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6 stellar libraries for profiling Python code

July 28, 2021

Via: InfoWorld

Every programming language has two kinds of speed: speed of development, and speed of execution. Python has always favored writing fast versus running fast. Although Python code is almost always fast enough for the task, sometimes it isn’t. In those cases, you need to find out where and why it lags, and do something about it.

A well-respected adage of software development, and engineering generally, is “Measure, don’t guess.” With software, it’s easy to assume what’s wrong, but never a good idea to do so. Statistics about actual program performance are always your best first tool to making applications faster.

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