conda-forge / pyfai-feedstock

A conda-smithy repository for pyfai.

About pyfai-base-feedstock

Feedstock license: BSD-3-Clause

Home: https://github.com/silx-kit/pyFAI/

Package license: MIT

Summary: Python implementation of fast azimuthal integration

Development: https://github.com/silx-kit/pyFAI/

Documentation: http://www.silx.org/doc/pyFAI/latest/

pyFAI is an azimuthal integration library that tries to be fast (as fast as C and even more using OpenCL and GPU). It is based on histogramming of the 2theta/Q positions of each (center of) pixel weighted by the intensity of each pixel, but parallel version uses a SparseMatrix-DenseVector multiplication. Neighboring output bins get also a contribution of pixels next to the border thanks to pixel splitting. Finally pyFAI provides also tools to calibrate the experimental setup using Debye-Scherrer rings of a reference compound.

Current build status

Azure

Variant Status linux_64_numpy1.22python3.10.____cpython linux_64_numpy1.22python3.8.____cpython linux_64_numpy1.22python3.9.____cpython linux_64_numpy1.23python3.11.____cpython linux_64_numpy1.26python3.12.____cpython linux_aarch64_numpy1.22python3.10.____cpython linux_aarch64_numpy1.22python3.8.____cpython linux_aarch64_numpy1.22python3.9.____cpython linux_aarch64_numpy1.23python3.11.____cpython linux_aarch64_numpy1.26python3.12.____cpython linux_ppc64le_numpy1.22python3.10.____cpython linux_ppc64le_numpy1.22python3.8.____cpython linux_ppc64le_numpy1.22python3.9.____cpython linux_ppc64le_numpy1.23python3.11.____cpython linux_ppc64le_numpy1.26python3.12.____cpython osx_64_numpy1.22python3.10.____cpython osx_64_numpy1.22python3.8.____cpython osx_64_numpy1.22python3.9.____cpython osx_64_numpy1.23python3.11.____cpython osx_64_numpy1.26python3.12.____cpython osx_arm64_numpy1.22python3.10.____cpython osx_arm64_numpy1.22python3.8.____cpython osx_arm64_numpy1.22python3.9.____cpython osx_arm64_numpy1.23python3.11.____cpython osx_arm64_numpy1.26python3.12.____cpython win_64_numpy1.22python3.10.____cpython win_64_numpy1.22python3.8.____cpython win_64_numpy1.22python3.9.____cpython win_64_numpy1.23python3.11.____cpython win_64_numpy1.26python3.12.____cpython

Current release info

Name	Downloads	Version	Platforms

Installing pyfai-base

Installing pyfai-base 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, pyfai, pyfai-base can be installed with conda:

conda install pyfai pyfai-base

or with mamba:

mamba install pyfai pyfai-base

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

conda search pyfai --channel conda-forge

or with mamba:

mamba search pyfai --channel conda-forge

Alternatively, mamba repoquery may provide more information:

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

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

# List dependencies of `pyfai`:
mamba repoquery depends pyfai --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 pyfai-base-feedstock

If you would like to improve the pyfai-base 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/pyfai-base-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

• @CJ-Wright
• @chiahaoliu
• @kif
• @t20100
• @tacaswell
• @tschoonj

pyfai-feedstock's Issues

Conda build fails with "No module named 'pyFAI'"

Hi, I am currently trying to update the packages for my anaconda channel (cprescher) under ubuntu linux. But cannot build pyFAI package successfully, even when using the same recipe as here in the feedstock.

It always fails with:
ModuleNotFoundError: No module named 'pyFAI'
during run_test.py

I tried to switch of the tests and found that the package is built in such a way, that it can only be importet as:

import pyfai

and not as previously with:

import pyFAI

$ conda info

     active environment : base
    active env location : /home/clemens/anaconda3
            shell level : 4
       user config file : /home/clemens/.condarc
 populated config files : /home/clemens/.condarc
          conda version : 4.8.3
    conda-build version : 3.18.11
         python version : 3.8.3.final.0
       virtual packages : __glibc=2.27
       base environment : /home/clemens/anaconda3  (writable)
           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/clemens/anaconda3/pkgs
                          /home/clemens/.conda/pkgs
       envs directories : /home/clemens/anaconda3/envs
                          /home/clemens/.conda/envs
               platform : linux-64
             user-agent : conda/4.8.3 requests/2.24.0 CPython/3.8.3 Linux/4.19.104-microsoft-standard ubuntu/18.04.5 glibc/2.27
                UID:GID : 1000:1000
             netrc file : None
           offline mode : False

BLD: windows and mac

At some point we may want to support windows and mac

Support build on linux-arm64 ?

Comment:

Some users are struggling with the installation of pyFAI within a docker onto a MacM1 ...
silx-kit/pyFAI#1896

BUG: package should require pyqt=4

Tested on both linux and mac, if pyqt=5, following error will appear:

ImportError                               Traceback (most recent call last)
<ipython-input-1-858340f8779d> in <module>()
----> 1 from pyFAI.calibration import Calibration

~/miniconda3/envs/bs_dev/lib/python3.5/site-packages/pyFAI/calibration.py in <module>()
     54 logger = logging.getLogger("pyFAI.calibration")
     55 import numpy
---> 56 from .gui.matplotlib import pylab, matplotlib
     57 from .gui.utils import update_fig
     58 from .gui import utils as gui_utils

~/miniconda3/envs/bs_dev/lib/python3.5/site-packages/pyFAI/gui/matplotlib.py in <module>()
     48
     49
---> 50 from . import qt
     51
     52 import matplotlib

~/miniconda3/envs/bs_dev/lib/python3.5/site-packages/pyFAI/gui/qt.py in <module>()
    116     import PyQt4 as QtBinding  # noqa
    117
--> 118     from PyQt4.QtCore import *  # noqa
    119     from PyQt4.QtGui import *  # noqa
    120

ImportError: No module named 'PyQt4.QtCore'

rerender & rebuild to update (at least) pypy versions

Additional comment:

A simple mamba create -c conda-forge -n pyfai-env pypy python=3.9 pyfai fails (on linux-64 using mambaforge) with:
nothing provides python 3.6.9 1_73_pypy needed by pypy-7.3.1-h9f0ad1d_1

I'm assuming that's due to a conflict in the ABI of the pypy packages,so hopefully this will be fixed by a rerender..

@conda-forge-admin, please rerender

ENH: re-render

We need a re-render to support py36

Add build for linux-ppc64le

Adding linux-ppc64le as a target platform is pretty straightforward but some direct or indirect dependencies are not built yet for ppc64le. Here is a non exhaustive list:

• fabio conda-forge/fabio-feedstock#32
• hdf5plugin conda-forge/hdf5plugin-feedstock#17
• silx-base conda-forge/silx-feedstock#37

Installing from pypi works fine, but with a few glitches, e.g. the entry points are not properly installed.

Once the dependencies are satisfied, I'll open a MR to add the linux-ppc64le platform.

ENH: add maintainers

@kif @vallsv Would either of you be interested, or know people interested in, being added to the maintainers list for this conda package?

MTN: 0.13.1

There is a 0.13.1 release on github.

MTN: update github repo

I guess we made this before they switched repos, pyFAI is now located here: https://github.com/silx-kit/pyFAI
I think we may also need to change the readme?