#! /usr/bin/env python # # Copyright (C) 2007-2009 Cournapeau David # 2010 Fabian Pedregosa # License: 3-clause BSD import sys import os import platform import shutil from distutils.command.clean import clean as Clean from pkg_resources import parse_version import traceback if sys.version_info[0] < 3: import __builtin__ as builtins else: import builtins # This is a bit (!) hackish: we are setting a global variable so that the main # sklearn __init__ can detect if it is being loaded by the setup routine, to # avoid attempting to load components that aren't built yet: # the numpy distutils extensions that are used by scikit-learn to recursively # build the compiled extensions in sub-packages is based on the Python import # machinery. builtins.__SKLEARN_SETUP__ = True DISTNAME = 'scikit-learn' DESCRIPTION = 'A set of python modules for machine learning and data mining' with open('README.rst') as f: LONG_DESCRIPTION = f.read() MAINTAINER = 'Andreas Mueller' MAINTAINER_EMAIL = 'amueller@ais.uni-bonn.de' URL = 'http://scikit-learn.org' DOWNLOAD_URL = 'https://pypi.org/project/scikit-learn/#files' LICENSE = 'new BSD' # We can actually import a restricted version of sklearn that # does not need the compiled code import sklearn VERSION = sklearn.__version__ if platform.python_implementation() == 'PyPy': SCIPY_MIN_VERSION = '1.1.0' NUMPY_MIN_VERSION = '1.14.0' else: SCIPY_MIN_VERSION = '0.13.3' NUMPY_MIN_VERSION = '1.8.2' # Optional setuptools features # We need to import setuptools early, if we want setuptools features, # as it monkey-patches the 'setup' function # For some commands, use setuptools SETUPTOOLS_COMMANDS = set([ 'develop', 'release', 'bdist_egg', 'bdist_rpm', 'bdist_wininst', 'install_egg_info', 'build_sphinx', 'egg_info', 'easy_install', 'upload', 'bdist_wheel', '--single-version-externally-managed', ]) if SETUPTOOLS_COMMANDS.intersection(sys.argv): import setuptools extra_setuptools_args = dict( zip_safe=False, # the package can run out of an .egg file include_package_data=True, extras_require={ 'alldeps': ( 'numpy >= {0}'.format(NUMPY_MIN_VERSION), 'scipy >= {0}'.format(SCIPY_MIN_VERSION), ), }, ) else: extra_setuptools_args = dict() # Custom clean command to remove build artifacts class CleanCommand(Clean): description = "Remove build artifacts from the source tree" def run(self): Clean.run(self) # Remove c files if we are not within a sdist package cwd = os.path.abspath(os.path.dirname(__file__)) remove_c_files = not os.path.exists(os.path.join(cwd, 'PKG-INFO')) if remove_c_files: print('Will remove generated .c files') if os.path.exists('build'): shutil.rmtree('build') for dirpath, dirnames, filenames in os.walk('sklearn'): for filename in filenames: if any(filename.endswith(suffix) for suffix in (".so", ".pyd", ".dll", ".pyc")): os.unlink(os.path.join(dirpath, filename)) continue extension = os.path.splitext(filename)[1] if remove_c_files and extension in ['.c', '.cpp']: pyx_file = str.replace(filename, extension, '.pyx') if os.path.exists(os.path.join(dirpath, pyx_file)): os.unlink(os.path.join(dirpath, filename)) for dirname in dirnames: if dirname == '__pycache__': shutil.rmtree(os.path.join(dirpath, dirname)) cmdclass = {'clean': CleanCommand} # Optional wheelhouse-uploader features # To automate release of binary packages for scikit-learn we need a tool # to download the packages generated by travis and appveyor workers (with # version number matching the current release) and upload them all at once # to PyPI at release time. # The URL of the artifact repositories are configured in the setup.cfg file. WHEELHOUSE_UPLOADER_COMMANDS = set(['fetch_artifacts', 'upload_all']) if WHEELHOUSE_UPLOADER_COMMANDS.intersection(sys.argv): import wheelhouse_uploader.cmd cmdclass.update(vars(wheelhouse_uploader.cmd)) def configuration(parent_package='', top_path=None): if os.path.exists('MANIFEST'): os.remove('MANIFEST') from numpy.distutils.misc_util import Configuration config = Configuration(None, parent_package, top_path) # Avoid non-useful msg: # "Ignoring attempt to set 'name' (from ... " config.set_options(ignore_setup_xxx_py=True, assume_default_configuration=True, delegate_options_to_subpackages=True, quiet=True) config.add_subpackage('sklearn') return config def get_numpy_status(): """ Returns a dictionary containing a boolean specifying whether NumPy is up-to-date, along with the version string (empty string if not installed). """ numpy_status = {} try: import numpy numpy_version = numpy.__version__ numpy_status['up_to_date'] = parse_version( numpy_version) >= parse_version(NUMPY_MIN_VERSION) numpy_status['version'] = numpy_version except ImportError: traceback.print_exc() numpy_status['up_to_date'] = False numpy_status['version'] = "" return numpy_status def setup_package(): metadata = dict(name=DISTNAME, maintainer=MAINTAINER, maintainer_email=MAINTAINER_EMAIL, description=DESCRIPTION, license=LICENSE, url=URL, download_url=DOWNLOAD_URL, version=VERSION, long_description=LONG_DESCRIPTION, classifiers=['Intended Audience :: Science/Research', 'Intended Audience :: Developers', 'License :: OSI Approved', 'Programming Language :: C', 'Programming Language :: Python', 'Topic :: Software Development', 'Topic :: Scientific/Engineering', 'Operating System :: Microsoft :: Windows', 'Operating System :: POSIX', 'Operating System :: Unix', 'Operating System :: MacOS', 'Programming Language :: Python :: 2', 'Programming Language :: Python :: 2.7', 'Programming Language :: Python :: 3', 'Programming Language :: Python :: 3.4', 'Programming Language :: Python :: 3.5', 'Programming Language :: Python :: 3.6', 'Programming Language :: Python :: 3.7', ('Programming Language :: Python :: ' 'Implementation :: CPython'), ('Programming Language :: Python :: ' 'Implementation :: PyPy') ], cmdclass=cmdclass, install_requires=[ 'numpy>={0}'.format(NUMPY_MIN_VERSION), 'scipy>={0}'.format(SCIPY_MIN_VERSION) ], **extra_setuptools_args) if len(sys.argv) == 1 or ( len(sys.argv) >= 2 and ('--help' in sys.argv[1:] or sys.argv[1] in ('--help-commands', 'egg_info', '--version', 'clean'))): # For these actions, NumPy is not required # # They are required to succeed without Numpy for example when # pip is used to install Scikit-learn when Numpy is not yet present in # the system. try: from setuptools import setup except ImportError: from distutils.core import setup metadata['version'] = VERSION else: numpy_status = get_numpy_status() numpy_req_str = "scikit-learn requires NumPy >= {0}.\n".format( NUMPY_MIN_VERSION) instructions = ("Installation instructions are available on the " "scikit-learn website: " "http://scikit-learn.org/stable/install.html\n") if numpy_status['up_to_date'] is False: if numpy_status['version']: raise ImportError("Your installation of Numerical Python " "(NumPy) {0} is out-of-date.\n{1}{2}" .format(numpy_status['version'], numpy_req_str, instructions)) else: raise ImportError("Numerical Python (NumPy) is not " "installed.\n{0}{1}" .format(numpy_req_str, instructions)) from numpy.distutils.core import setup metadata['configuration'] = configuration setup(**metadata) if __name__ == "__main__": setup_package()