diff --git a/google_sheets/app.py b/google_sheets/app.py index 134d843..bc8d894 100644 --- a/google_sheets/app.py +++ b/google_sheets/app.py @@ -392,9 +392,10 @@ async def process_data( target_resource, # type: ignore ) + issues_present = "Issues" in validated_df.columns values = [validated_df.columns.tolist(), *validated_df.values.tolist()] - return GoogleSheetValues(values=values) + return GoogleSheetValues(values=values, issues_present=issues_present) async def process_campaigns_and_ad_groups( @@ -544,5 +545,8 @@ async def process_spreadsheet( sheet_values=processed_values, ) response += f"Sheet with the name '{title}' has been created successfully.\n" + if processed_values.issues_present: + response += """But there are issues present in the data. +Please check the 'Issues' column and correct the data accordingly.\n\n""" return response diff --git a/google_sheets/data_processing/processing.py b/google_sheets/data_processing/processing.py index 4c97ac0..7968ee0 100644 --- a/google_sheets/data_processing/processing.py +++ b/google_sheets/data_processing/processing.py @@ -116,7 +116,8 @@ def process_data_f( def _validate_output_data_ad(df: pd.DataFrame) -> pd.DataFrame: # noqa: C901 - df["Issues"] = "" + df.insert(0, "Issues", "") + headline_columns = [col for col in df.columns if "Headline" in col] description_columns = [col for col in df.columns if "Description" in col] diff --git a/google_sheets/model.py b/google_sheets/model.py index e38fcd1..6109a9a 100644 --- a/google_sheets/model.py +++ b/google_sheets/model.py @@ -7,3 +7,8 @@ class GoogleSheetValues(BaseModel): values: List[List[Any]] = Field( ..., title="Values", description="Values to be written to the Google Sheet." ) + issues_present: bool = Field( + default=False, + title="Issues Present", + description="Whether any issues are present.", + ) diff --git a/tests/app/test_app.py b/tests/app/test_app.py index a3401e9..65d7202 100644 --- a/tests/app/test_app.py +++ b/tests/app/test_app.py @@ -294,7 +294,7 @@ class TestProcessData: ], ) @pytest.mark.asyncio() - async def test_process_data( + async def test_process_data_keywords( self, template_sheet_values: GoogleSheetValues, new_campaign_sheet_values: GoogleSheetValues, @@ -328,6 +328,116 @@ async def test_process_data( ) assert detail in exc.value.detail + @pytest.mark.asyncio() + async def test_process_data_ads(self) -> None: + template_sheet_values = GoogleSheetValues( + values=[ + [ + "Final URL", + "Headline 1", + "Headline 2", + "Headline 3", + "Description Line 1", + "Description Line 2", + "Path 1", + "Path 2", + ], + [ + "https://www.example.com/from", + "H" * 31, + "Headline 2", + "Headline 3", + "Description Line 1", + "Description Line 2", + "Path 1", + "Path 2", + ], + ] + ) + new_campaign_sheet_values = GoogleSheetValues( + values=[ + [ + "Country", + "Station From", + "Station To", + "Final Url From", + "Final Url To", + ], + [ + "India", + "Delhi", + "Mumbai", + "https://www.example.com/from", + "https://www.example.com/to", + ], + ] + ) + merged_campaigns_ad_groups_df = pd.DataFrame( + { + "Campaign Name": [ + "INSERT_COUNTRY - INSERT_STATION_FROM - INSERT_STATION_TO" + ], + "Ad Group Name": ["INSERT_STATION_FROM - INSERT_STATION_TO"], + "Match Type": ["Exact"], + } + ) + result = await process_data( + template_sheet_values=template_sheet_values, + new_campaign_sheet_values=new_campaign_sheet_values, + merged_campaigns_ad_groups_df=merged_campaigns_ad_groups_df, + target_resource="ad", + ) + + expected = GoogleSheetValues( + values=[ + [ + "Issues", + "Campaign Name", + "Ad Group Name", + "Match Type", + "Final URL", + "Headline 1", + "Headline 2", + "Headline 3", + "Description Line 1", + "Description Line 2", + "Path 1", + "Path 2", + ], + [ + "Headline length should be less than 30 characters, found 31 in column Headline 1.\n", + "India - Delhi - Mumbai", + "Delhi - Mumbai", + "Exact", + "https://www.example.com/from", + "HHHHHHHHHHHHHHHHHHHHHHHHHHHHHHH", + "Headline 2", + "Headline 3", + "Description Line 1", + "Description Line 2", + "Path 1", + "Path 2", + ], + [ + "Headline length should be less than 30 characters, found 31 in column Headline 1.\n", + "India - Delhi - Mumbai", + "Mumbai - Delhi", + "Exact", + "https://www.example.com/to", + "HHHHHHHHHHHHHHHHHHHHHHHHHHHHHHH", + "Headline 2", + "Headline 3", + "Description Line 1", + "Description Line 2", + "Path 1", + "Path 2", + ], + ], + issues_present=True, + ) + + assert result.model_dump() == expected.model_dump() + class TestOpenAPIJSON: def test_openapi(self) -> None: diff --git a/tests/data_processing/test_processing.py b/tests/data_processing/test_processing.py index f1cc9e6..2a155bf 100644 --- a/tests/data_processing/test_processing.py +++ b/tests/data_processing/test_processing.py @@ -167,33 +167,53 @@ def test_process_data_f( @pytest.mark.parametrize( - "issues_column", + ("df", "issues_column"), [ - [ - "Duplicate headlines found.\nDuplicate descriptions found.\n", - "Duplicate descriptions found.\n", - "", - "Minimum 3 headlines are required, found 2.\nMinimum 2 descriptions are required, found 1.\nHeadline length should be less than 30 characters, found 31 in column Headline 2.\n", - ], - None, + ( + pd.DataFrame( + { + "Headline 1": ["H1", "H1", "H1", "H1"], + "Headline 2": ["H1", "H2", "H2", ("H" * 31)], + "Headline 3": ["H3", "H3", "H3", ""], + "Description 1": ["D1", "D1", "D2", "D3"], + "Description 2": ["D1", "D1", "D3", ""], + "Path 1": ["P1", "P1", "P1", "P1"], + "Path 2": ["P2", "P2", "P2", "P2"], + "Final URL": ["URL", "URL", "URL", "URL"], + } + ), + [ + "Duplicate headlines found.\nDuplicate descriptions found.\n", + "Duplicate descriptions found.\n", + "", + "Minimum 3 headlines are required, found 2.\nMinimum 2 descriptions are required, found 1.\nHeadline length should be less than 30 characters, found 31 in column Headline 2.\n", + ], + ), + ( + pd.DataFrame( + { + "Headline 1": ["H1", "H1", "H1", "H1"], + "Headline 2": ["H2", "H2", "H2", "H2"], + "Headline 3": ["H3", "H3", "H3", "H3"], + "Description 1": ["D1", "D1", "D1", "D1"], + "Description 2": ["D2", "D2", "D2", "D2"], + "Path 1": ["P1", "P1", "P1", "P1"], + "Path 2": ["P2", "P2", "P2", "P2"], + "Final URL": ["URL", "URL", "URL", "URL"], + } + ), + None, + ), ], ) -def test_validate_output_data(issues_column: Optional[List[str]]) -> None: - df = pd.DataFrame( - { - "Headline 1": ["H1", "H1", "H1", "H1"], - "Headline 2": ["H1", "H2", "H2", ("H" * 31)], - "Headline 3": ["H3", "H3", "H3", ""], - "Description 1": ["D1", "D1", "D2", "D3"], - "Description 2": ["D1", "D1", "D3", ""], - "Path 1": ["P1", "P1", "P1", "P1"], - "Path 2": ["P2", "P2", "P2", "P2"], - "Final URL": ["URL", "URL", "URL", "URL"], - } - ) - result = validate_output_data(df, "ad") +def test_validate_output_data( + df: pd.DataFrame, issues_column: Optional[List[str]] +) -> None: expected = df.copy() + result = validate_output_data(df, "ad") + if issues_column: + expected.insert(0, "Issues", "") expected["Issues"] = issues_column assert result.equals(expected)