test: consolidated aggregation any value expectations tests

.github/workflows/main.yaml

@@ -2,7 +2,6 @@ name: CI
 
 on:
   push:
-  pull_request:
   workflow_dispatch:  # Allow manual triggering
 
 permissions:

.github/workflows/publish.yaml

@@ -1,9 +1,7 @@
 name: Publish to PyPI
 
 on:
-  push:
-    tags:
-      - 'v*'
+  workflow_dispatch:  # Allow manual triggering
 
 permissions:
   contents: read

dataframe_expectations/suite.pyi

@@ -2,22 +2,116 @@
 # Auto-generated by scripts/generate_suite_stubs.py
 # DO NOT EDIT - Regenerate with: python scripts/generate_suite_stubs.py
 
-from typing import List, Union
-from dataframe_expectations.expectations import DataFrameLike
-from dataframe_expectations.result_message import DataFrameExpectationFailureMessage
+from functools import wraps
+from typing import Union, Callable, List, Optional, cast
+from dataframe_expectations.core.types import DataFrameLike
+from dataframe_expectations.registry import DataFrameExpectationRegistry
+from dataframe_expectations.result_message import DataFrameExpectationFailureMessage, DataFrameExpectationSuccessMessage
 
 class DataFrameExpectationsSuiteFailure(Exception):
-    failures: List[DataFrameExpectationFailureMessage]
-    total_expectations: int
-    def __init__(
-        self,
-        total_expectations: int,
-        failures: List[DataFrameExpectationFailureMessage],
-        *args,
-    ) -> None: ...
+    """Raised when one or more expectations in the suite fail."""
+    def __init__(self, total_expectations: int, failures: List[DataFrameExpectationFailureMessage], *args):
+        ...
+    def __str__(self):
+        ...
+
+class DataFrameExpectationsSuiteRunner:
+    """
+    Immutable runner for executing a fixed set of expectations.
+
+    This class is created by DataFrameExpectationsSuite.build() and contains
+    a snapshot of expectations that won't change during execution.
+    """
+    def __init__(self, expectations: List):
+        """
+
+                Initialize the runner with a list of expectations.
+
+                :param expectations: List of expectation instances to run.
+
+        """
+        ...
+    @property
+    def expectation_count(self) -> int:
+        """
+        Return the number of expectations in this runner.
+        """
+        ...
+    def list_expectations(self) -> List[str]:
+        """
+
+                Return a list of expectation descriptions in this runner.
+
+                :return: List of expectation descriptions as strings in the format:
+                         "ExpectationName (description)"
+
+        """
+        ...
+    def run(self, data_frame: DataFrameLike) -> None:
+        """
+
+                Run all expectations on the provided DataFrame with PySpark caching optimization.
+
+                :param data_frame: The DataFrame to validate.
+
+        """
+        ...
+    def validate(self, func: Optional[Callable]=None, *, allow_none: bool=False) -> Callable:
+        """
+
+                Decorator to validate the DataFrame returned by a function.
+
+                This decorator runs the expectations suite on the DataFrame returned
+                by the decorated function. If validation fails, it raises
+                DataFrameExpectationsSuiteFailure.
+
+                Example:
+                    runner = suite.build()
+
+                    @runner.validate
+                    def load_data():
+                        return pd.read_csv("data.csv")
+
+                    df = load_data()  # Automatically validated
+
+                    # Allow None returns
+                    @runner.validate(allow_none=True)
+                    def maybe_load_data():
+                        if condition:
+                            return pd.read_csv("data.csv")
+                        return None
+
+                :param func: Function that returns a DataFrame.
+                :param allow_none: If True, allows the function to return None without validation.
+                                  If False (default), None will raise a ValueError.
+                :return: Wrapped function that validates the returned DataFrame.
+
+        """
+        ...
 
 class DataFrameExpectationsSuite:
-    def __init__(self) -> None: ...
+    """
+    A builder for creating expectation suites for validating DataFrames.
+
+    Use this class to add expectations, then call build() to create an
+    immutable runner that can execute the expectations on DataFrames.
+
+    Example:
+        suite = DataFrameExpectationsSuite()
+        suite.expect_value_greater_than(column_name="age", value=18)
+        suite.expect_value_less_than(column_name="salary", value=100000)
+
+        runner = suite.build()
+        runner.run(df1)
+        runner.run(df2)  # Same expectations, different DataFrame
+    """
+    def __init__(self):
+        """
+
+                Initialize the expectation suite builder.
+
+        """
+        ...
 
     def expect_column_max_between(
         self,
@@ -616,4 +710,36 @@ class DataFrameExpectationsSuite:
         """
         ...
 
-    def run(self, data_frame: DataFrameLike) -> None: ...
+    def __getattr__(self, name: str):
+        """
+
+                Dynamically create expectation methods.
+
+                This is called when Python can't find an attribute through normal lookup.
+                We use it to generate expect_* methods on-the-fly from the registry.
+
+        """
+        ...
+    def _create_expectation_method(self, suite_method_name: str):
+        """
+
+                Create a dynamic expectation method.
+
+                Returns a closure that captures the suite_method_name and self.
+
+        """
+        ...
+    def build(self) -> DataFrameExpectationsSuiteRunner:
+        """
+
+                Build an immutable runner from the current expectations.
+
+                The runner contains a snapshot of expectations at the time of building.
+                You can continue to add more expectations to this suite and build
+                new runners without affecting previously built runners.
+
+                :return: An immutable DataFrameExpectationsSuiteRunner instance.
+                :raises ValueError: If no expectations have been added.
+
+        """
+        ...