Merge pull request #8225 from freqtrade/ruff2

Ruff - add PTH rule and subsequent changes

freqtrade/configuration/load_config.py

@@ -58,7 +58,7 @@ def load_config_file(path: str) -> Dict[str, Any]:
     """
     try:
         # Read config from stdin if requested in the options
-        with open(path) if path != '-' else sys.stdin as file:
+        with Path(path).open() if path != '-' else sys.stdin as file:
             config = rapidjson.load(file, parse_mode=CONFIG_PARSE_MODE)
     except FileNotFoundError:
         raise OperationalException(

freqtrade/data/entryexitanalysis.py

@@ -24,9 +24,9 @@ def _load_signal_candles(backtest_dir: Path):
         scpf = Path(backtest_dir.parent / f"{backtest_dir.stem}_signals.pkl")
 
     try:
-        scp = open(scpf, "rb")
-        signal_candles = joblib.load(scp)
-        logger.info(f"Loaded signal candles: {str(scpf)}")
+        with scpf.open("rb") as scp:
+            signal_candles = joblib.load(scp)
+            logger.info(f"Loaded signal candles: {str(scpf)}")
     except Exception as e:
         logger.error("Cannot load signal candles from pickled results: ", e)
 

freqtrade/exchange/binance.py

@@ -195,7 +195,7 @@ class Binance(Exchange):
                 leverage_tiers_path = (
                     Path(__file__).parent / 'binance_leverage_tiers.json'
                 )
-                with open(leverage_tiers_path) as json_file:
+                with leverage_tiers_path.open() as json_file:
                     return json_load(json_file)
             else:
                 try:

freqtrade/freqai/data_drawer.py

@@ -126,7 +126,7 @@ class FreqaiDataDrawer:
         """
         exists = self.global_metadata_path.is_file()
         if exists:
-            with open(self.global_metadata_path, "r") as fp:
+            with self.global_metadata_path.open("r") as fp:
                 metatada_dict = rapidjson.load(fp, number_mode=rapidjson.NM_NATIVE)
                 return metatada_dict
         return {}
@@ -139,7 +139,7 @@ class FreqaiDataDrawer:
         """
         exists = self.pair_dictionary_path.is_file()
         if exists:
-            with open(self.pair_dictionary_path, "r") as fp:
+            with self.pair_dictionary_path.open("r") as fp:
                 self.pair_dict = rapidjson.load(fp, number_mode=rapidjson.NM_NATIVE)
         else:
             logger.info("Could not find existing datadrawer, starting from scratch")
@@ -152,7 +152,7 @@ class FreqaiDataDrawer:
         if self.freqai_info.get('write_metrics_to_disk', False):
             exists = self.metric_tracker_path.is_file()
             if exists:
-                with open(self.metric_tracker_path, "r") as fp:
+                with self.metric_tracker_path.open("r") as fp:
                     self.metric_tracker = rapidjson.load(fp, number_mode=rapidjson.NM_NATIVE)
                 logger.info("Loading existing metric tracker from disk.")
             else:
@@ -166,7 +166,7 @@ class FreqaiDataDrawer:
         exists = self.historic_predictions_path.is_file()
         if exists:
             try:
-                with open(self.historic_predictions_path, "rb") as fp:
+                with self.historic_predictions_path.open("rb") as fp:
                     self.historic_predictions = cloudpickle.load(fp)
                 logger.info(
                     f"Found existing historic predictions at {self.full_path}, but beware "
@@ -176,7 +176,7 @@ class FreqaiDataDrawer:
             except EOFError:
                 logger.warning(
                     'Historical prediction file was corrupted. Trying to load backup file.')
-                with open(self.historic_predictions_bkp_path, "rb") as fp:
+                with self.historic_predictions_bkp_path.open("rb") as fp:
                     self.historic_predictions = cloudpickle.load(fp)
                 logger.warning('FreqAI successfully loaded the backup historical predictions file.')
 
@@ -189,7 +189,7 @@ class FreqaiDataDrawer:
         """
         Save historic predictions pickle to disk
         """
-        with open(self.historic_predictions_path, "wb") as fp:
+        with self.historic_predictions_path.open("wb") as fp:
             cloudpickle.dump(self.historic_predictions, fp, protocol=cloudpickle.DEFAULT_PROTOCOL)
 
         # create a backup
@@ -200,16 +200,16 @@ class FreqaiDataDrawer:
         Save metric tracker of all pair metrics collected.
         """
         with self.save_lock:
-            with open(self.metric_tracker_path, 'w') as fp:
+            with self.metric_tracker_path.open('w') as fp:
                 rapidjson.dump(self.metric_tracker, fp, default=self.np_encoder,
                                number_mode=rapidjson.NM_NATIVE)
 
-    def save_drawer_to_disk(self):
+    def save_drawer_to_disk(self) -> None:
         """
         Save data drawer full of all pair model metadata in present model folder.
         """
         with self.save_lock:
-            with open(self.pair_dictionary_path, 'w') as fp:
+            with self.pair_dictionary_path.open('w') as fp:
                 rapidjson.dump(self.pair_dict, fp, default=self.np_encoder,
                                number_mode=rapidjson.NM_NATIVE)
 
@@ -218,7 +218,7 @@ class FreqaiDataDrawer:
         Save global metadata json to disk
         """
         with self.save_lock:
-            with open(self.global_metadata_path, 'w') as fp:
+            with self.global_metadata_path.open('w') as fp:
                 rapidjson.dump(metadata, fp, default=self.np_encoder,
                                number_mode=rapidjson.NM_NATIVE)
 
@@ -424,7 +424,7 @@ class FreqaiDataDrawer:
         dk.data["training_features_list"] = list(dk.data_dictionary["train_features"].columns)
         dk.data["label_list"] = dk.label_list
 
-        with open(save_path / f"{dk.model_filename}_metadata.json", "w") as fp:
+        with (save_path / f"{dk.model_filename}_metadata.json").open("w") as fp:
             rapidjson.dump(dk.data, fp, default=self.np_encoder, number_mode=rapidjson.NM_NATIVE)
 
         return
@@ -457,7 +457,7 @@ class FreqaiDataDrawer:
         dk.data["training_features_list"] = dk.training_features_list
         dk.data["label_list"] = dk.label_list
         # store the metadata
-        with open(save_path / f"{dk.model_filename}_metadata.json", "w") as fp:
+        with (save_path / f"{dk.model_filename}_metadata.json").open("w") as fp:
             rapidjson.dump(dk.data, fp, default=self.np_encoder, number_mode=rapidjson.NM_NATIVE)
 
         # save the train data to file so we can check preds for area of applicability later
@@ -471,7 +471,7 @@ class FreqaiDataDrawer:
 
         if self.freqai_info["feature_parameters"].get("principal_component_analysis"):
             cloudpickle.dump(
-                dk.pca, open(dk.data_path / f"{dk.model_filename}_pca_object.pkl", "wb")
+                dk.pca, (dk.data_path / f"{dk.model_filename}_pca_object.pkl").open("wb")
             )
 
         self.model_dictionary[coin] = model
@@ -491,7 +491,7 @@ class FreqaiDataDrawer:
         Load only metadata into datakitchen to increase performance during
         presaved backtesting (prediction file loading).
         """
-        with open(dk.data_path / f"{dk.model_filename}_metadata.json", "r") as fp:
+        with (dk.data_path / f"{dk.model_filename}_metadata.json").open("r") as fp:
             dk.data = rapidjson.load(fp, number_mode=rapidjson.NM_NATIVE)
             dk.training_features_list = dk.data["training_features_list"]
             dk.label_list = dk.data["label_list"]
@@ -514,7 +514,7 @@ class FreqaiDataDrawer:
             dk.data = self.meta_data_dictionary[coin]["meta_data"]
             dk.data_dictionary["train_features"] = self.meta_data_dictionary[coin]["train_df"]
         else:
-            with open(dk.data_path / f"{dk.model_filename}_metadata.json", "r") as fp:
+            with (dk.data_path / f"{dk.model_filename}_metadata.json").open("r") as fp:
                 dk.data = rapidjson.load(fp, number_mode=rapidjson.NM_NATIVE)
 
             dk.data_dictionary["train_features"] = pd.read_pickle(
@@ -552,7 +552,7 @@ class FreqaiDataDrawer:
 
         if self.config["freqai"]["feature_parameters"]["principal_component_analysis"]:
             dk.pca = cloudpickle.load(
-                open(dk.data_path / f"{dk.model_filename}_pca_object.pkl", "rb")
+                (dk.data_path / f"{dk.model_filename}_pca_object.pkl").open("rb")
             )
 
         return model

freqtrade/freqai/utils.py

@@ -211,7 +211,7 @@ def record_params(config: Dict[str, Any], full_path: Path) -> None:
         "pairs": config.get('exchange', {}).get('pair_whitelist')
     }
 
-    with open(params_record_path, "w") as handle:
+    with params_record_path.open("w") as handle:
         rapidjson.dump(
             run_params,
             handle,

freqtrade/misc.py

@@ -81,7 +81,7 @@ def file_dump_json(filename: Path, data: Any, is_zip: bool = False, log: bool =
     else:
         if log:
             logger.info(f'dumping json to "{filename}"')
-        with open(filename, 'w') as fp:
+        with filename.open('w') as fp:
             rapidjson.dump(data, fp, default=str, number_mode=rapidjson.NM_NATIVE)
 
     logger.debug(f'done json to "{filename}"')
@@ -98,7 +98,7 @@ def file_dump_joblib(filename: Path, data: Any, log: bool = True) -> None:
 
     if log:
         logger.info(f'dumping joblib to "{filename}"')
-    with open(filename, 'wb') as fp:
+    with filename.open('wb') as fp:
         joblib.dump(data, fp)
     logger.debug(f'done joblib dump to "{filename}"')
 
@@ -112,7 +112,7 @@ def json_load(datafile: IO) -> Any:
     return rapidjson.load(datafile, number_mode=rapidjson.NM_NATIVE)
 
 
-def file_load_json(file):
+def file_load_json(file: Path):
 
     if file.suffix != ".gz":
         gzipfile = file.with_suffix(file.suffix + '.gz')
@@ -125,7 +125,7 @@ def file_load_json(file):
             pairdata = json_load(datafile)
     elif file.is_file():
         logger.debug(f"Loading historical data from file {file}")
-        with open(file) as datafile:
+        with file.open() as datafile:
             pairdata = json_load(datafile)
     else:
         return None

freqtrade/optimize/backtest_caching.py

@@ -29,7 +29,7 @@ def get_strategy_run_id(strategy) -> str:
     # Include _ft_params_from_file - so changing parameter files cause cache eviction
     digest.update(rapidjson.dumps(
         strategy._ft_params_from_file, default=str, number_mode=rapidjson.NM_NAN).encode('utf-8'))
-    with open(strategy.__file__, 'rb') as fp:
+    with Path(strategy.__file__).open('rb') as fp:
         digest.update(fp.read())
     return digest.hexdigest().lower()
 

freqtrade/plugins/pairlist/RemotePairList.py

@@ -157,7 +157,7 @@ class RemotePairList(IPairList):
                 file_path = Path(filename)
 
                 if file_path.exists():
-                    with open(filename) as json_file:
+                    with file_path.open() as json_file:
                         # Load the JSON data into a dictionary
                         jsonparse = json.load(json_file)
 

pyproject.toml

@@ -72,7 +72,7 @@ extend-select = [
   # "DTZ",  # flake8-datetimez
   # "RSE",  # flake8-raise
   # "TCH",  # flake8-type-checking
-  # "PTH",  # flake8-use-pathlib
+  "PTH",  # flake8-use-pathlib
 ]
 
 [tool.ruff.mccabe]

tests/data/test_history.py

@@ -191,7 +191,7 @@ def test_load_cached_data_for_updating(mocker, testdatadir) -> None:
 
     test_data = None
     test_filename = testdatadir.joinpath('UNITTEST_BTC-1m.json')
-    with open(test_filename, "rt") as file:
+    with test_filename.open("rt") as file:
         test_data = json.load(file)
 
     test_data_df = ohlcv_to_dataframe(test_data, '1m', 'UNITTEST/BTC',

tests/optimize/test_optimize_reports.py

@@ -255,7 +255,7 @@ def test_write_read_backtest_candles(tmpdir):
 
     # test directory exporting
     stored_file = store_backtest_signal_candles(Path(tmpdir), candle_dict, '2022_01_01_15_05_13')
-    scp = open(stored_file, "rb")
+    scp = stored_file.open("rb")
     pickled_signal_candles = joblib.load(scp)
     scp.close()
 
@@ -269,7 +269,7 @@ def test_write_read_backtest_candles(tmpdir):
     # test file exporting
     filename = Path(tmpdir / 'testresult')
     stored_file = store_backtest_signal_candles(filename, candle_dict, '2022_01_01_15_05_13')
-    scp = open(stored_file, "rb")
+    scp = stored_file.open("rb")
     pickled_signal_candles = joblib.load(scp)
     scp.close()
 

tests/test_configuration.py

@@ -59,7 +59,7 @@ def test_load_config_incorrect_stake_amount(default_conf) -> None:
 def test_load_config_file(default_conf, mocker, caplog) -> None:
     del default_conf['user_data_dir']
     default_conf['datadir'] = str(default_conf['datadir'])
-    file_mock = mocker.patch('freqtrade.configuration.load_config.open', mocker.mock_open(
+    file_mock = mocker.patch('freqtrade.configuration.load_config.Path.open', mocker.mock_open(
         read_data=json.dumps(default_conf)
     ))
 
@@ -73,7 +73,8 @@ def test_load_config_file_error(default_conf, mocker, caplog) -> None:
     default_conf['datadir'] = str(default_conf['datadir'])
     filedata = json.dumps(default_conf).replace(
         '"stake_amount": 0.001,', '"stake_amount": .001,')
-    mocker.patch('freqtrade.configuration.load_config.open', mocker.mock_open(read_data=filedata))
+    mocker.patch('freqtrade.configuration.load_config.Path.open',
+                 mocker.mock_open(read_data=filedata))
     mocker.patch.object(Path, "read_text", MagicMock(return_value=filedata))
 
     with pytest.raises(OperationalException, match=r".*Please verify the following segment.*"):
@@ -272,7 +273,7 @@ def test_load_config_max_open_trades_minus_one(default_conf, mocker, caplog) ->
 
 def test_load_config_file_exception(mocker) -> None:
     mocker.patch(
-        'freqtrade.configuration.configuration.open',
+        'freqtrade.configuration.configuration.Path.open',
         MagicMock(side_effect=FileNotFoundError('File not found'))
     )
 

tests/test_misc.py

@@ -46,7 +46,7 @@ def test_shorten_date() -> None:
 
 
 def test_file_dump_json(mocker) -> None:
-    file_open = mocker.patch('freqtrade.misc.open', MagicMock())
+    file_open = mocker.patch('freqtrade.misc.Path.open', MagicMock())
     json_dump = mocker.patch('rapidjson.dump', MagicMock())
     file_dump_json(Path('somefile'), [1, 2, 3])
     assert file_open.call_count == 1