""" support numpy compatiblitiy across versions """
import re
import numpy as np
from distutils.version import LooseVersion
from pandas.compat import string_types, string_and_binary_types
# numpy versioning
_np_version = np.__version__
_nlv = LooseVersion(_np_version)
_np_version_under1p13 = _nlv < LooseVersion('1.13')
_np_version_under1p14 = _nlv < LooseVersion('1.14')
_np_version_under1p15 = _nlv < LooseVersion('1.15')
_np_version_under1p16 = _nlv < LooseVersion('1.16')
_np_version_under1p17 = _nlv < LooseVersion('1.17')
if _nlv < '1.12':
raise ImportError('this version of pandas is incompatible with '
'numpy < 1.12.0\n'
'your numpy version is {0}.\n'
'Please upgrade numpy to >= 1.12.0 to use '
'this pandas version'.format(_np_version))
_tz_regex = re.compile('[+-]0000$')
def tz_replacer(s):
if isinstance(s, string_types):
if s.endswith('Z'):
s = s[:-1]
elif _tz_regex.search(s):
s = s[:-5]
return s
def np_datetime64_compat(s, *args, **kwargs):
"""
provide compat for construction of strings to numpy datetime64's with
tz-changes in 1.11 that make '2015-01-01 09:00:00Z' show a deprecation
warning, when need to pass '2015-01-01 09:00:00'
"""
s = tz_replacer(s)
return np.datetime64(s, *args, **kwargs)
def np_array_datetime64_compat(arr, *args, **kwargs):
"""
provide compat for construction of an array of strings to a
np.array(..., dtype=np.datetime64(..))
tz-changes in 1.11 that make '2015-01-01 09:00:00Z' show a deprecation
warning, when need to pass '2015-01-01 09:00:00'
"""
# is_list_like
if (hasattr(arr, '__iter__')
and not isinstance(arr, string_and_binary_types)):
arr = [tz_replacer(s) for s in arr]
else:
arr = tz_replacer(arr)
return np.array(arr, *args, **kwargs)
__all__ = ['np',
'_np_version_under1p13',
'_np_version_under1p14',
'_np_version_under1p15',
'_np_version_under1p16',
'_np_version_under1p17'
]