tqdm VS more-itertools

yeah my code needs to use multiprocessing, which does not play nice with tqdm. thanks for the tip about positions though, that helped me search more effectively and came up with two promising comments. unmerged / require some workarounds, but might just work:

https://github.com/tqdm/tqdm/issues/1000#issuecomment-184208...

> Like tqdm (Python progressbar library) but as a Unix utility.

FYI: tqdm can be used in a shell pipeline as well. It's documented (at least) in their readme: https://github.com/tqdm/tqdm#module

BTW, my inspiration was https://github.com/tqdm/tqdm library for python and any contribution is welcome to add similar functionality.

I can recommend you the package tqdm (https://github.com/tqdm/tqdm) You can replace the standard for statement with it, or use it with any other iterable. By default, it gives you a progress bar with a percentage and ETA, but you can also configure it to only print the percentage, if you want that. If you want to use print statements, adding \r at the beginning and not putting a line end should also do the trick.

you try to run an python script that requires the tqdm package and also a regex package (what normally should be installed, when installing python). Blender tries to install these packages without success. You probably have to do it on your own by installing them in your pythons virtual environment.

If OP is using python that might be the output of python's tqdm.

I have a client-server socket program where the server sends a file to the client. The server is designed to allow multiple clients using threading. For the file transfer on the client, I am using the tqdm library (https://github.com/tqdm/tqdm).

I'd bet that reading through more-itertools would be a good exercise.

check out the code examples in itertools and the source code of more-itertools if you want to see cases where next and iter get used by themselves.

from itertools import islice # Copied from the more-itertools library (MIT license) # https://github.com/more-itertools/more-itertools def batched(iterable, n): "Batch data into lists of length n. The last batch may be shorter." # batched('ABCDEFG', 3) --> ABC DEF G if n < 1: raise ValueError('n must be at least one') it = iter(iterable) while (batch := list(islice(it, n))): yield batch

more_itertools.chunked

I've had a tab open to more-itertools on github for weeks; maybe I should go read it...

The popular more-itertools library implements (among many others) a chunked method which yields lists of size n from an iterator. There is also the ichunked method which yields iterators of size n instead of lists.

There's a function called consecutive_groups in the more-itertools library that will do this for you efficiently.

Here are some that might answer your question: - algorithms is a library which contains many of the most useful algorithms for sorting, searching, working with trees, math algorithms like factorials, prime finders and many more - data classes to save you the trouble of writing everytime special methods in a class like init, repr, set, get - box allows the use of dot on dictionaries to access the keys - more-itertools for more routines to operate on iterables than those itertools provide.