使用Python Typing构建坚固的Python源代码（视频教程） (英文)

使用Python Typing构建坚固的Python源代码（视频教程）

发布日期：2024年3月

课程信息：

• 格式：MP4
• 分辨率：2560×1440
• 音频：AAC，44.1 KHz，双声道
• 类型：电子学习
• 语言：英语
• 时长：73课时（4小时28分钟）
• 大小：1.73 GB

Python最初于1989年发明时，是一种真正的动态和无类型的编程语言。但在Python 3.5中，当类型“提示”被添加到语言中时，一切都改变了。随着时间的推移，令人惊奇的框架采用了这个想法并发扬光大。它们构建了功能强大且类型安全的框架。其中一些包括Pydantic、FastAPI、Beanie、SQLModel等等。在本课程中，您将学习Python类型在语言中的方方面面，探索一些使用类型的流行框架，并获得一些在应用程序和库中使用类型的出色建议和指导。

课程链接和GitHub仓库

课程源源代码和GitHub存储库

课程内容和特点：

本课程深入研究Python类型。您将看到许多示例和图形，传达了类型的动机以及它们在Python生态系统中的位置。但您也将非常实用，通过深入但易于理解的源代码演示学习所有这些想法。

课程主题涵盖：

• 将Python与流行的静态语言进行比较（如Swift、C＃、TypeScript等）
• 查看动态Python源代码库的精确克隆版本以及带有类型的版本
• 学习何时以及如何创建带有类型的变量
• 了解Python类型系统中的严格可空性
• 指定常量（不可更改）变量和值
• 使用LiteralString减少SQL注入攻击
• 使用类型与Python函数和方法
• 使用类型与类和类变量
• 使用Python的数值类型阶梯处理多种数值类型
• 使用Pydantic以类型严格的方式对复杂数据进行建模和解析
• 使用FastAPI创建API，实现数据的类型完整性交换
• 使用Beanie ODM使用Pydantic查询数据库
• 使用类型信息创建CLI应用程序以定义CLI界面
• 利用mypy验证整个源代码库在CI/CD中的完整性
• 为您的应用程序添加运行时类型安全性
• 将鸭子类型和静态类型与Python的新协议构造结合起来
• 学习在Python源代码中使用类型的设计模式和指导
• 以及更多内容，请查看完整课程大纲。

Talk Python – Rock Solid Python with Python Typing

Released 3/2024
MP4 | Video: h264, 2560×1440 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English | Duration: 73 Lessons ( 4h 28m ) | Size: 1.73 GB

When Python was originally invented way back in 1989, it was a truly dynamic and typeless programming language. But that all changed in Python 3.5 when type “hints” were added to the language. Over time, amazing frameworks took that idea and ran with it. They build powerful and type safe(er) frameworks. Some of these include Pydantic, FastAPI, Beanie, SQLModel, and many many more. In this course, you’ll learn the ins-and-outs of Python typing in the language, explore some popular frameworks using types, and get some excellent advice and guidance for using types in your applications and libraries.

Source code and course GitHub repository
github.com/talkpython/rock-solid-python-with-type-hints-course

What’s this course about and how is it different?
This course dives deep into Python types. You will see many examples and graphics communicating the motivation for types and where they fit into the Python ecosystem. But you will also get very hands-on and learn all of these ideas with deep yet approachable code demos.

What topics are covered
In this course, you will

Compare popular static languages with Python (such as Swift, C#, TypeScript, and others)
See a exact clone of a dynamic Python codebase along side the typed version
Learn how and when to create typed variables
Understand Python’s strict nullability in its type system
Specify constant (unchangeable) variables and values
Reduce SQL injection attacks with LiteralString
Uses typing with Python functions and methods
Use typing with classes and class variables
Work with multiple numerical types with Python’s numerical type ladder
Use Pydantic to model and parse complex data in a type strict manner
Create an API with FastAPI that exchanges data with type integrity
Query databases with Pydantic using the Beanie ODM
Create CLI apps using type information to define the CLI interface
Leverage mypy for verifying the integrity of your entire codebase in CI/CD
Add runtime type safety to your application
Marry duck typing and static typing with Python’s new Protocol construct
Learn design patterns and guidance for using types in Python code
And lots more, see the full course outline.

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