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| Prompt: This async Python server has a memory leak that only manifests under high concurrency. The leak grows at ~50MB/hour. Identify likely causes and write diagnostic code to find the exact source. | |
| Generated: | |
| This async Python server has a memory leak that only manifests under high concurrency. The leak grows at ~50MB/hour. Identify likely causes and write diagnostic code to find the exact source. | |
| <think> | |
| Here's a thinking process that leads to the suggested solution: | |
| 1. **Understand the Goal:** The user wants to identify and diagnose a memory leak in an asynchronous Python server (likely using `asyncio` or frameworks like FastAPI/Starlette/aiohttp) that occurs specifically under high concurrency, growing at approximately 50MB/hour. I need to provide potential causes and specific diagnostic code to pinpoint the issue. | |
| 2. **Analyze the Symptoms:** | |
| * **Environment:** Async Python Server (`asyncio`, `uvicorn`, etc.). | |
| * **Condition:** High concurrency (many concurrent tasks). | |
| * **Symptom:** Memory leak (~50MB/hour). | |
| * **Nature:** "Leak" implies objects aren't being garbage collected when they should be. In async contexts, this is often related to reference cycles, event loops holding references, or unclosed resources. | |
| 3. |