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/submit.py

@@ -4,6 +4,7 @@
 @Author :tao.chen
 """
 import secrets
+import uuid
 from datetime import datetime
 
 from common.logging import logger
@@ -17,8 +18,6 @@ from spark_executor.core.spark_submit import (
     run_spark_submit,
 )
 from spark_executor.models import Job, PendingSubmission, SubmitResult
-import uuid
-from datetime import datetime as _datetime
 
 
 def _new_pending_id() -> str:
@@ -35,6 +34,11 @@ def prepare_submit_job(
     num_executors: int = 2,
 ) -> dict[str, object]:
     """Snapshot connection params and persist a PendingSubmission. Does NOT submit."""
+    logger.debug(
+        f"prepare_submit_job enter connection={connection} script_path={script_path} "
+        f"queue={queue} executor_memory={executor_memory} executor_cores={executor_cores} "
+        f"num_executors={num_executors}"
+    )
     conn = conn_store.get(connection)
     if conn is None:
         raise KeyError(f"Unknown connection: {connection}")
@@ -56,7 +60,8 @@ def prepare_submit_job(
     )
     pending_store.save(pending)
     logger.info(
-        f"prepare_submit_job pending_id={pending_id} connection={connection} master={conn.master}"
+        f"prepare_submit_job ok pending_id={pending_id} connection={connection} "
+        f"master={conn.master} script_path={script_path}"
     )
     return {
         "pending_id": pending_id,
@@ -71,6 +76,7 @@ job_store: JobStore = JobStore()
 
 def confirm_submit_job(*, pending_id: str) -> SubmitResult:
     """Actually invoke spark-submit for a previously-prepared PendingSubmission."""
+    logger.debug(f"confirm_submit_job enter pending_id={pending_id}")
     pending = pending_store.get(pending_id)
     if pending is None:
         raise KeyError(f"Unknown pending_id: {pending_id}")
@@ -89,13 +95,17 @@ def confirm_submit_job(*, pending_id: str) -> SubmitResult:
         num_executors=pending.num_executors,
         spark_conf=pending.spark_conf,
     )
-    logger.info(f"confirm_submit_job pending_id={pending_id} cmd={cmd}")
+    logger.info(
+        f"confirm_submit_job start pending_id={pending_id} "
+        f"application_target={pending.master} script_path={pending.script_path}"
+    )
     try:
         result = run_spark_submit(cmd)
     except SparkSubmitError as exc:
         pending.status = "FAILED"
         pending.error = str(exc)
         pending_store.save(pending)
+        logger.error(f"confirm_submit_job failed pending_id={pending_id} err={exc}")
         raise
 
     application_id, tracking_url = parse_spark_submit_output(result.stderr)
@@ -107,7 +117,7 @@ def confirm_submit_job(*, pending_id: str) -> SubmitResult:
             application_id=application_id,
             script_path=pending.script_path,
             queue=pending.queue,
-            submit_time=_datetime.utcnow(),
+            submit_time=datetime.utcnow(),
             connection=pending.connection,
         )
     )
@@ -117,7 +127,8 @@ def confirm_submit_job(*, pending_id: str) -> SubmitResult:
     pending.application_id = application_id
     pending_store.save(pending)
     logger.info(
-        f"confirm_submit_job pending_id={pending_id} job_id={job_id} application_id={application_id}"
+        f"confirm_submit_job ok pending_id={pending_id} job_id={job_id} "
+        f"application_id={application_id}"
     )
     return SubmitResult(
         job_id=job_id,
@@ -127,10 +138,12 @@ def confirm_submit_job(*, pending_id: str) -> SubmitResult:
 
 
 def list_pending_jobs() -> list[dict[str, object]]:
+    logger.debug("list_pending_jobs enter")
     return [p.model_dump() for p in pending_store.list_all()]
 
 
 def get_pending_job(pending_id: str) -> dict[str, object]:
+    logger.debug(f"get_pending_job enter pending_id={pending_id}")
     p = pending_store.get(pending_id)
     if p is None:
         raise KeyError(f"Unknown pending_id: {pending_id}")
@@ -138,6 +151,7 @@ def get_pending_job(pending_id: str) -> dict[str, object]:
 
 
 def cancel_pending_job(pending_id: str) -> dict[str, str]:
+    logger.debug(f"cancel_pending_job enter pending_id={pending_id}")
     p = pending_store.get(pending_id)
     if p is None:
         raise KeyError(f"Unknown pending_id: {pending_id}")
@@ -147,5 +161,5 @@ def cancel_pending_job(pending_id: str) -> dict[str, str]:
         )
     p.status = "CANCELLED"
     pending_store.save(p)
-    logger.info(f"cancel_pending_job pending_id={pending_id}")
+    logger.info(f"cancel_pending_job ok pending_id={pending_id}")
     return {"pending_id": pending_id, "status": "CANCELLED"}