conda-forge / gpaw-feedstock

A conda-smithy repository for gpaw.

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

Azure

Variant Status linux_64_mpimpichnumpy1.22python3.10.____cpython linux_64_mpimpichnumpy1.22python3.8.____cpython linux_64_mpimpichnumpy1.22python3.9.____73_pypy linux_64_mpimpichnumpy1.22python3.9.____cpython linux_64_mpimpichnumpy1.23python3.11.____cpython linux_64_mpimpichnumpy1.26python3.12.____cpython linux_64_mpinompinumpy1.22python3.10.____cpython linux_64_mpinompinumpy1.22python3.8.____cpython linux_64_mpinompinumpy1.22python3.9.____73_pypy linux_64_mpinompinumpy1.22python3.9.____cpython linux_64_mpinompinumpy1.23python3.11.____cpython linux_64_mpinompinumpy1.26python3.12.____cpython linux_64_mpiopenmpinumpy1.22python3.10.____cpython linux_64_mpiopenmpinumpy1.22python3.8.____cpython linux_64_mpiopenmpinumpy1.22python3.9.____73_pypy linux_64_mpiopenmpinumpy1.22python3.9.____cpython linux_64_mpiopenmpinumpy1.23python3.11.____cpython linux_64_mpiopenmpinumpy1.26python3.12.____cpython linux_aarch64_mpimpichnumpy1.22python3.10.____cpython linux_aarch64_mpimpichnumpy1.22python3.8.____cpython linux_aarch64_mpimpichnumpy1.22python3.9.____73_pypy linux_aarch64_mpimpichnumpy1.22python3.9.____cpython linux_aarch64_mpimpichnumpy1.23python3.11.____cpython linux_aarch64_mpimpichnumpy1.26python3.12.____cpython linux_aarch64_mpinompinumpy1.22python3.10.____cpython linux_aarch64_mpinompinumpy1.22python3.8.____cpython linux_aarch64_mpinompinumpy1.22python3.9.____73_pypy linux_aarch64_mpinompinumpy1.22python3.9.____cpython linux_aarch64_mpinompinumpy1.23python3.11.____cpython linux_aarch64_mpinompinumpy1.26python3.12.____cpython linux_aarch64_mpiopenmpinumpy1.22python3.10.____cpython linux_aarch64_mpiopenmpinumpy1.22python3.8.____cpython linux_aarch64_mpiopenmpinumpy1.22python3.9.____73_pypy linux_aarch64_mpiopenmpinumpy1.22python3.9.____cpython linux_aarch64_mpiopenmpinumpy1.23python3.11.____cpython linux_aarch64_mpiopenmpinumpy1.26python3.12.____cpython linux_ppc64le_mpimpichnumpy1.22python3.10.____cpython linux_ppc64le_mpimpichnumpy1.22python3.8.____cpython linux_ppc64le_mpimpichnumpy1.22python3.9.____73_pypy linux_ppc64le_mpimpichnumpy1.22python3.9.____cpython linux_ppc64le_mpimpichnumpy1.23python3.11.____cpython linux_ppc64le_mpimpichnumpy1.26python3.12.____cpython linux_ppc64le_mpinompinumpy1.22python3.10.____cpython linux_ppc64le_mpinompinumpy1.22python3.8.____cpython linux_ppc64le_mpinompinumpy1.22python3.9.____73_pypy linux_ppc64le_mpinompinumpy1.22python3.9.____cpython linux_ppc64le_mpinompinumpy1.23python3.11.____cpython linux_ppc64le_mpinompinumpy1.26python3.12.____cpython linux_ppc64le_mpiopenmpinumpy1.22python3.10.____cpython linux_ppc64le_mpiopenmpinumpy1.22python3.8.____cpython linux_ppc64le_mpiopenmpinumpy1.22python3.9.____73_pypy linux_ppc64le_mpiopenmpinumpy1.22python3.9.____cpython linux_ppc64le_mpiopenmpinumpy1.23python3.11.____cpython linux_ppc64le_mpiopenmpinumpy1.26python3.12.____cpython osx_64_mpimpichnumpy1.22python3.10.____cpython osx_64_mpimpichnumpy1.22python3.8.____cpython osx_64_mpimpichnumpy1.22python3.9.____73_pypy osx_64_mpimpichnumpy1.22python3.9.____cpython osx_64_mpimpichnumpy1.23python3.11.____cpython osx_64_mpimpichnumpy1.26python3.12.____cpython osx_64_mpinompinumpy1.22python3.10.____cpython osx_64_mpinompinumpy1.22python3.8.____cpython osx_64_mpinompinumpy1.22python3.9.____73_pypy osx_64_mpinompinumpy1.22python3.9.____cpython osx_64_mpinompinumpy1.23python3.11.____cpython osx_64_mpinompinumpy1.26python3.12.____cpython osx_64_mpiopenmpinumpy1.22python3.10.____cpython osx_64_mpiopenmpinumpy1.22python3.8.____cpython osx_64_mpiopenmpinumpy1.22python3.9.____73_pypy osx_64_mpiopenmpinumpy1.22python3.9.____cpython osx_64_mpiopenmpinumpy1.23python3.11.____cpython osx_64_mpiopenmpinumpy1.26python3.12.____cpython

Current release info

Name	Downloads	Version	Platforms

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

• @gdonval
• @jan-janssen

gpaw-feedstock's Issues

@conda-forge-admin, please update version

Additional comment:

No response

GPAW 22.8

Comment:

When could the GPAW version 22.8 be expected in conda-forge?
https://wiki.fysik.dtu.dk/gpaw/releasenotes.html#releasenotes

Could you please add UCX?

Comment:

By default openmpi failed to run with ROSE – RDMA over Converged Ethernet.
Installing Unified Communication X (UCX) and adding "--mca btl_openib_rroce_enable 1" to the mpirun command, fixes the problem.
How about adding UCX to the GPAW feedstock?

Add Automerge

@conda-forge-admin, please add bot automerge

GPAW fail with openmpi 4.1.3

Solution to issue cannot be found in the documentation.

• I checked the documentation.

Issue

GPAW fails like
ImportError: libmpi.so.40: cannot open shared object file: No such file or directory
Then installed with
conda install -c conda-forge gpaw=*=openmpi
that picks the following packages
The following NEW packages will be INSTALLED:

ase conda-forge/noarch::ase-3.22.1-pyhd8ed1ab_1
click conda-forge/linux-64::click-8.1.3-py39hf3d152e_0
cycler conda-forge/noarch::cycler-0.11.0-pyhd8ed1ab_0
elpa conda-forge/linux-64::elpa-2021.11.001-mpi_openmpi_haf9840c_3
fftw conda-forge/linux-64::fftw-3.3.10-mpi_openmpi_h36312d9_2
flask conda-forge/noarch::flask-2.1.2-pyhd8ed1ab_1
freetype conda-forge/linux-64::freetype-2.10.4-h0708190_1
gpaw conda-forge/linux-64::gpaw-22.1.0-py39_mpi_openmpi_omp_1
gpaw-data conda-forge/linux-64::gpaw-data-0.9.20000-0
importlib-metadata conda-forge/linux-64::importlib-metadata-4.11.4-py39hf3d152e_0
itsdangerous conda-forge/noarch::itsdangerous-2.1.2-pyhd8ed1ab_0
jinja2 conda-forge/noarch::jinja2-3.1.2-pyhd8ed1ab_0
jpeg conda-forge/linux-64::jpeg-9e-h166bdaf_1
kiwisolver conda-forge/linux-64::kiwisolver-1.4.2-py39hf939315_1
lcms2 conda-forge/linux-64::lcms2-2.12-hddcbb42_0
libblas conda-forge/linux-64::libblas-3.9.0-14_linux64_openblas
libcblas conda-forge/linux-64::libcblas-3.9.0-14_linux64_openblas
libgfortran-ng conda-forge/linux-64::libgfortran-ng-12.1.0-h69a702a_16
libgfortran5 conda-forge/linux-64::libgfortran5-12.1.0-hdcd56e2_16
liblapack conda-forge/linux-64::liblapack-3.9.0-14_linux64_openblas
libopenblas conda-forge/linux-64::libopenblas-0.3.20-pthreads_h78a6416_0
libpng conda-forge/linux-64::libpng-1.6.37-h21135ba_2
libtiff pkgs/main/linux-64::libtiff-4.2.0-h85742a9_0
libvdwxc conda-forge/linux-64::libvdwxc-0.4.0-mpi_openmpi_h36312d9_0
libwebp-base conda-forge/linux-64::libwebp-base-1.2.2-h7f98852_1
libxc conda-forge/linux-64::libxc-5.2.3-py39hea1df8f_1
lz4-c conda-forge/linux-64::lz4-c-1.9.3-h9c3ff4c_1
markupsafe conda-forge/linux-64::markupsafe-2.1.1-py39hb9d737c_1
matplotlib-base conda-forge/linux-64::matplotlib-base-3.4.3-py39h2fa2bec_2
mpi conda-forge/linux-64::mpi-1.0-openmpi
numpy conda-forge/linux-64::numpy-1.22.3-py39hc58783e_2
olefile conda-forge/noarch::olefile-0.46-pyh9f0ad1d_1
openmpi conda-forge/linux-64::openmpi-4.1.3-external_3
pillow conda-forge/linux-64::pillow-7.2.0-py39h6f3857e_2
pyparsing conda-forge/noarch::pyparsing-3.0.9-pyhd8ed1ab_0
python-dateutil conda-forge/noarch::python-dateutil-2.8.2-pyhd8ed1ab_0
python_abi conda-forge/linux-64::python_abi-3.9-2_cp39
scalapack conda-forge/linux-64::scalapack-2.2.0-h67de57e_1
scipy conda-forge/linux-64::scipy-1.8.1-py39he49c0e8_0
six conda-forge/noarch::six-1.16.0-pyh6c4a22f_0
tornado conda-forge/linux-64::tornado-6.1-py39hb9d737c_3
werkzeug conda-forge/noarch::werkzeug-2.1.2-pyhd8ed1ab_1
zipp conda-forge/noarch::zipp-3.8.0-pyhd8ed1ab_0
zstd conda-forge/linux-64::zstd-1.4.9-ha95c52a_0

The issue is resolved by
conda install -c conda-forge openmpi=4.1.2

Installed packages

_libgcc_mutex             0.1                        main
_openmp_mutex             5.1                       1_gnu
ase                       3.22.1             pyhd8ed1ab_1    conda-forge
ca-certificates           2022.5.18.1          ha878542_0    conda-forge
certifi                   2022.5.18.1      py39hf3d152e_0    conda-forge
click                     8.1.3            py39hf3d152e_0    conda-forge
cycler                    0.11.0             pyhd8ed1ab_0    conda-forge
elpa                      2021.11.001     mpi_openmpi_haf9840c_3    conda-forge
fftw                      3.3.10          mpi_openmpi_h36312d9_2    conda-forge
flask                     2.1.2              pyhd8ed1ab_1    conda-forge
freetype                  2.10.4               h0708190_1    conda-forge
gpaw                      22.1.0          py39_mpi_openmpi_omp_1    conda-forge
gpaw-data                 0.9.20000                     0    conda-forge
importlib-metadata        4.11.4           py39hf3d152e_0    conda-forge
itsdangerous              2.1.2              pyhd8ed1ab_0    conda-forge
jinja2                    3.1.2              pyhd8ed1ab_0    conda-forge
jpeg                      9e                   h166bdaf_1    conda-forge
kiwisolver                1.4.2            py39hf939315_1    conda-forge
lcms2                     2.12                 hddcbb42_0    conda-forge
ld_impl_linux-64          2.38                 h1181459_1
libblas                   3.9.0           14_linux64_openblas    conda-forge
libcblas                  3.9.0           14_linux64_openblas    conda-forge
libffi                    3.3                  he6710b0_2
libgcc                    7.2.0                h69d50b8_2    conda-forge
libgcc-ng                 11.2.0               h1234567_1
libgfortran-ng            12.1.0              h69a702a_16    conda-forge
libgfortran5              12.1.0              hdcd56e2_16    conda-forge
libgomp                   11.2.0               h1234567_1
liblapack                 3.9.0           14_linux64_openblas    conda-forge
libopenblas               0.3.20          pthreads_h78a6416_0    conda-forge
libpng                    1.6.37               h21135ba_2    conda-forge
libstdcxx-ng              12.1.0              ha89aaad_16    conda-forge
libtiff                   4.2.0                h85742a9_0
libvdwxc                  0.4.0           mpi_openmpi_h36312d9_0    conda-forge
libwebp-base              1.2.2                h7f98852_1    conda-forge
libxc                     5.2.3            py39hea1df8f_1    conda-forge
libzlib                   1.2.11            h166bdaf_1014    conda-forge
lz4-c                     1.9.3                h9c3ff4c_1    conda-forge
markupsafe                2.1.1            py39hb9d737c_1    conda-forge
matplotlib-base           3.4.3            py39h2fa2bec_2    conda-forge
mpi                       1.0                     openmpi    conda-forge
ncurses                   6.3                  h7f8727e_2
numpy                     1.22.3           py39hc58783e_2    conda-forge
olefile                   0.46               pyh9f0ad1d_1    conda-forge
openmpi                   4.1.2                hbfc84c5_0    conda-forge
openssl                   1.1.1o               h166bdaf_0    conda-forge
pillow                    7.2.0            py39h6f3857e_2    conda-forge
pip                       21.2.4           py39h06a4308_0
pyparsing                 3.0.9              pyhd8ed1ab_0    conda-forge
python                    3.9.7           h49503c6_0_cpython    conda-forge
python-dateutil           2.8.2              pyhd8ed1ab_0    conda-forge
python_abi                3.9                      2_cp39    conda-forge
readline                  8.1.2                h7f8727e_1
scalapack                 2.2.0                h67de57e_1    conda-forge
scipy                     1.8.1            py39he49c0e8_0    conda-forge
setuptools                61.2.0           py39h06a4308_0
six                       1.16.0             pyh6c4a22f_0    conda-forge
sqlite                    3.38.5               h4ff8645_0    conda-forge
tk                        8.6.12               h27826a3_0    conda-forge
tornado                   6.1              py39hb9d737c_3    conda-forge
tzdata                    2022a                hda174b7_0
werkzeug                  2.1.2              pyhd8ed1ab_1    conda-forge
wheel                     0.37.1             pyhd3eb1b0_0
xz                        5.2.5                h7f8727e_1
zipp                      3.8.0              pyhd8ed1ab_0    conda-forge
zlib                      1.2.11            h166bdaf_1014    conda-forge
zstd                      1.4.9                ha95c52a_0    conda-forge

Environment info

active environment : gpaw
    active env location : /home/niflheim/vlaiv/miniconda3/envs/gpaw
            shell level : 2
       user config file : /home/niflheim/vlaiv/.condarc
 populated config files :
          conda version : 4.13.0
    conda-build version : not installed
         python version : 3.9.5.final.0
       virtual packages : __linux=3.10.0=0
                          __glibc=2.17=0
                          __unix=0=0
                          __archspec=1=x86_64
       base environment : /home/niflheim/vlaiv/miniconda3  (writable)
      conda av data dir : /home/niflheim/vlaiv/miniconda3/etc/conda
  conda av metadata url : None
           channel URLs : https://repo.anaconda.com/pkgs/main/linux-64
                          https://repo.anaconda.com/pkgs/main/noarch
                          https://repo.anaconda.com/pkgs/r/linux-64
                          https://repo.anaconda.com/pkgs/r/noarch
          package cache : /home/niflheim/vlaiv/miniconda3/pkgs
                          /home/niflheim/vlaiv/.conda/pkgs
       envs directories : /home/niflheim/vlaiv/miniconda3/envs
                          /home/niflheim/vlaiv/.conda/envs
               platform : linux-64
             user-agent : conda/4.13.0 requests/2.27.1 CPython/3.9.5 Linux/3.10.0-1160.66.1.el7.x86_64 centos/7.9.2009 glibc/2.17    
                UID:GID : 8516:17100
             netrc file : None
           offline mode : False

Release notes

Comment:

Could you please add some "release notes" about new packages?
It is visible that new packages are added to conda-forge, yet it is not obvious what has changed as the GPAW version remains the same.

GPAW with intelmpi

Comment:

Is it in principle possible to make a version of GPAW using intelmpi from conda-intel channel (https://anaconda.org/intel/impi_rt)?
That includes compilation of other libraries including libvdwxc and elpa using intelmpi.
I am asking because of a marked difference in speed between opempi and mpich versions of conda/GPAW 22.8. So, it is curious to know whether intelmpi is even faster.

GPAW_SETUP_PATH is corrupted when ls is set with coloring enabled

So this one took me a while.

I've got ls aliased to ls --color in my .bash_profile.

The following line prepends and appends colouring the the path string set at $GPAW_SETUP_PATH.

gpaw-feedstock/recipe/activate.sh

Line 1 in 7c33965

export GPAW_SETUP_PATH=$(ls -rd ${CONDA_PREFIX}/share/gpaw | head -n 1)

This meant that gpaw wasn't finding my files, despite everything seeming fine.

(gpaw) [thomasaar@ml7 ~]$ echo $GPAW_SETUP_PATH
/itf-fi-ml/home/thomasaar/.conda/envs/gpaw/share/gpaw

(gpaw) [thomasaar@ml7 ~]$ cd $GPAW_SETUP_PATH
-bash: cd: $'\E[0m\E[38;5;33m/itf-fi-ml/home/thomasaar/.conda/envs/gpaw/share/gpaw\E[0m': No such file or directory

Not sure how to suggest a more robust path setting mechanism.

GPAW with mpich

Do you plan to add mpich support along with openmpi?