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Proposed Outline:

I. Introduction (10 min) [Axel]

  • Common pitfalls of Python dynamic typing, delayed code failure, bad user experiences, and difficult-to-find bugs
  • Explain what Pydantic is and how it can help to solve the problem
  • Give a high level overview of Pydantic's key features and main use in web applications

II. Installation (5 min) [Nick]

  • Provide step-by-step instructions for installing Pydantic
  • Check if Pydantic is installed correctly
  • Pydantic v2.0 vs. v1.x. If available we will use Pydantic v2.0

III. Basic Usage (30 min) [Nick]

  • Refresher on Python type annotations and class definitions
  • Creation of a simple Pydantic model
  • Initializing models and setting model attributes
  • Overview of common “atomic” types, such as float, int, str, bool, etc.
  • Type parsing (without validation)
  • Default values, optional values and Optional type
  • Model Config and Config.extra = “forbid”

Hands on Exercises (15 min)

IV. Advanced Usage (45 min)

IV.a Complex Types [Axel]

  • More complex data types, such as typed lists and dictionaries
  • Working with Enums and Union types
  • Working with datetime types
  • Defining custom data types
  • Building hierarchical structures / recursive models
  • Defining private attributes via ClassVar, PrivateAttr and Config

IV.b Type Validation [Nick]

  • Validators and validation functions
  • Pre and post init validation
  • Root validators
  • Introduce validate_arguments decorator
  • Skip validation and .construct() method
  • Config settings related to validation

IV.c Dynamic Model Definition [Axel]

  • Refresher on builtin Python data structures
  • Model creation from NamedTuple, TypedDict or dataclasses
  • Dynamic model creation using create_model

Hands on Exercises (30 - 45 min)

V. Serialization and Deserialization (30 min) [Nick]

  • Motivate need for serialization and deserialization of Python objects, Why not just pickle?
  • Introduce JSON / YAML formats, also mention TOML
  • Serialize Pydantic model to and from JSON / YAML
  • Introduce .dict() and .json()
  • Implementing JSON encoders for custom types
  • Fields and extending schema definitions
  • Config of serialization, excluding and including fields
  • Performance remarks for serialization

Hands on Exercises (30 min)

  • Nick to work on interface with web API
  • Axel to work on interface with configuration file (i.e. build and compare simple models)

BREAK (10 min)

VI. Best Practices (15 min) [Axel w/ PyCharm support from Nick]

  • Mention Pycharm, VSCode, MyPy plugins etc.
  • Show best practices for using Pydantic in projects
  • List common mistakes and pitfalls

VII. Conclusion and Q&A(15 min) [Nick]

  • Summarize of key takeaways from the tutorial
  • List additional resources for learning Pydantic