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词条 Draft:Tqdm
释义

  1. Features

      Python Iterable Wrapper    Command-line Interface  

  2. Popularity

      References in Blogs and Public Media    Code Metrics  

  3. Licence

  4. See also

  5. References

{{AFC submission|d|adv|u=Casper da Costa-Luis|ns=118|decliner=Theroadislong|declinets=20190329154119|ts=20190124223704}} {{AFC comment|1=Please remove all external links from the body of the article we don't use them. Theroadislong (talk) 15:41, 29 March 2019 (UTC)}}
{{primary sources|date=January 2019}}{{Infobox software
| logo = tqdm gif logo.gif
| developer = Casper da Costa-Luis.[1]
| latest release version = 4.x.x
| latest release date = {{Start date and age|2016|02|04}}
| operating system = MS Windows, UNIX, MacOS
| programming language = Python[2]
| genre = Software profiling tools
| license = MPLv2.0, MIT
| website = {{URL|https://tqdm.github.io/}}
}}

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

Exhaustive documentation may be found on the project's [https://github.com/tqdm/tqdm/#documentation home page].

The package supports both Python versions 2 and 3, and is available for download via conda[5], pip[2], and snap [6]

The two basic use cases are within Python code and within a Command-line interface:

Python Iterable Wrapper

tqdm's primary (and original) use is as a wrapper around Python iterables. A simple case would be:

Supported features include:

  • Display customisation via arguments such as desc, postfix and bar_format
  • Automatic limiting of display updates to avoid slowing down due to excessive iteration rates[7]
  • 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:
    • Command-line interface
    • Jupyter HTML notebooks
    • matplotlib
  • Support for custom hooks/callbacks, including:
    • pandas
    • keras[8]

Command-line Interface

A Command-line interface is also provided, where tqdm may be used a pipe:

Popularity

Last updated: January 2019
  • Over 20 million downloads[9]
  • Over 315 thousand code inclusions[10]
    • Over 23 thousand dependent repositories[11]
    • 7 thousand dependent libraries[12]
  • SourceRank 22[13], in the world's top 20 Python packages as of early 2019[14]
  • 9 thousand stars on GitHub[15][16], and the top trending repository during a period in December 2015[17]
  • 500 thousand documentation hits[18]
  • Used in several textbooks[19][20][21] and peer-reviewed scientific publications[22][23][24][25][26]

References in Blogs and Public Media

  • A tqdm release becomes [https://twitter.com/WikimediaItalia/status/914448810117545985 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
  • [https://dominikschmidt.xyz/python-modules-tqdm-imageio-seaborn/ tqdm, imageio and Seaborn: 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

Code Metrics

  • Unit tested on Travis CI[27]
  • Style and security checked on [https://app.codacy.com/project/tqdm/tqdm/dashboard Codacy]
  • Code coverage reported on [https://coveralls.io/github/tqdm/tqdm Coveralls] and [https://codecov.io/gh/tqdm/tqdm Codecov]
  • Valuated using the COCOMO model by [https://www.openhub.net/p/tqdm OpenHub]
  • Performance tested against regression[28]

Licence

tqdm's source code is OSS, and may be cited using the DOI [https://doi.org/10.5281/zenodo.595120 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.[29]

See also

{{Portal|Free and open-source software}}
  • Ports of [https://github.com/search?q=tqdm&type=Repositories tqdm in other languages on GitHub]
    • [https://tqdm.github.io/ports/ Official List of Ports]
  • [https://notebooks.rmotr.com/demo/gh/tqdm/tqdm Interactive demonstration of tqdm in a Jupyter Notebook]

References

1. ^1 {{cite web |title=@casperdcl |url=https://github.com/casperdcl |website=GitHub |accessdate=22 January 2019}}
2. ^1 {{cite web |url=https://pypi.org/project/tqdm/ |title=tqdm | work=Python Package Index (PyPI) |publisher=Python Software Foundation |accessdate= 2019-01-22}}
3. ^{{cite book |last1=Alī Ġūl |first1=Maḥmūd |title=Early Southern Arabian Languages and Classical Arabic Sources: A Critical Examination of Literary and Lexicographical Sources by Comparison with the Inscriptions |date=1993 |publisher=Yarmouk University |location=Irbid}}
4. ^{{cite web |title=¿Lenguaje sms que significa esto? |url=https://es.answers.yahoo.com/question/index?qid=20090405052137AAF2YBo&guccounter=1 |website=es.answers.yahoo.com |language=es-ES}}
5. ^{{cite web |title=Tqdm :: Anaconda Cloud |url=https://anaconda.org/conda-forge/tqdm |website=anaconda.org |accessdate=24 January 2019}}
6. ^{{cite web |title=Install tqdm for Linux using the Snap Store |url=https://snapcraft.io/tqdm |website=Snapcraft |accessdate=17 February 2019 |language=en}}
7. ^{{cite web |title=Why is printing to stdout so slow? Can it be sped up? |url=https://stackoverflow.com/questions/3857052/why-is-printing-to-stdout-so-slow-can-it-be-sped-up |website=Stack Overflow |accessdate=24 January 2019}}
8. ^{{cite web |author=Ben |title=Keras integration with TQDM progress bars |url=https://github.com/bstriner/keras-tqdm |website=GitHub |accessdate=24 January 2019 |date=22 January 2019}}
9. ^{{cite web |title=Analyzing PyPI package downloads — Python Packaging User Guide |url=https://packaging.python.org/guides/analyzing-pypi-package-downloads/ |website=Python Packaging Authority (PyPA) |publisher=Python Software Foundation |accessdate=22 January 2019}}
10. ^{{cite web |title=tqdm Code Results |url=https://github.com/search?q=tqdm&type=Code |website=GitHub |accessdate=22 January 2019 |language=en}}
11. ^{{cite web |title=tqdm dependents |url=https://github.com/tqdm/tqdm/network/dependents |website=GitHub |accessdate=22 January 2019 |date=22 January 2019}}
12. ^{{cite web |title=tqdm on PyPI |url=https://libraries.io/pypi/tqdm |website=Libraries.io |language=en}}
13. ^{{cite web |title=SourceRank Breakdown for tqdm |url=https://libraries.io/pypi/tqdm/sourcerank |website=Libraries.io}}
14. ^{{cite web |title=Libraries - The Open Source Discovery Service |url=https://libraries.io/search?order=desc&platforms=PyPI&sort=rank |website=Libraries.io |accessdate=22 January 2019 |language=en}}
15. ^{{cite web |title=tqdm Stargazers |url=https://github.com/tqdm/tqdm/stargazers |website=GitHub |accessdate=22 January 2019 |date=22 January 2019}}
16. ^{{cite web |title=Star history |url=https://timqian.com/star-history/#tqdm/tqdm |website=timqian}}
17. ^{{cite web |last1=Takizawa |first1=Nihey |title=GitHub Trending History |url=https://github.com/nihey/trending-history/blob/master/histories/Python.md |website=GitHub |accessdate=25 January 2019 |date=19 July 2018}}
18. ^{{cite web |title=tqdm hits |url=https://caspersci.uk.to/cgi-bin/hits.cgi?q=tqdm&a=plot&r=https://github.com/tqdm/tqdm&l=https://caspersci.uk.to/images/tqdm.png&f=https://raw.githubusercontent.com/tqdm/tqdm/master/images/logo.gif&style=social |website=CasperSci |accessdate=22 January 2019}}
19. ^{{cite book |last1=Miller |first1=Preston |last2=Bryce |first2=Chapin |title=Python Digital Forensics Cookbook: Effective Python recipes for digital investigations |date=2017 |publisher=Packt Publishing Ltd |isbn=9781783987474}}
20. ^{{cite book |last1=Van Boxel |first1=Dan |title=Hands-On Deep Learning with TensorFlow. |date=2017 |publisher=Packt Publishing |isbn=9781787125827}}
21. ^{{cite book |last1=Nandy |first1=Abhishek |last2=Biswas |first2=Manisha |title=Reinforcement Learning : With Open AI, TensorFlow and Keras Using Python |date=2018 |publisher=Apress |isbn=9781484232859 |pages=129–153 |url=https://doi.org/10.1007/978-1-4842-3285-9_5 |language=en |chapter=Reinforcement Learning with Keras, TensorFlow, and ChainerRL}}
22. ^{{cite journal |last1=Stein |first1=Helge S. |last2=Guevarra |first2=Dan |last3=Newhouse |first3=Paul F. |last4=Soedarmadji |first4=Edwin |last5=Gregoire |first5=John M. |title=Machine learning of optical properties of materials – predicting spectra from images and images from spectra |journal=Chemical Science |date=2019 |volume=10 |issue=1 |pages=47–55 |doi=10.1039/C8SC03077D}}
23. ^{{cite journal |last1=Cook |first1=Neil J. |last2=Scholz |first2=Aleks |last3=Jayawardhana |first3=Ray |title=Very Low-mass Stars and Brown Dwarfs in Upper Scorpius Using Gaia DR1: Mass Function, Disks, and Kinematics |journal=The Astronomical Journal |date=28 November 2017 |volume=154 |issue=6 |pages=256 |doi=10.3847/1538-3881/aa9751|bibcode=2017AJ....154..256C |arxiv=1710.11625 }}
24. ^{{cite journal |last1=Madhikar |first1=Pranav |last2=Åström |first2=Jan |last3=Westerholm |first3=Jan |last4=Karttunen |first4=Mikko |title=CellSim3D: GPU accelerated software for simulations of cellular growth and division in three dimensions |journal=Computer Physics Communications |date=November 2018 |volume=232 |pages=206–213 |doi=10.1016/j.cpc.2018.05.024|bibcode=2018CoPhC.232..206M }}
25. ^{{cite journal |last1=Palmer |first1=Geraint I. |last2=Knight |first2=Vincent A. |last3=Harper |first3=Paul R. |last4=Hawa |first4=Asyl L. |title=Ciw: An open-source discrete event simulation library |journal=Journal of Simulation |date=20 May 2018 |pages=1–15 |doi=10.1080/17477778.2018.1473909}}
26. ^{{cite journal |last1=Knight |first1=Vincent |last2=Campbell |first2=Owen |last3=Harper |first3=Marc |last4=Langner |first4=Karol |last5=Campbell |first5=James |last6=Campbell |first6=Thomas |last7=Carney |first7=Alex |last8=Chorley |first8=Martin |last9=Davidson-Pilon |first9=Cameron |last10=Glass |first10=Kristian |last11=Glynatsi |first11=Nikoleta |last12=Ehrlich |first12=Tomáš |last13=Jones |first13=Martin |last14=Koutsovoulos |first14=Georgios |last15=Tibble |first15=Holly |last16=Jochen |first16=Müller |last17=Palmer |first17=Geraint |last18=Petunov |first18=Piotr |last19=Slavin |first19=Paul |last20=Standen |first20=Timothy |last21=Visintini |first21=Luis |last22=Molden |first22=Karl |title=An open reproducible framework for the study of the iterated prisoner's dilemma |journal=Journal of Open Research Software |date=31 August 2016 |volume=4 |doi=10.5334/jors.125 |url=https://arxiv.org/abs/1604.00896 |issn=2049-9647}}
27. ^{{cite web |title=tqdm/tqdm build status |url=https://travis-ci.org/tqdm/tqdm |website=Travis CI |accessdate=24 January 2019}}
28. ^{{cite web |title=airspeed velocity |url=https://tqdm.github.io/tqdm/ |website=tqdm.github.io |accessdate=24 January 2019}}
29. ^{{cite web |title=tqdm Licence |url=https://github.com/tqdm/tqdm/blob/master/LICENCE |website=GitHub |publisher=tqdm developers |accessdate=22 January 2019 |date=22 January 2019}}
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