Robust Data Workflows Made Easy: Classes with Pandera and Pydantic by Nathan McDougall

In this talk, we explore dataclass-style approaches to data validation and class design.
Learn a way to keep your DataFrames under control, along with other complex data structures!
Since Python 3.7, dataclasses have been a welcome addition to Python. In this talk, we explore similar options, turbocharged with data validation: DataFrameModel from the pandera package and BaseModel from the pydantic package. We will see how these can make your data pipelines simpler, more robust, as well as easier to document and test. The talk will feature plenty of examples, showing how you can avoid making "pandas Bolognese" out of your code.