PyCon Pune 2017

A conference on the Python programming language

Making Python Faster

Submitted by Saradindu Sengupta (@saradindusengupta) on Dec 1, 2016

Technical level: Intermediate Status: Submitted

Abstract

Python is cool, easy, unlike the previous programming languages . Afterall its main purpose of development was to be easy to code.But at the last python is not that fast as its predecessors. So to make any user-defined python module to run faster we can take the route of implementation of C libraries as Python modules.
This session is all about that importing messy,long C libraries to be used in Python as its native modules. There are many ways of doing that,using C modules in Python,using existing extension or even opting for alternative options. But among those which one works best,because we don’t need the second best for our resource-hungry operations.This session also covers that part of benchmarking different techniques or alternatives.
Myself being a data science student I feel the heat of slow Python scripts and that is one of the most important reasons of creating faster modules to work with Python.

Outline

Why someone needs a faster Python?
Speed up your py scripts using traditional tips
Introduction to PyPy
Why it is highly regarded for high-speed performance
Write your own Python C modules
With third party tools without third party tools Introduction to Pyrex
Ctypes,C modules,Pure C,CPython,PyPy
Benchmarking test against various ways of doing this

Requirements

Laptop(Preferably with Python 3.5) with Internet connection and your active engagement

Speaker bio

I am currently a Post grad student specializing in Machine Learning and Artificial Intelligence at Indian Institute of Information Technology & Management - Kerala. As being in the field of working with large data set and as a hard fan of Python I felt it is very much needed to get high-speed performance out of a Python script and one way to do that is using the good old classic C/C++. There is a very much relevant reason that why C is at the backend of almost all data hungry,greedy libraries.Recently released open source Tensorflow by Google also has a backend in C/C++ , your very adorable numpy is also having a C/C++ backend.

I have been using Python for over 3 years and my current role as a project associate at the institute for Computer Vision related project exposed me enough to the field.

I have been also highly involved in the field of text processing,sentiment analysis, and image analysis.

If you are also very fond of the topic of Artificial Neural Networks, SVM, Multilayer SVM,Deep learning,Genetic algorithm and its implementation in solving real life problems then ping me on any available social media sites.

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