Pandas data frames are used widely by data scientists, Pandera adds the ability to validate them.

Bugs in machine learning systems are often caused by data flaws. Having a tool for data validation can be really helpful for avoiding mistakes.

Features fo the Pandera library include:

• Checking a value is in a specified range
• Checking a string matches a regular expression
• Informative error messages
• Checking if combinations of columns pass hypothesis tests

I have been using FastAPI a lot, partly because of the data validation allowed by Pydantic. I was looking for something that generalised to the Pandas data frame and found Pandera. FastAPI integration is possibly in the pipeline.