| # |
| # 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: |
| 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 |