [**concurrently**](https://zarr.readthedocs.io/en/stable/tutorial.html#parallel-computing-and-synchronization) from multiple threads or processes.
- Write to an array concurrently from multiple threads or processes.
- Organize arrays into hierarchies via [**groups**](https://zarr.readthedocs.io/en/stable/tutorial.html#groups).
## Where to get it
Zarr can be installed from PyPI using `pip`:
```bash
pip install zarr
```
or via `conda`:
```bash
conda install -c conda-forge zarr
```
For more details, including how to install from source, see the [installation documentation](https://zarr.readthedocs.io/en/stable/index.html#installation).
%prep
%autosetup -n zarr-2.14.2
%build
%py3_build
%install
%py3_install
install -d -m755 %{buildroot}/%{_pkgdocdir}
if [ -d doc ]; then cp -arf doc %{buildroot}/%{_pkgdocdir}; fi
if [ -d docs ]; then cp -arf docs %{buildroot}/%{_pkgdocdir}; fi
if [ -d example ]; then cp -arf example %{buildroot}/%{_pkgdocdir}; fi
if [ -d examples ]; then cp -arf examples %{buildroot}/%{_pkgdocdir}; fi
pushd %{buildroot}
if [ -d usr/lib ]; then
find usr/lib -type f -printf "/%h/%f\n" >> filelist.lst
fi
if [ -d usr/lib64 ]; then
find usr/lib64 -type f -printf "/%h/%f\n" >> filelist.lst
fi
if [ -d usr/bin ]; then
find usr/bin -type f -printf "/%h/%f\n" >> filelist.lst
fi
if [ -d usr/sbin ]; then
find usr/sbin -type f -printf "/%h/%f\n" >> filelist.lst
fi
touch doclist.lst
if [ -d usr/share/man ]; then
find usr/share/man -type f -printf "/%h/%f.gz\n" >> doclist.lst
fi
popd
mv %{buildroot}/filelist.lst .
mv %{buildroot}/doclist.lst .
%files -n python3-zarr -f filelist.lst
%dir %{python3_sitelib}/*
%files help -f doclist.lst
%{_docdir}/*
%changelog
* Fri Apr 21 2023 Python_Bot - 2.14.2-1
- Package Spec generated