Developer builds tool to detect stale CSV outputs caused by silent code changes

A developer discovered that changing a single threshold value in a data pipeline silently invalidated a CSV output file, causing downstream analysis scripts and a written report to rely on wrong numbers. Existing tools like test suites, Git, and data validation libraries failed to catch the issue because they do not track the relationship between source code changes and the files those changes produce. To address this gap, the developer built a small library called Stalegate, which stamps output artifacts at write time and refuses to read them if the generating code has since changed. Rather than comparing file timestamps — which are unreliable across machines and CI environments — Stalegate parses Python source files using the AST module and hashes individual top-level definitions, ignoring docstrings and comments. This approach allows the tool to pinpoint exactly which code symbol triggered the staleness, reducing false positives and making the checks harder to dismiss or bypass.