𝗧𝗮𝗺𝗶𝗻𝗴 𝗔𝗜 𝗔𝗣𝗜 𝗥𝗮𝘁𝗲 𝗟𝗶𝗺𝗶𝘁𝘀 𝘄𝗶𝘁𝗵 𝗔𝘀𝘆𝗻𝗰𝗶𝗼 𝗤𝘂𝗲𝘂𝗲𝘀

𝗧𝗮𝗺𝗶𝗻𝗴 𝗔𝗜 𝗔𝗣𝗜 𝗥𝗮𝘁𝗲 𝗟𝗶𝗺𝗶𝘁𝘀 𝘄𝗶𝘁𝗵 𝗔𝘀𝘆𝗻𝗰𝗶𝗼 𝗤𝘂𝗲𝘂𝗲𝘀

I spent three days fighting API rate limits.

My app hit 429 errors. I tried three things.

• First, I used sleep. It was too slow.
• Second, I used a Semaphore. It limits tasks, not requests per second.
• Third, I used retry loops. I spent too much time waiting.

I used a Token Bucket and an asyncio.Queue.

The bucket keeps you under the limit. The queue handles retries in the background. A semaphore prevents too many tasks.

This approach stops random 429 errors. The main flow stays fast. You get a predictable system.

Next steps for improvement:

• Add random jitter to avoid spikes.
• Add a max retry count.
• Use a lock-free method for high scale.

Skip this if:

• You make few calls.
• The API gives a Retry-After header.
• Your library handles retries.

Rate limits happen. Use a queue and a backoff strategy.

Source: https://dev.to/__c1b9e06dc90a7e0a676b/taming-ai-api-rate-limits-with-asyncio-queues-2a16