We're sorry but this page doesn't work properly without JavaScript enabled. Please enable it to continue.
Feedback

The joy of PyPy JIT: abstractions for free

Formal Metadata

Title
The joy of PyPy JIT: abstractions for free
Title of Series
Number of Parts
160
Author
License
CC Attribution - NonCommercial - ShareAlike 3.0 Unported:
You are free to use, adapt and copy, distribute and transmit the work or content in adapted or unchanged form for any legal and non-commercial purpose as long as the work is attributed to the author in the manner specified by the author or licensor and the work or content is shared also in adapted form only under the conditions of this
Identifiers
Publisher
Release Date
Language

Content Metadata

Subject Area
Genre
Abstract
The joy of PyPy JIT: abstractions for free [EuroPython 2017 - Talk - 2017-07-12 - Anfiteatro 2] [Rimini, Italy] The joy of PyPy JIT: abstractions for free The PyPy JIT is a powerful piece of technology which makes Python program running faster: in this talk, we will see how it helps us to write our programs better without sacrificing performance. One of the key to write complex software systems of good quality is to make a good usage of abstractions, to clearly separate the various layers and components. However, often each layer of abstraction adds some cost in terms of runtime performance, so we need to struggle finding the best trade-off between maintainability and speed. Because of the way it works, the PyPy JIT naturally removes the cost of most abstractions: we will look at real-life examples of how this is possible, showing what the JIT can and can't do. We will also show how this compares to other popular systems of optimizing Python code, such as Cython