def read_view_as_pandas()

in notebooks/Utilities/finspace.py [0:0]

• 34 lines of code
• 10 McCabe index (conditional complexity)

    def read_view_as_pandas(self, dataset_id: str, view_id: str):
        """
        Returns a pandas dataframe the view of the given dataset.  Views in FinSpace can be quite large, be careful!

        :param dataset_id:
        :param view_id:

        :return: Pandas dataframe with all data of the view
        """
        import awswrangler as wr  # use awswrangler to read the table

        # @todo: switch to DescribeMateriliazation when available in HFS
        views = self.list_views(dataset_id=dataset_id, max_results=50)
        filtered = [v for v in views if v['id'] == view_id]

        if len(filtered) == 0:
            raise Exception('No such view found')
        if len(filtered) > 1:
            raise Exception('Internal Server error')
        view = filtered[0]

        # 0. Ensure view is ready to be read
        if (view['status'] != 'SUCCESS'):
            status = view['status']
            print(f'view run status is not ready: {status}. Returning empty.')
            return

        glue_db_name = view['destinationTypeProperties']['databaseName']
        glue_table_name = view['destinationTypeProperties']['tableName']

        # determine if the table has partitions first, different way to read is there are partitions
        p = wr.catalog.get_partitions(table=glue_table_name, database=glue_db_name, boto3_session=self._boto3_session)

        def no_filter(partitions):
            if len(partitions.keys()) > 0:
                return True

            return False

        df = None

        if len(p) == 0:
            df = wr.s3.read_parquet_table(table=glue_table_name, database=glue_db_name,
                                          boto3_session=self._boto3_session)
        else:
            spath = wr.catalog.get_table_location(table=glue_table_name, database=glue_db_name,
                                                  boto3_session=self._boto3_session)
            cpath = wr.s3.list_directories(f"{spath}/*", boto3_session=self._boto3_session)

            read_path = f"{spath}/"

            # just one?  Read it
            if len(cpath) == 1:
                read_path = cpath[0]

            df = wr.s3.read_parquet(read_path, dataset=True, partition_filter=no_filter,
                                    boto3_session=self._boto3_session)

        # Query Glue table directly with wrangler
        return df