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所在平台: Udemy |
课程主页: https://www.udemy.com/course/python-3-deep-dive-part-1/
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课程名称：Python 3: 深度探讨（第一部分 - 函数式编程） 课程概述： 欢迎！这是一个系列课程的第一部分，旨在深入探讨Python 3的内部机制和更复杂的方面。该课程不是面向初学者的！如果你刚学习Python一周或几个月，建议你先继续练习Python，之后再学习这个系列课程。相反，如果你已经学习或编程Python一段时间，并开始思考以下问题： - 我想知道这个是如何工作的？ - 有没有更“Pythonic”的方式来做到这一点？ - 什么是闭包？它与lambda一样吗？ - 我会如何写自己的装饰器？ - 为什么某些布尔表达式不返回布尔值？我如何利用这个？ - Python的导入机制是怎样的，为什么会出现副作用？ 那么，这门课程非常适合你。 为了最大限度地利用本课程，你应该准备好暂停编程视频，并尝试在我之前写代码！在概念和理论视频中你可以放松，但在编码视频中则要积极参与！请确保你回顾课程的先决条件，虽然我在课程开始时会简要回顾基本概念，但这些内容你在开始时应该非常熟悉。 在这一系列课程中，我将为你提供对Python语言及其标准库更深入的理解。Python被称为“内置电池”的语言，这个称号名副其实——基础Python中有大量功能等待探索和学习。因此，这门课不是关于我最喜欢的第三方库，而是关于Python语言本身和标准库。 在《Python 3: 深度探讨（第一部分）》中，我们将更加仔细地研究以下内容： - 变量——它们实际上只是指向内存中对象的符号（引用） - 命名空间和作用域 - Python的数值类型 - Python布尔类型——一个简单的或语句远不止你想的那么简单！ - 运行时与编译时，以及它如何影响函数默认值、装饰器、模块导入等 - 一般函数（包括lambda） - 函数式编程技术（例如map、reduce、filter、zip等） - 闭包 - 装饰器 - 导入、模块和包 - 元组作为数据结构 - 命名元组 课程先决条件： 这是一个中级到高级的Python课程。要充分受益于本课程，你应当熟悉以下基本Python语言知识： - 变量和简单类型（如str、bool、int和float类型） - for和while循环 - if...else语句 - 使用简单的列表、元组、字典和集合 - 定义函数（使用def语句） - 使用class关键字编写简单类，编写实例方法，使用@property装饰器创建基本属性 - 从标准库导入模块（例如：import math） 你还应该： - 在你的系统上安装Python 3.6（或更高版本） - 能够使用命令行或喜欢的IDE（如PyCharm）编写和运行Python程序 - 安装Jupyter Notebook（我将在本课程中使用它以提供完全注释的Python代码示例）
Hello!This is Part 1 of a series of courses intended to dive into the inner mechanics and more complicated aspects of Python 3.This is not a beginner course!If you've been coding Python for a week or a couple of months, you probably should keep writing Python for a bit longer before tackling this series.On the other hand, if you've been studying or programming in Python for a while, and are now starting to ask yourself questions such as:I wonder how this works?is there another, more pythonic, way, of doing this?what's a closure? is that the same as a lambda?I know how to use a decorator someone else wrote, but how does it work? How do I write my own?why do some boolean expressions not return a boolean value? How can I use that to my advantage?how does the import mechanism in Python work, and why am I getting side effects?and similar types of question...then this course is for you.To get the most out of this course, you should be prepared to pause the coding videos, and attempt to write code before I do! Sit back during the concept/theory videos, but lean in for the code videos!Please make sure you review the pre-requisites for this course (below) - although I give a brief refresh of basic concepts at the beginning of the course, those are concepts you should already be very comfortable with as you being this course.In this course series, I will give you a much more fundamental and deeper understanding of the Python language and the standard library.Python is called a "batteries-included" language for good reason - there is a ton of functionality in base Python that remains to be explored and studied.So this course is not about explaining my favorite 3rd party libraries - it's about Python, as a language, and the standard library.In particular this course is based on the canonical CPython. You will also need Jupyter Notebooks to view the downloadable fully-annotated Python notebooks. It's about helping you explore Python and answer questions you are asking yourself as you develop more and more with the language.In Python 3: Deep Dive (Part 1) we will take a much closer look at:Variables - in particular that they are just symbols pointing to objects in memory (references)Namespaces and scopesPython's numeric typesPython boolean type - there's more to a simple or statement than you might think!Run-time vs compile-time and how that affects function defaults, decorators, importing modules, etcFunctions in general (including lambdas)Functional programming techniques (such as map, reduce, filter, zip, etc)ClosuresDecoratorsImports, modules and packagesTuples as data structuresNamed tuplesCourse PrerequisitesThis is an intermediate to advanced Python course.To have the full benefit of this course you should be comfortable with the basic Python language including:variables and simple types such as str , bool , int and float typesfor and while loopsif...else. statementsusing simple lists , tuples , dictionaries and setsdefining functions (using the def statement)writing simple classes using the class keyword and the __init__ method, writing instance methods, creating basic properties using @property decoratorsimporting modules from the standard library (e.g. import math)You should also:have Python 3.6 (or higher) installed on your system be able to write and run Python programs using either:the command line, or a favorite IDE (such as PyCharm), have Jupyter Notebooks installed (which I use throughout this course so as to provide you fully annotated Python code samples)
