Rate limiting restricts how many requests an API accepts within a specified period. It protects services from improper use and can interrupt data collection during rapid testing or scheduled pipeline runs. section 10.1.1 section 10.4
Plan API extraction around the service's stated limits:
- Read the API documentation to identify request limits and restrictions before automating collection. section 10.1.1
- Pause between requests with Python's built-in time.sleep function; a delay of at least a few seconds helps avoid faster-than-human request rates. section 10.1.1
- Add pauses to pagination loops when retrieving large datasets through multiple API calls. section 10.1.1
- Treat rate limits as part of assessing an API's viability alongside automation resources, time saved, and data-warehouse integration. section 10.4
Scheduled forecast extraction
A script that retrieves forecast pages may work during occasional testing but hit the service limit when run repeatedly or on a schedule. Delaying requests inside its pagination loop reduces that risk, while documentation determines whether the planned frequency is permitted. section 10.1.1
