add RUF

awswrangler/__init__.py

@@ -7,7 +7,7 @@
 
 import logging as _logging
 
-from awswrangler import (  # noqa
+from awswrangler import (
     athena,
     catalog,
     chime,
@@ -34,9 +34,9 @@
     timestream,
     typing,
 )
-from awswrangler.__metadata__ import __description__, __license__, __title__, __version__  # noqa
-from awswrangler._config import config  # noqa
-from awswrangler._distributed import EngineEnum, MemoryFormatEnum, engine, memory_format  # noqa
+from awswrangler.__metadata__ import __description__, __license__, __title__, __version__
+from awswrangler._config import config
+from awswrangler._distributed import EngineEnum, MemoryFormatEnum, engine, memory_format
 
 engine.register()
 

awswrangler/_databases.py

@@ -132,8 +132,8 @@ def _convert_params(sql: str, params: Optional[Union[List[Any], Tuple[Any, ...],
     args: List[Any] = [sql]
     if params is not None:
         if hasattr(params, "keys"):
-            return args + [params]
-        return args + [list(params)]
+            return [*args, params]
+        return [*args, params]
     return args
 
 

awswrangler/_distributed.py

@@ -9,7 +9,7 @@
 from enum import Enum, unique
 from functools import wraps
 from importlib import reload
-from typing import Any, Callable, Dict, Literal, Optional, TypeVar, cast
+from typing import Any, Callable, ClassVar, Dict, Literal, Optional, TypeVar, cast
 
 EngineLiteral = Literal["python", "ray"]
 MemoryFormatLiteral = Literal["pandas", "modin"]
@@ -42,7 +42,7 @@ class Engine:
 
     _engine: Optional[EngineEnum] = EngineEnum[WR_ENGINE.upper()] if WR_ENGINE else None
     _initialized_engine: Optional[EngineEnum] = None
-    _registry: Dict[EngineLiteral, Dict[str, Callable[..., Any]]] = defaultdict(dict)
+    _registry: ClassVar[Dict[EngineLiteral, Dict[str, Callable[..., Any]]]] = defaultdict(dict)
     _lock: threading.RLock = threading.RLock()
 
     @classmethod

awswrangler/athena/__init__.py

@@ -12,13 +12,13 @@
     delete_prepared_statement,
     list_prepared_statements,
 )
-from awswrangler.athena._read import (  # noqa
+from awswrangler.athena._read import (
     get_query_results,
     read_sql_query,
     read_sql_table,
     unload,
 )
-from awswrangler.athena._utils import (  # noqa
+from awswrangler.athena._utils import (
     create_athena_bucket,
     create_ctas_table,
     describe_table,

awswrangler/athena/_read.py

@@ -40,7 +40,7 @@
 
 @_utils.check_optional_dependency(shapely_wkt, "shapely")
 @_utils.check_optional_dependency(geopandas, "geopandas")
-def _cast_geometry(df: pd.DataFrame, parse_geometry: List[str] = None):
+def _cast_geometry(df: pd.DataFrame, parse_geometry: Optional[List[str]] = None):
     def load_geom_wkt(x):
         """Load geometry from well-known text."""
         return shapely_wkt.loads(x)
@@ -166,7 +166,7 @@ def _fetch_parquet_result(
         ret = _apply_query_metadata(df=ret, query_metadata=query_metadata)
     else:
         ret = _add_query_metadata_generator(dfs=ret, query_metadata=query_metadata)
-    paths_delete: List[str] = paths + [manifest_path, metadata_path]
+    paths_delete: List[str] = [*paths, manifest_path, metadata_path]
     if chunked is False:
         if keep_files is False:
             s3.delete_objects(

awswrangler/catalog/__init__.py

@@ -7,9 +7,7 @@
     add_orc_partitions,
     add_parquet_partitions,
 )
-
-# noqa
-from awswrangler.catalog._create import (  # noqa
+from awswrangler.catalog._create import (
     _create_csv_table,
     _create_json_table,
     _create_parquet_table,
@@ -21,14 +19,14 @@
     overwrite_table_parameters,
     upsert_table_parameters,
 )
-from awswrangler.catalog._delete import (  # noqa
+from awswrangler.catalog._delete import (
     delete_all_partitions,
     delete_column,
     delete_database,
     delete_partitions,
     delete_table_if_exists,
 )
-from awswrangler.catalog._get import (  # noqa
+from awswrangler.catalog._get import (
     _get_table_input,
     databases,
     get_columns_comments,
@@ -48,7 +46,7 @@
     table,
     tables,
 )
-from awswrangler.catalog._utils import (  # noqa
+from awswrangler.catalog._utils import (
     does_table_exist,
     drop_duplicated_columns,
     extract_athena_types,

awswrangler/distributed/ray/__init__.py

@@ -1,6 +1,6 @@
 """Ray Module."""
 
-from awswrangler.distributed.ray._core import RayLogger, initialize_ray, ray_get, ray_logger, ray_remote  # noqa
+from awswrangler.distributed.ray._core import RayLogger, initialize_ray, ray_get, ray_logger, ray_remote
 
 __all__ = [
     "RayLogger",

awswrangler/distributed/ray/datasources/arrow_parquet_datasource.py

@@ -13,7 +13,7 @@
 import numpy as np
 
 # fs required to implicitly trigger S3 subsystem initialization
-import pyarrow.fs  # noqa: F401 pylint: disable=unused-import
+import pyarrow.fs  # pylint: disable=unused-import
 from pyarrow.dataset import ParquetFileFragment
 from pyarrow.lib import Schema
 from ray import cloudpickle
@@ -246,7 +246,7 @@ def __init__(
             _handle_read_os_error(e, paths)
         except pyarrow.ArrowInvalid as ex:
             if "Parquet file size is 0 bytes" in str(ex):
-                raise exceptions.InvalidFile(f"Invalid Parquet file. {str(ex)}")
+                raise exceptions.InvalidFile(f"Invalid Parquet file. {ex!s}")
             raise
         self._pq_ds = pq_ds
         self._meta_provider = meta_provider

awswrangler/emr.py

@@ -245,7 +245,7 @@ def _build_cluster_args(**pars: Any) -> Dict[str, Any]:  # pylint: disable=too-m
             {
                 "Classification": "spark-hive-site",
                 "Properties": {
-                    "hive.metastore.client.factory.class": "com.amazonaws.glue.catalog.metastore.AWSGlueDataCatalogHiveClientFactory"  # noqa
+                    "hive.metastore.client.factory.class": "com.amazonaws.glue.catalog.metastore.AWSGlueDataCatalogHiveClientFactory"
                 },
                 "Configurations": [],
             }

awswrangler/lakeformation/__init__.py

@@ -1,7 +1,7 @@
 """Amazon Lake Formation Module."""
 
-from awswrangler.lakeformation._read import read_sql_query, read_sql_table  # noqa
-from awswrangler.lakeformation._utils import (  # noqa
+from awswrangler.lakeformation._read import read_sql_query, read_sql_table
+from awswrangler.lakeformation._utils import (
     _build_table_objects,
     _get_table_objects,
     _update_table_objects,

awswrangler/lakeformation/_utils.py

@@ -34,9 +34,9 @@ def _build_partition_predicate(
     partition_predicates: List[str] = []
     for col, val in zip(partition_cols, partitions_values):
         if partitions_types[col].startswith(("tinyint", "smallint", "int", "bigint", "float", "double", "decimal")):
-            partition_predicates.append(f"{col}={str(val)}")
+            partition_predicates.append(f"{col}={val!s}")
         else:
-            partition_predicates.append(f"{col}='{str(val)}'")
+            partition_predicates.append(f"{col}='{val!s}'")
     return " AND ".join(partition_predicates)
 
 

awswrangler/neptune/_neptune.py

@@ -260,10 +260,10 @@ def to_rdf_graph(
         # build up a query
         if is_quads:
             insert = f"""INSERT DATA {{ GRAPH <{row[graph_column]}> {{<{row[subject_column]}>
-                    <{str(row[predicate_column])}> <{row[object_column]}> . }} }}; """
+                    <{row[predicate_column]!s}> <{row[object_column]}> . }} }}; """
             query = query + insert
         else:
-            insert = f"""INSERT DATA {{ <{row[subject_column]}> <{str(row[predicate_column])}>
+            insert = f"""INSERT DATA {{ <{row[subject_column]}> <{row[predicate_column]!s}>
                     <{row[object_column]}> . }}; """
             query = query + insert
         # run the query

awswrangler/opensearch/_read.py

@@ -116,7 +116,7 @@ def search(
     if is_scroll:
         if isinstance(filter_path, str):
             filter_path = [filter_path]
-        filter_path = ["_scroll_id", "_shards"] + list(filter_path)  # required for scroll
+        filter_path = ["_scroll_id", "_shards", *list(filter_path)]  # required for scroll
         documents_generator = opensearchpy.helpers.scan(
             client, index=index, query=search_body, filter_path=filter_path, **kwargs
         )

awswrangler/pandas/__init__.py

@@ -8,7 +8,7 @@
     from pandas import *  # noqa: F403
 
     # Explicit import because mypy doesn't support forward references to a star import
-    from pandas import (  # noqa: F401
+    from pandas import (
         DataFrame,
         Series,
         concat,
@@ -24,7 +24,7 @@
     from modin.pandas import *  # noqa: F403
 
     # Explicit import because mypy doesn't support forward references to a star import
-    from modin.pandas import (  # noqa: F401
+    from modin.pandas import (
         DataFrame,
         Series,
         concat,

awswrangler/quicksight/__init__.py

@@ -1,8 +1,8 @@
 """Amazon QuickSight Module."""
 
-from awswrangler.quicksight._cancel import cancel_ingestion  # noqa
-from awswrangler.quicksight._create import create_athena_data_source, create_athena_dataset, create_ingestion  # noqa
-from awswrangler.quicksight._delete import (  # noqa
+from awswrangler.quicksight._cancel import cancel_ingestion
+from awswrangler.quicksight._create import create_athena_data_source, create_athena_dataset, create_ingestion
+from awswrangler.quicksight._delete import (
     delete_all_dashboards,
     delete_all_data_sources,
     delete_all_datasets,
@@ -12,14 +12,14 @@
     delete_dataset,
     delete_template,
 )
-from awswrangler.quicksight._describe import (  # noqa
+from awswrangler.quicksight._describe import (
     describe_dashboard,
     describe_data_source,
     describe_data_source_permissions,
     describe_dataset,
     describe_ingestion,
 )
-from awswrangler.quicksight._get_list import (  # noqa
+from awswrangler.quicksight._get_list import (
     get_dashboard_id,
     get_dashboard_ids,
     get_data_source_arn,

awswrangler/s3/__init__.py

@@ -1,23 +1,23 @@
 """Amazon S3 Read Module."""
 
-from awswrangler.s3._copy import copy_objects, merge_datasets  # noqa
-from awswrangler.s3._delete import delete_objects  # noqa
-from awswrangler.s3._describe import describe_objects, get_bucket_region, size_objects  # noqa
-from awswrangler.s3._download import download  # noqa
-from awswrangler.s3._list import does_object_exist, list_buckets, list_directories, list_objects  # noqa
-from awswrangler.s3._read_deltalake import read_deltalake  # noqa
-from awswrangler.s3._read_excel import read_excel  # noqa
-from awswrangler.s3._read_orc import read_orc, read_orc_metadata, read_orc_table  # noqa
-from awswrangler.s3._read_parquet import read_parquet, read_parquet_metadata, read_parquet_table  # noqa
-from awswrangler.s3._read_text import read_csv, read_fwf, read_json  # noqa
+from awswrangler.s3._copy import copy_objects, merge_datasets
+from awswrangler.s3._delete import delete_objects
+from awswrangler.s3._describe import describe_objects, get_bucket_region, size_objects
+from awswrangler.s3._download import download
+from awswrangler.s3._list import does_object_exist, list_buckets, list_directories, list_objects
+from awswrangler.s3._read_deltalake import read_deltalake
+from awswrangler.s3._read_excel import read_excel
+from awswrangler.s3._read_orc import read_orc, read_orc_metadata, read_orc_table
+from awswrangler.s3._read_parquet import read_parquet, read_parquet_metadata, read_parquet_table
+from awswrangler.s3._read_text import read_csv, read_fwf, read_json
 from awswrangler.s3._select import select_query
-from awswrangler.s3._upload import upload  # noqa
-from awswrangler.s3._wait import wait_objects_exist, wait_objects_not_exist  # noqa
-from awswrangler.s3._write_deltalake import to_deltalake  # noqa
-from awswrangler.s3._write_excel import to_excel  # noqa
-from awswrangler.s3._write_orc import to_orc  # noqa
-from awswrangler.s3._write_parquet import store_parquet_metadata, to_parquet  # noqa
-from awswrangler.s3._write_text import to_csv, to_json  # noqa
+from awswrangler.s3._upload import upload
+from awswrangler.s3._wait import wait_objects_exist, wait_objects_not_exist
+from awswrangler.s3._write_deltalake import to_deltalake
+from awswrangler.s3._write_excel import to_excel
+from awswrangler.s3._write_orc import to_orc
+from awswrangler.s3._write_parquet import store_parquet_metadata, to_parquet
+from awswrangler.s3._write_text import to_csv, to_json
 
 __all__ = [
     "copy_objects",

awswrangler/s3/_read.py

@@ -52,7 +52,7 @@ def _get_path_ignore_suffix(path_ignore_suffix: Union[str, List[str], None]) ->
     elif path_ignore_suffix is None:
         path_ignore_suffix = ["/_SUCCESS"]
     else:
-        path_ignore_suffix = path_ignore_suffix + ["/_SUCCESS"]
+        path_ignore_suffix = [*path_ignore_suffix, "/_SUCCESS"]
     return path_ignore_suffix
 
 

awswrangler/timestream/_write.py

@@ -330,7 +330,7 @@ def write(
         _data_types.timestream_type_from_pandas(df.loc[:, measure_cols]) if all(measure_cols) else []
     )
     dimensions_cols = dimensions_cols if dimensions_cols else [dimensions_cols]  # type: ignore[list-item]
-    cols_names: List[Optional[str]] = [time_col] + measure_cols + dimensions_cols
+    cols_names: List[Optional[str]] = [time_col, *measure_cols, *dimensions_cols]
     measure_name = measure_name if measure_name else measure_cols[0]
     common_attributes = _sanitize_common_attributes(common_attributes, version, time_unit, measure_name)
 

fix.sh

@@ -2,4 +2,4 @@
 set -ex
 
 black .
-ruff --fix --select "I001" --select "I002" awswrangler
+ruff --fix awswrangler

pyproject.toml

@@ -158,9 +158,9 @@ extend_exclude = '''
 '''
 
 [tool.ruff]
-select = ["D", "E", "F", "I001", "I002", "PL", "W", "PD"]
-ignore = ["E501", "PLR2004", "PLR0911", "PLR0912", "PLR0913", "PLR0915", "PD901"]
-fixable = ["I001"]
+select = ["D", "E", "F", "I001", "I002", "PL", "W", "PD", "RUF"]
+ignore = ["E501", "PLR2004", "PLR0911", "PLR0912", "PLR0913", "PLR0915", "PD901", "RUF002", "RUF015"]
+fixable = ["I001", "I002", "RUF100", "RUF010"]
 exclude = [
     ".eggs",
     ".git",

validate.sh

@@ -2,7 +2,7 @@
 set -ex
 
 black --check .
-ruff . --ignore "PL" --ignore "D"
+ruff . --ignore "PL" --ignore "D" --ignore "RUF" --ignore "PD"
 ruff awswrangler
 mypy --install-types --non-interactive awswrangler
 pylint -j 0 --disable=all --enable=R0911,R0912,R0913,R0915 awswrangler