About gpaw-feedstock
Feedstock license: BSD-3-Clause
Home: https://wiki.fysik.dtu.dk/gpaw
Package license: GPL-3.0-or-later
Summary: GPAW: DFT and beyond within the projector-augmented wave method
Development: https://gitlab.com/gpaw/gpaw
Documentation: https://wiki.fysik.dtu.dk/gpaw/documentation/documentation.html
GPAW is a density-functional theory (DFT) Python code based on the
projector-augmented wave (PAW) method and the atomic simulation environment
(ASE). It uses plane-waves, atom-centered basis-functions or real-space
uniform grids combined with multigrid methods.
Current build status
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linux_64_mpimpichnumpy1.22python3.10.____cpython |
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linux_64_mpimpichnumpy1.22python3.8.____cpython |
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linux_64_mpimpichnumpy1.22python3.9.____73_pypy |
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linux_64_mpimpichnumpy1.22python3.9.____cpython |
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linux_64_mpimpichnumpy1.23python3.11.____cpython |
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linux_64_mpimpichnumpy1.26python3.12.____cpython |
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linux_64_mpinompinumpy1.22python3.10.____cpython |
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linux_64_mpinompinumpy1.22python3.8.____cpython |
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linux_64_mpinompinumpy1.22python3.9.____73_pypy |
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linux_64_mpinompinumpy1.22python3.9.____cpython |
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linux_64_mpinompinumpy1.23python3.11.____cpython |
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linux_64_mpinompinumpy1.26python3.12.____cpython |
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linux_64_mpiopenmpinumpy1.22python3.10.____cpython |
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linux_64_mpiopenmpinumpy1.22python3.8.____cpython |
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linux_64_mpiopenmpinumpy1.22python3.9.____73_pypy |
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linux_64_mpiopenmpinumpy1.22python3.9.____cpython |
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linux_64_mpiopenmpinumpy1.23python3.11.____cpython |
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linux_64_mpiopenmpinumpy1.26python3.12.____cpython |
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linux_aarch64_mpimpichnumpy1.22python3.10.____cpython |
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linux_aarch64_mpimpichnumpy1.22python3.8.____cpython |
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linux_aarch64_mpimpichnumpy1.22python3.9.____73_pypy |
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linux_aarch64_mpimpichnumpy1.22python3.9.____cpython |
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linux_aarch64_mpimpichnumpy1.23python3.11.____cpython |
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linux_aarch64_mpimpichnumpy1.26python3.12.____cpython |
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linux_aarch64_mpinompinumpy1.22python3.10.____cpython |
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linux_aarch64_mpinompinumpy1.22python3.8.____cpython |
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linux_aarch64_mpinompinumpy1.22python3.9.____73_pypy |
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linux_aarch64_mpinompinumpy1.22python3.9.____cpython |
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linux_aarch64_mpinompinumpy1.23python3.11.____cpython |
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linux_aarch64_mpinompinumpy1.26python3.12.____cpython |
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linux_aarch64_mpiopenmpinumpy1.22python3.10.____cpython |
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linux_aarch64_mpiopenmpinumpy1.22python3.8.____cpython |
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linux_aarch64_mpiopenmpinumpy1.22python3.9.____73_pypy |
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linux_aarch64_mpiopenmpinumpy1.22python3.9.____cpython |
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linux_aarch64_mpiopenmpinumpy1.23python3.11.____cpython |
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linux_aarch64_mpiopenmpinumpy1.26python3.12.____cpython |
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linux_ppc64le_mpimpichnumpy1.22python3.10.____cpython |
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linux_ppc64le_mpimpichnumpy1.22python3.8.____cpython |
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linux_ppc64le_mpimpichnumpy1.22python3.9.____73_pypy |
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linux_ppc64le_mpimpichnumpy1.22python3.9.____cpython |
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linux_ppc64le_mpimpichnumpy1.23python3.11.____cpython |
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linux_ppc64le_mpimpichnumpy1.26python3.12.____cpython |
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linux_ppc64le_mpinompinumpy1.22python3.10.____cpython |
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linux_ppc64le_mpinompinumpy1.22python3.8.____cpython |
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linux_ppc64le_mpinompinumpy1.22python3.9.____73_pypy |
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linux_ppc64le_mpinompinumpy1.22python3.9.____cpython |
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linux_ppc64le_mpinompinumpy1.23python3.11.____cpython |
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linux_ppc64le_mpinompinumpy1.26python3.12.____cpython |
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linux_ppc64le_mpiopenmpinumpy1.22python3.10.____cpython |
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linux_ppc64le_mpiopenmpinumpy1.22python3.8.____cpython |
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linux_ppc64le_mpiopenmpinumpy1.22python3.9.____73_pypy |
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linux_ppc64le_mpiopenmpinumpy1.22python3.9.____cpython |
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linux_ppc64le_mpiopenmpinumpy1.23python3.11.____cpython |
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linux_ppc64le_mpiopenmpinumpy1.26python3.12.____cpython |
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osx_64_mpimpichnumpy1.22python3.10.____cpython |
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osx_64_mpimpichnumpy1.22python3.8.____cpython |
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osx_64_mpimpichnumpy1.22python3.9.____73_pypy |
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osx_64_mpimpichnumpy1.22python3.9.____cpython |
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osx_64_mpimpichnumpy1.23python3.11.____cpython |
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osx_64_mpimpichnumpy1.26python3.12.____cpython |
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osx_64_mpinompinumpy1.22python3.10.____cpython |
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osx_64_mpinompinumpy1.22python3.8.____cpython |
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osx_64_mpinompinumpy1.22python3.9.____73_pypy |
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osx_64_mpinompinumpy1.22python3.9.____cpython |
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osx_64_mpinompinumpy1.23python3.11.____cpython |
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osx_64_mpinompinumpy1.26python3.12.____cpython |
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osx_64_mpiopenmpinumpy1.22python3.10.____cpython |
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osx_64_mpiopenmpinumpy1.22python3.8.____cpython |
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osx_64_mpiopenmpinumpy1.22python3.9.____73_pypy |
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osx_64_mpiopenmpinumpy1.22python3.9.____cpython |
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osx_64_mpiopenmpinumpy1.23python3.11.____cpython |
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osx_64_mpiopenmpinumpy1.26python3.12.____cpython |
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Current release info
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Installing gpaw
Installing gpaw
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, gpaw
can be installed with conda
:
conda install gpaw
or with mamba
:
mamba install gpaw
It is possible to list all of the versions of gpaw
available on your platform with conda
:
conda search gpaw --channel conda-forge
or with mamba
:
mamba search gpaw --channel conda-forge
Alternatively, mamba repoquery
may provide more information:
# Search all versions available on your platform:
mamba repoquery search gpaw --channel conda-forge
# List packages depending on `gpaw`:
mamba repoquery whoneeds gpaw --channel conda-forge
# List dependencies of `gpaw`:
mamba repoquery depends gpaw --channel conda-forge
About conda-forge
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 gpaw-feedstock
If you would like to improve the gpaw 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/gpaw-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:
- If the version of a package is not being increased, please add or increase
the
build/number
.
- If the version of a package is being increased, please remember to return
the
build/number
back to 0.
Feedstock Maintainers