update cache dataframe config args, fix tests (#1437)

This PR renames the pandera config arguments introduced in this PR:
#1414 and makes the names
more generic. Fixes tests that were broken by the config changes.

Signed-off-by: Niels Bantilan <[email protected]>

Author: cosmicBboy

pandera/backends/pyspark/decorators.py

@@ -156,7 +156,7 @@ def _wrapper(func):
         @functools.wraps(func)
         def wrapper(self, *args, **kwargs):
             # Skip if not enabled
-            if CONFIG.pyspark_cache is not True:
+            if CONFIG.cache_dataframe is not True:
                 return func(self, *args, **kwargs)
 
             check_obj: DataFrame = None
@@ -186,7 +186,7 @@ def cached_check_obj():
 
                 yield  # Execute the decorated function
 
-                if not CONFIG.pyspark_keep_cache:
+                if not CONFIG.keep_cached_dataframe:
                     # If not cached, `.unpersist()` does nothing
                     logger.debug("Unpersisting dataframe...")
                     check_obj.unpersist()

pandera/config.py

@@ -26,8 +26,8 @@ class PanderaConfig(BaseModel):
 
     validation_enabled: bool = True
     validation_depth: ValidationDepth = ValidationDepth.SCHEMA_AND_DATA
-    pyspark_cache: bool = False
-    pyspark_keep_cache: bool = False
+    cache_dataframe: bool = False
+    keep_cached_dataframe: bool = False
 
 
 # this config variable should be accessible globally
@@ -39,11 +39,11 @@ class PanderaConfig(BaseModel):
     validation_depth=os.environ.get(
         "PANDERA_VALIDATION_DEPTH", ValidationDepth.SCHEMA_AND_DATA
     ),
-    pyspark_cache=os.environ.get(
+    cache_dataframe=os.environ.get(
         "PANDERA_CACHE_DATAFRAME",
         False,
     ),
-    pyspark_keep_cache=os.environ.get(
+    keep_cached_dataframe=os.environ.get(
         "PANDERA_KEEP_CACHED_DATAFRAME",
         False,
     ),

tests/core/test_pandas_config.py

@@ -44,6 +44,8 @@ class TestSchema(DataFrameModel):
             price_val: int = pa.Field()
 
         expected = {
+            "cache_dataframe": False,
+            "keep_cached_dataframe": False,
             "validation_enabled": False,
             "validation_depth": ValidationDepth.SCHEMA_AND_DATA,
         }
@@ -61,6 +63,8 @@ class TestPandasSeriesConfig:
     def test_disable_validation(self, disable_validation):
         """This function validates that a none object is loaded if validation is disabled"""
         expected = {
+            "cache_dataframe": False,
+            "keep_cached_dataframe": False,
             "validation_enabled": False,
             "validation_depth": ValidationDepth.SCHEMA_AND_DATA,
         }

tests/pyspark/test_pyspark_config.py

@@ -42,8 +42,8 @@ class TestSchema(DataFrameModel):
         expected = {
             "validation_enabled": False,
             "validation_depth": ValidationDepth.SCHEMA_AND_DATA,
-            "pyspark_cache": False,
-            "pyspark_keep_cache": False,
+            "cache_dataframe": False,
+            "keep_cached_dataframe": False,
         }
 
         assert CONFIG.dict() == expected
@@ -66,8 +66,8 @@ def test_schema_only(self, spark, sample_spark_schema):
         expected = {
             "validation_enabled": True,
             "validation_depth": ValidationDepth.SCHEMA_ONLY,
-            "pyspark_cache": False,
-            "pyspark_keep_cache": False,
+            "cache_dataframe": False,
+            "keep_cached_dataframe": False,
         }
         assert CONFIG.dict() == expected
 
@@ -146,8 +146,8 @@ def test_data_only(self, spark, sample_spark_schema):
         expected = {
             "validation_enabled": True,
             "validation_depth": ValidationDepth.DATA_ONLY,
-            "pyspark_cache": False,
-            "pyspark_keep_cache": False,
+            "cache_dataframe": False,
+            "keep_cached_dataframe": False,
         }
         assert CONFIG.dict() == expected
 
@@ -233,8 +233,8 @@ def test_schema_and_data(self, spark, sample_spark_schema):
         expected = {
             "validation_enabled": True,
             "validation_depth": ValidationDepth.SCHEMA_AND_DATA,
-            "pyspark_cache": False,
-            "pyspark_keep_cache": False,
+            "cache_dataframe": False,
+            "keep_cached_dataframe": False,
         }
         assert CONFIG.dict() == expected
 
@@ -339,21 +339,21 @@ class TestSchema(DataFrameModel):
     @pytest.mark.parametrize("cache_enabled", [True, False])
     @pytest.mark.parametrize("keep_cache_enabled", [True, False])
     # pylint:disable=too-many-locals
-    def test_pyspark_cache_settings(
+    def test_cache_dataframe_settings(
         self,
         cache_enabled,
         keep_cache_enabled,
     ):
         """This function validates setters and getters for cache/keep_cache options."""
         # Set expected properties in Config object
-        CONFIG.pyspark_cache = cache_enabled
-        CONFIG.pyspark_keep_cache = keep_cache_enabled
+        CONFIG.cache_dataframe = cache_enabled
+        CONFIG.keep_cached_dataframe = keep_cache_enabled
 
         # Evaluate expected Config
         expected = {
             "validation_enabled": True,
             "validation_depth": ValidationDepth.SCHEMA_AND_DATA,
-            "pyspark_cache": cache_enabled,
-            "pyspark_keep_cache": keep_cache_enabled,
+            "cache_dataframe": cache_enabled,
+            "keep_cached_dataframe": keep_cache_enabled,
         }
         assert CONFIG.dict() == expected

tests/pyspark/test_pyspark_decorators.py

@@ -22,10 +22,10 @@ class TestPanderaDecorators:
 
     sample_data = [("Bread", 9), ("Cutter", 15)]
 
-    def test_pyspark_cache_requirements(self, spark, sample_spark_schema):
+    def test_cache_dataframe_requirements(self, spark, sample_spark_schema):
         """Validates if decorator can only be applied in a proper function."""
         # Set expected properties in Config object
-        CONFIG.pyspark_cache = True
+        CONFIG.cache_dataframe = True
         input_df = spark_df(spark, self.sample_data, sample_spark_schema)
 
         class FakeDataFrameSchemaBackend:
@@ -74,7 +74,7 @@ def func_wo_check_obj(self, message: str):
     )
 
     # pylint:disable=too-many-locals
-    def test_pyspark_cache_settings(
+    def test_cache_dataframe_settings(
         self,
         spark,
         sample_spark_schema,
@@ -86,8 +86,8 @@ def test_pyspark_cache_settings(
     ):
         """This function validates that caching/unpersisting works as expected."""
         # Set expected properties in Config object
-        CONFIG.pyspark_cache = cache_enabled
-        CONFIG.pyspark_keep_cache = keep_cache_enabled
+        CONFIG.cache_dataframe = cache_enabled
+        CONFIG.keep_cached_dataframe = keep_cache_enabled
 
         # Prepare test data
         input_df = spark_df(spark, self.sample_data, sample_spark_schema)