Why ValidationError Is Just the Beginning, Not the End of Data Handling

A software developer argues that raising a ValidationError is only the starting point of data handling, not a complete solution. Writing from experience building a science-and-tech news digest, the author identifies three distinct validation boundaries within a single process, each requiring a different response strategy. Key decisions include rejecting the smallest possible unit of bad data rather than an entire batch, and sometimes accepting fabricated fallback values when the cost of doing so is well understood. The author also highlights that schema validation cannot address quantity-based failures, such as a feed dumping its entire archive in one poll. The central takeaway is that what a system does after detecting invalid data is a deliberate design choice, not a default outcome.