On January Github's most popular open source Python project!

January on GitHub most popular open source Python project ranking has been released you, take a look at the list details:

 

 

1

fastapi

https://github.com/tiangolo/fastapi Star 9051

 

FastAPI Rails is a library for fast data query interdependent set of human-readable and return time, standard API output. By constructing complex SQL queries and efficient use of JOIN and sub-queries.

 

 

2

ALBERT

https://github.com/google-research/ALBERT Star 3802

 

ALBERT model is an improved version of BERT, and other recent State of the art model different is that this is a small model pre-trained, better, fewer parameters. It has been three BERT renovation:

  • Word embedded vector parameter factorization

  • Cross-layer parameter sharing

  • Paragraph continuous task

 

 

3

spiderfoot

https://github.com/smicallef/spiderfoot Star 3802

 

 

SpiderFoot is a free, open-source Web site information gathering tool, you can get information based on the specified domain name, such as website subdomains, email addresses, web server version, etc., can help penetration testers for automating web site information collection, asset discovery the process, improve work efficiency.

 

 

4

JobFunnel

https://github.com/PaulMcInnis/JobFunnel Star 1244

 

Crawl work sites, filtering and inspection checklist tool for the job posting climb .csv file.

 

 

5

SlowFast

https://github.com/facebookresearch/SlowFast Star 2005

 

PySlowfast is based PyTorch code base, so that researchers can easily reproduced from basic to cutting-edge video recognition (Video Classification) and behavior detection (Action Detection) algorithm.

 

 

Not only that, PySlowFast open source code base at the same time a large number of pre-training model (pretrain models), allowing researchers to eliminating the trouble of repeated training model can be used directly FAIR pre-trained frontier (cutting edge performance) model. By a Facebook Open Source

 

 

6

system-design-primer

https://github.com/donnemartin/system-design-primer Star 82155

 

 

The project is on how to design large-scale systems, as well as how to deal with system design interview. The system design is a very broad topic. On the Internet, the resources on the system design principles is a dime a dozen. The warehouse is to organize the collection of these resources, it can help you learn how to build scalable systems.

 

 

7

ansible

https://github.com/ansible/ansible Star  41269

 

Ansible is a configuration management and configuration tools, like Chef, Puppet or Salt. This is a very simple and very easy to deploy tools to get started, it uses the SSH connection to the server and runs the configured tasks, without having to install any extra software on the server only needs to open ssh, all the work to be responsible for client-side ansible .

 

 

8

pandas

https://github.com/pandas-dev/pandas Star  23377

 

 

 

Pandas is a data analysis package python, the first in April 2008, was developed by AQR Capital Management, and at the end of 2009 revenue came out, there continue to develop a focus on Python packets developed PyData development team and maintenance, are PyData part of the project . Pandas and was originally developed as a financial data analysis tools, therefore, pandas time series analysis provides a good support. Pandas name from python and data analysis (data analysis) data of the panel (panel data). panel data is a term regarding economics cube, also provided in the panel Pandas data types.

 

 

9

GitHub-Chinese-Top-Charts

https://github.com/kon9chunkit/GitHub-Chinese-Top-Charts Star 14343

 

GitHub中文排行榜,帮助你发现高分优秀中文项目、更高效地吸收国人的优秀经验成果;榜单每周更新一次。

 

 

10

mlflow

https://github.com/mlflow/mlflow Star 5832

 

MLflow 是由 Apache Spark 技术团队开源的一个机器学习平台,主打开放性:

开放接口:可与任意 ML 库、算法、部署工具或编程语言一起使用。

开源:开发者可轻松地对其进行扩展,并跨组织共享工作流步骤和模型。

MLflow的当前版本是alpha版本。这意味着API和数据格式可能会发生变化!

 

 

11

spinningup

https://github.com/openai/spinningup Star 4105

 

Spinning Up 是大名鼎鼎的Open AI推出的免费强化学习教学项目,旨在降低强化学习的门槛,让初学者能在项目实践的过程中一步一步循序渐进地学习。项目不仅提供了详细的理论介绍,同时还有完整的练习代码,真的不不愧是学习深度强化学习的良心之作。

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Origin blog.csdn.net/aa120515692/article/details/104265777