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Coding competitions with PyPy aka "Python for the win!"

Coding contests have been historically the playground of C++ and JAVA programmers, but with the advent of competitions like the Google Code Jam and the Facebook Hacker Cup many more languages, including Python, are making to the popularity charts with good results.

In the last couple of years the PyPy interpreter has given a serious boost to the competitiveness of Python thanks to its optimizing Just-In-Time compiler that makes tight loops and low-level memory management not just feasible but even close in efficiency to C++.

Coding for extreme performance with PyPy feels quite different from usual Python coding, but several general lessons can be learned about speed and memory efficiency, that can be applied to real world scenarios, especially in numerical and scientific computing.

In the talk we are going to present a competition-ready PyPy set-up, the solutions to a few Google Code Jam problems and several techniques to effectively use “Python for the win!”

in on Tuesday 2 July at 14:30 See schedule

Do you have some questions on this talk? Leave a comment to the speaker!

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Language
EN
Duration
60 minutes (inc Q&A)

Tagged as

numpy JIT networkx performance scientific-computing pypy
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