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5 GitHub Projects Essential For Every Beginner Python Developer

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!

GitHub logo 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

Build Status

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, Español, Traditional Chinese.

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…


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!

GitHub logo scikit-learn / scikit-learn

scikit-learn: machine learning in Python

Azure Travis Codecov CircleCI Nightly wheels Black PythonVersion PyPi DOI Benchmark

https://raw.githubusercontent.com/scikit-learn/scikit-learn/main/doc/logos/scikit-learn-logo.png

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 (>= 1.0.0)
  • 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 (>= 2.2.3) For running the examples Matplotlib >= 2.2.3 is required. A few examples require scikit-image >= 0.14.5, a…


3. A curated list of awesome Python frameworks, libraries, software and resources.


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)

GitHub logo 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制作了一个名为“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。如果需要Python基础视频,可以在“B站”搜索《Python零基础快速上手》,这套视频是我讲课的时候录制的随堂视频,画质尚可、音质一般,但是对初学者应该会有些帮助,欢迎大家留言、评论、发弹幕。学习之后觉得有收获的小伙伴可以“一键三连”来支持UP主(千锋Python)。国内用户如果访问GitHub比较慢的话,可以关注我的知乎号Python-Jack,上面的“从零开始学Python”专栏比较适合初学者,其他的专栏也在持续创作和更新中,欢迎大家关注并点赞评论。

创作不易,感谢大家的打赏支持,这些钱不会用于个人消费(例如: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学习群的可以扫描下面的二维码,三个群加一个即可,不要重复进群。学习群会为大家提供学习资源问题解答,如果有Python体验课行业公开课会提前在群里通知大家,欢迎大家加入。

项目“Day80~90”部分目前仍在创作中,因为作者平时也挤不出太多时间来写文档,因此更新的速度比较缓慢,感谢大家的理解。

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,数据分析和数据挖掘是非常热门的方向,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,各行各业都需要数据分析师从已有的数据中发现更多的商业价值,从而为企业的决策提供数据的支撑,这就是所谓的数据驱动决策。

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…

1. A python repo that implements, explains and demonstrates almost every python algorithm that you would ever need to learn!

GitHub logo TheAlgorithms / Python

All Algorithms implemented in Python

The Algorithms - Python

Gitpod Ready-to-Code Contributions Welcome Donate Discord chat Gitter chat
GitHub Workflow Status LGTM pre-commit code style: black

All algorithms implemented in Python - for education

Implementations are for learning purposes only. As they may be less efficient than the implementations in the Python standard library, use them at your discretion.

Getting Started

Read through our Contribution Guidelines before you contribute.

Community Channels

We're on Discord and Gitter! Community channels are great for you to ask questions and get help. Please join us!

List of Algorithms

See our directory for easier navigation and better overview of the project.





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Discussion (2)

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fingerzz profile image
Lazar Slavkovic-Raco

This is quite interesting for people who got entry-level jobs in I.T. industries. Great article!

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MOHAMMAD SHAHBAZ ALAM

Thank you for sharing.