Stephen Karl Larroque

Here are the final results of the benchmarking and optimizing, everything is clarified: - So I applied the same dynamic_miniters fix, and we get the same boost for tqdm_bare, so...

Also note that to benchmark correctly, you need to restart twice your test script: the first run will recompile `.pyc` files, and the second run will use them. You can...

Could you please describe quickly what you want to achieve with this PR (what kind of case you want to cover), and provide if possible a minimal example?

Thank you @cscanlin for taking the time to provide examples and explanations, this is much clearer. If I understand your intent, you'd like `tqdm` to manage errors/completion of a task,...

Ok thank you for the clarification. I agree It can be a very good addition to tqdm as a submodule, but I'm still not sure it should make it in...

PS: if you are wondering whether we could implement analytical regression with numpy, the answer is: not by ourselves, way too much complicated because we would have to reimplement a...

Ah maybe we could implement an additional algorithm (Moving average regression model) as pointed here: https://github.com/tqdm/tqdm/issues/48#issuecomment-155596815

@CrazyPython Exponential is implemented, just use `order=1.5` and it will compute linear, exp, sqrt and log (yes because log can always be useful in machine learning ;) ). You can...

@CrazyPython Not exactly, normal `tqdm` is exponential moving average, so it cannot predict at all when iterations are taking longer and longer because it assumes constance. Linear regression is with...

@CrazyPython No need, I can make them, I can recycle my testing code into unit tests + already done unit tests for machine learning libraries, so it won't be too...