GitHub hot quick view Vol.24: programmers self-value-added, elegant earn pocket money

Author: HelloGitHub- Dried fish

Abstract: It is the dream of many people to get promoted, get a raise, serve as CTO, marry Bai Fumei/gao Shuai fu, and walk towards the peak of life. Find out how Easy, a freelance writer, makes an elegant way to earn pocket money and change your life by making time to get rich. When it comes to self-appreciation of programmers, in addition to making money gracefully, they can also study the code implementation of various small tools in life, such as vanillawebprojects, which collects 20+ Web applets. Apply technology to your life, show your technology to assist your daily “liver” pocket goblins, or occasionally use technology to add a little fun to your life, using genetic algorithms to create a small toy that draws the image process.

The following is an excerpt from GitHub Trending at @helloGithub. Newly released | | practical and interesting, according to the project classification, the release time release time not more than 7 day program will be marked New, without the mark shows the project release more than one week. Due to the limited space in this paper, there are some projects not shown in this paper, please refer to 🌝

This article directory
- 1. This week, pushing
  - 1.1 Genetic algorithm toys: gene-drawing
  - 1.2 Musk Rocket: SpaceX-API
- 1. Making Trending Zhou Bang
  - 2.1 Go Grammar book: Go-ast-book
  - 2.2 Database partner: Xgenecloud
  - 2.3 front-end gadgets: vanillawebprojects
  - 2.4 Statistical code: Lihang-code
  - 2.5 Poke 辅助工具：Pokedex
  - 2.6 High-performance Framework: Fastapi
  - 2.7 JS Questions: javascript-questions
- 1. This week’s GitHub Trending is the focus of # Coders add Value
  - 3.1 Elegant money making: howto-make-more-money
  - 3.2 Investing changes destiny: regular-investing-in-box
  - 3.3 Personal Notes for machine Learning Courses: Coursera-ML-AndrewNg-Notes
- 1. Recommended reading

1. Tweet this week

1.1 Genetic algorithm toys: gene-drawing

Star growth this week: 1200+

In 2017, the author of Newgene-drawing made a toy project that imitates the drawing process of a given target image. The effect is shown in the following figure. Inspired by many examples of gene mapping on the Internet, the project has been so popular that the authors have recently made it open source.

Making address – https://github.com/anopara/genetic-drawing

1.2 Musk Rocket: SpaceX-API

Star growth this week: 900+

SpaceX-API is an open source REST API for rockets, core modules, capsules, launch pads, and launch data. Technology stack

Deployed on Linode servers in Central America
Nodejs Koa framework is used
Redis, Nginx, and Cloudflare are used for content caching
Jest and Supertest were used for testing
Circle CI is used for continuous integration/deployment
All data is stored in a replica set cluster of MongoDB Atlas 3 nodes
Use Mongodump to back up data at night

Making address – https://github.com/r-spacex/SpaceX-API

2. GitHub Trending Weekly

2.1 Go Grammar book: Go-ast-book

Star growth this week: 1000+

Go-ast-book is a go syntax tree introduction project. Let’s revisit the Go language program in the syntax tree dimension, and we’ll get the technology to create the Go language itself. This book provides a brief introduction to the use of syntax tree related packages.

Making address – https://github.com/chai2010/go-ast-book

2.2 Database partner: Xgenecloud

Star growth this week: 800+

New Xgenecloud is a REST and GraphQL API tool that generates real-time data on any database. It supports MySQL, PostgreSQL, MsSQL, SQLite, MariaDB, etc. Features:

Generate REST apis for existing databases
Provides a GUI for debugging
The generated apis can be deployed on any cloud platform based on Serverless

Making address – https://github.com/xgenecloud/xgenecloud

2.3 front-end gadgets: vanillawebprojects

Star growth this week: 1100+

Vanillawebprojects is a collection of over 20 small apps developed with front-end technologies (Javascript, CSS, HTML5), including: form validation, currency calculation, typing games, voice reading, New Year countdown, and more.

Making address – https://github.com/bradtraversy/vanillawebprojects

2.4 Statistical code: Lihang-code

Star growth this week: 10900+

“Statistical Learning Methods” can be said to be the introduction of machine learning treasure book, many machine learning training courses, Internet enterprises interview, written questions, many reference this book. This project includes all the code implementations of the book, especially supervised learning methods, including perceptron, K-nearest neighbor, Naive Bayes, decision trees, Logistic regression and support vector machines, lifting methods, EM algorithms, hidden Markov models and conditional random fields.

Making address – https://github.com/fengdu78/lihang-code

2.5 Poke 辅助工具：Pokedex

Star growth this week: 500+

NewPokedex uses the Dagger Hilt, Motion, Coroutines, And Poke (pocket goblin) AIDS developed by Jetpack based on MVVM architecture. This project focuses on implementing a new library for dependency injection that supports fetching data from the network and integrating persistent data in a database through a repository pattern.

Making address – https://github.com/skydoves/Pokedex

2.6 High-performance Framework: Fastapi

Star growth this week: 1300+

Fastapi is a Python-based framework that encourages documentation using Pydantic and OpenAPI, rapid development and deployment using Docker, and simple testing based on the Starlette framework. Features:

A high performance
Code quickly: Speed up feature development by about 200% to 300%
Fewer errors: approximately 40% fewer human errors (developers)
Intuitive: Powerful editor support. Completion is everywhere. Less debugging time
Simplicity: Designed to be easy to use and learn. Reduce the time you spend reading documents
Short: Minimizes code duplication. Multiple functions per parameter declaration, with fewer errors
Robust: Get production-ready code, with automated interactive documentation.
Standards-based: Open standards based on (and fully compatible with) apis

Making address – https://github.com/tiangolo/fastapi

2.7 JS Questions: javascript-questions

Star growth this week: 800+

From basic to advanced, JavaScript Questions includes JS related interview Questions and solutions.

Making address – https://github.com/lydiahallie/javascript-questions

3. This week GitHub Trending is leading the # Coders add Value # theme

In the theme module of this issue, Dried Fish has selected 3 value-added gadgets to improve your happiness in life and work.

3.1 Elegant money making: howto-make-more-money

Howto -make-more-money is an elegant program that @easy tells you howto earn your pocket money. It’s a program that teaches you howto earn your pocket money, but you can learn about your core resources and howto create assets by reading this how-make-more-money book.

Making address – https://github.com/easychen/howto-make-more-money

3.2 Investing changes destiny: regular-investing-in-box

Make a decision to change your fate — and let time get you rich. Regular-investing -in-box is the path for ordinary people to get out of class – absolutely doable, waterless, and all on your own. Ordinary people here, regardless of national boundaries, regions, races, genders, ages, tall, short, thin, beautiful, ugly, and sexual orientation… The point is, it doesn’t even matter what IQ or degree you have! In other words, it’s a solution that could work even for a delivery boy running errands in Beijing…

Making address – https://github.com/xiaolai/regular-investing-in-box

3.3 Personal Notes for machine Learning Courses: Coursera-ML-AndrewNg-Notes

Coursera-ml-andrew ng-notes is a personal note from AndrewNg’s machine learning course, which aims to provide a broad introduction to machine learning, data mining, and statistical pattern recognition. Topics include:

Supervised learning (parametric/nonparametric algorithms, support vector machines, kernel functions, neural networks).
Unsupervised learning (clustering, dimensionality reduction, recommendation system, deep learning recommendation).
Best practices in machine learning (bias/variance theory; In machine learning and artificial intelligence innovation processes).

Using extensive case studies, you can learn how to use learning algorithms to build intelligent robots (perception, control), text comprehension (Web search, anti-spam), computer vision, medical information, audio, data mining, and other fields.

Making address – https://github.com/fengdu78/Coursera-ML-AndrewNg-Notes