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How to profile slow code in Python

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In this video we look at an interesting use case we stumbled upon the other day, a Bite submission that timed out.
We first look at which of the functions is slow using a timer decorator.
When we pinpointed the slow function we look at where exactly in this function the most time is spent / calls are made.
It becomes soon apparent that it's an expensive operation in a for loop.
Hopefully this video helps you whenever you are hit with slow code.
Used decorators are here:
Also check out mentioned useful profiling context manager here:
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There's plenty more to discover with PyBites:
We first look at which of the functions is slow using a timer decorator.
When we pinpointed the slow function we look at where exactly in this function the most time is spent / calls are made.
It becomes soon apparent that it's an expensive operation in a for loop.
Hopefully this video helps you whenever you are hit with slow code.
Used decorators are here:
Also check out mentioned useful profiling context manager here:
----------------------------
----------------------------
There's plenty more to discover with PyBites: