Comments (1)
I actually wrote this library because something wasn't working with tqdm.contrib.concurrent for me back in the day, not sure what anymore now.
I think the main diffs are that the executors are fairly exchangable, instead of being limited to using predefined ones (i.e. someone writes some custom executor - it is easy to plug in), the task submission step to the executor queue is explicit - as it can take some time in most applications, with pqdm you can see how much it will take. But apart from that the solutions are quite similar, actually I'm planning to add some of the things you implemented, especially getting rid of my jupyter detection code and use tqdm.auto, but also supporting chunking and tqdm_class.
Lot's of kudos for your work!
I am not sure the differences are worth creating a PR - tqdm's most common usecases will be related to the two standard python executors and most users will expect tqdm to yield one progress bar instead of three - there's even an issue for pqdm to hide them :D - I just enjoy knowing how much every step will take.
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Related Issues (13)
- When will you release new version in pip or conda? HOT 1
- Support for tqdm manual mode HOT 1
- Passing iterable and non-iterable args to function HOT 3
- concurrent.futures.process.BrokenProcessPool('A process in the process pool was terminated abruptly while the future was running or pending.') HOT 1
- Error displaying widget: model not found
- Is it possible that pqdm passes over error messages HOT 9
- Feature Request: return iterable instead of list
- Arguments not parsing for class method HOT 1
- pqdm.processes 'AttributeError' object is not iterable while it works with pdqm.threads
- RuntimeError with example in multiprocessing.spawn HOT 1
- Allow control over which progress bars to show. HOT 2
- BrokenProcessPool returned HOT 1
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