Merge pull request #38 from cparmet/new-asserts

Add new assert methods

README.md

@@ -158,12 +158,14 @@ Types:
 - `.check.assert_type()` - [DataFrame](https://cparmet.github.io/pandas-checks/API%20reference/DataFrameChecks/#pandas_checks.DataFrameChecks.DataFrameChecks.assert_type) | [Series](https://cparmet.github.io/pandas-checks/API%20reference/SeriesChecks/#pandas_checks.SeriesChecks.SeriesChecks.assert_type)
 
 Values:
+- `.check.assert_all_nulls()` - [DataFrame](https://cparmet.github.io/pandas-checks/API%20reference/DataFrameChecks/#pandas_checks.DataFrameChecks.DataFrameChecks.assert_all_nulls) | [Series](https://cparmet.github.io/pandas-checks/API%20reference/SeriesChecks/#pandas_checks.SeriesChecks.SeriesChecks.assert_all_nulls)
 - `.check.assert_less_than()` - [DataFrame](https://cparmet.github.io/pandas-checks/API%20reference/DataFrameChecks/#pandas_checks.DataFrameChecks.DataFrameChecks.assert_less_than) | [Series](https://cparmet.github.io/pandas-checks/API%20reference/SeriesChecks/#pandas_checks.SeriesChecks.SeriesChecks.assert_less_than)
 - `.check.assert_greater_than()` - [DataFrame](https://cparmet.github.io/pandas-checks/API%20reference/DataFrameChecks/#pandas_checks.DataFrameChecks.DataFrameChecks.assert_greater_than) | [Series](https://cparmet.github.io/pandas-checks/API%20reference/SeriesChecks/#pandas_checks.SeriesChecks.SeriesChecks.assert_greater_than)
 - `.check.assert_negative()` - [DataFrame](https://cparmet.github.io/pandas-checks/API%20reference/DataFrameChecks/#pandas_checks.DataFrameChecks.DataFrameChecks.assert_negative) | [Series](https://cparmet.github.io/pandas-checks/API%20reference/SeriesChecks/#pandas_checks.SeriesChecks.SeriesChecks.assert_negative)
 - `.check.assert_no_nulls()` - [DataFrame](https://cparmet.github.io/pandas-checks/API%20reference/DataFrameChecks/#pandas_checks.DataFrameChecks.DataFrameChecks.assert_no_nulls) | [Series](https://cparmet.github.io/pandas-checks/API%20reference/SeriesChecks/#pandas_checks.SeriesChecks.SeriesChecks.assert_no_nulls)
-- `.check.assert_all_nulls()` - [DataFrame](https://cparmet.github.io/pandas-checks/API%20reference/DataFrameChecks/#pandas_checks.DataFrameChecks.DataFrameChecks.assert_all_nulls) | [Series](https://cparmet.github.io/pandas-checks/API%20reference/SeriesChecks/#pandas_checks.SeriesChecks.SeriesChecks.assert_all_nulls)
+- `.check.assert_nrows()` - [DataFrame](https://cparmet.github.io/pandas-checks/API%20reference/DataFrameChecks/#pandas_checks.DataFrameChecks.DataFrameChecks.assert_nrows) | [Series](https://cparmet.github.io/pandas-checks/API%20reference/SeriesChecks/#pandas_checks.SeriesChecks.SeriesChecks.assert_nrows)
 - `.check.assert_positive()` - [DataFrame](https://cparmet.github.io/pandas-checks/API%20reference/DataFrameChecks/#pandas_checks.DataFrameChecks.DataFrameChecks.assert_positive) | [Series](https://cparmet.github.io/pandas-checks/API%20reference/SeriesChecks/#pandas_checks.SeriesChecks.SeriesChecks.assert_positive)
+- `.check.assert_same_nrows()`: Check that DataFrame/Series has same number of rows as another DF/Series, for example to validate 1:1 joins - [DataFrame](https://cparmet.github.io/pandas-checks/API%20reference/DataFrameChecks/#pandas_checks.DataFrameChecks.DataFrameChecks.assert_same_nrows) | [Series](https://cparmet.github.io/pandas-checks/API%20reference/SeriesChecks/#pandas_checks.SeriesChecks.SeriesChecks.assert_same_nrows)
 - `.check.assert_unique()` - [DataFrame](https://cparmet.github.io/pandas-checks/API%20reference/DataFrameChecks/#pandas_checks.DataFrameChecks.DataFrameChecks.assert_unique) | [Series](https://cparmet.github.io/pandas-checks/API%20reference/SeriesChecks/#pandas_checks.SeriesChecks.SeriesChecks.assert_unique)
 
 ### Visualize data

docs/usage.md

@@ -131,12 +131,14 @@ Types:
 - `.check.assert_type()` - [DataFrame](https://cparmet.github.io/pandas-checks/API%20reference/DataFrameChecks/#pandas_checks.DataFrameChecks.DataFrameChecks.assert_type) | [Series](https://cparmet.github.io/pandas-checks/API%20reference/SeriesChecks/#pandas_checks.SeriesChecks.SeriesChecks.assert_type)
 
 Values:
+- `.check.assert_all_nulls()` - [DataFrame](https://cparmet.github.io/pandas-checks/API%20reference/DataFrameChecks/#pandas_checks.DataFrameChecks.DataFrameChecks.assert_all_nulls) | [Series](https://cparmet.github.io/pandas-checks/API%20reference/SeriesChecks/#pandas_checks.SeriesChecks.SeriesChecks.assert_all_nulls)
 - `.check.assert_less_than()` - [DataFrame](https://cparmet.github.io/pandas-checks/API%20reference/DataFrameChecks/#pandas_checks.DataFrameChecks.DataFrameChecks.assert_less_than) | [Series](https://cparmet.github.io/pandas-checks/API%20reference/SeriesChecks/#pandas_checks.SeriesChecks.SeriesChecks.assert_less_than)
 - `.check.assert_greater_than()` - [DataFrame](https://cparmet.github.io/pandas-checks/API%20reference/DataFrameChecks/#pandas_checks.DataFrameChecks.DataFrameChecks.assert_greater_than) | [Series](https://cparmet.github.io/pandas-checks/API%20reference/SeriesChecks/#pandas_checks.SeriesChecks.SeriesChecks.assert_greater_than)
 - `.check.assert_negative()` - [DataFrame](https://cparmet.github.io/pandas-checks/API%20reference/DataFrameChecks/#pandas_checks.DataFrameChecks.DataFrameChecks.assert_negative) | [Series](https://cparmet.github.io/pandas-checks/API%20reference/SeriesChecks/#pandas_checks.SeriesChecks.SeriesChecks.assert_negative)
 - `.check.assert_no_nulls()` - [DataFrame](https://cparmet.github.io/pandas-checks/API%20reference/DataFrameChecks/#pandas_checks.DataFrameChecks.DataFrameChecks.assert_no_nulls) | [Series](https://cparmet.github.io/pandas-checks/API%20reference/SeriesChecks/#pandas_checks.SeriesChecks.SeriesChecks.assert_no_nulls)
-- `.check.assert_all_nulls()` - [DataFrame](https://cparmet.github.io/pandas-checks/API%20reference/DataFrameChecks/#pandas_checks.DataFrameChecks.DataFrameChecks.assert_all_nulls) | [Series](https://cparmet.github.io/pandas-checks/API%20reference/SeriesChecks/#pandas_checks.SeriesChecks.SeriesChecks.assert_all_nulls)
+- `.check.assert_nrows()` - [DataFrame](https://cparmet.github.io/pandas-checks/API%20reference/DataFrameChecks/#pandas_checks.DataFrameChecks.DataFrameChecks.assert_nrows) | [Series](https://cparmet.github.io/pandas-checks/API%20reference/SeriesChecks/#pandas_checks.SeriesChecks.SeriesChecks.assert_nrows)
 - `.check.assert_positive()` - [DataFrame](https://cparmet.github.io/pandas-checks/API%20reference/DataFrameChecks/#pandas_checks.DataFrameChecks.DataFrameChecks.assert_positive) | [Series](https://cparmet.github.io/pandas-checks/API%20reference/SeriesChecks/#pandas_checks.SeriesChecks.SeriesChecks.assert_positive)
+- `.check.assert_same_nrows()`: Check that this DataFrame/Series has same number of rows as another DataFrame/Series, for example to validate 1:1 joins - [DataFrame](https://cparmet.github.io/pandas-checks/API%20reference/DataFrameChecks/#pandas_checks.DataFrameChecks.DataFrameChecks.assert_same_nrows) | [Series](https://cparmet.github.io/pandas-checks/API%20reference/SeriesChecks/#pandas_checks.SeriesChecks.SeriesChecks.assert_same_nrows)
 - `.check.assert_unique()` - [DataFrame](https://cparmet.github.io/pandas-checks/API%20reference/DataFrameChecks/#pandas_checks.DataFrameChecks.DataFrameChecks.assert_unique) | [Series](https://cparmet.github.io/pandas-checks/API%20reference/SeriesChecks/#pandas_checks.SeriesChecks.SeriesChecks.assert_unique)
 
 ### Visualize data

pandas_checks/DataFrameChecks.py

@@ -544,6 +544,48 @@ def assert_no_nulls(
         )
         return self._obj
 
+    def assert_nrows(
+        self,
+        nrows: int,
+        fail_message: str = " ㄨ Assert nrows failed ",
+        pass_message: str = " ✔️ Assert nrows passed ",
+        raise_exception: bool = True,
+        exception_to_raise: Type[BaseException] = DataError,
+        verbose: bool = False,
+    ) -> pd.DataFrame:
+        """Tests whether Dataframe has a given number of rows. Optionally raises an exception. Does not modify the DataFrame itself.
+
+        Example:
+            (
+                iris
+                .check.assert_nrows(20)
+            )
+
+            # See docs for .check.assert_data() for examples of how to customize assertions
+
+        Args:
+            nrows: The expected number of rows
+            fail_message: Message to display if the condition fails.
+            pass_message: Message to display if the condition passes.
+            raise_exception: Whether to raise an exception if the condition fails.
+            exception_to_raise: The exception to raise if the condition fails and raise_exception is True.
+            verbose: Whether to display the pass message if the condition passes.
+
+        Returns:
+            The original DataFrame, unchanged.
+        """
+
+        self._obj.check.assert_data(
+            condition=lambda df: df.shape[0] == nrows,
+            fail_message=fail_message,
+            pass_message=pass_message,
+            raise_exception=raise_exception,
+            exception_to_raise=exception_to_raise,
+            message_shows_condition=False,
+            verbose=verbose,
+        )
+        return self._obj
+
     def assert_positive(
         self,
         fail_message: str = " ㄨ Assert positive failed ",
@@ -598,6 +640,53 @@ def assert_positive(
         )
         return self._obj
 
+    def assert_same_nrows(
+        self,
+        other: Union[pd.DataFrame, pd.Series],
+        fail_message: str = " ㄨ Assert same_nrows failed ",
+        pass_message: str = " ✔️ Assert same_nrows passed ",
+        raise_exception: bool = True,
+        exception_to_raise: Type[BaseException] = DataError,
+        verbose: bool = False,
+    ) -> pd.DataFrame:
+        """Tests whether Dataframe has the same number of rows as another DataFrame/Series has.
+
+        Optionally raises an exception. Does not modify the DataFrame itself.
+
+        Example:
+            # Validate that an expected one-to-one join didn't add rows due to duplicate keys in the right table.
+            (
+                transactions_df
+                .merge(how="left", right=products_df, on="product_id")
+                .check.assert_same_nrows(transactions_df, "Left join changed row count! Check for duplicate `product_id` keys in product_df.")
+            )
+
+            # See docs for .check.assert_data() for examples of how to customize assertions
+
+        Args:
+            other: The DataFrame or Series that we expect to have the same # of rows as
+            fail_message: Message to display if the condition fails.
+            pass_message: Message to display if the condition passes.
+            subset: Optional, which column or columns to check the condition against.
+            raise_exception: Whether to raise an exception if the condition fails.
+            exception_to_raise: The exception to raise if the condition fails and raise_exception is True.
+            verbose: Whether to display the pass message if the condition passes.
+
+        Returns:
+            The original DataFrame, unchanged.
+        """
+
+        self._obj.check.assert_data(
+            condition=lambda df: df.shape[0] == other.shape[0],
+            fail_message=fail_message,
+            pass_message=pass_message,
+            raise_exception=raise_exception,
+            exception_to_raise=exception_to_raise,
+            message_shows_condition=False,
+            verbose=verbose,
+        )
+        return self._obj
+
     def assert_str(
         self,
         fail_message: Union[str, None] = None,

pandas_checks/SeriesChecks.py

@@ -514,6 +514,49 @@ def assert_no_nulls(
         )
         return self._obj
 
+    def assert_nrows(
+        self,
+        nrows: int,
+        fail_message: str = " ㄨ Assert nrows failed ",
+        pass_message: str = " ✔️ Assert nrows passed ",
+        raise_exception: bool = True,
+        exception_to_raise: Type[BaseException] = DataError,
+        verbose: bool = False,
+    ) -> pd.DataFrame:
+        """Tests whether Series has a given number of rows. Optionally raises an exception. Does not modify the Series itself.
+
+        Example:
+            (
+                iris
+                ["species"]
+                .check.assert_nrows(20)
+            )
+
+            # See docs for .check.assert_data() for examples of how to customize assertions
+
+        Args:
+            nrows: The expected number of rows
+            fail_message: Message to display if the condition fails.
+            pass_message: Message to display if the condition passes.
+            raise_exception: Whether to raise an exception if the condition fails.
+            exception_to_raise: The exception to raise if the condition fails and raise_exception is True.
+            verbose: Whether to display the pass message if the condition passes.
+
+        Returns:
+            The original Series, unchanged.
+        """
+
+        self._obj.check.assert_data(
+            condition=lambda s: s.shape[0] == nrows,
+            fail_message=fail_message,
+            pass_message=pass_message,
+            raise_exception=raise_exception,
+            exception_to_raise=exception_to_raise,
+            message_shows_condition=False,
+            verbose=verbose,
+        )
+        return self._obj
+
     def assert_positive(
         self,
         fail_message: str = " ㄨ Assert positive failed ",
@@ -566,6 +609,52 @@ def assert_positive(
         )
         return self._obj
 
+    def assert_same_nrows(
+        self,
+        other: Union[pd.DataFrame, pd.Series],
+        fail_message: str = " ㄨ Assert same_nrows failed ",
+        pass_message: str = " ✔️ Assert same_nrows passed ",
+        raise_exception: bool = True,
+        exception_to_raise: Type[BaseException] = DataError,
+        verbose: bool = False,
+    ) -> pd.DataFrame:
+        """Tests whether Series has the same number of rows as another DataFrame/Series has.
+
+        Optionally raises an exception. Does not modify the Series itself.
+
+        Example:
+            (
+                df1
+                ["column"]
+                .check.assert_same_nrows(df2)
+            )
+
+            # See docs for .check.assert_data() for examples of how to customize assertions
+
+        Args:
+            other: The DataFrame or Series that we expect to have the same # of rows as
+            fail_message: Message to display if the condition fails.
+            pass_message: Message to display if the condition passes.
+            subset: Optional, which column or columns to check the condition against.
+            raise_exception: Whether to raise an exception if the condition fails.
+            exception_to_raise: The exception to raise if the condition fails and raise_exception is True.
+            verbose: Whether to display the pass message if the condition passes.
+
+        Returns:
+            The original DataFrame, unchanged.
+        """
+
+        self._obj.check.assert_data(
+            condition=lambda df: df.shape[0] == other.shape[0],
+            fail_message=fail_message,
+            pass_message=pass_message,
+            raise_exception=raise_exception,
+            exception_to_raise=exception_to_raise,
+            message_shows_condition=False,
+            verbose=verbose,
+        )
+        return self._obj
+
     def assert_str(
         self,
         fail_message: Union[str, None] = None,