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cvxopt-feedstock's Introduction

About cvxopt-feedstock

Feedstock license: BSD-3-Clause

Home: https://cvxopt.org

Package license: GPL-3.0-or-later

Summary: Convex optimization package

Development: https://github.com/cvxopt/cvxopt

Documentation: https://cvxopt.org/userguide

Current build status

Azure
VariantStatus
linux_64_python3.10.____cpython variant
linux_64_python3.11.____cpython variant
linux_64_python3.12.____cpython variant
linux_64_python3.8.____cpython variant
linux_64_python3.9.____73_pypy variant
linux_64_python3.9.____cpython variant
linux_aarch64_python3.10.____cpython variant
linux_aarch64_python3.11.____cpython variant
linux_aarch64_python3.12.____cpython variant
linux_aarch64_python3.8.____cpython variant
linux_aarch64_python3.9.____73_pypy 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_python3.8.____cpython variant
linux_ppc64le_python3.9.____73_pypy 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_python3.8.____cpython variant
osx_64_python3.9.____73_pypy 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_python3.8.____cpython variant
osx_arm64_python3.9.____cpython variant
win_64_python3.10.____cpython variant
win_64_python3.11.____cpython variant
win_64_python3.12.____cpython variant
win_64_python3.8.____cpython variant
win_64_python3.9.____73_pypy variant
win_64_python3.9.____cpython variant

Current release info

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

Installing cvxopt

Installing cvxopt 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, cvxopt can be installed with conda:

conda install cvxopt

or with mamba:

mamba install cvxopt

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

conda search cvxopt --channel conda-forge

or with mamba:

mamba search cvxopt --channel conda-forge

Alternatively, mamba repoquery may provide more information:

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

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

# List dependencies of `cvxopt`:
mamba repoquery depends cvxopt --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-Cloud 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 cvxopt-feedstock

If you would like to improve the cvxopt 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/cvxopt-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

cvxopt-feedstock's People

Contributors

beckermr avatar bgruening avatar chrisburr avatar conda-forge-admin avatar conda-forge-curator[bot] avatar corneliusroemer avatar github-actions[bot] avatar h-vetinari avatar hmaarrfk avatar isuruf avatar jakirkham avatar jayfurmanek avatar jjhelmus avatar jschueller avatar loriab avatar mariusvniekerk avatar martinandersen avatar msarahan avatar nehaljwani avatar ocefpaf avatar regro-cf-autotick-bot avatar xhochy avatar

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cvxopt-feedstock's Issues

Possibly add DSDP5 support

Not sure that I want to do this, but I do want to make a note about the possibility.

cvxopt supports DSDP5 as an optional dependency, but is currently not being built with it. Might be worth considering packaging DSDP5 and adding it as a dependency.

However, it is a bit tricky as the most recent release of DSDP5 is over 10yrs old (2005). So, this may not be an easy dependency to package. Looking at the tarball suggested that there are going to have to be some special tweaks to get this to work right.

cvxopt on windows effectively uninstallable

Since #38, there exists a windows build of this feedstock, however, it remains essentially uninstallable (as I'll explain). For #38, I didn't touch the existing host-requirement

    - suitesparse         # [not win]
    - suitesparse 5.1.*   # [win]

and it seems this is creating an incompatibility with all newer versions of openblas (it's possible that I'm overlooking another reason, but this is the only thing that jumps out at me from the recipe and the recipes of the dependencies).

Hence, the conda solver will usually suggest the build from the main channel (note: conda-forge has a higher priority in my channels):

>conda install cvxopt
Collecting package metadata: done
Solving environment: done


==> WARNING: A newer version of conda exists. <==
  current version: 4.6.14
  latest version: 4.8.3

Please update conda by running

    $ conda update -n base conda



## Package Plan ##

  environment location: C:\Users\xxx\.conda\envs\cvxopt_test

  added / updated specs:
    - cvxopt


The following NEW packages will be INSTALLED:

  cvxopt             pkgs/main/win-64::cvxopt-1.2.0-py36hdc3235a_0
  glpk               conda-forge/win-64::glpk-4.65-h2fa13f4_1002
  gsl                conda-forge/win-64::gsl-2.4-h631dd0c_1006


Proceed ([y]/n)?

And if forced to choose the conda-forge build, it would lead to large-scale downgrades across packages (esp. from the scientific stack) as openblas is incompatible.

Xref conda-forge/suitesparse-feedstock#51.

Windows Packages?

Hi, I am trying to install cvxopt using anaconda, but I am getting the following error:

`PackageNotFoundError: Package missing in current win-64 channels:

  • cvxopt`

I also tried conda install -c conda-forge cvxopt and pip install cvxopt , still getting some error. Could you please help me with this issue.

Thanks,

Split out SuiteSparse

cvxopt builds its own copy of SuiteSparse. However, it would be much better in the long run if we build it ourselves. This lets us better customize it to server our needs. See this PR ( conda-forge/staged-recipes#655 ) to package SuiteSparse.

Build for osx-arm64

Hi,
Would it be possible to create a CVXOPT build for the new MacBooks (with the osx-arm64 chips)? It is the only package for my project that doesn't yet run on my new laptop, and an attempt to build it myself failed miserably.
Thanks!

Import from cvxopt fails on path related to libgomp

cvxopt got added to cvxpy as a test dependency, and fails upon import in conda-forge/cvxpy-feedstock#60, though only on aarch (interestingly, even though those imports are part of the test suite here):

>   from cvxopt import base, blas, lapack, cholmod, misc_solvers
650s
3360E   ImportError: $PREFIX/lib/python3.7/site-packages/cvxopt/../../.././libgomp.so.1: cannot allocate memory in static TLS block

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