team-10/env/Lib/site-packages/joblib/test/data/create_numpy_pickle.py
2025-08-02 07:34:44 +02:00

106 lines
3.3 KiB
Python

"""
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())