Performant Python

Explore techniques for optimizing Python code performance in this 25-minute conference talk from EuroPython 2016. Discover tools and strategies to enhance Python's speed without sacrificing code readability or maintainability. Learn to write "pythonic" code that leverages built-in features and the Python ecosystem. Gain insights into profiling, vectorization, and utilizing NumPy for improved efficiency. Compare Python's performance to C and understand when to consider alternative approaches. Through practical examples like optimizing sum functions and quote shakers, master the art of balancing speed and simplicity in Python development. Suitable for Python developers seeking to boost their code's performance while maintaining its clarity and ease of use.

Introduction
What is good code
Python
Pythonic
Python Performance
Python 101
Test Code
Sum Function
Numpy
C vs Python
Vectorized Python
Quote Shaker
Profiling
Python profiling
Python profiler
Current prof demo