Python 有哪些好的学习资料或者博客

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Python 有哪些好的学习资料或者博客,第1张

推荐Full Stack Python 有各种python资源汇总,从基础入门到各种框架web应用开发和部署,再到高级的ORM、Docker都有。以下是Full Stack Python 上总结的一些教程,我拙劣的翻译了以下,并调整(调整顺序并删了部分内容)了一下:

1、无开发经验,初学python

如果你不会其他语言,python是你的第一门语言:

A Byte of Python (简明python教程,这个有中文版简明 Python 教程)是非常好的入门教程。

Learn Python the Hard Way (Zed Shaw的免费教程,个人强烈推荐)

Python, Django and Flask教程: Real Python (收费,需购买)

short 5 minute video 解释了为什么你的出发点应该是要完成什么项目,或者解决什么问题,而不是为了学一门语言而去学一门语言。

Dive into Python 3 是一本开源的python教程,提供HTML和PDF版。

Code Academy 有一个为纯新手准备的 Python track 。

Introduction to Programming with Python 介绍了基本语法和控制结构等,提供了大量代码示例。

O'Reilly 的书 Think Python: How to Think Like a Computer Scientist 是非常好的入门教材。

Python Practice Book 是一本python练习的书,帮你掌握python基本语法。

想通过做实际项目来学编程?看看这个 this list of 5 programming project for Python beginners(5个适合python初学者的编程项目)。

Reddit的创造者之一写了一个教程,如何用python构建一个博客网站(use Python to build a blog.),使非常好的web编程入门。

The fullstack python的作者写了一篇关于如何学习python的文章learning Python 。

2、有开发经验 ,初学Python

Learn Python in y minutes ,让你在几分钟内快速上手,有个大概了解。

Python for you and me , python的语法,语言的主要结构等,还包含来Flask Web App的教程。

The Hitchhiker’s Guide to Python

How to Develop Quality Python Code ,如何开发高质量的python代码

3、进阶

The Python Ecosystem: An Introduction , 关于python生态系统,虚拟机、python包管理器pip、虚拟环境virtualenv、还有很多进阶主题

The Python Subreddit ,就是python的reddit节点(相当于中国的贴吧),是一个活跃的社区,可以交流讨论,解决问题等。

Good to Great Python Reads ,收集进阶和高级python文章,讲了很多细微差异和python语言本身的细节。

博客 Free Python Tips ,有很多python和python生态系统的文章。

Python Books ,有一些免费的Python, Django, 数据分析等方面的书。

Python IAQ: Infrequently Asked Questions ,关于python 经常问到的问题。

4、视频,屏幕录像,演示文稿等

一些技术交流会议的视频录像: best Python videos

5、python的包

awesome-python ,收集了python各种非常好用非常酷的包,确实非常awesome,让作者相见恨晚( I wish I had this page when I was just getting started)。

easy-python

6、 播客(Podcasts)

Talk Python to Me , 关注使用python的人们和组织,每一期都会邀请一些开发者谈谈他们的工作等。

Podcast.__init__ ,关于python和让python更牛B的人们。

7、新闻资讯(可订阅)

Python Weekly , 最新的python文章、视频、项目、资讯 。

PyCoder's Weekly ,和python weekly类似。

Import Python

以下是引用的原文:

New to programming

If you're learning your first programming language these books were written with you in mind. Developers learning Python as a second or later language should skip down to the next section for "experienced developers".

To get an introduction to Python, Django and Flask at the same time, consider purchasing the Real Python course by Fletcher, Michael and Jeremy.

This short 5 minute video explains why it's better to think of projects you'd like to build and problems you want to solve with programming. Start working on those projects and problems rather than jumping into a specific language that's recommended to you by a friend.

CS for All is an open book by professors at Harvey Mudd College which teaches the fundamentals of computer science using Python. It's an accessible read and perfect for programming beginners.

If you've never programmed before check out the Getting Started page on Learn To Code with Me by Laurence Bradford. She's done an incredible job of breaking down the steps beginners should take when they're uncertain about where to begin.

Learn Python the Hard Way is a free book by Zed Shaw.

Dive into Python 3 is an open source book provided under the Creative Commons license and available in HTML or PDF form.

While not Python-specific, Mozilla put together a Learning the Web tutorial for beginners and intermediate web users who want to build websites. It's worth a look from a general web development perspective.

A Byte of Python is a beginner's tutorial for the Python language.

Code Academy has a Python track for people completely new to programming.

Introduction to Programming with Python goes over the basic syntax and control structures in Python. The free book has numerous code examples to go along with each topic.

Google put together a great compilation of materials and subjects you should read and learn from if you want to be a professional programmer. Those resources are useful not only for Python beginners but any developer who wants to have a strong professional career in software.

The O'Reilly book Think Python: How to Think Like a Computer Scientist is available in HTML form for free on the web.

Python Practice Book is a book of Python exercises to help you learn the basic language syntax.

Looking for ideas about what projects to use to learn to code? Check out this list of 5 programming project for Python beginners.

There's a Udacity course by one of the creators of Reddit that shows how to use Python to build a blog. It's a great introduction to web development concepts through coding.

I wrote a quick blog post on learning Python that non-technical folks trying to learn to program may find useful.

Experienced developers new to Python

Learn Python in y minutes provides a whirlwind tour of the Python language. The guide is especially useful if you're coming in with previous software development experience and want to quickly grasp how the language is structured.

Python for you and me is an approachable book with sections for Python syntax and the major language constructs. The book also contains a short guide at the end to get programmers to write their first Flask web application.

Kenneth Reitz's The Hitchhiker’s Guide to Python contains a wealth of information both on the Python programming language and the community.

How to Develop Quality Python Code is a good read to begin learning about development environments, application dependencies and project structure.

Beyond the basics

The Python Ecosystem: An Introduction provides context for virtual machines, Python packaging, pip, virutalenv and many other topics after learning the basic Python syntax.

The Python Subreddit rolls up great Python links and has an active community ready to answer questions from beginners and advanced Python developers alike.

Good to Great Python Reads is a collection of intermediate and advanced Python articles around the web focused on nuances and details of the Python language itself.

The blog Free Python Tips provides posts on Python topics as well as news for the Python ecosystem.

Python Books is a collection of freely available books on Python, Django, and data analysis.

Python IAQ: Infrequently Asked Questions is a list of quirky queries on rare Python features and why certain syntax was or was not built into the language.

Videos, screencasts and presentations

Videos from conferences and meetups along with screencasts are listed on the best Python videos page.

Curated Python packages lists

awesome-python is an incredible list of Python frameworks, libraries and software. I wish I had this page when I was just getting started.

easy-python is like awesome-python although instead of just a Git repository this site is in the Read the Docs format.

Podcasts

Talk Python to Me focuses on the people and organizations coding on Python. Each episode features a different guest interviewee to talk about his or her work.

Podcast.__init__ is another podcast on "about Python and the people who make it great".

Newsletters

Python Weekly is a free weekly roundup of the latest Python articles, videos, projects and upcoming events.

PyCoder's Weekly is another great free weekly email newsletter similar to Python Weekly. The best resources are generally covered in both newsletters but they often cover different articles and projects from around the web.

Import Python is a newer newsletter than Python Weekly and PyCoder's Weekly. So far I've found this newsletter often pulls from different sources than the other two. It's well worth subscribing to all three so you don't miss anything.

我这里有两个Flask的项目,非常适合用来入门。可以说,是目前互联网上质量较高的Flask学习资料。

这两个项目的每一个commit都被精心准备,用以演示一个功能。并且,每个commit都能够运行。通过运行各个commit查看界面的变化,以及通过代码变更查看功能实现,对大家学习Flask开发,有很大的帮助。

项目一:今日头条

今日头条项目就是将各大网站的新闻头条和天气预报拿过来,做了一个聚合操作。这个项目不涉及前端、不涉及数据库,只涉及爬虫(一点点),也没有用到Flask插件,所以非常简单,很适合用来入门。

github地址:lalor/headlines

项目二:todo list

todo list(lalor/todolist)是代办事项列表,效果图如下:

支持登录、退出、增加todo、删除已完成的todo、修改未完成的todo。使用到的插件包括Flask-Bootstrap、Flask-wtf、Flask-SQLAlchemy和Flask-login。当然,还有一些没有实现,这个项目主要用于教学用,方便新同学学习。

希望大家喜欢。

使用Python进行数据挖掘是最近几年才开始火起来的,之前网上很多的资料都是关于Python网页开发等。但使用Python进行数据挖掘的侧重点已经完成不一样了。本人就是浪费了很多时间来筛选这些博客、书籍。所以就有了本文,希望能帮大家少走一点弯路。

熟练掌握任何一门语言,几乎都需要经过以下过程:

良师--学习Python课程+入门书籍+浏览技术博客

社区帮助--善于使用搜索引擎、Mail List

益友 -- 寻找学习伙伴

Learn by Code --项目实践

一、Python学习课程推荐

这两个学习课程从最基础的Python语法开始,介绍了Python数据分析、统计模型以及机器学习的各个方面,内容十分充足。之所以建议使用老外的课程是因为,老外上课假定你什么都不会,讲解深入浅出,尤其是对于华盛顿大学的机器学习课程,把复杂的概念讲解得十分简单。

1. 密歇根大学的《学习使用Python编程并分析数据》主要包括以下课程(讲解十分详细,深入浅出,非常适合入门学习,视频都是有字幕的):

《大家的编程 (Python 入门》:课程涵盖了如何使用Python的基本指令编写程序. 课程对学生没有先设要求, 我们只涉及到最基本的数学, 有一定使用电脑经验的人都可以完全掌握这门课的内容.

《Python 数据结构》:本课程将介绍Python编程语言的核心数据结构。我们将学习编程语言的基础概念,探索如何使用Python的内置数据结构,如列表、字典、元组,进行更为复杂的数据分析。

《使用 Python 访问网络数据》:使用Python爬取和解析网络数据

《Python 数据库开发》:使用Python和数据库进行交互

《使用 Python 获取并处理数据,并用可视化方式展现数据》

2. 华盛顿大学的《机器学习》专项课程

在专项课程页面无法选择旁听,必须点击进入单独课程页面才可,这个课程专题旁听是有限制的,无法提交作业;如有需求,可以申请奖学金,回答三个问题即可,系统自动通过申请。

《机器学习基础:案例研究》:你是否好奇数据可以告诉你什么?你是否想在关于机器学习促进商业的核心方式上有深层次的理解?你是否想能同专家们讨论关于回归,分类,深度学习以及推荐系统的一切?在这门课上,你将会通过一系列实际案例学习来获取实践经历。

《机器学习:回归》

《机器学习:分类》

《机器学习:聚类和检索》

《机器学习:推荐系统和降维》

《机器学习:应用深度学习创建智能运用》

二、网上打码教程

Learn by doing!!! 学习编程最有效的方式就是敲代码!

Codecademy 围绕Python 的基础语法,内容非常丰富。

Datacamp Python基本语法(他家的R语言课程十分不错!)

三、Python技术博客

简单介绍一些非常棒的Python技术学习的博客

1. 廖雪峰Python教程 简单易上手的Python基础语法教程,值得学习, Python 2和Python 3版本都有。

2. 非常棒的pandas练习Github Repo

3. 很详细的Python 爬虫教程

4. 国外Data Science博客大全

四、Python入门书籍推荐

常用书籍下载网址,几乎囊括了网上能找得到的所有Python相关的书籍(PDF、Epub和mo bi格式),且提供云盘下载链接。你值得拥有!

python | 搜索结果

1. 掌握Python语法的基础上学习《Python for data analysis》是比较不错的选择,涵盖了ipython notebook、Numpy、Scipy和Pandas包的使用。

2.《Python数据分析与挖掘实战》介绍了使用Python进行数据挖掘的详细案例,数据和代码都可以下载,作为机器学习的进阶学习是不错的选择(这本书也用对应的R语言和Matlab 版本)。

3. 《Python Cookbook》很厚的一本书,可以作为Python语法查询手册。

再添加几个外文书籍下载网址:

1. All IT eBooks 全

2. Library Genesis 各种书籍,不局限于编程书籍

3. Fox eBook - eBooks Free Download Site

4. Development / Programming / AvaxHome

五、推荐订阅博客(更细频率较高)

iPhone上可以使用Reeder阅读器,Instapaper用来保存后稍后阅读,因为信息量比较大。

No free Hunch Kaggle竞赛平台的官方博客,包括一些优秀的代码解读以及高分选手的采访,十分有用的经验(来自不同背景,不同年龄层次,不同职业的选手)

Flowing Data 十分有用的数据分析的案例

Python日报 内容十分精彩的集锦(中文)

六、FAQ (待续)

Python 2.x还是Python 3.x?

如何安装Python包? 强烈推荐Anaconda包,你值得拥有!尤其是Windows系统。

是否需要很强的统计和数学背景? 有良好的数学和统计背景固然很好,但是现在很多岗位对数学和统计背景要求并不很多,都是简单的算法,Python编程已经能够很方便地实现,更多的是对业务的深入理解。如有需要建议,边学习Python边学习数学统计。

七、实践项目

Kaggle竞赛项目,里面不仅仅有很多竞赛项目,而且有很多可供学习的代码、博客以及论坛,都是实战项目,有很强的实践价值。