anthropic python sdk async not working

The Anthropic Python SDK provides an asynchronous client for non-blocking concurrent requests. If your async Claude calls are hanging, blocking the main execution thread, or throwing unhandled coroutine exceptions, you need to adjust your event loop integration.

Instantiate the correct client class

A common mistake is attempting to use asynchronous calls with the standard synchronous client. Make sure you import and instantiate AsyncAnthropic instead of the standard Anthropic class. If you try to call async methods on the synchronous client, Python will fail to execute the coroutines, resulting in unexecuted tasks or crashes.

Correctly await all API actions

Every message creation request made through the async client returns a coroutine. You must prefix these calls with the 'await' keyword inside an 'async def' block. Forgetting to await the client's messages.create call will cause Python to return a coroutine object instead of the actual message response, breaking any subsequent data parsing.

Manage the event loop environment

If you are running the async client inside existing frameworks like FastAPI or inside Jupyter Notebooks, you may encounter event loop conflicts. Jupyter has an active event loop running, meaning running asyncio.run() will throw a 'RuntimeError'. In these environments, you should run your tasks using the existing loop or utilise nested-event-loop packages to synchronise executions safely.

Iterate async stream generators correctly

If you are streaming responses using the async client, a standard 'for' loop will fail. You must use 'async for' to iterate over the message stream chunks. Using the wrong iteration method blocks the event loop and prevents real-time token rendering. If your SDK issues are related to billing suspensions or empty balance blocks stopping requests entirely, refer to our walkthrough on /fix/claude-billing-problem.