![]() Why data processing applications have specific memory measurement needs, different than those of a web applications and other servers.To explain the motivation behind creating a new memory profiler, this article will cover: ![]() What you need is some way to know exactly where peak memory usage is, and what code was responsible for memory at that point.Īnd that’s exactly what the Fil memory profiler does. Yes, there are existing memory profilers for Python that help you measure memory usage, but none of them are designed for batch processing applications that read in data, process it, and write out the result. If your Python data pipeline is using too much memory, it can be very difficult to figure where exactly all that memory is going.Īnd when you do make changes, it can be difficult to figure out if your changes helped.
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