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lal-feedstock's Introduction

About lal-feedstock

Feedstock license: BSD-3-Clause

About lal

Home: https://wiki.ligo.org/Computing/LALSuite

Package license: GPL-2.0-or-later

Summary: LSC Algorithm Library

Development: https://git.ligo.org/lscsoft/lalsuite/

Documentation: https://lscsoft.docs.ligo.org/lalsuite/lal/

The LSC Algorithm Library for gravitational wave data analysis. This package contains the shared-object libraries needed to run applications that use the LAL library. If you want to install the Python bindings, please install the associated python-lal package.

About liblal

Home: https://wiki.ligo.org/Computing/LALSuite

Package license: GPL-2.0-or-later

Summary: LSC Algorithm Library shared object libraries

Development: https://git.ligo.org/lscsoft/lalsuite.git

Documentation: https://lscsoft.docs.ligo.org/lalsuite/lal/

The LSC Algorithm Library for gravitational wave data analysis. This package contains the shared-object libraries needed to run applications that use the LAL library.

About python-lal

Home: https://wiki.ligo.org/Computing/LALSuite

Package license: GPL-2.0-or-later

Summary: LSC Algorithm Library Python bindings

Development: https://git.ligo.org/lscsoft/lalsuite/

Documentation: https://lscsoft.docs.ligo.org/lalsuite/lal/

The LSC Algorithm Library for gravitational wave data analysis. This package contains the Python bindings of the LAL C libraries and additional Python modules.

Note: this package only provides the importable Python libraries. All command-line interfaces, scripts, and executables are part of the lal package.

About lal

Home: https://wiki.ligo.org/Computing/LALSuite

Package license: GPL-2.0-or-later

Summary: LSC Algorithm Library

Development: https://git.ligo.org/lscsoft/lalsuite/

Documentation: https://lscsoft.docs.ligo.org/lalsuite/lal/

The LSC Algorithm Library for gravitational wave data analysis.

Current build status

Azure
VariantStatus
linux_64_fft_implfftw variant
linux_64_fft_implmkl variant
linux_aarch64 variant
linux_ppc64le variant
osx_64_fft_implfftw variant
osx_64_fft_implmkl variant
osx_arm64 variant

Current release info

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

Installing lal

Installing lal 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, lal, liblal, python-lal can be installed with conda:

conda install lal liblal python-lal

or with mamba:

mamba install lal liblal python-lal

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

conda search lal --channel conda-forge

or with mamba:

mamba search lal --channel conda-forge

Alternatively, mamba repoquery may provide more information:

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

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

# List dependencies of `lal`:
mamba repoquery depends lal --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 lal-feedstock

If you would like to improve the lal 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/lal-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

lal-feedstock's People

Contributors

beckermr avatar conda-forge-admin avatar conda-forge-curator[bot] avatar duncanmmacleod avatar github-actions[bot] avatar hmaarrfk avatar isuruf avatar mariusvniekerk avatar minrk avatar ocefpaf avatar regro-cf-autotick-bot avatar skymoo avatar xhochy avatar

Stargazers

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Watchers

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lal-feedstock's Issues

anaconda upload failing with 'file does not exist'

anaconda upload from both CircleCI and TravisCI is failing for the new release with errors like this [ref, ref]:

[ERROR] File "/home/conda/feedstock_root/build_artifacts/linux-64/lal-6.19.0-hee24be8_0.tar.bz2" does not exist
Traceback (most recent call last):
  File "/opt/conda/bin/upload_package", line 11, in <module>
    sys.exit(upload_package())
  File "/opt/conda/lib/python3.6/site-packages/click/core.py", line 722, in __call__
    return self.main(*args, **kwargs)
  File "/opt/conda/lib/python3.6/site-packages/click/core.py", line 697, in main
    rv = self.invoke(ctx)
  File "/opt/conda/lib/python3.6/site-packages/click/core.py", line 895, in invoke
    return ctx.invoke(self.callback, **ctx.params)
  File "/opt/conda/lib/python3.6/site-packages/click/core.py", line 535, in invoke
    return callback(*args, **kwargs)
  File "/opt/conda/lib/python3.6/site-packages/conda_forge_ci_setup/build_utils.py", line 82, in upload_package
    upload_or_check(recipe_root, owner, channel, [config_file])
  File "/opt/conda/lib/python3.6/site-packages/conda_forge_ci_setup/upload_or_check_non_existence.py", line 135, in upload_or_check
    upload(token_fn, path, owner, channel)
  File "/opt/conda/lib/python3.6/site-packages/conda_forge_ci_setup/upload_or_check_non_existence.py", line 65, in upload
    env=os.environ)
  File "/opt/conda/lib/python3.6/subprocess.py", line 291, in check_call
    raise CalledProcessError(retcode, cmd)
subprocess.CalledProcessError: Command '['anaconda', '--quiet', '-t', '/tmp/tmptxtgcqgp/binstar.token', 'upload', '/home/conda/feedstock_root/build_artifacts/linux-64/lal-6.19.0-hee24be8_0.tar.bz2', '--user=conda-forge', '--channel=main']' returned non-zero exit status 1.
Exited with code 1

cc: @conda-forge/core - help is greatly appreciated.

Mark lal packages as 'broken' on anaconda cloud

@jakirkham, @mariusvniekerk, we're just getting used to building packages with conda, and our first few attempts didn't go so well. Is it possible for you to mark the following builds as broken:

  • lal-6.18.0-*hc3780f3_?

Basically, everything that exists except the two most recent openblas variant packages.

This is required, I think, because conda install lal seems to prefer the non-openblas variants despite having a lower build number. If you think that's just a quirk on my system, or user error, please let me know. Thanks.

Reminder to update LAL acronym for next release

Comment:

In the next release the LAL acronym will be changed to stand for LVK Algorithm Library instead of LIGO Algorithm Library to indicate that LIGO, Virgo, and Kagra develop the package and not just LIGO. This ticket is to serve as a reminder that we need to do that...

Mark lal packages as 'broken' on anaconda cloud

@conda-forge/core, I would appreciate some help in marking the following builds as broken on anaconda.org/conda-forge/ for all platforms:

lal          6.18.0  hc3780f3_1
lal          6.18.0  py27hc3780f3_0
lal          6.18.0  py35hc3780f3_0
lal          6.18.0  py36hc3780f3_0
lal          6.18.0  blas_openblash96c67fe_2
lalframe     1.4.3   py27h7eb728f_0
lalframe     1.4.3   py35h7eb728f_0
lalframe     1.4.3   py36h7eb728f_0
python-lal   6.18.0  py27_blas_openblash7eb728f_2
python-lal   6.18.0  py27h7eb728f_1
python-lal   6.18.0  py35_blas_openblash7eb728f_2
python-lal   6.18.0  py35h7eb728f_1
python-lal   6.18.0  py36_blas_openblash7eb728f_2
python-lal   6.18.0  py36h7eb728f_1

Many thanks.

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