changed all Dataframe references to DataFrame

Author: ryanseq-gyg

README.md

@@ -24,21 +24,24 @@ cd dataframe-expectations
 # 2. Install UV package manager
 pip install uv
 
-# 3. Install development dependencies
+# 3. Install development dependencies (this will automatically create a virtual environment)
 uv sync --group dev
 
-# 4. Run tests
+# 4. (Optional) To explicitly activate the virtual environment:
+source .venv/bin/activate  # On Windows: .venv\Scripts\activate
+
+# 5. Run tests (this will run the tests in the virtual environment)
 uv run pytest tests/ --cov=dataframe_expectations
 ```
 
 ### Using the library
 
 **Pandas example:**
 ```python
-from dataframe_expectations.expectations_suite import DataframeExpectationsSuite
+from dataframe_expectations.expectations_suite import DataFameExpectationsSuite
 
 suite = (
-    DataframeExpectationsSuite()
+    DataFrameExpectationsSuite()
     .expect_value_greater_than("age", 18)
     .expect_value_less_than("age", 10)
 )
@@ -54,10 +57,10 @@ suite.run(test_pandas_df)
 
 **PySpark example:**
 ```python
-from dataframe_expectations.expectations_suite import DataframeExpectationsSuite
+from dataframe_expectations.expectations_suite import DataFrameExpectationsSuite
 
 suite = (
-    DataframeExpectationsSuite()
+    DataFrameExpectationsSuite()
     .expect_value_greater_than("age", 18)
     .expect_value_less_than("age", 40)
 )

dataframe_expectations/expectations/__init__.py

@@ -13,11 +13,11 @@
 
 from dataframe_expectations import DataFrameLike, DataFrameType
 from dataframe_expectations.result_message import (
-    DataframeExpectationResultMessage,
+    DataFrameExpectationResultMessage,
 )
 
 
-class DataframeExpectation(ABC):
+class DataFrameExpectation(ABC):
     """
     Base class for DataFrame expectations.
     """
@@ -75,7 +75,7 @@ def validate(self, data_frame: DataFrameLike, **kwargs):
     @abstractmethod
     def validate_pandas(
         self, data_frame: DataFrameLike, **kwargs
-    ) -> DataframeExpectationResultMessage:
+    ) -> DataFrameExpectationResultMessage:
         """
         Validate a pandas DataFrame against the expectation.
         """
@@ -86,7 +86,7 @@ def validate_pandas(
     @abstractmethod
     def validate_pyspark(
         self, data_frame: DataFrameLike, **kwargs
-    ) -> DataframeExpectationResultMessage:
+    ) -> DataFrameExpectationResultMessage:
         """
         Validate a PySpark DataFrame against the expectation.
         """

dataframe_expectations/expectations/aggregation_expectation.py

@@ -2,14 +2,14 @@
 from typing import List, Union
 
 from dataframe_expectations import DataFrameLike, DataFrameType
-from dataframe_expectations.expectations import DataframeExpectation
+from dataframe_expectations.expectations import DataFrameExpectation
 from dataframe_expectations.result_message import (
-    DataframeExpectationFailureMessage,
-    DataframeExpectationResultMessage,
+    DataFrameExpectationFailureMessage,
+    DataFrameExpectationResultMessage,
 )
 
 
-class DataframeAggregationExpectation(DataframeExpectation):
+class DataFrameAggregationExpectation(DataFrameExpectation):
     """
     Base class for DataFrame aggregation expectations.
     This class is designed to first aggregate data and then validate the aggregation results.
@@ -48,7 +48,7 @@ def get_description(self) -> str:
     @abstractmethod
     def aggregate_and_validate_pandas(
         self, data_frame: DataFrameLike, **kwargs
-    ) -> DataframeExpectationResultMessage:
+    ) -> DataFrameExpectationResultMessage:
         """
         Aggregate and validate a pandas DataFrame against the expectation.
 
@@ -62,7 +62,7 @@ def aggregate_and_validate_pandas(
     @abstractmethod
     def aggregate_and_validate_pyspark(
         self, data_frame: DataFrameLike, **kwargs
-    ) -> DataframeExpectationResultMessage:
+    ) -> DataFrameExpectationResultMessage:
         """
         Aggregate and validate a PySpark DataFrame against the expectation.
 
@@ -75,15 +75,15 @@ def aggregate_and_validate_pyspark(
 
     def validate_pandas(
         self, data_frame: DataFrameLike, **kwargs
-    ) -> DataframeExpectationResultMessage:
+    ) -> DataFrameExpectationResultMessage:
         """
         Validate a pandas DataFrame against the expectation.
         Automatically checks column existence before calling the implementation.
         """
         # Check if all required columns exist
         column_error = self._check_columns_exist(data_frame)
         if column_error:
-            return DataframeExpectationFailureMessage(
+            return DataFrameExpectationFailureMessage(
                 expectation_str=str(self),
                 data_frame_type=DataFrameType.PANDAS,
                 message=column_error,
@@ -94,15 +94,15 @@ def validate_pandas(
 
     def validate_pyspark(
         self, data_frame: DataFrameLike, **kwargs
-    ) -> DataframeExpectationResultMessage:
+    ) -> DataFrameExpectationResultMessage:
         """
         Validate a PySpark DataFrame against the expectation.
         Automatically checks column existence before calling the implementation.
         """
         # Check if all required columns exist
         column_error = self._check_columns_exist(data_frame)
         if column_error:
-            return DataframeExpectationFailureMessage(
+            return DataFrameExpectationFailureMessage(
                 expectation_str=str(self),
                 data_frame_type=DataFrameType.PYSPARK,
                 message=column_error,