def export_to_bigquery()

in src/dfcx_scrapi/tools/datastore_evaluator.py [0:0]

• 36 lines of code
• 2 McCabe index (conditional complexity)

    def export_to_bigquery(
            self,
            eval_results,
            project_id: str,
            dataset_id: str,
            table_name: str,
            credentials
            ):
        data=eval_results.scrape_outputs["query_result"].apply(
            lambda x: x.to_row())
        data = pd.DataFrame(data.to_list(),eval_results.scrape_outputs.index)
        eval_results.scrape_outputs["query_result"] = None
        df = pd.concat(
            [
                data,
                eval_results.scrape_outputs,
                eval_results.metric_outputs
                ],
                axis=1)

        df = EvaluationResult.sanitize_column_names(df)
        client = bigquery.Client(project=project_id, credentials=credentials)

        try:
            df['conversation_id'] = df['conversation_id'].astype(str)
            df['latency'] = df['latency'].astype(str)
            df['expected_uri'] = df['expected_uri'].astype(str)
            df['answerable'] = df['answerable'].astype(str)
            df['golden_snippet'] = df['golden_snippet'].astype(str)

            df = df.drop('query_result', axis=1)
            df = df.drop('golden_snippet', axis=1)
            df = df.drop('answerable', axis=1)

            load_job = client.load_table_from_dataframe(df, '.'.join(
                [project_id, dataset_id, table_name]))

            return load_job.result()
        except Exception as e:
            print(f"Error exporting data: {e}")
            return None  # Indicate failure