GitHub十大热门Python项目-FlyAI

GitHub十大热门Python项目

Python3

最后更新 2020-11-05 14:52 阅读 5392

最后更新 2020-11-05 14:52

阅读 5392

Python3

##FlyAI文献翻译
**英文原文：**[：Top 10 Trending Python Projects On GitHub](https://towardsdatascience.com/top-10-trending-python-projects-on-github-fb852cd58262)
> **标签** ：Python

![](https://static.leiphone.com/uploads/new/sns/article/202010/1604038120289268.png)

Photo by Lee Campbell on Unsplash

>图源 Unsplash，由Lee Campbell拍摄。

The joy of coding Python should be in seeing short, concise, readable classes that express a lot of action in a small amount of clear code — not in reams of trivial code that bores the reader to death.

- Guido van Rossum

>编写Python的乐趣应该是看到短小精悍、可读性强的类，用少量清晰的代码表达大量的操作--而不是看到成堆的琐碎代码，让读者厌烦至极。
- Guido van Rossum

For a decent amount of time, developers over the world have preferred Python for a majority of their projects. The ease of using the programming language, its efficiency in real-time as well as non-real-time systems, and its wide collection of life-saving packages are just some of the reasons why developers love Python.

Programming languages like Python give you the freedom to turn your dream project into reality and showcase your talent to the world. This is why we are going to explore a handful of top Python projects available on GitHub to not only inspire you but to also give you a taste of what you can do with an innovative mind and Python.

>在相当长的时间里，全世界的开发者在大部分项目中都首选Python。编程语言的易用性、在实时以及非实时系统中的高效性、以及广泛的救生包集合，这些都是开发者热爱Python的部分原因。

>像Python这样的编程语言可以让你自由地将你的梦想项目变成现实，向世界展示你的才华。这就是为什么我们要探索GitHub上的一些顶级Python项目，不仅能激发你的灵感，还能让你体验一下用创新的头脑和Python可以做什么。

**Did You Know?**

[According to Stackoverflow](https://insights.stackoverflow.com/survey/2020 "According to Stackoverflow"), Python is the most preferred language which means that the majority of developers use python.

Python is GitHub’s second-most popular language and the most popular language for machine learning.

>根据Stackoverflow的数据，Python是最受欢迎的语言，这意味着大多数开发人员使用python。

>Python是GitHub第二受欢迎的语言，也是机器学习最受欢迎的语言。

[Top Python Interview Questions and Answers for Freshers in 2020](https://blog.digitalogy.co/python-interview-questions-and-answers-for-freshers/ "Top Python Interview Questions and Answers for Freshers in 2020")

>[2020年应届生Python面试题及答案大全](https://blog.digitalogy.co/python-interview-questions-and-answers-for-freshers/ "2020年应届生Python面试题及答案大全")

**Top Python Projects On GitHub**

GitHub is clearly home to a wide majority of code online. Python being an amazing and versatile programming language that it is has been used by thousands of developers to build all sorts of fun and useful projects. In the following section, we will try to cover some of the best projects on GitHub that are built using Python.

>**GitHub上的顶级Python项目**

>GitHub显然是绝大多数在线代码的家园。Python作为一种神奇而又通用的编程语言，已经被成千上万的开发者用来构建各种有趣而有用的项目。在下面的部分，我们将尝试涵盖GitHub上一些使用Python构建的最佳项目。

But before diving into this you can also check out some cool Python Project Ideas for Python Developers here —But before diving into this you can also check out some cool Python Project Ideas for Python Developers here —

>但在深入研究之前，你还可以在这里查看一些适合Python开发者的很酷的Python项目想法--。

>[为Python开发者提供10个酷炫的Python项目创意](https://towardsdatascience.com/10-cool-python-project-ideas-for-python-developers-7953047e203 "为Python开发者提供10个酷炫的Python项目创意")

###1. Manim

>https://youtu.be/ENMyFGmq5OA

Stars: 26.2k

Forked By: 3.4k

Developed by : Grant Sanderson

GitHub Link: https://github.com/3b1b/manim

Manim stands for Mathematical Animation Engine. The idea behind this project is to make it easier for people to integrate fun and intuitive animations with graphs and charts in Math teaching material, breaking away from the stereotype that learning Math has to be boring.

Grant runs a YouTube channel called 3Brown1Blue, where he uses the manim library to create and control these animations as required, to teach higher Mathematics to its audience. Using manim, you can also create animated videos with precise control over the animations used for your charts and illustrations. If this seems like a fun idea to you, you should check out his channel to see the library in action.

Youtube Link: https://www.youtube.com/channel/UCYO_jab_esuFRV4b17AJtAw

>关注量：26.2k

>复制量: 3.4k

>开发者：: Grant Sanderson

>GitHub链接: https://github.com/3b1b/manim

>Manim是Mathematical Animation Engine的缩写。这个项目背后的理念是让人们更容易在数学教材中整合有趣直观的动画与图形和图表，摆脱学习数学必须枯燥的刻板印象。

>格兰特在YouTube上经营着一个名为3Brown1Blue的频道，他根据需要使用manim库来创建和控制这些动画，向受众传授高等数学知识。使用manim，你还可以创建动画视频，精确控制用于图表和插图的动画。如果你觉得这是个有趣的想法，你应该去他的频道看看这个库的操作。

>Youtube链接：https://www.youtube.com/channel/UCYO_jab_esuFRV4b17AJtAw

###2. DeepFaceLab
Stars: 20.4k

Forked By: 4.8k

Developed By: iperov

GitHub Link: https://github.com/iperov/DeepFaceLab

DeepFaceLab is one of the most fun GitHub projects on Python on this list. DeepFaceLab is a tool that can create deep fakes images and videos, allowing you to do a lot of fun stuff such as change, de-age, and swap faces. To make things more compelling, you can even change their speech, although this requires proficiency in video editing software.

The developer claims that more than 95% of deep fake videos on the internet have been created with this tool. You can find the set-up guide and a bunch of facesets to get yourself started on the project’s GitHub page.

>###2. DeepFaceLab

>关注量: 20.4k

>复制量: 4.8k

>开发者: ieberov

>GitHub链接：https://github.com/iperov/DeepFaceLab

>DeepFaceLab是这个榜单上Python上最有趣的GitHub项目之一。DeepFaceLab是一个可以创建深度伪造图像和视频的工具，让你可以做很多有趣的事情，比如改变、去年龄、交换面孔。为了让事情更有说服力，你甚至可以改变他们的语音，不过这需要熟练掌握视频编辑软件。

>开发者声称，互联网上95%以上的深度假视频都是用这个工具制作的。你可以在项目的GitHub页面上找到设置指南和一堆面孔集来让自己入门。

>https://youtu.be/lSM-9RBk3HQ

###3. Airflow
Stars: 18.6k

Forked By: 7.3k

Developed By: Apache Software Foundation

GitHub Link: https://github.com/apache/airflow

Airflow is an open-source workflow management tool from the Apache Software Foundation that is powered by Python. Airflow lets you perform a range of activities on your workflows, such as authoring, scheduling, and monitoring them. Workflows, when defined as code, become much easier to manage, test, and collaborate.

It offers scalability, dynamic pipeline generation, and extensibility. The simple user interface makes working with Airflow smooth, and its robust integration capabilities with other tools and services help in getting the most out of it by saving time. Airflow is actively being used by some of the big names in the industry, such as Adobe, Lyft, Slack, Expedia, and more.

>###3. Airflow

>关注量: 18.6k

>复制量: 7.3k

>开发者： Apache软件基金会

>GitHub链接：https://github.com/apache/airflow

>Airflow是Apache软件基金会推出的一款开源工作流管理工具，由Python驱动。Airflow可以让你对你的工作流进行一系列的活动，比如编写、调度和监控它们。当工作流被定义为代码时，就会变得更容易管理、测试和协作。

>它提供了可扩展性、动态管道生成和可扩展性。简单的用户界面使Airflow的工作变得顺畅，其与其他工具和服务的强大集成能力有助于通过节省时间来获得最大的效益。Airflow正被业内一些大公司积极使用，如Adobe、Lyft、Slack、Expedia等。

>[10家使用Python的世界级公司](https://towardsdatascience.com/10-world-class-companies-using-python-26cde24919a8 "10家使用Python的世界级公司")

###4. GPT-2

Stars: 13.4k

Forked By: 3.4k

GitHub Link: https://github.com/openai/gpt-2

GPT-2 is a huge transformer-based language model that is trained on an equally massive dataset, text from over 8 billion web pages, to be exact. The goal? Predict the next word/s when given a set or all of the previous words from a context.

In simpler terms, you give GPT-2 some text, and the language model will predict and generate a lengthy continuation of the text of extraordinary quality.

The GitHub repo has the code and the models for OpenAI’s paper “Language Models are Unsupervised Multitask Learners”, while the page mentions the description and a few of caveats of GPT-2.

>###4. GPT-2

>关注量: 13.4k

>复制量: 3.4k

>GitHub链接: https://github.com/openai/gpt-2

>GPT-2是一个庞大的基于转换的语言模型，它是在一个同样庞大的数据集上进行训练的，确切地说，是来自80多亿网页的文本。它的目标是什么？当给定一组或所有前文中的单词时，预测下一个单词/s。

>简单来说，你给GPT-2一些文本，语言模型就会预测并生成一个质量非凡的冗长的文本延续。
GitHub repo上有OpenAI的论文 "Language Models are Unsupervised Multitask Learners "的代码和模型，而页面上提到了GPT-2的描述和一些注意事项。

>[2020年你必读的Python书籍](https://towardsdatascience.com/python-books-you-must-read-in-2020-a0fc33798bb "2020年你必读的Python书籍")

###5. XSStrike

https://youtu.be/Q_iymD9EWXM

Stars: 8.5k

Forked By: 1.2k

Developed By: Somdev Sangwan

GitHub Link: https://github.com/s0md3v/XSStrike

Cross-Site Scripting, aka XSS, is a vulnerability that can be extremely annoying and harmful for websites. By injecting malicious code from the client’s side, the attacker can cause damage to the website and the data beyond control. s0md3v’s XSStrike is essentially an XSS detection suite that is unique in itself.

The developer claims that instead of simply testing random payloads, his tool analyzes the websites and generates specially engineered payloads that work. Some of the various features of this tool include:

- Context analysis

- A powerful fuzzing engine

- Supports multi-threaded analysis

- Support for Bruteforcing payloads from a file

- A custom-made HTML and JavaScript parser

- Scanning of any outdated Javascript libraries

>###5. XSStrike

>https://youtu.be/Q_iymD9EWXM

>关注量: 8.5k

>复制量: 1.2k

>开发者: Somdev Sangwan

>GitHub 链接: https://github.com/s0md3v/XSStrike

>跨站脚本（Cross-Site Scripting），又名XSS，是一种对网站来说极为恼人和有害的漏洞。通过从客户端注入恶意代码，攻击者可以对网站和数据造成无法控制的破坏。s0md3v的XSStrike本质上是一个XSS检测套件，它本身就是独一无二的。

>开发者称，他的工具不是简单地测试随机的有效载荷，而是分析网站，并生成专门设计的有效载荷。该工具的一些不同功能包括。

>- 上下文分析
- 强大的模糊引擎
- 支持多线程分析
- 支持从文件中强制执行有效载荷。
- 一个定制的HTML和JavaScript解析器
- 扫描任何过时的Javascript库

>[Best Python Libraries for Machine Learning and Deep Learning](https://towardsdatascience.com/best-python-libraries-for-machine-learning-and-deep-learning-b0bd40c7e8c "Best Python Libraries for Machine Learning and Deep Learning")

###6. Google Images Download
Stars: 7.1k

Forked By: 1.7k

Developed By: Hardik Vasa

GitHub Link: https://github.com/hardikvasa/google-images-download

Hardik Vasa’s script lets you download hundreds of images off Google to your computer at once. The way this tool works is you install the library, use the command, mention your desired keywords as arguments, and let the tool work its magic. rebound essentially searches for the images with the specified keywords in Google Images’ index, and once found downloads them.

You can also use the library from another Python file, and it would still work as usual. A fun and useful project indeed, if you ever need to download images from Google in bulk in one go.

>###6. Google Images Download

>关注量: 7.1k

>复制量: 1.7k

>开发者: Hardik Vasa

>GitHub 链接: https://github.com/hardikvasa/google-images-download

>Hardik Vasa的脚本可以让你一次性从谷歌下载数百张图片到你的电脑上。这个工具的工作方式是你安装库，使用命令，提到你想要的关键字作为参数，然后让这个工具发挥它的魔力。rebound本质上是在Google Images的索引中搜索指定关键字的图片，一旦找到就下载它们。

>你也可以从另一个Python文件中使用该库，它仍然会像往常一样工作。如果你需要一次性从Google批量下载图片，这的确是一个有趣而有用的项目。

###7. Photon

Stars: 7k

Forked By: 965

Developed By: Somdev Sangwan

GitHub Link: https://github.com/s0md3v/Photon

Photon is a powerful and easy to use web-crawler that is built using Python. s0md3v’s lightweight and fast crawler follow the guidelines and methodologies from the Open-Source Intelligence framework, which allows the collection and analysis of information acquired from open or public sources.

Some of the many sources Photon can crawl information from include:

- URLs, including ones with parameters

- Social Media accounts, Emails

- Files such as pdf, png, XML documents

- Subdomains

- JavaScript files

Photon saves all the extracted information in an organized manner, which can even be exported as a JSON file. The tool also offers various options to customize its working, such as controlling the timeout, excluding some URLs, and so much more that we recommend you give it a deep dive.

>###7. Photon

>关注量: 7k

>复制量: 965

>开发者: Somdev Sangwan

>GitHub 链接: https://github.com/s0md3v/Photon

>Photon是一个使用Python构建的强大且易于使用的网络爬虫。s0md3v的轻量级和快速爬虫遵循开源智能框架的指导方针和方法，允许收集和分析从公开或公共来源获得的信息。

>Photon可以从众多来源中抓取的信息包括。

>- URL，包括带参数的URL

>- 社交媒体账户、电子邮件

>- 文件，如pdf、png、xml文件

>- 子域

>- JavaScript文件

>Photon将所有提取的信息有条理的保存起来，甚至可以导出为JSON文件。该工具还提供了各种选项来定制其工作，如控制超时，排除一些URL等。

>[Best Python IDEs and Code Editors You Must Use in 2020](https://towardsdatascience.com/best-python-ides-and-code-editors-you-must-use-in-2020-2303a53db24 "Best Python IDEs and Code Editors You Must Use in 2020")

###8. NeuralTalk

Stars: 5k

Forked By: 1.2k

Developed By: Andrej Karpathy

GitHub Link: https://github.com/karpathy/neuraltalk2

At its core, NeuralTalk is an image captioning project in Python and NumPy that used Multimodal Recurrent Neural Networks. Thanks to the improvements in the technology and better hardware support, the developer released NeuralTalk2, which is leagues better and faster than the original NeuralTalk.

Using a batched implementation, NeuralTalk2 still makes use of RNNs and is based on Torch, and can run on a GPU while supporting CNN finetuning. Although the developer has deprecated the original NeuralTalk, it is still available on GitHub for anyone to take a look.

>###8. NeuralTalk

>关注量: 5k

>复制量: 1.2k

>开发者: Andrej Karpathy

>GitHub 链接: https://github.com/karpathy/neuraltalk2

>NeuralTalk的核心是一个使用Python和NumPy的图像字幕项目，它使用了多模态循环神经网络。由于技术的改进和更好的硬件支持，开发者发布了NeuralTalk2，它比原来的NeuralTalk更好更快。

>NeuralTalk2采用了批量化的实现方式，仍然使用了RNNs，并且基于Torch，可以在GPU上运行，同时支持CNN微调。虽然开发者已经废弃了原来的NeuralTalk，但GitHub上仍然有，大家可以看看。

###9. Xonsh

Stars: 3.9k

Forked By: 434

GitHub Link: https://github.com/xonsh/xonsh

Pronounced as conch, you can think of Xonsh as a cross-platform shell language that is powered by Python. Xonsh makes working with Python, even the most basic of its tasks, miles better as it is integrated deeply within Xonsh.

With Xonsh, instead of typing “$ echo 2+2”, you could get away with using just $ 2+2, and it would still give you the correct result. How simple is that!

Getting started with Xonsh shell is super easy too, just install it with the right command for your environment and you’re all set. Xonsh is available for many package managers, including pip, Conda, Apt, Brew, and more. As for its features, Xonsh is easily scriptable, has a large standard library with typed variables, and much more.

>###9. Xonsh

>关注量：3.9万

>复制量: 434

>GitHub链接：https://github.com/xonsh/xonsh

>Xonsh 的发音是 “conch”  ，你可以把 Xonsh 看成是一个由 Python 支持的跨平台 shell 语言。Xonsh使Python的工作，即使是最基本的任务，也会变得更好，因为它深深地集成在Xonsh中。

>有了 Xonsh，你可以不输入"$ echo 2+2"，而只输入$ 2+2，它仍然会给你正确的结果。多么简单啊Xonsh shell的入门也非常简单，只需根据你的环境安装正确的命令就可以了。Xonsh适用于许多包管理器，包括pip、Conda、Apt、Brew等。至于它的功能，Xonsh很容易编写脚本，有一个大型的标准库，有类型化的变量，等等。

###10. Rebound

Stars: 3.3k

Forked By: 299

Developed By: Jonathan Shobrook

GitHub Link: https://github.com/shobrook/rebound

Compiler errors can often be extremely frustrating and confusing. The only solution there is then is to head over to Stack Overflow or read the documentation. Jonathan Shobrook and his famous tool rebound, has found a way to make your life easier while dealing with those pesky compiler errors.

The way rebound works is that you run your file with the tool, and it will check for any compiler errors present in the file and fetch you any related Stack Overflow threads it can find.

Rebound’s ability to load threads within the terminal as well as in the browser can be a life-saver for not just rookies but also veteran coders, saving their time in endlessly searching for answers. At the moment, rebound only supports Python, Node.js, Ruby, Golang, and Java.

>###10. 反弹

>关注量：3.3万

>复制量: 299

>开发者：Jonathan Shobrook Jonathan Shobrook

>GitHub链接：https://github.com/shobrook/rebound

>编译器错误往往是非常令人沮丧和困惑的。那么唯一的解决办法就是前往Stack Overflow或阅读文档。Jonathan Shobrook和他著名的工具rebound，已经找到了一种方法，让你在处理那些讨厌的编译器错误时，生活更加轻松。

>rebound的工作方式是，你用这个工具运行你的文件，它将检查文件中存在的任何编译器错误，并为你调取它能找到的任何相关的Stack Overflow线程。

>Rebound能够在终端内以及浏览器中加载线程，这不仅对菜鸟来说是救命稻草，对老手来说也是救命稻草，节省了他们无休止地寻找答案的时间。目前，rebound只支持Python、Node.js、Ruby、Golang和Java。

###Conclusion

Creativity also has no limits. GitHub projects like these that are the perfect showcase of people’s creativity and talent. But this is just the tip of the iceberg as Python can be used to carry out a broad range of activities, granted you have the know-how and a clear picture of what you want to achieve. As Python continues to evolve, more and more developers will start to use it to build amazing and resourceful projects like the ones we mentioned above. Let this article be a source of inspiration for you to wake up that sleeping idea in your mind and set things into motion.

Note: To eliminate problems of different kinds, I want to alert you to the fact this article represent just my personal opinion I want to share, and you possess every right to disagree with it.

If you have more suggestions or ideas, I’d love to hear about them

>###结论

>创意也是没有限制的。GitHub这样的项目，是人们创造力和天赋的完美展示。但这仅仅是冰山一角，因为Python可以用来进行广泛的活动，前提是你有技术诀窍，并且清楚地了解你想要实现的目标。随着Python的不断发展，越来越多的开发者将开始使用它来构建像我们上面提到的那些令人惊奇和资源丰富的项目。让这篇文章成为您的灵感来源，唤醒您脑海中沉睡的想法，并将事情付诸行动。

>注：为了杜绝各种问题，我要提醒你，本文仅代表我个人的观点，我想与大家分享，你拥有完全不同意的权利。

>如果你有更多的建议或想法，我很想听听。

本作品采用知识共享署名-非商业性使用-相同方式共享 4.0 国际许可协议进行许可，转载请附上原文出处链接和本声明。
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