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所在平台: Udemy |
课程主页: https://www.udemy.com/course/pydantic-advanced-data-validation/
课程评论：没有评论
课程名称：学习Pydantic：Python中的高级数据验证 课程概述： 欢迎来到在线学习现代Pydantic的最佳资源，这是一个在Python社区中广受欢迎的数据验证库。Pydantic于2018年首次发布，自此成为最受欢迎的Python库之一。目前每月下载量超过1.3亿次，许多大型企业包括谷歌、亚马逊、苹果、Meta、Netflix等都在使用它，还有一些其他行业的大型企业如星巴克、摩根大通，甚至NASA都在使用它。这一切并非偶然，Pydantic是一款强大的库，优雅地解决了软件开发中的一个常见问题：数据验证。其快速、简单的声明性语法和可扩展性使其成为现代Python开发中不可或缺的工具。 在本课程中，您将学习到从定义数据模型的基础知识到更高级主题（如具有工厂默认值的字段、创建自定义模型验证器、数据序列化等）的所有内容。课程的第一部分将专注于Pydantic的使用，您将学习到： - 如何使用Pydantic定义数据模型 - 如何通过继承将简单模型组合成更复杂的模型 - Python中类型提示的基础知识，包括枚举、字面量以及其他高级类型 - 如何使用Pydantic强大的验证系统 - 如何进行数据的序列化和反序列化 - 如何将模型提取到架构中 - 如何根据Pydantic模型验证数据 课程的第二部分将关注一个顶点项目，您将使用Pydantic开发并部署一个Python Web API，允许用户创建和投票于投票。这款应用将使用Redis作为持久的键值数据存储，并作为无服务器函数部署到生产环境中。顶点项目将在约30个技能挑战的系列中一步一步开发，您会被要求逐步实现小功能。这将让您有机会实践在课程第一部分所学的知识，并： - 体验Pydantic在实际应用中的使用 - 学习现代Python API开发 - 了解Redis及其作为持久数据存储的使用 - 学习Python的虚拟环境和依赖管理 - 练习使用Git和GitHub - 了解无服务器计算的基础知识，并将API部署为无服务器函数 课程将使用最新版本的Pydantic，该版本利用Rust的强大性能实现快速执行。此外，如果您是Python新手或有一段时间没有使用该语言，课程附录中还包含了一个全面的Python速成课程，帮助您迅速上手。 我非常期待与您分享这门课程，期待在课堂上见到您！
Welcome to the best resource online for learning modern Pydantic, a data validation library that has taken the python community by storm. Pydantic is was first released in 2018 and has since become one of the most popular python libraries. It is nowadays downloaded more than 130 million times a month, and is used by some of the largest organizations out there, from the tech giants like Google, Amazon, Apple, Meta, and Netflix, to large conglomerates in various other industries, such as Starbucks, JPMorgan Chase. Oh, and yes, even NASA. There's a good reason for this. Pydantic is a powerful library that elegantly solves a very common problem in software development: data validation. Pydantic's speed, simple declarative syntax, and extensibility make it an indispensable utility in modern python development. And in this course, you will learn everything you need to know to get started with Pydantic, from the very basics of defining data models, to more advanced topics such as fields with factory defaults, creating custom model-validators, data serialization, and much more.The first part of the course will be purely about pydantic, where we explore it in isolation. You will learn:how to define data models with pydantichow to compose more complex models from simpler ones via inheritancethe foundations of type hinting in python, including enumerations, literals, and other advanced types- how to use pydantic's powerful validation systemhow to serialize and deserialize data how to extract models to schemashow to validate data against pydantic modelsThen in the second part of the course we will turn our attention to the Capstone Project, where we will use pydantic to develop and deploy a python web API that allows users to create and vote on polls. This app will use Redis as our durable key-value data store, and will be deployed to production as a serverless function. The Capstone will be developed step by step, in a series of about 30 skill challenges, where you will be asked to incrementally implement small features. This will give you the opportunity to practice what you've learned in the first part of the course, and to: get a practical feel for how Pydantic is used in real-world applications learn about modern API development with python understand what Redis is and how it can be used as a durable data storelearn about virtual environments and dependency management in pythonpractice using git and githublearn the basics of serverless computing by deploying the API as a serverless functionThe course will use the latest version of Pydantic, which leverages the power of Rust to achieve blazing fast performance. Also, if you're new to python or haven't used the used the language in a while, there's a full-featured python crash course included as an extra appendix which will get you up to speed in no time.I'm very excited to share this with you, and I look forward to seeing you in the course!
