79 lines
2.3 KiB
Python
79 lines
2.3 KiB
Python
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""" support numpy compatiblitiy across versions """
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import re
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import numpy as np
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from distutils.version import LooseVersion
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from pandas.compat import string_types, string_and_binary_types
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# numpy versioning
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_np_version = np.__version__
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_nlv = LooseVersion(_np_version)
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_np_version_under1p10 = _nlv < LooseVersion('1.10')
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_np_version_under1p11 = _nlv < LooseVersion('1.11')
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_np_version_under1p12 = _nlv < LooseVersion('1.12')
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_np_version_under1p13 = _nlv < LooseVersion('1.13')
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_np_version_under1p14 = _nlv < LooseVersion('1.14')
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_np_version_under1p15 = _nlv < LooseVersion('1.15')
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if _nlv < '1.9':
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raise ImportError('this version of pandas is incompatible with '
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'numpy < 1.9.0\n'
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'your numpy version is {0}.\n'
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'Please upgrade numpy to >= 1.9.0 to use '
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'this pandas version'.format(_np_version))
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_tz_regex = re.compile('[+-]0000$')
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def tz_replacer(s):
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if isinstance(s, string_types):
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if s.endswith('Z'):
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s = s[:-1]
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elif _tz_regex.search(s):
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s = s[:-5]
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return s
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def np_datetime64_compat(s, *args, **kwargs):
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"""
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provide compat for construction of strings to numpy datetime64's with
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tz-changes in 1.11 that make '2015-01-01 09:00:00Z' show a deprecation
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warning, when need to pass '2015-01-01 09:00:00'
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"""
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if not _np_version_under1p11:
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s = tz_replacer(s)
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return np.datetime64(s, *args, **kwargs)
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def np_array_datetime64_compat(arr, *args, **kwargs):
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"""
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provide compat for construction of an array of strings to a
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np.array(..., dtype=np.datetime64(..))
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tz-changes in 1.11 that make '2015-01-01 09:00:00Z' show a deprecation
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warning, when need to pass '2015-01-01 09:00:00'
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"""
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if not _np_version_under1p11:
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# is_list_like
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if hasattr(arr, '__iter__') and not \
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isinstance(arr, string_and_binary_types):
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arr = [tz_replacer(s) for s in arr]
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else:
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arr = tz_replacer(arr)
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return np.array(arr, *args, **kwargs)
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__all__ = ['np',
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'_np_version_under1p10',
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'_np_version_under1p11',
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'_np_version_under1p12',
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'_np_version_under1p13',
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'_np_version_under1p14',
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'_np_version_under1p15'
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]
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