Script to find airflow jobs that failed to parse rt data

runbooks/data/find_missing_rt_parsed_files.py

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+"""
+Script that checks if an outcomes file exists for an RT parsing job.  If it exists, that means the job completed successfully.
+
+If it doesn't exist, the job either failed midway or or never ran.  This only properly analyzes results from the parse_and_validate_v2 airflow job.  In the new airflow job parse_and_validate,
+now each agency is parsed separately so it's possible some agencies were parsed and others were not.
+"""
+import time
+
+import pandas as pd
+from google.cloud import storage
+
+client = storage.Client(project="cal-itp-data-infra")
+
+# calitp-gtfs-rt-parsed/trip_updates_outcomes/dt=2025-08-25/hour=2025-08-25T00:00:00+00:00/trip_updates.jsonl
+# calitp-gtfs-rt-parsed/service_alerts_outcomes/dt=2022-09-15/hour=2022-09-15T20:00:00+00:00
+# vehicle_positions_outcomes/
+hours = [
+    f"{dt.strftime('%Y-%m-%dT%H:00:00+00:00')}"
+    for dt in pd.date_range("2022-09-15", "2025-09-09", freq="H")[:-1]
+]
+
+generated_file_paths = []
+paths = [
+    "trip_updates_outcomes/",
+    "service_alerts_outcomes/",
+    "vehicle_positions_outcomes/",
+]
+for path in paths:
+    for hour in hours:
+        dt_str = hour[0:10]
+        full_path = f"{path}dt={dt_str}/hour={hour}"
+        generated_file_paths.append(full_path)
+print(generated_file_paths[20])
+
+
+bucket_name = "calitp-gtfs-rt-parsed"
+# calitp-gtfs-rt-parsed/trip_updates_outcomes/dt=2025-08-25/hour=2025-08-25T04:00:00+00:00/trip_updates.jsonl
+prefixes = [
+    "trip_updates_outcomes/",
+    "service_alerts_outcomes/",
+    "vehicle_positions_outcomes/",
+]
+bucket = client.get_bucket(bucket_name)
+seen_files_in_parsed_bucket = []
+start = time.time()
+for prefix in prefixes:
+    blob_iterator = bucket.list_blobs(prefix=prefix)
+    seen_files_in_parsed_bucket.extend([(blob.name) for blob in blob_iterator])
+end = time.time()
+print(f"Elapsed time: {end - start:.2f} seconds")
+
+
+# Remove the filename from each path keeping only the directory portion
+seen_dirs_in_parsed_bucket = [
+    fp.rsplit("/", 1)[0] for fp in seen_files_in_parsed_bucket
+]
+print(seen_dirs_in_parsed_bucket[:5])
+
+
+# Use sets to find the difference between expected and actual file paths
+expected_set = set(generated_file_paths)
+actual_set = set(seen_dirs_in_parsed_bucket)
+missing_files = expected_set - actual_set
+extra_files = actual_set - expected_set
+print(f"Missing files: {len(missing_files)}")
+print(f"Extra files: {len(extra_files)}")
+print("Sample missing files:", list(missing_files)[:5])
+print("Sample extra files:", list(extra_files)[:5])
+
+
+# Write missing files to a text file
+with open("missing_files_to_process.txt", "w") as f:
+    for path in sorted(missing_files):
+        f.write(path + "\n")