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# Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements. See the NOTICE file
# distributed with this work for additional information
# regarding copyright ownership. The ASF licenses this file
# to you under the Apache License, Version 2.0 (the
# "License"); you may not use this file except in compliance
# with the License. You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing,
# software distributed under the License is distributed on an
# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
# KIND, either express or implied. See the License for the
# specific language governing permissions and limitations
# under the License.
# pandas lazy-loading API shim that reduces API call and import overhead
import warnings
cdef class _PandasAPIShim(object):
"""
Lazy pandas importer that isolates usages of pandas APIs and avoids
importing pandas until it's actually needed
"""
cdef:
bint _tried_importing_pandas
bint _have_pandas
cdef readonly:
object _loose_version, _version
object _pd, _types_api, _compat_module
object _data_frame, _index, _series, _categorical_type
object _datetimetz_type, _extension_array, _extension_dtype
object _array_like_types, _is_extension_array_dtype
bint has_sparse
bint _pd024
def __init__(self):
self._tried_importing_pandas = False
self._have_pandas = 0
cdef _import_pandas(self, bint raise_):
try:
import pandas as pd
import pyarrow.pandas_compat as pdcompat
except ImportError:
self._have_pandas = False
if raise_:
raise
else:
return
from pyarrow.vendored.version import Version
self._pd = pd
self._version = pd.__version__
self._loose_version = Version(pd.__version__)
if self._loose_version < Version('0.23.0'):
self._have_pandas = False
if raise_:
raise ImportError(
"pyarrow requires pandas 0.23.0 or above, pandas {} is "
"installed".format(self._version)
)
else:
warnings.warn(
"pyarrow requires pandas 0.23.0 or above, pandas {} is "
"installed. Therefore, pandas-specific integration is not "
"used.".format(self._version), stacklevel=2)
return
self._compat_module = pdcompat
self._data_frame = pd.DataFrame
self._index = pd.Index
self._categorical_type = pd.Categorical
self._series = pd.Series
self._extension_array = pd.api.extensions.ExtensionArray
self._array_like_types = (
self._series, self._index, self._categorical_type,
self._extension_array)
self._extension_dtype = pd.api.extensions.ExtensionDtype
if self._loose_version >= Version('0.24.0'):
self._is_extension_array_dtype = \
pd.api.types.is_extension_array_dtype
else:
self._is_extension_array_dtype = None
self._types_api = pd.api.types
self._datetimetz_type = pd.api.types.DatetimeTZDtype
self._have_pandas = True
if self._loose_version > Version('0.25'):
self.has_sparse = False
else:
self.has_sparse = True
self._pd024 = self._loose_version >= Version('0.24')
cdef inline _check_import(self, bint raise_=True):
if self._tried_importing_pandas:
if not self._have_pandas and raise_:
self._import_pandas(raise_)
return
self._tried_importing_pandas = True
self._import_pandas(raise_)
def series(self, *args, **kwargs):
self._check_import()
return self._series(*args, **kwargs)
def data_frame(self, *args, **kwargs):
self._check_import()
return self._data_frame(*args, **kwargs)
cdef inline bint _have_pandas_internal(self):
if not self._tried_importing_pandas:
self._check_import(raise_=False)
return self._have_pandas
@property
def have_pandas(self):
return self._have_pandas_internal()
@property
def compat(self):
self._check_import()
return self._compat_module
@property
def pd(self):
self._check_import()
return self._pd
cpdef infer_dtype(self, obj):
self._check_import()
try:
return self._types_api.infer_dtype(obj, skipna=False)
except AttributeError:
return self._pd.lib.infer_dtype(obj)
cpdef pandas_dtype(self, dtype):
self._check_import()
try:
return self._types_api.pandas_dtype(dtype)
except AttributeError:
return None
@property
def loose_version(self):
self._check_import()
return self._loose_version
@property
def version(self):
self._check_import()
return self._version
@property
def categorical_type(self):
self._check_import()
return self._categorical_type
@property
def datetimetz_type(self):
self._check_import()
return self._datetimetz_type
@property
def extension_dtype(self):
self._check_import()
return self._extension_dtype
cpdef is_array_like(self, obj):
self._check_import()
return isinstance(obj, self._array_like_types)
cpdef is_categorical(self, obj):
if self._have_pandas_internal():
return isinstance(obj, self._categorical_type)
else:
return False
cpdef is_datetimetz(self, obj):
if self._have_pandas_internal():
return isinstance(obj, self._datetimetz_type)
else:
return False
cpdef is_extension_array_dtype(self, obj):
self._check_import()
if self._is_extension_array_dtype:
return self._is_extension_array_dtype(obj)
else:
return False
cpdef is_sparse(self, obj):
if self._have_pandas_internal():
return self._types_api.is_sparse(obj)
else:
return False
cpdef is_data_frame(self, obj):
if self._have_pandas_internal():
return isinstance(obj, self._data_frame)
else:
return False
cpdef is_series(self, obj):
if self._have_pandas_internal():
return isinstance(obj, self._series)
else:
return False
cpdef is_index(self, obj):
if self._have_pandas_internal():
return isinstance(obj, self._index)
else:
return False
cpdef get_values(self, obj):
"""
Get the underlying array values of a pandas Series or Index in the
format (np.ndarray or pandas ExtensionArray) as we need them.
Assumes obj is a pandas Series or Index.
"""
self._check_import()
if isinstance(obj.dtype, (self.pd.api.types.IntervalDtype,
self.pd.api.types.PeriodDtype)):
if self._pd024:
# only since pandas 0.24, interval and period are stored as
# such in Series
return obj.array
return obj.values
def assert_frame_equal(self, *args, **kwargs):
self._check_import()
return self._pd.util.testing.assert_frame_equal
def get_rangeindex_attribute(self, level, name):
# public start/stop/step attributes added in pandas 0.25.0
self._check_import()
if hasattr(level, name):
return getattr(level, name)
return getattr(level, '_' + name)
cdef _PandasAPIShim pandas_api = _PandasAPIShim()
_pandas_api = pandas_api
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