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Full Version: How do you systematically debug silent failures in Python data pipelines?
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I'm a junior developer working on a complex data pipeline in Python, and I keep hitting a bug where my script silently fails midway through processing without throwing an error, making it incredibly difficult to trace. I've been relying heavily on print statements, but they're becoming unwieldy and I know there must be more efficient Python debugging techniques. For more experienced developers, what is your systematic approach to debugging these kinds of elusive issues? When do you reach for a full debugger like pdb versus logging frameworks, and are there specific tools or strategies for debugging within asynchronous code or large pandas DataFrames where the problem isn't immediately obvious?