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.
Disable tqdm within context and refresh tqdm when exits. Useful when writing to standard output stream set_lock [view source]
tqdm.notebook IPython/Jupyter Notebook progressbar decorator for iterators. Includes a default range iterator printing to stderr. Usage:
A Fast, Extensible Progress Meter tqdm.asyncio Asynchronous progressbar decorator for iterators. Includes a default range iterator printing to stderr. Usage:
CLI tqdm 's command line interface (CLI) can be used in a script or on the terminal/console. Simply inserting tqdm (or python -m tqdm) between pipes will pass through all stdin to stdout while printing progress to stderr. Run tqdm --help for a full list of options.
A Fast, Extensible Progress Meter >>> from tqdm.gui import trange, tqdm >>> for i in trange(10): ... ...
First public release of the next generation of tqdm, with lots of new features, more speed, more unit testing, more coverage (100% yeah!), more beer and coffee.
batch_size: int, optional Number of training pairs per batch. verbose: int 0: epoch, 1: batch (transient), 2: batch. [default: 1]. Will be set to 0 unless both data_size and batch_size are given. tqdm_class: optional tqdm class to use for bars [default: tqdm.auto.tqdm]. tqdm_kwargs: optional Any other arguments used for all bars. display [view ...