Httpx vs. Aiohttp (miguel-mendez-ai.com)

A developer running a FastAPI computer-vision REST service (Python 3.11.3) experienced intermittent crashes when bombarding the API with many concurrent requests from an httpx-based async client (httpx 0.27.2). The server simulated work with asyncio.sleep and multiple replicas/batching behind a load balancer; the client launched up to 300 concurrent connections and 1,000 total requests. Under heavy load httpx began raising opaque httpx.ReadError exceptions while reading responses, causing the whole client to crash intermittently and making root-cause debugging difficult. After tracing the problem to known httpx/httpcore limitations under very high concurrency, the author swapped to aiohttp (3.10.10). Replacing httpx.AsyncClient(limits=...) with aiohttp.ClientSession using TCPConnector(limit=...) and ClientTimeout resolved the ReadError crashes and improved throughput. The takeaway for AI/ML engineers: when you need extreme concurrent HTTP traffic (large batches, many parallel inference requests), validate client transport behavior under stress—httpx is convenient and modern but may still hit performance/transport edge cases; aiohttp’s mature connector and transport have proven more robust in this scenario. Recommendations: load-test your client-library choice, tune connection limits and timeouts, and monitor underlying transports (httpcore vs asyncio/TCPConnector) before deploying high-concurrency inference clients.