tirkarthi opened a new issue, #59082: URL: https://github.com/apache/airflow/issues/59082
### Description While looking into fastapi discussions I noticed that returning models could result in revalidation of the model though the validation was done during model construction. There were also issues with serialization using jsonable_encoder mentioned in the thread. To validate this I did some combinations benchmark to return pydantic model, serialized response using json and serialized response using orjson after validation for a simple "ui/dags" endpoint. Returning json or orjson encoded response seems to result in 2x requests per second. Tradeoffs * Using orjson results in extra dependency and in that case FastAPI JSONResponse can be used as builtin option. * Skipping validation for response could be * Need to check how automatic API generation works when return value is not specified in method. Start below as app.py with 10 workers in uvicorn using `uvicorn app:app --workers 10 --port 8000` command. Start a benchmark session for the endpoints with fixed response. Benchmark for different endpoints 1. Return pydantic model with no return value signature 2. Return orjson response with pydantic model in return value signature but no response validation 3. Return orjson response with no model in return value signature but response validated using pydantic 4. Response dict validated with pydantic and dict returned with model in return value signature. 5. Return json response with model validation for response but no model in return signature https://github.com/fastapi/fastapi/issues/1359 https://github.com/fastapi/fastapi/issues/1224#issuecomment-617243856 ``` seq 1 5 | xargs -I{} time hey -c 100 -n 10000 http://localhost:8000/dags\{\} | grep -iE 'Average:|Requests/sec' Average: 0.0137 secs Requests/sec: 5766.3920 1.05user 0.47system 0:01.75elapsed 86%CPU (0avgtext+0avgdata 20088maxresident)k 0inputs+0outputs (1major+4194minor)pagefaults 0swaps Average: 0.0059 secs Requests/sec: 15063.7350 0.86user 0.34system 0:00.68elapsed 178%CPU (0avgtext+0avgdata 21236maxresident)k 0inputs+0outputs (0major+4595minor)pagefaults 0swaps Average: 0.0063 secs Requests/sec: 13714.7256 0.89user 0.35system 0:00.74elapsed 167%CPU (0avgtext+0avgdata 26076maxresident)k 0inputs+0outputs (0major+5741minor)pagefaults 0swaps Average: 0.0134 secs Requests/sec: 7052.8467 1.03user 0.41system 0:01.43elapsed 100%CPU (0avgtext+0avgdata 19932maxresident)k 0inputs+0outputs (0major+4202minor)pagefaults 0swaps Average: 0.0070 secs Requests/sec: 13043.1176 0.87user 0.38system 0:00.78elapsed 160%CPU (0avgtext+0avgdata 23416maxresident)k 0inputs+0outputs (0major+5021minor)pagefaults 0swaps ``` app.py ```python from __future__ import annotations import orjson from fastapi import FastAPI from fastapi.responses import JSONResponse from airflow.api_fastapi.core_api.datamodels.monitor import HealthInfoResponse from airflow.api_fastapi.core_api.datamodels.ui.dags import ( DAGWithLatestDagRunsCollectionResponse, ) app = FastAPI() class ORJSONCustomResponse(JSONResponse): media_type = "application/json" def render(self, content) -> bytes: return orjson.dumps(content, option=orjson.OPT_NON_STR_KEYS | orjson.OPT_UTC_Z) @app.get("/health1") def get_health() -> HealthInfoResponse: res = { "metadatabase": {"status": "healthy"}, "scheduler": { "status": "unhealthy", "latest_scheduler_heartbeat": "2025-12-04T15:14:35.876302+00:00", }, "triggerer": {"status": None, "latest_triggerer_heartbeat": None}, "dag_processor": { "status": "unhealthy", "latest_dag_processor_heartbeat": "2025-12-04T16:04:49.023929+00:00", }, } return HealthInfoResponse.model_validate(res) @app.get("/health2", response_model=HealthInfoResponse, response_class=ORJSONCustomResponse) def get_health2() -> HealthInfoResponse: res = { "metadatabase": {"status": "healthy"}, "scheduler": { "status": "unhealthy", "latest_scheduler_heartbeat": "2025-12-04T15:14:35.876302+00:00", }, "triggerer": {"status": None, "latest_triggerer_heartbeat": None}, "dag_processor": { "status": "unhealthy", "latest_dag_processor_heartbeat": "2025-12-04T16:04:49.023929+00:00", }, } return ORJSONCustomResponse(res) @app.get("/health3") def get_health3(): res = { "metadatabase": {"status": "healthy"}, "scheduler": { "status": "unhealthy", "latest_scheduler_heartbeat": "2025-12-04T15:14:35.876302+00:00", }, "triggerer": {"status": None, "latest_triggerer_heartbeat": None}, "dag_processor": { "status": "unhealthy", "latest_dag_processor_heartbeat": "2025-12-04T16:04:49.023929+00:00", }, } return res res = { "total_entries": 2, "dags": [ { "dag_id": "gh58560", "dag_display_name": "gh58560", "is_paused": False, "is_stale": False, "last_parsed_time": "2025-12-04T16:04:24.620735Z", "last_parse_duration": 0.06622079999942798, "bundle_name": "dags-folder-1", "relative_fileloc": "gh58560.py", "fileloc": "/home/karthikeyan/airflow/dagsgh58560/gh58560.py", "timetable_description": "Never, external triggers only", "tags": [], "description": None, "next_dagrun": None, "next_dagrun_data_interval_start": None, "next_dagrun_data_interval_end": None, "next_dagrun_create_after": None, "last_expired": None, "timetable_summary": None, "asset_expression": None, "bundle_version": None, "max_active_tasks": 16, "max_active_runs": 16, "max_consecutive_failed_dag_runs": 0, "has_task_concurrency_limits": False, "has_import_errors": False, "owners": ["airflow"], "latest_dag_runs": [ { "id": 1, "dag_id": "gh58560", "run_id": "manual__2025-12-04T14:57:33+00:00", "logical_date": "2025-12-04T14:57:33Z", "run_after": "2025-12-04T14:57:33Z", "start_date": "2025-12-04T15:19:37.873413Z", "end_date": "2025-12-04T15:19:37.873413Z", "state": "success", } ], "pending_actions": [], "is_favorite": False, "file_token": "eyJidW5kbGVfbmFtZSI6ImRhZ3MtZm9sZGVyLTEiLCJyZWxhdGl2ZV9maWxlbG9jIjoiZ2g1ODU2MC5weSJ9.bLgsjNGrIc5g1XjK1mzyqIOLPWM", }, { "dag_id": "gh58560_1", "dag_display_name": "gh58560_1", "is_paused": False, "is_stale": False, "last_parsed_time": "2025-12-04T16:04:24.695772Z", "last_parse_duration": 0.09828795900102705, "bundle_name": "dags-folder-1", "relative_fileloc": "gh58560_1.py", "fileloc": "/home/karthikeyan/airflow/dagsgh58560/gh58560_1.py", "timetable_description": "Never, external triggers only", "tags": [], "description": None, "next_dagrun": None, "next_dagrun_data_interval_start": None, "next_dagrun_data_interval_end": None, "next_dagrun_create_after": None, "last_expired": None, "timetable_summary": None, "asset_expression": None, "bundle_version": None, "max_active_tasks": 16, "max_active_runs": 16, "max_consecutive_failed_dag_runs": 0, "has_task_concurrency_limits": False, "has_import_errors": False, "owners": ["airflow"], "latest_dag_runs": [], "pending_actions": [], "is_favorite": False, "file_token": "eyJidW5kbGVfbmFtZSI6ImRhZ3MtZm9sZGVyLTEiLCJyZWxhdGl2ZV9maWxlbG9jIjoiZ2g1ODU2MF8xLnB5In0.-xfPS1613MuegDAlA93RyV_K1kI", }, ], } @app.get("/dags1") def get_dags1(): return DAGWithLatestDagRunsCollectionResponse(total_entries=res["total_entries"], dags=res["dags"]) @app.get("/dags2") def get_dags2() -> DAGWithLatestDagRunsCollectionResponse: return ORJSONCustomResponse(res) @app.get("/dags3") def get_dags3(): DAGWithLatestDagRunsCollectionResponse(total_entries=res["total_entries"], dags=res["dags"]) return ORJSONCustomResponse(res) @app.get("/dags4") def get_dags4() -> DAGWithLatestDagRunsCollectionResponse: DAGWithLatestDagRunsCollectionResponse(total_entries=res["total_entries"], dags=res["dags"]) return res @app.get("/dags5") def get_dags5(): DAGWithLatestDagRunsCollectionResponse(total_entries=res["total_entries"], dags=res["dags"]) return JSONResponse(res) ``` ### Use case/motivation _No response_ ### Related issues _No response_ ### Are you willing to submit a PR? - [ ] Yes I am willing to submit a PR! ### Code of Conduct - [x] I agree to follow this project's [Code of Conduct](https://github.com/apache/airflow/blob/main/CODE_OF_CONDUCT.md) -- This is an automated message from the Apache Git Service. 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