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Python - Under the hood.

by Haris Ibrahim K. V. (speaking)

Section
Core Python
Technical level
Intermediate

Objective

To teach what happens under the hood when a Python script is being run. After all, the simplicity must come with some cost.

Description

"Getting things done" comes at a cost. Even though we have enormous computing power, sometimes the abstraction just leaks. Of course, it does not matter most of the times, but as an Engineer, understanding how much of your actual troubles are being taken care of by an abstraction, is necessary to know.

This talk is expected to cover how Python manages memory and what are the common things that a developer overlooks while comfortbaly coding away.

We will look at live examples of how much memory a particular python program would use and talk about why and how the memory is being allocated in such a fashion.

It will be mostly presented in a dissected format where we will look at particular data structures and data types; how much memory they consume.

Requirements

Basic Python programming experience.

Speaker bio

A struggling writer by passion and a Computer Science Engineer by profession.

I work as a Python programmer since November'13 at Eventifier (http://eventifier.com/).

I have only been using Python extensively since the past 8 months. Hence the topic I have proposed is something I am currently learning and digging deep into.

I gave a talk on "Redis - What, Why and Where" at PyCon Singapore in June 2014 which I have linked to below.

Comments


  • 2

    [-] Kracekumar Ramaraju 252 days ago

    How are you planning to cover the topic. Does the talk cover what happens to memory when python foo.py is run till the program ends ? Will the talk cover how python allocates memory to data structures and classes ?


    • 1

      [-] Haris Ibrahim K. V. 232 days ago

      The talk will cover how Python allocates memory to data structures and classes. I am planning to present each specific data structure on its own first, and then talk about how things will add up, thereby giving the big picture of how memory will be eaten up while a Python program is being run.

      I have edited my description a little bit.

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