image-match/python/py/Lib/site-packages/joblib/test/data/create_numpy_pickle.py

"""
This script is used to generate test data for joblib/test/test_numpy_pickle.py
"""

import re
import sys

# pytest needs to be able to import this module even when numpy is
# not installed
try:
    import numpy as np
except ImportError:
    np = None

import joblib


def get_joblib_version(joblib_version=joblib.__version__):
    """Normalize joblib version by removing suffix.

    >>> get_joblib_version('0.8.4')
    '0.8.4'
    >>> get_joblib_version('0.8.4b1')
    '0.8.4'
    >>> get_joblib_version('0.9.dev0')
    '0.9'
    """
    matches = [re.match(r"(\d+).*", each) for each in joblib_version.split(".")]
    return ".".join([m.group(1) for m in matches if m is not None])


def write_test_pickle(to_pickle, args):
    kwargs = {}
    compress = args.compress
    method = args.method
    joblib_version = get_joblib_version()
    py_version = "{0[0]}{0[1]}".format(sys.version_info)
    numpy_version = "".join(np.__version__.split(".")[:2])

    # The game here is to generate the right filename according to the options.
    body = "_compressed" if (compress and method == "zlib") else ""
    if compress:
        if method == "zlib":
            kwargs["compress"] = True
            extension = ".gz"
        else:
            kwargs["compress"] = (method, 3)
            extension = ".pkl.{}".format(method)
        if args.cache_size:
            kwargs["cache_size"] = 0
            body += "_cache_size"
    else:
        extension = ".pkl"

    pickle_filename = "joblib_{}{}_pickle_py{}_np{}{}".format(
        joblib_version, body, py_version, numpy_version, extension
    )

    try:
        joblib.dump(to_pickle, pickle_filename, **kwargs)
    except Exception as e:
        # With old python version (=< 3.3.), we can arrive there when
        # dumping compressed pickle with LzmaFile.
        print(
            "Error: cannot generate file '{}' with arguments '{}'. "
            "Error was: {}".format(pickle_filename, kwargs, e)
        )
    else:
        print("File '{}' generated successfully.".format(pickle_filename))


if __name__ == "__main__":
    import argparse

    parser = argparse.ArgumentParser(description="Joblib pickle data generator.")
    parser.add_argument(
        "--cache_size",
        action="store_true",
        help="Force creation of companion numpy files for pickled arrays.",
    )
    parser.add_argument(
        "--compress", action="store_true", help="Generate compress pickles."
    )
    parser.add_argument(
        "--method",
        type=str,
        default="zlib",
        choices=["zlib", "gzip", "bz2", "xz", "lzma", "lz4"],
        help="Set compression method.",
    )
    # We need to be specific about dtypes in particular endianness
    # because the pickles can be generated on one architecture and
    # the tests run on another one. See
    # https://github.com/joblib/joblib/issues/279.
    to_pickle = [
        np.arange(5, dtype=np.dtype("<i8")),
        np.arange(5, dtype=np.dtype("<f8")),
        np.array([1, "abc", {"a": 1, "b": 2}], dtype="O"),
        # all possible bytes as a byte string
        np.arange(256, dtype=np.uint8).tobytes(),
        np.matrix([0, 1, 2], dtype=np.dtype("<i8")),
        # unicode string with non-ascii chars
        "C'est l'\xe9t\xe9 !",
    ]

    write_test_pickle(to_pickle, parser.parse_args())