Tqdm
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| Developer(s) | Casper da Costa-Luis.[1] |
|---|---|
| Stable release | 4.x.x
/ February 4, 2016 |
| Written in | Python[2] |
| Engine | |
| Operating system | MS Windows, UNIX, MacOS |
| Type | Software profiling tools |
| License | MPLv2.0, MIT |
| Website | tqdm |
Search Tqdm on Amazon.
tqdm is a progress bar library designed to be fast and extensible. It is written in Python, though ports in other languages are available. tqdm means progress in Arabic (taqadum, تقدّم)[3] and is an abbreviation for I love you so much in Spanish (te quiero demasiado)[4].
Features[edit]
Exhaustive documentation may be found on the project's home page.
The package supports both Python versions 2 and 3, and is available for download via conda, pip, and snap.
The two basic use cases are within Python code and within a Command-line interface:
Python Iterable Wrapper[edit]
tqdm's primary (and original) use is as a wrapper around Python iterables. A simple case would be:
from tqdm import tqdm
from time import sleep
for i in tqdm(range(100)):
sleep(0.1)
100%|█████████████████████████████████████████| 100/100 [00:10<00:00, 9.95it/s]
Supported features include:
- Display customisation via arguments such as
desc,postfixandbar_format - Automatic limiting of display updates to avoid slowing down due to excessive iteration rates
- Automatic detection of console width to fill the display
- Automatic use of Unicode to render smooth-filling progress bars on supported terminals
- Support for custom rendering frontends, including:
- Support for custom hooks/callbacks, including:
Command-line Interface[edit]
A Command-line interface is also provided, where tqdm may be used a pipe:
$ cat *.txt | wc -l # count lines of text in all *.txt files 1075075 $ cat *.txt | python3 -m tqdm --unit loc --unit_scale | wc -l # same but with continuously updating progress information 1.08Mloc [00:07, 142kloc/s] 1075075
Popularity[edit]
Last updated: May 2019
- Over 39 million downloads[5]
- Over 410 thousand code inclusions[6]
- Over 32 thousand dependent repositories[7]
- 7 thousand dependent libraries[8]
- SourceRank 22[9], in the world's top 20 Python packages as of early 2019[10]
- 10 thousand stars on GitHub[11], and the top trending repository during a period in December 2015[12]
- 500 thousand documentation hits[13]
- Used in several textbooks[14][15][16] and peer-reviewed scientific publications[17][18][19][20][21]
Code Metrics[edit]
The library uses:
- Travis CI for unit testing;
- Codacy for style and security checks;
- Coveralls and Codecov for coverage reporting;
- OpenHub for COCOMO valuation, and
- airspeed velocity for performance testing
Licence[edit]
tqdm's source code is OSS, and may be cited using the DOI 10.5281/zenodo.595120. The primary maintainer Casper da Costa-Luis[1] releases contributions under the terms of the MPLv2.0, while all other contributions are released under the terms of the MIT licence.
See also[edit]
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References in Blogs and Public Media[edit]
- A tqdm release becomes Zenodo's 1 millionth record
- A Hymn to Progress, a poem or song with suggested tune of For those in Peril on the C, where C is a pun on Sea and the C programming language
- My top 5 'new' Python modules of 2015
tqdm,imageioandSeaborn: Three essential python modules (Nov 2018)- https://pythontips.com/2018/06/03/top-14-most-famous-python-libraries-frameworks
- https://github.com/IliaGavrilov/Machine_Learning_libraries_and_Python_3.6_tricks
- https://github.com/robclewley/TqdmAudioRicker
References[edit]
- ↑ 1.0 1.1 "@casperdcl". GitHub. Retrieved 22 January 2019.
- ↑ "tqdm". Python Package Index (PyPI). Python Software Foundation. Retrieved 2019-01-22.
- ↑ Alī Ġūl, Maḥmūd (1993). Early Southern Arabian Languages and Classical Arabic Sources: A Critical Examination of Literary and Lexicographical Sources by Comparison with the Inscriptions. Irbid: Yarmouk University. Search this book on
- ↑ "¿Lenguaje sms que significa esto?". es.answers.yahoo.com (in español).
- ↑ "Analyzing PyPI package downloads — Python Packaging User Guide". Python Packaging Authority (PyPA). Python Software Foundation. Retrieved 22 January 2019.
- ↑ "tqdm Code Results". GitHub. Retrieved 22 January 2019.
- ↑ "tqdm dependents". GitHub. 22 January 2019. Retrieved 22 January 2019.
- ↑ "tqdm on PyPI". Libraries.io.
- ↑ "SourceRank Breakdown for tqdm". Libraries.io.
- ↑ "Libraries - The Open Source Discovery Service". Libraries.io. Retrieved 22 January 2019.
- ↑ "tqdm Stargazers". GitHub. 22 January 2019. Retrieved 22 January 2019.
- ↑ Takizawa, Nihey (19 July 2018). "GitHub Trending History". GitHub. Retrieved 25 January 2019.
- ↑ "tqdm hits". CasperSci. Retrieved 22 January 2019.
- ↑ Miller, Preston; Bryce, Chapin (2017). Python Digital Forensics Cookbook: Effective Python recipes for digital investigations. Packt Publishing Ltd. ISBN 9781783987474. Search this book on
- ↑ Van Boxel, Dan (2017). Hands-On Deep Learning with TensorFlow. Packt Publishing. ISBN 9781787125827. Search this book on
- ↑ Nandy, Abhishek; Biswas, Manisha (2018). "Reinforcement Learning with Keras, TensorFlow, and ChainerRL". Reinforcement Learning : With Open AI, TensorFlow and Keras Using Python. Apress. pp. 129–153. ISBN 9781484232859. Search this book on
- ↑ Stein, Helge S.; Guevarra, Dan; Newhouse, Paul F.; Soedarmadji, Edwin; Gregoire, John M. (2019). "Machine learning of optical properties of materials – predicting spectra from images and images from spectra". Chemical Science. 10 (1): 47–55. doi:10.1039/C8SC03077D.
- ↑ Cook, Neil J.; Scholz, Aleks; Jayawardhana, Ray (28 November 2017). "Very Low-mass Stars and Brown Dwarfs in Upper Scorpius Using Gaia DR1: Mass Function, Disks, and Kinematics". The Astronomical Journal. 154 (6): 256. arXiv:1710.11625. Bibcode:2017AJ....154..256C. doi:10.3847/1538-3881/aa9751.
- ↑ Madhikar, Pranav; Åström, Jan; Westerholm, Jan; Karttunen, Mikko (November 2018). "CellSim3D: GPU accelerated software for simulations of cellular growth and division in three dimensions". Computer Physics Communications. 232: 206–213. Bibcode:2018CoPhC.232..206M. doi:10.1016/j.cpc.2018.05.024.
- ↑ Palmer, Geraint I.; Knight, Vincent A.; Harper, Paul R.; Hawa, Asyl L. (20 May 2018). "Ciw: An open-source discrete event simulation library". Journal of Simulation: 1–15. doi:10.1080/17477778.2018.1473909.
- ↑ Knight, Vincent; Campbell, Owen; Harper, Marc; Langner, Karol; Campbell, James; Campbell, Thomas; Carney, Alex; Chorley, Martin; Davidson-Pilon, Cameron; Glass, Kristian; Glynatsi, Nikoleta; Ehrlich, Tomáš; Jones, Martin; Koutsovoulos, Georgios; Tibble, Holly; Jochen, Müller; Palmer, Geraint; Petunov, Piotr; Slavin, Paul; Standen, Timothy; Visintini, Luis; Molden, Karl (31 August 2016). "An open reproducible framework for the study of the iterated prisoner's dilemma". Journal of Open Research Software. 4. doi:10.5334/jors.125. ISSN 2049-9647.
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