feat: structured DEBUG/INFO logging via loguru

- common/logging.py: improve format to timestamp|LEVEL|module:func:line - message
- core/ layer: DEBUG log every subprocess invocation (cmd, rc, byte counts),
  JSON load/dump events, parsed application_id. ERROR log on failures.
- tools/ layer: DEBUG log every public tool entry with key parameters,
  INFO log on business outcomes (saved/submitted/killed/...).
- New tests/unit/test_logging.py: capture loguru output via in-memory sink
  and assert DEBUG + INFO messages are emitted for representative flows.

spark_executor/tools/connections.py

@@ -16,6 +16,10 @@ def save_connection(
     yarn_rm_url: str | None = None,
     spark_conf: dict[str, str] | None = None,
 ) -> dict[str, str]:
+    logger.debug(
+        f"save_connection enter name={name} master={master} deploy_mode={deploy_mode} "
+        f"yarn_rm_url={yarn_rm_url} spark_conf_keys={list((spark_conf or {}).keys())}"
+    )
     conn = Connection(
         name=name,
         master=master,
@@ -24,15 +28,16 @@ def save_connection(
         spark_conf=spark_conf or {},
     )
     store.save(conn)
-    logger.info(f"save_connection name={name} master={master}")
     return {"name": name, "status": "SAVED"}
 
 
 def list_connections() -> list[dict[str, object]]:
+    logger.debug("list_connections enter")
     return [c.model_dump() for c in store.list_all()]
 
 
 def get_connection(name: str) -> dict[str, object]:
+    logger.debug(f"get_connection enter name={name}")
     conn = store.get(name)
     if conn is None:
         raise KeyError(f"Unknown connection: {name}")
@@ -40,8 +45,8 @@ def get_connection(name: str) -> dict[str, object]:
 
 
 def delete_connection(name: str) -> dict[str, str]:
+    logger.debug(f"delete_connection enter name={name}")
     removed = store.delete(name)
     if not removed:
         raise KeyError(f"Unknown connection: {name}")
-    logger.info(f"delete_connection name={name}")
     return {"name": name, "status": "DELETED"}