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Skip to content tqdm documentation Home Type to start searching tqdm/tqdm * v4.64.0 * 21.8k * 1.1k tqdm documentation tqdm/tqdm * v4.64.0 * 21.8k * 1.1k * Home * Library Reference Library Reference * tqdm.tqdm * tqdm.notebook * tqdm.asyncio * tqdm.keras * tqdm.dask * tqdm.tk * tqdm.gui * tqdm.rich * CLI * tqdm.contrib * tqdm.contrib.concurrent * tqdm.contrib.itertools * tqdm.contrib.logging * tqdm.contrib.slack * tqdm.contrib.discord * tqdm.contrib.telegram * Shortcuts * Developer Reference Developer Reference * Warnings and Exceptions * tqdm.TMonitor * Release History * Contributing * Merch Store! * Ports to Other Languages * Presentation (PyData) Presentation (PyData) * Video * Slides * External Links External Links * Source Code (ENTIRE DOCUMENTATION ON ONE PAGE) * wiki * FAQs * Issues * Downloads Downloads * GitHub * PyPI * Conda * Tests Tests * GitHub Actions * Coveralls * Codecov * Codacy * Performance Benchmarks (asv) * Citations Citations * DOI * Metrics (Open Hub) * Licence * Video TQDM# -------------------------------------------------------------------------------- tqdm means "progress" in Arabic (taqadum, تقدّم) and is an abbreviation for "I love you so much" in Spanish (te quiero demasiado). Instantly make your loops show a smart progress meter - just wrap any iterable with tqdm(iterable), and you're done! from tqdm import tqdm for i in tqdm(range(10000)): ... 76%|████████████████████████████ | 7568/10000 [00:33<00:10, 229.00it/s] trange(N) can be also used as a convenient shortcut for tqdm(xrange(N)). It can also be executed as a module with pipes: $ seq 9999999 | tqdm --bytes | wc -l 75.2MB [00:00, 217MB/s] 9999999 $ 7z a -bd -r backup.7z docs/ | grep Compressing | \ tqdm --total $(find docs/ -type f | wc -l) --unit files >> backup.log 100%|███████████████████████████████▉| 8014/8014 [01:37<00:00, 82.29files/s] Overhead is low -- about 60ns per iteration (80ns with tqdm_gui), and is unit tested against performance regression. By comparison, the well-established ProgressBar has an 800ns/iter overhead. In addition to its low overhead, tqdm uses smart algorithms to predict the remaining time and to skip unnecessary iteration displays, which allows for a negligible overhead in most cases. tqdm works on any platform (Linux, Windows, Mac, FreeBSD, NetBSD, Solaris/SunOS), in any console or in a GUI, and is also friendly with IPython/Jupyter notebooks. tqdm does not require any dependencies (not even curses!), just Python and an environment supporting carriage return \r and line feed \n control characters. Next tqdm.tqdm © Casper da Costa-Luis @casperdcl 2015-2022