Coverage for pyspark/pandas/__init__.py : 20%

# 

# 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. 

# 

""" 

.. versionadded:: 3.2.0 

pandas API on Spark 

""" 

import os 

import sys 

from distutils.version import LooseVersion 

import warnings 

from pyspark.sql.pandas.utils import require_minimum_pandas_version, require_minimum_pyarrow_version 

try: 

require_minimum_pandas_version() 

require_minimum_pyarrow_version() 

except ImportError as e: 

34 ↛ 38line 34 didn't jump to line 38, because the condition on line 34 was never false if os.environ.get("SPARK_TESTING"): 

warnings.warn(str(e)) 

sys.exit() 

else: 

raise 

import pyarrow 

if ( 

LooseVersion(pyarrow.__version__) >= LooseVersion("2.0.0") 

and "PYARROW_IGNORE_TIMEZONE" not in os.environ 

): 

import logging 

logging.warning( 

"'PYARROW_IGNORE_TIMEZONE' environment variable was not set. It is required to " 

"set this environment variable to '1' in both driver and executor sides if you use " 

"pyarrow>=2.0.0. " 

"pandas-on-Spark will set it for you but it does not work if there is a Spark context " 

"already launched." 

) 

os.environ["PYARROW_IGNORE_TIMEZONE"] = "1" 

from pyspark.pandas.frame import DataFrame 

from pyspark.pandas.indexes.base import Index 

from pyspark.pandas.indexes.category import CategoricalIndex 

from pyspark.pandas.indexes.datetimes import DatetimeIndex 

from pyspark.pandas.indexes.multi import MultiIndex 

from pyspark.pandas.indexes.numeric import Float64Index, Int64Index 

from pyspark.pandas.series import Series 

from pyspark.pandas.groupby import NamedAgg 

__all__ = [ # noqa: F405 

"read_csv", 

"read_parquet", 

"to_datetime", 

"date_range", 

"from_pandas", 

"get_dummies", 

"DataFrame", 

"Series", 

"Index", 

"MultiIndex", 

"Int64Index", 

"Float64Index", 

"CategoricalIndex", 

"DatetimeIndex", 

"sql", 

"range", 

"concat", 

"melt", 

"get_option", 

"set_option", 

"reset_option", 

"read_sql_table", 

"read_sql_query", 

"read_sql", 

"options", 

"option_context", 

"NamedAgg", 

] 

def _auto_patch_spark() -> None: 

import os 

import logging 

# Attach a usage logger. 

logger_module = os.getenv("KOALAS_USAGE_LOGGER", "") 

if logger_module != "": 

try: 

from pyspark.pandas import usage_logging 

usage_logging.attach(logger_module) 

except Exception as e: 

logger = logging.getLogger("pyspark.pandas.usage_logger") 

logger.warning( 

"Tried to attach usage logger `{}`, but an exception was raised: {}".format( 

logger_module, str(e) 

) 

) 

_frame_has_class_getitem = False 

_series_has_class_getitem = False 

def _auto_patch_pandas() -> None: 

import pandas as pd 

# In order to use it in test cases. 

global _frame_has_class_getitem 

global _series_has_class_getitem 

_frame_has_class_getitem = hasattr(pd.DataFrame, "__class_getitem__") 

_series_has_class_getitem = hasattr(pd.Series, "__class_getitem__") 

if sys.version_info >= (3, 7): 

# Just in case pandas implements '__class_getitem__' later. 

if not _frame_has_class_getitem: 

pd.DataFrame.__class_getitem__ = lambda params: DataFrame.__class_getitem__(params) 

if not _series_has_class_getitem: 

pd.Series.__class_getitem__ = lambda params: Series.__class_getitem__(params) 

_auto_patch_spark() 

_auto_patch_pandas() 

# Import after the usage logger is attached. 

from pyspark.pandas.config import get_option, options, option_context, reset_option, set_option 

from pyspark.pandas.namespace import * # F405 

from pyspark.pandas.sql_processor import sql