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How do I deal with rate limits on public APIs?
I add delays between requests to ensure my requests fall within the API’s rate limits. This prevents interruptions due to throttling.
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7 Replies
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If the API rate limit is very strict, I distribute requests across multiple accounts with different API keys to maximize throughput.
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Implementing caching for repeat requests reduces load and makes my scraper more efficient, especially for static data that doesn’t change often.
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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.
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For batch processing, I queue requests and handle them in smaller chunks, which lets me stay within limits while gathering data continuously.
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Exponential backoff is a good strategy for handling temporary limits. I gradually increase wait times between requests until they’re accepted again.
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Using a cron job to schedule API requests during non-peak hours can reduce competition for resources, which helps avoid rate limits.
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I sometimes find alternative APIs for the same data. Combining multiple sources reduces dependency on any one API and spreads out the request load.
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