diff --git a/Makefile b/makefile similarity index 96% rename from Makefile rename to makefile index a060e434..314c0095 100644 --- a/Makefile +++ b/makefile @@ -25,8 +25,9 @@ kafka-cluster-stop: rm -rf /tmp/kafka-logs endif -cov: check kafka-cluster-start - @poetry run coverage run --source=spark_expectations --omit "spark_expectations/examples/*" -m pytest && \ +cov: kafka-cluster-start + -make check + @poetry run coverage run --source=spark_expectations --omit "spark_expectations/examples/*" -m pytest -v -x && \ poetry run coverage report -m && \ poetry run coverage xml diff --git a/poetry.lock b/poetry.lock index 60073fcd..ee0ec347 100644 --- a/poetry.lock +++ b/poetry.lock @@ -1,4 +1,4 @@ -# This file is automatically @generated by Poetry 1.8.3 and should not be changed by hand. +# This file is automatically @generated by Poetry 1.8.2 and should not be changed by hand. 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+content-hash = "6c723446cb578fdd5512768c7ef139a72c5048ad89af321a0345e2a372e34111" diff --git a/pyproject.toml b/pyproject.toml index 638ebe84..0fca7d3a 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -7,39 +7,35 @@ readme = "README.md" packages = [{ include = "spark_expectations" }] [tool.poetry.dependencies] -python = "^3.9,<3.12" +python = "^3.9,<3.13" pluggy = ">=1" -pyspark = "^3.0.0" -requests = "^2.28.1" +pyspark = ">=3.0.0,<4.0.0" +requests = ">=2.28.1" [tool.poetry.group.dev.dependencies] black = "23.3.0" -pytest = "7.3.1" -pytest-mock = "3.10.0" +botocore = "1.29.133" # This is just for fixing the dependency resolution version on cerberus-python-client +cerberus-python-client = "2.5.4" coverage = "7.2.5" -pyspark = "^3.0.0" -pandas = "1.5.3" -numpy = "1.26.4" -pyarrow = "7.0.0" -grpcio = "1.48.1" -google = "3.0.0" -protobuf = "4.21.12" -mypy = "1.3.0" +ipykernel = "^6.29.2" +mdx-include = ">=1.4.1,<2.0.0" +mike = "1.1.2" mkdocs = "1.4.3" -prospector = "1.10.0" 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a/spark_expectations/core/expectations.py +++ b/spark_expectations/core/expectations.py @@ -1,15 +1,13 @@ import functools +import importlib from dataclasses import dataclass from typing import Dict, Optional, Any, Union -import packaging.version as package_version -from pyspark import version as spark_version + +from pyspark.version import __version__ as spark_version from pyspark import StorageLevel -from pyspark.sql import DataFrame, SparkSession +from pyspark import sql + -try: - from pyspark.sql.connect.dataframe import DataFrame as connectDataFrame -except ImportError: - pass from spark_expectations import _log from spark_expectations.config.user_config import Constants as user_config from spark_expectations.core.context import SparkExpectationsContext @@ -29,12 +27,52 @@ from spark_expectations.utils.regulate_flow import SparkExpectationsRegulateFlow -min_spark_version_for_connect = "3.4.0" -installed_spark_version = spark_version.__version__ -is_spark_connect_supported = bool( - package_version.parse(installed_spark_version) - >= package_version.parse(min_spark_version_for_connect) -) +def get_spark_minor_version() -> float: + """Returns the minor version of the spark instance. + + For example, if the spark version is 3.3.2, this function would return 3.3 + """ + return float(".".join(spark_version.split(".")[:2])) + + +MIN_SPARK_VERSION_FOR_CONNECT: float = 3.4 +SPARK_MINOR_VERSION: float = get_spark_minor_version() + + +def check_if_pyspark_connect_is_supported() -> bool: + """Check if the current version of PySpark supports the connect module""" + result = False + module_name: str = "pyspark" + if SPARK_MINOR_VERSION >= MIN_SPARK_VERSION_FOR_CONNECT: + try: + importlib.import_module(f"{module_name}.sql.connect") + from pyspark.sql.connect.column import Column + + _col: Column + result = True + except (ModuleNotFoundError, ImportError): + result = False + return result + + +# pylint: disable=ungrouped-imports +if check_if_pyspark_connect_is_supported(): + # Import the connect module if the current version of PySpark supports it + from pyspark.sql.connect.dataframe import DataFrame as ConnectDataFrame + from pyspark.sql.connect.session import SparkSession as ConnectSparkSession + + DataFrame = Union[sql.DataFrame, ConnectDataFrame] # type: ignore + SparkSession = Union[sql.SparkSession, ConnectSparkSession] # type: ignore +else: + # Otherwise, use the default PySpark classes + from pyspark.sql.dataframe import DataFrame # type: ignore + from pyspark.sql.session import SparkSession # type: ignore + + +__all__ = [ + "SparkExpectations", + "WrappedDataFrameWriter", +] @dataclass @@ -58,19 +96,28 @@ class SparkExpectations: stats_table_writer: "WrappedDataFrameWriter" debugger: bool = False stats_streaming_options: Optional[Dict[str, Union[str, bool]]] = None + spark: Optional[SparkSession] = None def __post_init__(self) -> None: - # Databricks runtime 14 and above could pass either instance of a Dataframe depending on how data was read - if ( - is_spark_connect_supported is True - and isinstance(self.rules_df, (DataFrame, connectDataFrame)) - ) or ( - is_spark_connect_supported is False and isinstance(self.rules_df, DataFrame) - ): + if isinstance(self.rules_df, DataFrame): # type: ignore try: - self.spark: Optional[SparkSession] = self.rules_df.sparkSession + self.spark = self.rules_df.sparkSession except AttributeError: - self.spark = SparkSession.getActiveSession() + # we need to ensure to use the correct SparkSession type based + # on if pyspark[connect] is supported or not + if check_if_pyspark_connect_is_supported(): + from pyspark.sql.connect.session import ( + SparkSession as _ConnectSparkSession, + ) + + session = ( + _ConnectSparkSession.getActiveSession() + or sql.SparkSession.getActiveSession() + ) # type: ignore + else: + session = sql.SparkSession.getActiveSession() # type: ignore + + self.spark = session if self.spark is None: raise SparkExpectationsMiscException( @@ -376,13 +423,7 @@ def wrapper(*args: tuple, **kwargs: dict) -> DataFrame: self._context.get_run_id, ) - if ( - is_spark_connect_supported is True - and isinstance(_df, (DataFrame, connectDataFrame)) - ) or ( - is_spark_connect_supported is False - and isinstance(_df, DataFrame) - ): + if isinstance(_df, DataFrame): # type: ignore _log.info("The function dataframe is created") self._context.set_table_name(table_name) if write_to_temp_table: diff --git a/tests/core/test_expectations.py b/tests/core/test_expectations.py index 52e4fb57..e7264d68 100644 --- a/tests/core/test_expectations.py +++ b/tests/core/test_expectations.py @@ -1,7 +1,7 @@ # pylint: disable=too-many-lines import os import datetime -from unittest.mock import Mock, PropertyMock +from unittest.mock import MagicMock, Mock, PropertyMock from unittest.mock import patch import pytest from pyspark.sql import DataFrame, SparkSession @@ -19,6 +19,8 @@ from spark_expectations.core.expectations import ( SparkExpectations, WrappedDataFrameWriter, + check_if_pyspark_connect_is_supported, + get_spark_minor_version, ) from spark_expectations.config.user_config import Constants as user_config from spark_expectations.core import get_spark_session @@ -37,7 +39,7 @@ def fixture_setup_local_kafka_topic(): os.getenv("UNIT_TESTING_ENV") != "spark_expectations_unit_testing_on_github_actions" ): - # remove if docker conatiner is running + # remove if docker container is running os.system( f"sh {current_dir}/../../spark_expectations/examples/docker_scripts/docker_kafka_stop_script.sh" ) @@ -3404,3 +3406,32 @@ def test_delta_bucketby_exception(): match=r"Bucketing is not supported for delta tables yet", ): writer.build() + + +class TestCheckIfPysparkConnectIsSupported: + def test_if_pyspark_connect_is_not_supported(self): + """Test that check_if_pyspark_connect_is_supported returns False when + pyspark connect is not supported.""" + with patch.dict("sys.modules", {"pyspark.sql.connect": None}): + assert check_if_pyspark_connect_is_supported() is False + + def test_check_if_pyspark_connect_is_supported(self): + """Test that check_if_pyspark_connect_is_supported returns True when + pyspark connect is supported.""" + with ( + patch("spark_expectations.core.expectations.SPARK_MINOR_VERSION", 3.5), + patch.dict( + "sys.modules", + { + "pyspark.sql.connect.column": MagicMock(Column=MagicMock()), + "pyspark.sql.connect": MagicMock(), + }, + ), + ): + assert check_if_pyspark_connect_is_supported() is True + + +def test_get_spark_minor_version(): + """Test that get_spark_minor_version returns the correctly formatted version.""" + with patch("spark_expectations.core.expectations.spark_version", "9.9.42"): + assert get_spark_minor_version() == 9.9