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conda-forge / numexpr-feedstock

A conda-smithy repository for numexpr.
BSD 3-Clause "New" or "Revised" License
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About numexpr-feedstock

Feedstock license: BSD-3-Clause

Home: https://github.com/pydata/numexpr

Package license: MIT

Summary: Fast numerical expression evaluator for NumPy.

Development: https://github.com/pydata/numexpr

Documentation: https://github.com/pydata/numexpr/wiki/Numexpr-Users-Guide

Numexpr is a fast numerical expression evaluator for NumPy. With it, expressions that operate on arrays (like "3a+4b") are accelerated and use less memory than doing the same calculation in Python.

Current build status

Azure
VariantStatus
linux_64_mkl_supportmklpython3.10.____cpython variant
linux_64_mkl_supportmklpython3.11.____cpython variant
linux_64_mkl_supportmklpython3.12.____cpython variant
linux_64_mkl_supportmklpython3.13.____cp313 variant
linux_64_mkl_supportmklpython3.9.____cpython variant
linux_64_mkl_supportnomklpython3.10.____cpython variant
linux_64_mkl_supportnomklpython3.11.____cpython variant
linux_64_mkl_supportnomklpython3.12.____cpython variant
linux_64_mkl_supportnomklpython3.13.____cp313 variant
linux_64_mkl_supportnomklpython3.9.____cpython variant
linux_aarch64_python3.10.____cpython variant
linux_aarch64_python3.11.____cpython variant
linux_aarch64_python3.12.____cpython variant
linux_aarch64_python3.13.____cp313 variant
linux_aarch64_python3.9.____cpython variant
linux_ppc64le_python3.10.____cpython variant
linux_ppc64le_python3.11.____cpython variant
linux_ppc64le_python3.12.____cpython variant
linux_ppc64le_python3.13.____cp313 variant
linux_ppc64le_python3.9.____cpython variant
osx_64_python3.10.____cpython variant
osx_64_python3.11.____cpython variant
osx_64_python3.12.____cpython variant
osx_64_python3.13.____cp313 variant
osx_64_python3.9.____cpython variant
osx_arm64_python3.10.____cpython variant
osx_arm64_python3.11.____cpython variant
osx_arm64_python3.12.____cpython variant
osx_arm64_python3.13.____cp313 variant
osx_arm64_python3.9.____cpython variant
win_64_mkl_supportmklpython3.10.____cpython variant
win_64_mkl_supportmklpython3.11.____cpython variant
win_64_mkl_supportmklpython3.12.____cpython variant
win_64_mkl_supportmklpython3.13.____cp313 variant
win_64_mkl_supportmklpython3.9.____cpython variant
win_64_mkl_supportnomklpython3.10.____cpython variant
win_64_mkl_supportnomklpython3.11.____cpython variant
win_64_mkl_supportnomklpython3.12.____cpython variant
win_64_mkl_supportnomklpython3.13.____cp313 variant
win_64_mkl_supportnomklpython3.9.____cpython variant

Current release info

Name Downloads Version Platforms
Conda Recipe Conda Downloads Conda Version Conda Platforms

Installing numexpr

Installing numexpr from the conda-forge channel can be achieved by adding conda-forge to your channels with:

conda config --add channels conda-forge
conda config --set channel_priority strict

Once the conda-forge channel has been enabled, numexpr can be installed with conda:

conda install numexpr

or with mamba:

mamba install numexpr

It is possible to list all of the versions of numexpr available on your platform with conda:

conda search numexpr --channel conda-forge

or with mamba:

mamba search numexpr --channel conda-forge

Alternatively, mamba repoquery may provide more information:

# Search all versions available on your platform:
mamba repoquery search numexpr --channel conda-forge

# List packages depending on `numexpr`:
mamba repoquery whoneeds numexpr --channel conda-forge

# List dependencies of `numexpr`:
mamba repoquery depends numexpr --channel conda-forge

About conda-forge

Powered by NumFOCUS

conda-forge is a community-led conda channel of installable packages. In order to provide high-quality builds, the process has been automated into the conda-forge GitHub organization. The conda-forge organization contains one repository for each of the installable packages. Such a repository is known as a feedstock.

A feedstock is made up of a conda recipe (the instructions on what and how to build the package) and the necessary configurations for automatic building using freely available continuous integration services. Thanks to the awesome service provided by Azure, GitHub, CircleCI, AppVeyor, Drone, and TravisCI it is possible to build and upload installable packages to the conda-forge anaconda.org channel for Linux, Windows and OSX respectively.

To manage the continuous integration and simplify feedstock maintenance conda-smithy has been developed. Using the conda-forge.yml within this repository, it is possible to re-render all of this feedstock's supporting files (e.g. the CI configuration files) with conda smithy rerender.

For more information please check the conda-forge documentation.

Terminology

feedstock - the conda recipe (raw material), supporting scripts and CI configuration.

conda-smithy - the tool which helps orchestrate the feedstock. Its primary use is in the construction of the CI .yml files and simplify the management of many feedstocks.

conda-forge - the place where the feedstock and smithy live and work to produce the finished article (built conda distributions)

Updating numexpr-feedstock

If you would like to improve the numexpr recipe or build a new package version, please fork this repository and submit a PR. Upon submission, your changes will be run on the appropriate platforms to give the reviewer an opportunity to confirm that the changes result in a successful build. Once merged, the recipe will be re-built and uploaded automatically to the conda-forge channel, whereupon the built conda packages will be available for everybody to install and use from the conda-forge channel. Note that all branches in the conda-forge/numexpr-feedstock are immediately built and any created packages are uploaded, so PRs should be based on branches in forks and branches in the main repository should only be used to build distinct package versions.

In order to produce a uniquely identifiable distribution:

Feedstock Maintainers