Bound assigned-issue reminder snapshots

src/gitea_proxy.py

@@ -403,15 +403,39 @@ async def work_page(stream: str, page: int = 1, limit: int = 50) -> dict:
     }
 
 
-async def assigned_issue_snapshot(*, limit: int = 50, max_pages: int = 20) -> dict:
+async def assigned_issue_snapshot(
+    *,
+    limit: int = 50,
+    max_pages: int = 20,
+    max_concurrency: int = 4,
+    deadline_seconds: float = 5.0,
+) -> dict:
     """Load a complete, bounded assigned-issue snapshot for deadline dispatch."""
-    items = []
-    for page in range(1, max_pages + 1):
-        result = await work_page("issue", page, limit)
-        items.extend(result["items"])
-        if not result["has_more"]:
-            return {"items": items, "complete": True}
-    return {"items": [], "complete": False}
+    async with asyncio.timeout(deadline_seconds):
+        first = await work_page("issue", 1, limit)
+        page_count = max(1, (first["total"] + limit - 1) // limit)
+        if page_count > max_pages:
+            raise ValueError("Assigned issue snapshot exceeds the scan limit")
+        semaphore = asyncio.Semaphore(max(1, max_concurrency))
+
+        async def load(page: int) -> dict:
+            async with semaphore:
+                return await work_page("issue", page, limit)
+
+        remaining = await asyncio.gather(
+            *(load(page) for page in range(2, page_count + 1))
+        )
+    pages = [first, *remaining]
+    if any(page.get("total") != first["total"] for page in pages[1:]):
+        raise ValueError("Assigned issue pagination changed during the scan")
+    items = [item for page in pages for item in page["items"]]
+    issue_ids = [
+        item.get("id") for item in items
+        if isinstance(item, dict) and isinstance(item.get("id"), int) and item["id"] > 0
+    ]
+    if len(items) != first["total"] or len(set(issue_ids)) != first["total"]:
+        raise ValueError("Assigned issue snapshot has an incomplete issue set")
+    return {"items": items, "complete": True}
 
 
 def _normalize_global_search_item(item: Any, kind: str) -> dict | None: