Clone of https://github.com/NixOS/nixpkgs.git (to stress-test knotserver)
at gcc-offload 86 lines 2.4 kB view raw
1{ 2 lib, 3 buildPythonPackage, 4 fetchPypi, 5 isPyPy, 6 blas, 7 lapack, 8 suitesparse, 9 unittestCheckHook, 10 glpk ? null, 11 gsl ? null, 12 fftw ? null, 13 withGlpk ? true, 14 withGsl ? true, 15 withFftw ? true, 16}: 17 18assert (!blas.isILP64) && (!lapack.isILP64); 19 20buildPythonPackage rec { 21 pname = "cvxopt"; 22 version = "1.3.2"; 23 format = "setuptools"; 24 25 disabled = isPyPy; # hangs at [translation:info] 26 27 src = fetchPypi { 28 inherit pname version; 29 hash = "sha256-NGH6QsGyJAuk2h2YXKc1A5FBV/xMd0FzJ+1tfYWs2+Y="; 30 }; 31 32 buildInputs = [ 33 blas 34 lapack 35 ]; 36 37 # similar to Gsl, glpk, fftw there is also a dsdp interface 38 # but dsdp is not yet packaged in nixpkgs 39 env = 40 { 41 CVXOPT_BLAS_LIB = "blas"; 42 CVXOPT_LAPACK_LIB = "lapack"; 43 CVXOPT_BUILD_DSDP = "0"; 44 CVXOPT_SUITESPARSE_LIB_DIR = "${lib.getLib suitesparse}/lib"; 45 CVXOPT_SUITESPARSE_INC_DIR = "${lib.getDev suitesparse}/include"; 46 } 47 // lib.optionalAttrs withGsl { 48 CVXOPT_BUILD_GSL = "1"; 49 CVXOPT_GSL_LIB_DIR = "${lib.getLib gsl}/lib"; 50 CVXOPT_GSL_INC_DIR = "${lib.getDev gsl}/include"; 51 } 52 // lib.optionalAttrs withGlpk { 53 CVXOPT_BUILD_GLPK = "1"; 54 CVXOPT_GLPK_LIB_DIR = "${lib.getLib glpk}/lib"; 55 CVXOPT_GLPK_INC_DIR = "${lib.getDev glpk}/include"; 56 } 57 // lib.optionalAttrs withFftw { 58 CVXOPT_BUILD_FFTW = "1"; 59 CVXOPT_FFTW_LIB_DIR = "${lib.getLib fftw}/lib"; 60 CVXOPT_FFTW_INC_DIR = "${lib.getDev fftw}/include"; 61 }; 62 63 nativeCheckInputs = [ unittestCheckHook ]; 64 65 unittestFlagsArray = [ 66 "-s" 67 "tests" 68 ]; 69 70 meta = with lib; { 71 homepage = "https://cvxopt.org/"; 72 description = "Python Software for Convex Optimization"; 73 longDescription = '' 74 CVXOPT is a free software package for convex optimization based on the 75 Python programming language. It can be used with the interactive 76 Python interpreter, on the command line by executing Python scripts, 77 or integrated in other software via Python extension modules. Its main 78 purpose is to make the development of software for convex optimization 79 applications straightforward by building on Python's extensive 80 standard library and on the strengths of Python as a high-level 81 programming language. 82 ''; 83 maintainers = with maintainers; [ edwtjo ]; 84 license = licenses.gpl3Plus; 85 }; 86}