This content originally appeared on DEV Community and was authored by Code_Jedi
Here is a researched and handpicked list of the top python github repos and libraries containing the essentials of learning python, from zero to hero!
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5. A python cheatsheet of python essentials such as: operators, data types, functions and more!
trekhleb
/
learn-python
? Playground and cheatsheet for learning Python. Collection of Python scripts that are split by topics and contain code examples with explanations.
Playground and Cheatsheet for Learning Python
This is a collection of Python scripts that are split by topics and contain code examples with explanations, different use cases and links to further readings.
Read this in Português.
It is a playground because you may change or add the code to see how it works and test it out using assertions. It also allows you to lint the code you've wrote and check if it fits to Python code style guide Altogether it might make your learning process to be more interactive and it might help you to keep code quality pretty high from very beginning.
It is a cheatsheet because you may get back to these code examples once you want to recap the syntax of standard Python statements and constructions. Also because the code is full of assertions you'll be able to see expected functions/statements output right away…
4. A python module perfect for machine learning. If you're going to be looking into machine learning further down the line in your python development journey, keep this library at the back of your head!
scikit-learn
/
scikit-learn
scikit-learn: machine learning in Python
scikit-learn is a Python module for machine learning built on top of SciPy and is distributed under the 3-Clause BSD license.
The project was started in 2007 by David Cournapeau as a Google Summer of Code project, and since then many volunteers have contributed. See the About us page for a list of core contributors.
It is currently maintained by a team of volunteers.
Website: https://scikit-learn.org
Installation
Dependencies
scikit-learn requires:
- Python (>= 3.7)
- NumPy (>= 1.14.6)
- SciPy (>= 1.1.0)
- joblib (>= 0.11)
- threadpoolctl (>= 2.0.0)
Scikit-learn 0.20 was the last version to support Python 2.7 and Python 3.4. scikit-learn 0.23 and later require Python 3.6 or newer scikit-learn 1.0 and later require Python 3.7 or newer.
Scikit-learn plotting capabilities (i.e., functions start with plot_ and
classes end with "Display") require Matplotlib (>= 2.2.2)
For running the examples Matplotlib >= 2.2.2 is required.
A few examples require scikit-image >= 0.14.5, a…
3. A curated list of awesome Python frameworks, libraries, software and resources.
vinta
/
awesome-python
A curated list of awesome Python frameworks, libraries, software and resources
Awesome Python 
A curated list of awesome Python frameworks, libraries, software and resources.
Inspired by awesome-php.
-
Awesome Python
- Admin Panels
- Algorithms and Design Patterns
- ASGI Servers
- Asynchronous Programming
- Audio
- Authentication
- Build Tools
- Built-in Classes Enhancement
- Caching
- ChatOps Tools
- CMS
- Code Analysis
- Command-line Interface Development
- Command-line Tools
- Compatibility
- Computer Vision
- Concurrency and Parallelism
- Configuration
- Cryptography
- Data Analysis
- Data Validation
- Data Visualization
- Database Drivers
- Database
- Date and Time
- Debugging Tools
- Deep Learning
- DevOps Tools
- Distributed Computing
- Distribution
- Documentation
- Downloader
- E-commerce
- Editor Plugins and IDEs
- Enterprise Application Integrations
- Environment Management
- Files
- Foreign Function Interface
- Forms
- Functional Programming
- Game Development
- Geolocation
- GUI Development
- Hardware
- HTML Manipulation
- HTTP Clients
- Image Processing
- Implementations
- Interactive Interpreter
- Internationalization
- Job Scheduler
- Logging
- Machine Learning
- Miscellaneous
- Natural Language Processing
- Network Virtualization
- News Feed
- ORM
- Package Management
- Package Repositories
- Penetration testing
- Permissions
- Processes
- Recommender Systems
- Refactoring
- RESTful API
- Robotics
- RPC Servers
- Science
- Search
- Serialization
- Serverless Frameworks
- Shell
- Specific Formats…
2. A 100 day python guide packed with great projects, tutorials, info and more!(will need to be translated to english using google translate since it's written in Chinese)
jackfrued
/
Python-100-Days
Python - 100天从新手到大师
Python - 100天从新手到大师
作者：骆昊
说明：从项目上线到获得8w+星标以来，一直收到反馈说基础部分（前15天的内容）对新手来说是比较困难的，建议有配套视频进行讲解。最近把基础部分的内容重新创建了一个名为“Python-Core-50-Courses”的项目，用更为简单通俗的方式重写了这部分内容并附带了视频讲解，初学者可以关注下这个新项目。国内用户如果访问GitHub比较慢的话，也可以关注我的知乎号Python-Jack上的“从零开始学Python”专栏，专栏会持续更新，还有大家比较期待的“数据分析”的内容也即将上线，欢迎大家关注我在知乎的专栏、文章和回答。
创作不易，感谢大家的打赏支持，这些钱基本不会用于购买咖啡，而是通过腾讯公益、美团公益、水滴筹等平台捐赠给需要帮助的人（点击了解捐赠情况）。需要加入QQ交流群的可以扫描下面的二维码，交流群会为大家提供学习资源和问题解答，还会持续为大家带来免费的线上Python体验课和行业公开课，敬请关注。
Python应用领域和职业发展分析
简单的说，Python是一个“优雅”、“明确”、“简单”的编程语言。
- 学习曲线低，非专业人士也能上手
- 开源系统，拥有强大的生态圈
- 解释型语言，完美的平台可移植性
- 动态类型语言，支持面向对象和函数式编程
- 代码规范程度高，可读性强
Python在以下领域都有用武之地。
- 后端开发 - Python / Java / Go / PHP
- DevOps - Python / Shell / Ruby
- 数据采集 - Python / C++ / Java
- 量化交易 - Python / C++ / R
- 数据科学 - Python / R / Julia / Matlab
- 机器学习 - Python / R / C++ / Julia
- 自动化测试 - Python / Shell
作为一名Python开发者，根据个人的喜好和职业规划，可以选择的就业领域也非常多。
- Python后端开发工程师（服务器、云平台、数据接口）
- Python运维工程师（自动化运维、SRE、DevOps）
- Python数据分析师（数据分析、商业智能、数字化运营）
- Python数据挖掘工程师（机器学习、深度学习、算法专家）
- Python爬虫工程师
- Python测试工程师（自动化测试、测试开发）
说明：目前，数据分析是一个非常热门的方向，因为不管是互联网行业还是传统行业都已经积累了大量的数据，现在需要的就是从这些数据中提取有价值的信息，以便打造更好的产品或者为将来的决策提供支持。
给初学者的几个建议：
- Make English as your working language. （让英语成为你的工作语言）
- Practice makes perfect. （熟能生巧）
- All experience comes from mistakes. （所有的经验都源于你犯过的错误）
- Don't be one of the leeches. （不要当伸手党）
- Either outstanding or out. （要么出众，要么出局）
Day01~15 - Python语言基础
Day01 - 初识Python
- Python简介 - Python的历史 / Python的优缺点 / Python的应用领域
- 搭建编程环境 - Windows环境 / Linux环境 / MacOS环境
- 从终端运行Python程序 -…
1. A python repo that implements, explains and demonstrates almost every python algorithm that you would ever need to learn!
TheAlgorithms
/
Python
All Algorithms implemented in Python
The Algorithms - Python
All algorithms implemented in Python (for education)
These implementations are for learning purposes only. Therefore they may be less efficient than the implementations in the Python standard library.
Contribution Guidelines
Read our Contribution Guidelines before you contribute.
Community Channel
We're on Gitter! Please join us.
List of Algorithms
See our directory.
If you want more of a hands-on approach to python, Here is a course popular among python beginners that will give you just that:The Python Mega Course: Build 10 Real World Applications
NOTE: I'm not affiliated with this course or udemy in any way.
That's it for this compilation!
Byeeeee?
This content originally appeared on DEV Community and was authored by Code_Jedi
Code_Jedi | Sciencx (2021-07-18T09:22:53+00:00) 5 GitHub Projects Essential For Every Beginner Python Developer. Retrieved from https://www.scien.cx/2021/07/18/5-github-projects-essential-for-every-beginner-python-developer/
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