Uploaded Test files
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venv/Lib/site-packages/joblib/test/data/__init__.py
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venv/Lib/site-packages/joblib/test/data/__init__.py
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"""
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This script is used to generate test data for joblib/test/test_numpy_pickle.py
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"""
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import sys
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import re
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# pytest needs to be able to import this module even when numpy is
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# not installed
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try:
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import numpy as np
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except ImportError:
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np = None
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import joblib
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def get_joblib_version(joblib_version=joblib.__version__):
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"""Normalize joblib version by removing suffix.
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>>> get_joblib_version('0.8.4')
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'0.8.4'
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>>> get_joblib_version('0.8.4b1')
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'0.8.4'
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>>> get_joblib_version('0.9.dev0')
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'0.9'
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"""
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matches = [re.match(r'(\d+).*', each)
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for each in joblib_version.split('.')]
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return '.'.join([m.group(1) for m in matches if m is not None])
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def write_test_pickle(to_pickle, args):
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kwargs = {}
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compress = args.compress
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method = args.method
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joblib_version = get_joblib_version()
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py_version = '{0[0]}{0[1]}'.format(sys.version_info)
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numpy_version = ''.join(np.__version__.split('.')[:2])
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# The game here is to generate the right filename according to the options.
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body = '_compressed' if (compress and method == 'zlib') else ''
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if compress:
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if method == 'zlib':
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kwargs['compress'] = True
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extension = '.gz'
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else:
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kwargs['compress'] = (method, 3)
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extension = '.pkl.{}'.format(method)
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if args.cache_size:
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kwargs['cache_size'] = 0
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body += '_cache_size'
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else:
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extension = '.pkl'
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pickle_filename = 'joblib_{}{}_pickle_py{}_np{}{}'.format(
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joblib_version, body, py_version, numpy_version, extension)
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try:
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joblib.dump(to_pickle, pickle_filename, **kwargs)
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except Exception as e:
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# With old python version (=< 3.3.), we can arrive there when
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# dumping compressed pickle with LzmaFile.
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print("Error: cannot generate file '{}' with arguments '{}'. "
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"Error was: {}".format(pickle_filename, kwargs, e))
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else:
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print("File '{}' generated successfuly.".format(pickle_filename))
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if __name__ == '__main__':
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import argparse
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parser = argparse.ArgumentParser(description="Joblib pickle data "
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"generator.")
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parser.add_argument('--cache_size', action="store_true",
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help="Force creation of companion numpy "
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"files for pickled arrays.")
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parser.add_argument('--compress', action="store_true",
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help="Generate compress pickles.")
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parser.add_argument('--method', type=str, default='zlib',
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choices=['zlib', 'gzip', 'bz2', 'xz', 'lzma', 'lz4'],
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help="Set compression method.")
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# We need to be specific about dtypes in particular endianness
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# because the pickles can be generated on one architecture and
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# the tests run on another one. See
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# https://github.com/joblib/joblib/issues/279.
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to_pickle = [np.arange(5, dtype=np.dtype('<i8')),
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np.arange(5, dtype=np.dtype('<f8')),
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np.array([1, 'abc', {'a': 1, 'b': 2}], dtype='O'),
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# all possible bytes as a byte string
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np.arange(256, dtype=np.uint8).tobytes(),
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np.matrix([0, 1, 2], dtype=np.dtype('<i8')),
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# unicode string with non-ascii chars
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u"C'est l'\xe9t\xe9 !"]
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write_test_pickle(to_pickle, parser.parse_args())
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