[MAINTENANCE] Have Expectation inherit from pydantic.BaseModel (#…

…8965)

great_expectations/core/expectation_configuration.py

@@ -1477,7 +1477,7 @@ def validate(
         """
         expectation_impl: Type[Expectation] = self._get_expectation_impl()
         # noinspection PyCallingNonCallable
-        return expectation_impl(self).validate(
+        return expectation_impl(meta=self.meta, **self.kwargs).validate_(
             validator=validator,
             runtime_configuration=runtime_configuration,
         )
@@ -1491,7 +1491,7 @@ def metrics_validate(
     ):
         expectation_impl: Type[Expectation] = self._get_expectation_impl()
         # noinspection PyCallingNonCallable
-        return expectation_impl(self).metrics_validate(
+        return expectation_impl(meta=self.meta, **self.kwargs).metrics_validate(
             metrics=metrics,
             runtime_configuration=runtime_configuration,
             execution_engine=execution_engine,

great_expectations/core/expectation_suite.py

@@ -754,7 +754,9 @@ def _validate_expectation_configuration_before_adding(
     ):
         try:
             class_ = get_expectation_impl(expectation_configuration.expectation_type)
-            _ = class_(expectation_configuration)  # Implicitly validates in constructor
+            _ = class_(
+                meta=expectation_configuration.meta, **expectation_configuration.kwargs
+            )  # Implicitly validates in constructor
         except (
             gx_exceptions.ExpectationNotFoundError,
             gx_exceptions.InvalidExpectationConfigurationError,

great_expectations/expectations/core/expect_column_quantile_values_to_be_between.py

@@ -1,5 +1,5 @@
 from numbers import Number
-from typing import TYPE_CHECKING, Dict, List, Optional, Union
+from typing import TYPE_CHECKING, ClassVar, Dict, List, Optional, Union
 
 import numpy as np
 
@@ -182,7 +182,9 @@ class ExpectColumnQuantileValuesToBeBetween(ColumnAggregateExpectation):
     validation_parameter_builder_configs: List[ParameterBuilderConfig] = [
         quantile_value_ranges_estimator_parameter_builder_config,
     ]
-    default_profiler_config = RuleBasedProfilerConfig(
+    default_profiler_config: ClassVar[
+        RuleBasedProfilerConfig
+    ] = RuleBasedProfilerConfig(
         name="expect_column_quantile_values_to_be_between",  # Convention: use "expectation_type" as profiler name.
         config_version=1.0,
         variables={},

great_expectations/expectations/core/expect_column_values_to_be_between.py

@@ -1,4 +1,4 @@
-from typing import TYPE_CHECKING, List, Optional
+from typing import TYPE_CHECKING, ClassVar, List, Optional
 
 import great_expectations.exceptions as gx_exceptions
 from great_expectations.core import (
@@ -160,7 +160,9 @@ class ExpectColumnValuesToBeBetween(ColumnMapExpectation):
         column_min_range_estimator_parameter_builder_config,
         column_max_range_estimator_parameter_builder_config,
     ]
-    default_profiler_config = RuleBasedProfilerConfig(
+    default_profiler_config: ClassVar[
+        RuleBasedProfilerConfig
+    ] = RuleBasedProfilerConfig(
         name="expect_column_values_to_be_between",  # Convention: use "expectation_type" as profiler name.
         config_version=1.0,
         variables={},

great_expectations/expectations/core/expect_column_values_to_not_be_null.py

@@ -1,6 +1,6 @@
 from __future__ import annotations
 
-from typing import TYPE_CHECKING, ClassVar, Dict, Optional
+from typing import TYPE_CHECKING, ClassVar, Dict, Optional, Tuple
 
 from great_expectations.compatibility.typing_extensions import override
 from great_expectations.core.expectation_configuration import parse_result_format
@@ -90,7 +90,7 @@ class ExpectColumnValuesToNotBeNull(ColumnMapExpectation):
     }
 
     map_metric: ClassVar[str] = "column_values.nonnull"
-    args_keys: ClassVar[tuple[str, ...]] = ("column",)
+    args_keys: ClassVar[Tuple[str, ...]] = ("column",)
 
     @override
     def validate_configuration(

great_expectations/expectations/expectation.py

@@ -10,7 +10,7 @@
 import time
 import traceback
 import warnings
-from abc import ABC, ABCMeta, abstractmethod
+from abc import ABC, abstractmethod
 from collections import Counter, defaultdict
 from copy import deepcopy
 from inspect import isabstract
@@ -37,6 +37,8 @@
 from typing_extensions import ParamSpec
 
 from great_expectations import __version__ as ge_version
+from great_expectations.compatibility import pydantic
+from great_expectations.compatibility.pydantic import ModelMetaclass
 from great_expectations.compatibility.typing_extensions import override
 from great_expectations.core._docs_decorators import (
     deprecated_method_or_class,
@@ -265,7 +267,7 @@ def wrapper(
 
 
 # noinspection PyMethodParameters
-class MetaExpectation(ABCMeta):
+class MetaExpectation(ModelMetaclass):
     """MetaExpectation registers Expectations as they are defined, adding them to the Expectation registry.
 
     Any class inheriting from Expectation will be registered based on the value of the "expectation_type" class
@@ -297,7 +299,7 @@ def __new__(cls, clsname, bases, attrs):
 
 
 @public_api
-class Expectation(metaclass=MetaExpectation):
+class Expectation(pydantic.BaseModel, metaclass=MetaExpectation):
     """Base class for all Expectations.
 
     Expectation classes *must* have the following attributes set:
@@ -329,7 +331,13 @@ class Expectation(metaclass=MetaExpectation):
         2. Data Docs rendering methods decorated with the @renderer decorator. See the
     """
 
-    version: ClassVar = ge_version
+    class Config:
+        arbitrary_types_allowed = True
+        extra = pydantic.Extra.allow
+
+    meta: Union[dict, None] = None
+
+    version: ClassVar[str] = ge_version
     domain_keys: ClassVar[Tuple[str, ...]] = ()
     success_keys: ClassVar[Tuple[str, ...]] = ()
     runtime_keys: ClassVar[Tuple[str, ...]] = (
@@ -338,7 +346,7 @@ class Expectation(metaclass=MetaExpectation):
         "result_format",
     )
     default_kwarg_values: ClassVar[
-        dict[str, bool | str | float | RuleBasedProfilerConfig | None]
+        dict[str, Union[bool, str, float, RuleBasedProfilerConfig, None]]
     ] = {
         "include_config": True,
         "catch_exceptions": False,
@@ -349,10 +357,27 @@ class Expectation(metaclass=MetaExpectation):
     expectation_type: ClassVar[str]
     examples: ClassVar[List[dict]] = []
 
-    def __init__(self, configuration: ExpectationConfiguration) -> None:
-        self._configuration = configuration
+    def __init__(self, meta: dict | None = None, **kwargs) -> None:
+        # Safety precaution to prevent old-style instantiation
+        if "configuration" in kwargs:
+            raise ValueError(
+                "Cannot directly pass configuration into Expectation constructor; please pass in individual success keys and domain kwargs."
+            )
+
+        super().__init__(**kwargs)
+
+        # Everything below is purely to maintain current validation logic but should be migrated to Pydantic validators
+        configuration = ExpectationConfiguration(
+            expectation_type=camel_to_snake(self.__class__.__name__),
+            kwargs=kwargs,
+            meta=meta,
+        )
         self.validate_configuration(configuration)
 
+        # Currently only used in Validator.validate_expectation
+        # Once the V1 Validator is live, we can remove this and its related property
+        self._configuration = configuration
+
     @classmethod
     def is_abstract(cls) -> bool:
         return isabstract(cls)
@@ -1239,8 +1264,9 @@ def validate_configuration(
         except AssertionError as e:
             raise InvalidExpectationConfigurationError(str(e))
 
+    # Renamed from validate due to collision with Pydantic method of the same name
     @public_api
-    def validate(  # noqa: PLR0913
+    def validate_(  # noqa: PLR0913
         self,
         validator: Validator,
         configuration: Optional[ExpectationConfiguration] = None,
@@ -2344,7 +2370,7 @@ class BatchExpectation(Expectation, ABC):
         "condition_parser",
     )
     metric_dependencies: ClassVar[Tuple[str, ...]] = ()
-    domain_type: ClassVar = MetricDomainTypes.TABLE
+    domain_type: ClassVar[MetricDomainTypes] = MetricDomainTypes.TABLE
     args_keys: ClassVar[Tuple[str, ...]] = ()
 
     @override
@@ -2742,14 +2768,14 @@ class ColumnMapExpectation(BatchExpectation, ABC):
     """
 
     map_metric: ClassVar[Optional[str]] = None
-    domain_keys: ClassVar[tuple[str, ...]] = (
+    domain_keys: ClassVar[Tuple[str, ...]] = (
         "batch_id",
         "table",
         "column",
         "row_condition",
         "condition_parser",
     )
-    domain_type: ClassVar = MetricDomainTypes.COLUMN
+    domain_type: ClassVar[MetricDomainTypes] = MetricDomainTypes.COLUMN
     success_keys: ClassVar[Tuple[str, ...]] = ("mostly",)
     default_kwarg_values = {
         "row_condition": None,
@@ -3023,7 +3049,7 @@ class ColumnPairMapExpectation(BatchExpectation, ABC):
             kwargs from the Expectation Configuration.
     """
 
-    map_metric = None
+    map_metric: ClassVar[Optional[str]] = None
     domain_keys = (
         "batch_id",
         "table",
@@ -3295,7 +3321,7 @@ class MulticolumnMapExpectation(BatchExpectation, ABC):
             kwargs from the Expectation Configuration.
     """
 
-    map_metric = None
+    map_metric: ClassVar[Optional[str]] = None
     domain_keys = (
         "batch_id",
         "table",

great_expectations/expectations/registry.py

@@ -341,7 +341,9 @@ def get_metric_kwargs(
         }
         if configuration:
             expectation_impl = get_expectation_impl(configuration.expectation_type)
-            configuration_kwargs = expectation_impl(configuration).get_runtime_kwargs(
+            configuration_kwargs = expectation_impl(
+                **configuration.kwargs
+            ).get_runtime_kwargs(
                 configuration=configuration, runtime_configuration=runtime_configuration
             )
             if len(metric_kwargs["metric_domain_keys"]) > 0:

great_expectations/validator/validator.py

@@ -543,15 +543,17 @@ def inst_expectation(*args: dict, **kwargs):  # noqa: PLR0912
                 )
 
             try:
-                expectation = expectation_impl(configuration)
+                expectation = expectation_impl(
+                    meta=configuration.meta, **configuration.kwargs
+                )
                 """Given an implementation and a configuration for any Expectation, returns its validation result"""
 
                 if not self.interactive_evaluation and not self._active_validation:
                     validation_result = ExpectationValidationResult(
                         expectation_config=copy.deepcopy(expectation.configuration)
                     )
                 else:
-                    validation_result = expectation.validate(
+                    validation_result = expectation.validate_(
                         validator=self,
                         evaluation_parameters=self._expectation_suite.evaluation_parameters,
                         data_context=self._data_context,
@@ -1124,7 +1126,7 @@ def _generate_metric_dependency_subgraphs_for_each_expectation_configuration(
 
             expectation_impl = get_expectation_impl(evaluated_config.expectation_type)
             validation_dependencies: ValidationDependencies = expectation_impl(
-                evaluated_config
+                **evaluated_config.kwargs
             ).get_validation_dependencies(
                 configuration=evaluated_config,
                 execution_engine=self._execution_engine,

tests/expectations/metrics/test_map_metric.py

@@ -140,7 +140,7 @@ def _expecation_configuration_to_validation_result_pandas(
         expectation_configuration (ExpectationConfiguration): configuration that is being tested
 
     """
-    expectation = ExpectColumnValuesToBeInSet(expectation_configuration)
+    expectation = ExpectColumnValuesToBeInSet(**expectation_configuration.kwargs)
     batch_definition = BatchDefinition(
         datasource_name="pandas_datasource",
         data_connector_name="runtime_data_connector",
@@ -160,7 +160,7 @@ def _expecation_configuration_to_validation_result_pandas(
             batch,
         ],
     )
-    result = expectation.validate(validator)
+    result = expectation.validate_(validator)
     return result
 
 
@@ -176,7 +176,7 @@ def _expecation_configuration_to_validation_result_sql(
         expectation_configuration (ExpectationConfiguration): configuration that is being tested
 
     """
-    expectation = ExpectColumnValuesToBeInSet(expectation_configuration)
+    expectation = ExpectColumnValuesToBeInSet(**expectation_configuration.kwargs)
     sqlite_path = file_relative_path(__file__, "../../test_sets/metrics_test.db")
     connection_string = f"sqlite:///{sqlite_path}"
     engine = SqlAlchemyExecutionEngine(
@@ -236,7 +236,7 @@ def _expecation_configuration_to_validation_result_sql(
             batch,
         ],
     )
-    result = expectation.validate(validator)
+    result = expectation.validate_(validator)
     return result
 
 
@@ -774,7 +774,7 @@ def test_include_unexpected_rows_without_explicit_result_format_raises_error(
         },
     )
 
-    expectation = ExpectColumnValuesToBeInSet(expectation_configuration)
+    expectation = ExpectColumnValuesToBeInSet(**expectation_configuration.kwargs)
     batch_definition = BatchDefinition(
         datasource_name="pandas_datasource",
         data_connector_name="runtime_data_connector",
@@ -795,7 +795,7 @@ def test_include_unexpected_rows_without_explicit_result_format_raises_error(
         ],
     )
     with pytest.raises(ValueError):
-        expectation.validate(validator)
+        expectation.validate_(validator)
 
 
 # Spark
@@ -814,7 +814,7 @@ def test_spark_single_column_complete_result_format(
             },
         },
     )
-    expectation = ExpectColumnValuesToBeInSet(expectation_configuration)
+    expectation = ExpectColumnValuesToBeInSet(**expectation_configuration.kwargs)
     batch_definition = BatchDefinition(
         datasource_name="spark_datasource",
         data_connector_name="runtime_data_connector",
@@ -834,7 +834,7 @@ def test_spark_single_column_complete_result_format(
             batch,
         ],
     )
-    result = expectation.validate(validator)
+    result = expectation.validate_(validator)
     assert convert_to_json_serializable(result.result) == {
         "element_count": 6,
         "missing_count": 0,
@@ -871,7 +871,7 @@ def test_spark_single_column_complete_result_format_with_id_pk(
             },
         },
     )
-    expectation = ExpectColumnValuesToBeInSet(expectation_configuration)
+    expectation = ExpectColumnValuesToBeInSet(**expectation_configuration.kwargs)
     batch_definition = BatchDefinition(
         datasource_name="spark_datasource",
         data_connector_name="runtime_data_connector",
@@ -894,7 +894,7 @@ def test_spark_single_column_complete_result_format_with_id_pk(
 
     # result_format configuration at ExpectationConfiguration-level will emit warning
     with pytest.warns(UserWarning):
-        result = expectation.validate(validator)
+        result = expectation.validate_(validator)
 
     assert convert_to_json_serializable(result.result) == {
         "element_count": 6,
@@ -942,7 +942,7 @@ def test_spark_single_column_summary_result_format(
             },
         },
     )
-    expectation = ExpectColumnValuesToBeInSet(expectation_configuration)
+    expectation = ExpectColumnValuesToBeInSet(**expectation_configuration.kwargs)
     batch_definition = BatchDefinition(
         datasource_name="spark_datasource",
         data_connector_name="runtime_data_connector",
@@ -962,7 +962,7 @@ def test_spark_single_column_summary_result_format(
             batch,
         ],
     )
-    result = expectation.validate(validator)
+    result = expectation.validate_(validator)
     assert convert_to_json_serializable(result.result) == {
         "element_count": 6,
         "missing_count": 0,
@@ -995,7 +995,7 @@ def test_spark_single_column_basic_result_format(
             },
         },
     )
-    expectation = ExpectColumnValuesToBeInSet(expectation_configuration)
+    expectation = ExpectColumnValuesToBeInSet(**expectation_configuration.kwargs)
     batch_definition = BatchDefinition(
         datasource_name="spark_datasource",
         data_connector_name="runtime_data_connector",
@@ -1015,7 +1015,7 @@ def test_spark_single_column_basic_result_format(
             batch,
         ],
     )
-    result = expectation.validate(validator)
+    result = expectation.validate_(validator)
     assert convert_to_json_serializable(result.result) == {
         "element_count": 6,
         "missing_count": 0,