Talks - Sebastian Buczyński: Having fun with pydantic and pattern matching

Pattern matching with match/case in Python is more powerful than simple switch statements, allowing matching on types and attributes

Order of cases in pattern matching is significant - similar to exception handling, more specific patterns should come before general ones

Pydantic models provide schema validation and type checking for data structures, helping handle complex nested data more safely

Using Pydantic’s Type Adapter and Union types can replace explicit pattern matching while providing better validation

functools.singledispatch offers an alternative approach for handling different types of events, allowing handler registration based on type

When handling event streams, it’s important to handle unexpected/malformed messages gracefully through validation and error handling

Combining Pydantic with pattern matching allows for both type validation and flow control, but be careful about duplicating logic

Union discriminants in Pydantic 2 can simplify handling different message types by looking at type fields automatically

Complex nested data structures should be broken down into specialized types rather than handling everything in one large pattern match

Consider performance implications - pattern matching implementations may have overhead compared to simpler approaches