Multithreading for historical forecast methods#34
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sam-watttime merged 21 commits intomainfrom Feb 11, 2025
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Thanks for your patience on this -- I tested the multithreading code here, and this works great! Thanks for adding this, I think this will be a big improvement. I tested this over a few different time periods -- performance very much improved. I didn't hit any rate limit errors, but I realized that my API account may not be subject to rate limits anyway so that part I couldn't test. Other than that I think this looks great. Did you revert your other changes just to more narrowly focus the scope of this PR?
…possibly non continuous) forecast dates (e.g. sampled)
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For many upcoming analysis use cases, grabbing a large volume of historical forecasts is desired. Our API has a maximum request size that requires batching large periods into smaller date chunks. In these cases, it's desirable to use multi-threading to reduce the time needed to pull this data.
This PR introduces multithreading into the historical forecast method. Currently the parameters (e.g. number of threads, size of date chunks) are hardcoded, as we do not want to make this too complicated for users.
Testing on my local machine shows that the average response time for a single day (in a large chunk) reduces from around 5 seconds per day, to 1 second per day.