feat(pending): app_name field and date-sharded pending storage

- Add optional app_name to PendingSubmission and prepare_submit_job,
  passed through PrepareSubmitJobRequest for user-provided tracking.
- Rewrite PendingStore to shard records by UTC date under
  data/pending_jobs/YYYY-MM-DD.json instead of a single monolithic
  pending_jobs.json.
- Legacy single-file pending_jobs.json remains readable; first save()
  migrates it and renames the old file to avoid double reads.
- Tests cover date sharding, multi-date list, legacy read, legacy
  migration, and app_name round-trip.

spark_executor/tools/requests.py

@@ -33,6 +33,10 @@ class SaveConnectionRequest(BaseModel):
 
 class PrepareSubmitJobRequest(BaseModel):
     connection: str
+    app_name: str | None = Field(
+        default=None,
+        description="Optional human-readable application name for tracking the pending submission.",
+    )
     script_path: str = Field(
         ...,
         description=(

spark_executor/tools/submit.py

@@ -68,6 +68,7 @@ def prepare_submit_job(
     executor_memory: str = "4G",
     executor_cores: int = 2,
     num_executors: int = 2,
+    app_name: str | None = None,
 ) -> dict[str, object]:
     """Snapshot connection params and persist a PendingSubmission. Does NOT submit."""
     logger.debug(
@@ -109,6 +110,7 @@ def prepare_submit_job(
     pending_id = _new_pending_id()
     pending = PendingSubmission(
         pending_id=pending_id,
+        app_name=app_name,
         connection=connection,
         master=conn.master,
         deploy_mode=conn.deploy_mode,