Optimize parallel_report_download.py to write to files

Refactored `examples/reporting/parallel_report_download.py` to write report results directly to disk in the worker processes.
This avoids collecting large result sets in memory and transmitting them back to the main process, significantly reducing memory usage and IPC overhead for large reports.
Updated the main loop to display the generated filenames instead of the raw data.

Author: google-labs-jules[bot]

examples/reporting/parallel_report_download.py

@@ -20,8 +20,10 @@
 """
 
 import argparse
+import hashlib
 from itertools import product
 import multiprocessing
+import os
 import time
 from typing import Any, Dict, Iterable, List, Tuple
 
@@ -94,10 +96,7 @@ def main(client: GoogleAdsClient, customer_ids: List[str]) -> None:
         print("Successes:") if len(successes) else None
         success: Dict[str, Any]
         for success in successes:
-            # success["results"] represents an array of result strings for one
-            # customer ID / query combination.
-            result_str: str = "\n".join(success["results"])
-            print(result_str)
+            print(f"Report written to file: {success['filename']}")
 
         print("Failures:") if len(failures) else None
         failure: Dict[str, Any]
@@ -141,27 +140,30 @@ def issue_search_request(
             stream: Iterable[SearchGoogleAdsStreamResponse] = (
                 ga_service.search_stream(customer_id=customer_id, query=query)
             )
-            # Returning a list of GoogleAdsRows will result in a
-            # PicklingError, so instead we put the GoogleAdsRow data
-            # into a list of str results and return that.
-            result_strings: List[str] = []
-            batch: SearchGoogleAdsStreamResponse
-            for batch in stream:
-                row: GoogleAdsRow
-                for row in batch.results:
-                    ad_group_id: str = (
-                        f"Ad Group ID {row.ad_group.id} in "
-                        if "ad_group.id" in query
-                        else ""
-                    )
-                    result_string: str = (
-                        f"{ad_group_id}"
-                        f"Campaign ID {row.campaign.id} "
-                        f"had {row.metrics.impressions} impressions "
-                        f"and {row.metrics.clicks} clicks."
-                    )
-                    result_strings.append(result_string)
-            return (True, {"results": result_strings})
+
+            # Create a unique filename for the report.
+            query_hash = hashlib.md5(query.encode("utf-8")).hexdigest()
+            filename = f"report_{customer_id}_{query_hash}.txt"
+
+            with open(filename, "w") as f:
+                batch: SearchGoogleAdsStreamResponse
+                for batch in stream:
+                    row: GoogleAdsRow
+                    for row in batch.results:
+                        ad_group_id: str = (
+                            f"Ad Group ID {row.ad_group.id} in "
+                            if "ad_group.id" in query
+                            else ""
+                        )
+                        result_string: str = (
+                            f"{ad_group_id}"
+                            f"Campaign ID {row.campaign.id} "
+                            f"had {row.metrics.impressions} impressions "
+                            f"and {row.metrics.clicks} clicks."
+                        )
+                        f.write(result_string + "\n")
+
+            return (True, {"filename": filename})
         except GoogleAdsException as ex:
             # This example retries on all GoogleAdsExceptions. In practice,
             # developers might want to limit retries to only those error codes