refactor: move _get_max_threads() to CommandExecutor

- Move function from common.py to CommandExecutor as private method
- Simplifies code by using self.parameter_manager directly
- Remove unnecessary import and parameter passing

https://claude.ai/code/session_01XGuw7AxoKRWHr9EZX1SDXi

Author: claude

src/common/common.py

@@ -32,33 +32,6 @@
 OS_PLATFORM = sys.platform
 
 
-def get_max_threads(parameter_manager=None) -> int:
-    """
-    Get max threads for current deployment mode.
-
-    In local mode, reads from parameter manager (persisted params.json).
-    In online mode, uses the configured value directly from settings.
-
-    Args:
-        parameter_manager: Optional ParameterManager instance for reading persisted params.
-
-    Returns:
-        int: Maximum number of threads to use for parallel processing.
-    """
-    settings = st.session_state.get("settings", {})
-    max_threads_config = settings.get("max_threads", {"local": 4, "online": 2})
-
-    if settings.get("online_deployment", False):
-        return max_threads_config.get("online", 2)
-    else:
-        # Local mode: read from parameter manager if available
-        default = max_threads_config.get("local", 4)
-        if parameter_manager is not None:
-            params = parameter_manager.get_parameters_from_json()
-            return params.get("max_threads", default)
-        return default
-
-
 def is_safe_workspace_name(name: str) -> bool:
     """
     Check if a workspace name is safe (no path traversal characters).

src/workflow/CommandExecutor.py

@@ -25,6 +25,27 @@ def __init__(self, workflow_dir: Path, logger: Logger, parameter_manager: Parame
         self.logger = logger
         self.parameter_manager = parameter_manager
 
+    def _get_max_threads(self) -> int:
+        """
+        Get max threads for current deployment mode.
+
+        In local mode, reads from parameter manager (persisted params.json).
+        In online mode, uses the configured value directly from settings.
+
+        Returns:
+            int: Maximum number of threads to use for parallel processing.
+        """
+        import streamlit as st
+        settings = st.session_state.get("settings", {})
+        max_threads_config = settings.get("max_threads", {"local": 4, "online": 2})
+
+        if settings.get("online_deployment", False):
+            return max_threads_config.get("online", 2)
+        else:
+            default = max_threads_config.get("local", 4)
+            params = self.parameter_manager.get_parameters_from_json()
+            return params.get("max_threads", default)
+
     def run_multiple_commands(
         self, commands: list[str]
     ) -> bool:
@@ -43,10 +64,8 @@ def run_multiple_commands(
         Returns:
             bool: True if all commands succeeded, False if any failed.
         """
-        from src.common.common import get_max_threads
-
         # Get thread settings and calculate distribution
-        max_threads = get_max_threads(self.parameter_manager)
+        max_threads = self._get_max_threads()
         num_commands = len(commands)
         parallel_commands = min(num_commands, max_threads)
 
@@ -234,8 +253,7 @@ def run_topp(self, tool: str, input_output: dict, custom_params: dict = {}) -> b
             n_processes = max(io_lengths)
 
         # Calculate threads per command based on max_threads setting
-        from src.common.common import get_max_threads
-        max_threads = get_max_threads(self.parameter_manager)
+        max_threads = self._get_max_threads()
         parallel_commands = min(n_processes, max_threads)
         threads_per_command = max(1, max_threads // parallel_commands)