kartothek.io.testing.write module

class kartothek.io.testing.write.NoPickle

Bases: object

kartothek.io.testing.write.mark_nopickle(obj)

kartothek.io.testing.write.no_pickle_factory(url)

kartothek.io.testing.write.no_pickle_store(url)

kartothek.io.testing.write.store_input_types(request, tmpdir)

kartothek.io.testing.write.test_file_structure_dataset_v4(store_factory, bound_store_dataframes)

kartothek.io.testing.write.test_file_structure_dataset_v4_partition_on(store_factory, bound_store_dataframes)

kartothek.io.testing.write.test_file_structure_dataset_v4_partition_on_second_table_no_index_col(store_factory, bound_store_dataframes)

kartothek.io.testing.write.test_file_structure_dataset_v4_partition_on_second_table_no_index_col_simple_group(store_factory, bound_store_dataframes)

Pandas seems to stop evaluating the groupby expression if the dataframes after the first column split is of length 1. This seems to be an optimization which should, however, still raise a KeyError

kartothek.io.testing.write.test_metadata_consistency_errors_fails(store_factory, metadata_version, bound_store_dataframes)

kartothek.io.testing.write.test_schema_check_write(dfs, ok, store_factory, bound_store_dataframes)

kartothek.io.testing.write.test_schema_check_write_cut_error(store_factory, bound_store_dataframes)

kartothek.io.testing.write.test_schema_check_write_nice_error(store_factory, bound_store_dataframes)

kartothek.io.testing.write.test_schema_check_write_shared(store_factory, bound_store_dataframes)

kartothek.io.testing.write.test_secondary_index_on_partition_column(store_factory, bound_store_dataframes)

kartothek.io.testing.write.test_store_dataframes_as_dataset(store_factory, metadata_version, bound_store_dataframes)

kartothek.io.testing.write.test_store_dataframes_as_dataset_auto_uuid(store_factory, metadata_version, mock_uuid, bound_store_dataframes)

kartothek.io.testing.write.test_store_dataframes_as_dataset_batch_mode(store_factory, metadata_version, bound_store_dataframes)

kartothek.io.testing.write.test_store_dataframes_as_dataset_empty_dataframe(store_factory, metadata_version, df_all_types, bound_store_dataframes)

Test that writing an empty column succeeds. In particular, this may fail due to too strict schema validation.

kartothek.io.testing.write.test_store_dataframes_as_dataset_list_input(store_factory, metadata_version, bound_store_dataframes)

kartothek.io.testing.write.test_store_dataframes_as_dataset_mp_partition_on_none(metadata_version, store, store_factory, bound_store_dataframes)

kartothek.io.testing.write.test_store_dataframes_as_dataset_overwrite(store_factory, dataset_function, bound_store_dataframes)

kartothek.io.testing.write.test_store_dataframes_partition_on(store_factory, bound_store_dataframes)

kartothek.io.testing.write.test_store_empty_dataframes_partition_on(store_factory, bound_store_dataframes)

kartothek.io.testing.write.test_store_input_types(store_input_types, bound_store_dataframes)

kartothek.io.testing.write.test_store_overwrite_none(store_factory, bound_store_dataframes)

kartothek.io.testing.write.test_table_consistency_resistance(store_factory, metadata_version, bound_store_dataframes)