Streamlining Data Preparation with Pydantic - A 25-Minute Guide

Explore the power of Pydantic for streamlining data preparation in this 25-minute guide from Python Data Science Day. Learn how to leverage Pydantic for data validation, type hinting, and structured data cleaning in Python projects. Discover core concepts, practical applications, and a hands-on demo of GitHub data crawling ETL. Follow along as the presenter demonstrates fetching data with the GitHub API, creating Pydantic models for repositories, gists, followers, and users, and implementing object initialization, serialization, and database loading. Gain valuable insights into ensuring data consistency, handling missing values, and optimizing your data science workflow with Pydantic.

Streamlining Data Preparation with Pydantic
Pydantic overview
Why use Pydantic
Pydantic by the numbers
Core Concepts of Pydantic
Demo - GitHub Data Crawling ETL Extract, Transfer, Load
Fetching Data with GitHub API
Repository & Gist Pydantic Model
Follower & User Pydantic Model
Object initialization, serializing, dumping
Load into SQLite
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