How do I deal with rate limits on public APIs?

[Mhairi Virginie]

If the API rate limit is very strict, I distribute requests across multiple accounts with different API keys to maximize throughput.

[Allochka Wangari]

Implementing caching for repeat requests reduces load and makes my scraper more efficient, especially for static data that doesn’t change often.

[Tahvo Eulalia]

I monitor error codes, like 429 (Too Many Requests), to detect rate limits in real time. My script pauses or retries after a delay when it sees this code.

[Norbu Nata]

For batch processing, I queue requests and handle them in smaller chunks, which lets me stay within limits while gathering data continuously.

[Zyta Orla]

Exponential backoff is a good strategy for handling temporary limits. I gradually increase wait times between requests until they’re accepted again.

[Thurstan Radovan]

Using a cron job to schedule API requests during non-peak hours can reduce competition for resources, which helps avoid rate limits.

[Vieno Amenemhat]

I sometimes find alternative APIs for the same data. Combining multiple sources reduces dependency on any one API and spreads out the request load.