Ihar Hrachyshka
567e8dfd8e
This commit was created by a combination of scripts and tools: - an ast-grep script to prefix things in meta with `lib.`, - a modified nixf-diagnose / nixf combination to remove unused `with lib;`, and - regular nixfmt. Co-authored-by: Wolfgang Walther <walther@technowledgy.de>
89 lines
2.3 KiB
Nix
89 lines
2.3 KiB
Nix
{
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lib,
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buildPythonPackage,
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fetchPypi,
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isPyPy,
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blas,
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lapack,
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setuptools-scm,
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suitesparse,
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unittestCheckHook,
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glpk ? null,
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gsl ? null,
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fftw ? null,
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withGlpk ? true,
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withGsl ? true,
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withFftw ? true,
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}:
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assert (!blas.isILP64) && (!lapack.isILP64);
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buildPythonPackage rec {
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pname = "cvxopt";
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version = "1.3.2";
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format = "setuptools";
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disabled = isPyPy; # hangs at [translation:info]
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src = fetchPypi {
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inherit pname version;
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hash = "sha256-NGH6QsGyJAuk2h2YXKc1A5FBV/xMd0FzJ+1tfYWs2+Y=";
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};
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buildInputs = [
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blas
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lapack
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];
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build-system = [ setuptools-scm ];
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# similar to Gsl, glpk, fftw there is also a dsdp interface
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# but dsdp is not yet packaged in nixpkgs
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env = {
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CVXOPT_BLAS_LIB = "blas";
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CVXOPT_LAPACK_LIB = "lapack";
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CVXOPT_BUILD_DSDP = "0";
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CVXOPT_SUITESPARSE_LIB_DIR = "${lib.getLib suitesparse}/lib";
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CVXOPT_SUITESPARSE_INC_DIR = "${lib.getDev suitesparse}/include";
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SETUPTOOLS_SCM_PRETEND_VERSION = version;
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}
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// lib.optionalAttrs withGsl {
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CVXOPT_BUILD_GSL = "1";
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CVXOPT_GSL_LIB_DIR = "${lib.getLib gsl}/lib";
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CVXOPT_GSL_INC_DIR = "${lib.getDev gsl}/include";
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}
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// lib.optionalAttrs withGlpk {
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CVXOPT_BUILD_GLPK = "1";
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CVXOPT_GLPK_LIB_DIR = "${lib.getLib glpk}/lib";
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CVXOPT_GLPK_INC_DIR = "${lib.getDev glpk}/include";
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}
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// lib.optionalAttrs withFftw {
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CVXOPT_BUILD_FFTW = "1";
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CVXOPT_FFTW_LIB_DIR = "${lib.getLib fftw}/lib";
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CVXOPT_FFTW_INC_DIR = "${lib.getDev fftw}/include";
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};
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nativeCheckInputs = [ unittestCheckHook ];
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unittestFlagsArray = [
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"-s"
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"tests"
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];
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meta = {
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homepage = "https://cvxopt.org/";
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description = "Python Software for Convex Optimization";
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longDescription = ''
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CVXOPT is a free software package for convex optimization based on the
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Python programming language. It can be used with the interactive
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Python interpreter, on the command line by executing Python scripts,
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or integrated in other software via Python extension modules. Its main
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purpose is to make the development of software for convex optimization
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applications straightforward by building on Python's extensive
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standard library and on the strengths of Python as a high-level
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programming language.
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'';
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license = lib.licenses.gpl3Plus;
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};
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}
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