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Full Version: How do APIs handle edge cases and rate limits in real projects?
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APIs are powerful, but sometimes the biggest challenge isn't the integration itself—it's handling edge cases, managing rate limits, or dealing with unexpected changes in the API's response format. What's one API quirk that took you a while to figure out?
One quirk I learned the hard way is rate limits that differ by endpoint and plan Some endpoints reset every minute others every hour and some return 429 with no clear retry hint I ended up guessing and got blocked The fix was to implement per endpoint backoff respect actual headers when present and track the exact reset time for each key That small change saved a lot of random 429s and kept the workflow smooth
Time stamps in ms vs seconds can wreck a timeline if you assume one unit everywhere A migration that seemed easy turned into a data alignment headache until I mapped every endpoint to its time format and added a conversion layer
Pagination traps show up when data moves during paging If you mix offset with live inserts you skip items or see duplicates The trick is to pick a stable cursor or use a checkpoint and fetch with ranges rather than relying on page numbers alone
Webhook verification surprised me when the signature relies on the raw request body and you accidentally modify it in transit Always use the original body as received and use a constant time comparison to avoid timing leaks
APIs 2025 trends suggest plan for versioning early and support old and new responses in parallel while guiding users to migrate