The abstraction layer you built here makes sense for teams that need to iterate quickly on financial models without wrestling with raw API responses every time. One thing that could be useful to add down the road is caching with TTL on the snapshot endpoint, since fundamentals don't change intraday but you might hit rate limits if you're querying the same symbol across multiple notebooks. I've had good luck with Redis or even just simple in-memory caching for that kind of use case.
Yes! I agree with the point. This is just a simple example that might hit rate limit issues, which could be solved better with caching. Thank you for the additional insight.
The abstraction layer you built here makes sense for teams that need to iterate quickly on financial models without wrestling with raw API responses every time. One thing that could be useful to add down the road is caching with TTL on the snapshot endpoint, since fundamentals don't change intraday but you might hit rate limits if you're querying the same symbol across multiple notebooks. I've had good luck with Redis or even just simple in-memory caching for that kind of use case.
Yes! I agree with the point. This is just a simple example that might hit rate limit issues, which could be solved better with caching. Thank you for the additional insight.