aiohttp

aiohttp is the de facto standard for async HTTP in Python, offering both client and server capabilities with excellent performance. The API is mostly intuitive once you understand asyncio patterns, and the middleware system provides good hooks for authentication and request validation. However, you need to be deliberate about security configuration—it doesn't hold your hand.

From a security perspective, the framework requires careful setup. TLS certificate validation is enabled by default for clients (good), but you'll need to explicitly configure timeouts, payload limits, and CORS policies. The ClientSession connection pooling is solid, but improper session management can leak connections. Error handling exposes raw tracebacks by default in debug mode, so ensure you configure proper error middleware for production.

The project has reasonable CVE response times, but dependency churn can be high—particularly with yarl and multidict. Input validation is your responsibility; the framework parses but doesn't sanitize. The documentation covers security basics but assumes you know what you're doing with async patterns and HTTP security fundamentals.

aiohttp has been my go-to for async HTTP in Python for years, and it shines in production environments. The ClientSession connection pooling is excellent - configure connector limits, timeout behavior (ClientTimeout with separate connect/sock_read/total timeouts), and TCP keepalive settings granularly. Resource cleanup is critical though: always use context managers or explicit close() calls, as leaked sessions will haunt you with ResourceWarning spam and fd exhaustion.

The server side is surprisingly capable with middleware support, proper signal handling for graceful shutdown, and good observability hooks through on_response_prepare/on_request_end. Performance under load is solid once you tune connector limits and worker counts. The traces API lets you instrument every phase of requests for timing breakdowns.

Error handling requires discipline - ClientError hierarchy is comprehensive but you need to catch connection errors, timeouts, and payload errors separately. The retry story is bare-bones; you'll build your own with exponential backoff. Breaking changes between major versions (especially 2->3) required significant refactoring. Default timeouts are 5 minutes which is absurd for production - always set explicit ClientTimeout configurations.

aiohttp is the de facto standard for async HTTP in Python, offering both client and server capabilities with solid performance. The ClientSession connection pooling is efficient once configured properly, though the default timeouts are surprisingly generous (5 minutes for total timeout). You'll want to explicitly set ClientTimeout with reasonable values for production.

Resource management requires discipline - forgetting to properly close sessions or use context managers leads to "Unclosed client session" warnings that can mask real leaks. The TCPConnector's limit and limit_per_host parameters are essential for controlling concurrency, buttuning them requires understanding your workload. Tracing hooks via TraceConfig provide excellent observability into DNS resolution, connection establishment, and request timing, which is invaluable for debugging performance issues.

Error handling is generally predictable with well-defined exception hierarchies, though you need separate handling for ClientError, ServerTimeoutError, and asyncio.TimeoutError. The streaming response API works well for large payloads, but you must remember to explicitly read/release responses or connections stay occupied.