10 cool GitHub projects in Python

Developers are increasingly choosing for their projects Python. On GitHub it has become the second most popular language, and since we are talking about the largest of its kind in the IT-web service, that means a lot.

Why developers are so fond of Python? There are several reasons: simple syntax, concise and clear code, high efficiency, large selection of important packages, etc.

Python is one of those languages that allow to implement almost any project and to demonstrate all facets of his talent.

In this article we will tell you about a few great projects GitHub created this language, which not only clearly show you all the capabilities of Python, but also will bring a lot of inspiration. Go!

1. Manim

Assessment: 26,2 To

Cloned: 3.4 To

Author: Grant Sanderson

Manim (Mathematical Animation Engine) is an engine animation for explanatory math videos. Thanks to him, boring learning materials can be presented in easy-to-read animated graphs, charts, etc. Thus, the study of mathematical science becomes more fun and effective.

If you want to see for yourself, visit YouTube channel, Grant Sanderson 3Blue1Brown. He uses Manim for the design of materials for higher mathematics. With all the features of the library you can get acquainted by watching this video.

2. DeepFaceLab

Rating: 20,4 To

Cloned: 4,8 To

Author: iperov

This project is likely to impress you more than all the others in this collection. DeepFaceLab using technology deepfake allows you to change the way people look at photos and videos, including rejuvenate, swap faces and even adjust it. According to the developer, 95% of all deepfake clips were created from this software. Visit DeepFaceLab on GitHub posted a guide and even a bit of workpieces individuals to start work. And here you can see instructions on how to do deepfake video with DeepFaceLab.

3. Airflow

Assessment: 18,6 K

Cloned: 7,3 K

Author: Apache Software Foundation

This link leads to a platform for creating, planning and monitoring workflows. The Airflow through them much easier to manage, test, and make it work. The advantages of this scheduler are simple interface, scalability, integration with other services, the ability to connect third-party tools. No wonder they are team giants such as Adobe, Lyft, and Expedia.

4. GPT-2

Assessment: 13,4 To

Cloned: 3.4 To

Author: WuTheFWasThat

This project is a big language model, a learning on a huge dataset (text in 8 billion web pages). It predicts the next word or continuation proposal, when the user sets the first word (the initial part of the context). In other words, you give GPT-2 text, and it generates on its basis high-quality a detailed proposal. On GitHub there is a description of the project and its main features.

5. XSStrike

Rating: 8,5 To

Cloned: 1.2 To

Author: Somdev Sangwan

The most advanced scanner XSS, protecting the sites against malicious code that an attacker can inject client-side.

Features XSStrike:

  • analyzes the context;
  • has a strong fuzzing engine;
  • supports multithreaded analysis;
  • there are individual JS and HTML analyzer;
  • scans outdated JS libraries.

A detailed review in this video.

6. Download the image files from Google

Rating: 7.1 K

Cloned: 1.7

Author: Hardik Vasa

Python script to download on the PC the images from Google Images. Need to install the library, select the command to set the keywords and the program will start to do wonders! It will find all the images that match the entered keywords, and downloads them to your computer. Quite unusual, interesting and useful project, if you need to quickly and easily download images from Google.

7. Photon

Assessment: 7K

Cloned: 965

Author: Somdev Sangwan

Incredibly powerful, fast and simple scanner that uses intelligence technology. It carries out collection and analysis of information found in open sources.

That’s where Photon receives and scans the data where:

  • URL;
  • profiles in social networks;
  • email address;
  • files (documents);
  • subdomains;
  • JS-files.

Photon received information organizes and maintains, so then you can do data export to a text file JSON. This tool provides these settings, as changing the timeout, add URLS to exclude, etc.

8. NeuralTalk

Assessment: 5K

Cloned: 1.2 To

Author: Andrej Karpathy

Efficient code for signature creation to a graphic file that uses a neural network. There is a second version – NeuralTalk2 more perfect, technologically advanced and fastest option. The basis of the new version lies Torch, it functions on the GPU and supports fine-tuning of the neural network. Although the original NeuralTalk stopped, she was still publicly available on GitHub.

9. Xonsh

Guest Rating: 3.9 K

Cloned: 434

Author: Anthony Scopatz

Cross-platform shell with the Unix support on the basis of Python. Xonsh significantly improves the use of Python, even if we consider the most basic tasks, due to the deep integration.

For example, Xonsh you can earn $ 3 + 3 is “$ echo 3+3”, and the result will not change.

To start working with this shell simple – it is installed with one single command (depending on the environment you are using). Xonsh supports scripts, an extensive collection of typed variables, etc.

10. Rebound

Guest Rating: 3.3 To

Cloned: 299

Author: Jonathan Shobrook

Rebound is a very useful tool, because it is almost a panacea for the nervous breakdowns, the reason for the compiler error. What we usually do when they arise? Of course, we go on Stack Overflow and trying to find an answer there, or studying the documentation. Thanks to Rebound this process easier at times!

The principle of operation of this device is simple: the developer runs your file, the program checks it for errors compiler, and then immediately loads all associated with the detected problem answers portal Stack Overflow.

Thus, Rebound is useful not only for beginners but also for experienced programmers, because it allows not to waste time looking for the right answer among the endless ocean of information. Rebound now supports Java, Ruby, Go, Node.js and, of course, Python.

Conclusion

The imagination and creativity of talented people has no limits. The collection of projects – a clear confirmation. But don’t forget that Python is not static: it develops very fast. So very soon you will be able to use it to solve more complex tasks! The main thing is to have clear objectives, a good knowledge and work hard, do not bow to difficulties.

 

Let this material will inspire you on your own awesome projects!

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