NEW: Column Type check validation

Requires documentation, still need to write

docs/source/ValidationCatalogue.rst

@@ -29,6 +29,20 @@ String Validation
    :undoc-members:
    :show-inheritance:
 
+Type Validation
+---------------
+.. automodule:: validoopsie.validation_catalogue.TypeValidation
+   :members:
+   :undoc-members:
+   :show-inheritance:
+
+Unique Validation
+-----------------
+.. automodule:: validoopsie.validation_catalogue.UniqueValidation
+   :members:
+   :undoc-members:
+   :show-inheritance:
+
 Values Validation
 -----------------
 .. automodule:: validoopsie.validation_catalogue.ValuesValidation

tests/test_validation_catalogue/test_TypesValidation/test_type_check.py

@@ -0,0 +1,228 @@
+from __future__ import annotations
+
+from datetime import date, datetime, timedelta
+
+import pytest
+from narwhals.dtypes import Boolean, Date, Datetime, Duration, List, String
+from narwhals.typing import Frame
+
+from tests.utils.create_frames import create_frame_fixture
+from validoopsie import Validate
+from validoopsie.typing import FloatType, IntType
+from validoopsie.validation_catalogue.TypeValidation import TypeCheck
+
+
+@create_frame_fixture
+def sample_data() -> dict[str, list]:
+    return {
+        "IntType": [
+            1,
+            -15,
+            32,
+            64,
+            128,
+        ],  # Example data for Int8, Int16, Int32, Int64, Int128
+        "FloatType": [
+            1.23,
+            -45.67,
+            0.01,
+            3.14159,
+            2.71828,
+        ],  # Example data for Float32, Float64, Decimal
+        "String": ["hello", "world", "narwhals", "data", "type"],  # Example strings
+        "Boolean": [True, False, True, False, True],  # Example booleans
+        "UIntType": [
+            0,
+            15,
+            32,
+            64,
+            128,
+        ],  # Example unsigned integers (UInt8, UInt16, UInt32, UInt64, UInt128)
+        "CategoryType": ["A", "B", "C", "A", "B"],  # Example categorical data
+        "ObjectType": [
+            {"key1": "value1"},
+            {"key2": "value2"},
+            {},
+            {"key3": "value3"},
+            {"key4": "value4"},
+        ],  # Example objects
+        "EnumType": [
+            "Red",
+            "Green",
+            "Blue",
+            "Yellow",
+            "Black",
+        ],  # Example enumeration values
+        "List": [[1, 2, 3], [4, 5], [], [6], [7, 8]],  # Example arrays/lists
+        "Datetime": [
+            datetime(2023, 1, 1, 10, 0),
+            datetime(2023, 6, 15, 15, 30),
+            datetime(2023, 12, 31, 23, 59),
+            datetime(2024, 1, 1),
+            datetime(2024, 11, 11, 11, 11),
+        ],  # Example datetimes
+        "Date": [
+            date(2023, 1, 1),
+            date(2023, 6, 15),
+            date(2023, 12, 31),
+            date(2024, 1, 1),
+            date(2024, 11, 11),
+        ],  # Example dates
+        "Duration": [
+            timedelta(days=1),  # Duration of 1 day
+            timedelta(days=2),  # Duration of 2 days
+            timedelta(days=3),  # Duration of 3 days
+            timedelta(hours=4),  # Duration of 4 hours
+            timedelta(minutes=5),  # Duration of 5 minutes
+        ],  # Example durations
+    }
+
+
+# Unit Tests
+def test_type_check_success_single_column(sample_data: Frame) -> None:
+    ds = TypeCheck("IntType", IntType)
+    result = ds.__execute_check__(frame=sample_data)
+    assert result["result"]["status"] == "Success"
+
+
+def test_type_check_failure_single_column(sample_data: Frame) -> None:
+    ds = TypeCheck("IntType", FloatType)
+    result = ds.__execute_check__(frame=sample_data)
+    assert result["result"]["status"] == "Fail"
+
+
+def test_date_check_success_single_column(
+    sample_data: Frame,
+    request: pytest.FixtureRequest,
+) -> None:
+    if request.node.callspec.id == "pandas":
+        pytest.skip("Pandas does not support Date type")
+    ds = TypeCheck("Date", Date)
+    result = ds.__execute_check__(frame=sample_data)
+    assert result["result"]["status"] == "Success"
+
+
+def test_type_check_success_multiple_columns(sample_data: Frame) -> None:
+    frame_schema_definition = {
+        "IntType": IntType,
+        "FloatType": FloatType,
+        "String": String,
+        "Boolean": Boolean,
+    }
+    ds = TypeCheck(frame_schema_definition=frame_schema_definition)
+    result = ds.__execute_check__(frame=sample_data)
+    assert result["result"]["status"] == "Success"
+
+
+def test_type_check_failure_multiple_columns(sample_data: Frame) -> None:
+    frame_schema_definition = {
+        "IntType": IntType,
+        "FloatType": FloatType,
+        "String": FloatType,
+    }
+    ds = TypeCheck(None, None, frame_schema_definition=frame_schema_definition)
+    result = ds.__execute_check__(frame=sample_data)
+    assert result["result"]["status"] == "Fail"
+    assert result["result"]["failing items"][0] == "String"
+
+
+def test_type_check_threshold_success(sample_data: Frame) -> None:
+    frame_schema_definition = {
+        "IntType": IntType,
+        "FloatType": FloatType,
+        "String": String,
+        "Boolean": Boolean,
+        "Date": Date,
+        "Duration": Duration,
+        "List": List,
+    }
+    ds = TypeCheck(
+        None,
+        None,
+        frame_schema_definition=frame_schema_definition,
+        threshold=0.75,
+    )
+    result = ds.__execute_check__(frame=sample_data)
+    assert result["result"]["status"] == "Success"
+
+
+def test_type_check_threshold_failure(sample_data: Frame) -> None:
+    frame_schema_definition = {
+        "IntType": FloatType,  # Intentional error
+        "FloatType": String,  # Intentional error
+        "String": FloatType,  # Intentional error
+        "Boolean": Boolean,
+    }
+    ds = TypeCheck(
+        None,
+        None,
+        frame_schema_definition=frame_schema_definition,
+        threshold=0.20,  # only 20% of columns can fail
+    )
+    result = ds.__execute_check__(frame=sample_data)
+    assert result["result"]["status"] == "Fail"
+
+
+# Integration Tests
+
+
+def test_type_check_integration_success(sample_data: Frame) -> None:
+    vd = Validate(sample_data)
+    vd.TypeValidation.TypeCheck("IntType", IntType)
+    result = vd.validate().results
+    key = list(vd.results.keys())[-1]
+    assert result[key]["result"]["status"] == "Success"
+
+
+def test_type_check_integration_failure_high_impact(sample_data: Frame) -> None:
+    vd = Validate(sample_data)
+    vd.TypeValidation.TypeCheck("IntType", FloatType, impact="high")
+    with pytest.raises(ValueError):
+        vd.validate()
+
+
+def test_type_check_integration_failure_low_impact(sample_data: Frame) -> None:
+    vd = Validate(sample_data)
+    vd.TypeValidation.TypeCheck("IntType", FloatType, impact="low")
+    result = vd.validate().results
+    key = list(vd.results.keys())[-1]
+    assert result[key]["result"]["status"] == "Fail"
+
+
+def test_type_check_integration_threshold_success(sample_data: Frame) -> None:
+    vd = Validate(sample_data)
+    frame_schema_definition = {
+        "IntType": IntType,
+        "FloatType": FloatType,
+        "Boolean": Boolean,
+        "String": String,
+        "Date": Date,
+        "Duration": Duration,
+    }
+    vd.TypeValidation.TypeCheck(
+        None,
+        None,
+        frame_schema_definition=frame_schema_definition,
+        threshold=0.8,
+    )
+    result = vd.validate().results
+    key = list(vd.results.keys())[-1]
+    assert result[key]["result"]["status"] == "Success"
+
+
+def test_type_check_integration_threshold_failure(sample_data: Frame) -> None:
+    vd = Validate(sample_data)
+    frame_schema_definition = {
+        "IntType": FloatType,  # Intentional error
+        "FloatType": String,  # Intentional error
+        "Boolean": Boolean,
+        "String": FloatType,  # Intentional error
+        "Date": Datetime,  # Intentional mismatch
+    }
+    vd.TypeValidation.TypeCheck(
+        frame_schema_definition=frame_schema_definition,
+        impact="high",
+    )
+
+    with pytest.raises(ValueError):
+        vd.validate()