chore: drop redundant "r" mode argument to open() (ruff UP015)

examples/episodic_stage5_smoke_test.py

@@ -196,7 +196,7 @@ async def test_5_6_pgvector_upsert():
     )
 
     try:
-        with open(pgvector_path, "r", encoding="utf-8") as f:
+        with open(pgvector_path, encoding="utf-8") as f:
             source = f.read()
     except FileNotFoundError:
         print("  ⚠️ PGVectorAdapter.py 文件未找到，跳过测试")

m_flow/debug/trace_cli.py

@@ -58,7 +58,7 @@ def list_recent_traces(base_dir: str, limit: int = 20) -> List[Dict[str, Any]]:
 def load_events(path: str) -> List[Dict[str, Any]]:
     """Load trace events."""
     events = []
-    with open(path, "r", encoding="utf-8") as f:
+    with open(path, encoding="utf-8") as f:
         for line in f:
             try:
                 events.append(json.loads(line))

m_flow/eval/config.py

@@ -88,7 +88,7 @@ def save(self, path: str) -> None:
     @classmethod
     def load(cls, path: str) -> "EvalConfig":
         """Load configuration from file"""
-        with open(path, "r", encoding="utf-8") as f:
+        with open(path, encoding="utf-8") as f:
             data = json.load(f)
 
         return cls(

m_flow/eval/loader.py

@@ -134,7 +134,7 @@ def load(self) -> List[EvalCase]:
         if not os.path.exists(self.dataset_path):
             raise FileNotFoundError(f"Dataset not found: {self.dataset_path}")
 
-        with open(self.dataset_path, "r", encoding="utf-8") as f:
+        with open(self.dataset_path, encoding="utf-8") as f:
             for line_num, line in enumerate(f, 1):
                 line = line.strip()
                 if not line:

m_flow/eval/report.py

@@ -357,7 +357,7 @@ def save_markdown(self, path: str) -> None:
     @classmethod
     def load(cls, path: str) -> "EvalReport":
         """Load report from JSON."""
-        with open(path, "r", encoding="utf-8") as f:
+        with open(path, encoding="utf-8") as f:
             data = json.load(f)
 
         from .metrics import TypeMetrics, EvalMetricsResult

m_flow/llm/prompts/read_query_prompt.py

@@ -33,7 +33,7 @@ def read_query_prompt(
     target = path.join(base, prompt_file_name)
 
     try:
-        with open(target, "r", encoding="utf-8") as f:
+        with open(target, encoding="utf-8") as f:
             return f.read()
     except FileNotFoundError:
         _log.error(f"Prompt not found: {target}")

m_flow/shared/loaders/core/csv_loader.py

@@ -86,7 +86,7 @@ async def load(
 
         # Parse CSV and format rows
         formatted_rows: list[str] = []
-        with open(file_path, "r", encoding=encoding, newline="") as text_handle:
+        with open(file_path, encoding=encoding, newline="") as text_handle:
             reader = csv.DictReader(text_handle)
             for row_index, row_data in enumerate(reader, start=1):
                 formatted_rows.append(_format_row(row_index, row_data))

m_flow/shared/loaders/core/text_loader.py

@@ -49,7 +49,7 @@ async def load(self, file_path: str, encoding: str = "utf-8", **kwargs):
 
         dest_name = f"text_{meta['content_hash']}.txt"
 
-        with open(file_path, "r", encoding=encoding) as fh:
+        with open(file_path, encoding=encoding) as fh:
             body = fh.read()
 
         cfg = get_storage_config()

m_flow/tests/tasks/descriptive_metrics/metrics_test_utils.py

@@ -129,7 +129,7 @@ async def build_connected_graph() -> None:
 def load_ground_truth() -> dict[str, Any]:
     """Load expected metrics from ground truth JSON."""
     gt_file = Path(__file__).parent / "ground_truth_metrics.json"
-    with open(gt_file, "r", encoding="utf-8") as f:
+    with open(gt_file, encoding="utf-8") as f:
         return json.load(f)