How to Use Simple Data Contracts in Python for Data Scientists

Data pipelines often break due to unexpected changes in upstream data, a problem known as schema drift. The Python library Pandera can be used to create simple data contracts that define the expected structure and quality of a pandas DataFrame. By defining a `SchemaModel`, data scientists can specify column types, value ranges, and formats, and then validate incoming data against this contract. This approach allows pipelines to "fail fast" by catching all data errors at once, providing clear failure reports, and serving as living documentation for the data schema.