Recipes of the IPython Cookbook, the definitive guide to high-performance scientific computing and data science in Python
Shell
Switch branches/tags
Nothing to show
Clone or download
Pull request Compare This branch is 39 commits behind ipython-books:master.
Fetching latest commit…
Cannot retrieve the latest commit at this time.
Permalink
Failed to load latest commit information.
featured
notebooks
references
tools
.gitignore
LICENSE.txt
README.md
errata.md
installation.md
toc.md

README.md

IPython Cookbook

This repository contains the recipes of the IPython Cookbook, the definitive guide to high-performance scientific computing and data science in Python, by Dr. Cyrille Rossant, Packt Publishing, 500 pages, September 2014.

Follow me on Twitter to get all updates

Featured recipes

A selection of free recipes from the book:

  1. Getting the best performance out of NumPy
  2. Simulating a physical system by minimizing an energy
  3. Creating a route planner for road network
  4. Introduction to machine learning in Python with scikit-learn
  5. Simulating a partial differential equation: reaction-diffusion systems and Turing patterns
  6. Getting started with Vispy
  • more coming soon...

Table of contents

Errata

You can report inaccuracies or errors in the GitHub issue tracker. Even better, propose your own corrections by submitting a pull request!

Example data

You will find the data used in the recipes here.

Structure of the repository

The structure of the repo is the following:

notebooks/                      all notebooks with the code of all examples
    chapter01_tour/             
    chapter02_best_practices/   
    ...
    extra/                      extra code example that didn't make it in the book
    guests/                     guest recipes
featured/                       a selection of complete recipes with all text, figures and code
references/                     a curated list of references about scientific Python programming
tools/                          various building Python scripts

Installation

You need Python 3 (or 2) and a bunch of scientific modules for the code examples, mainly IPython 2.0+, NumPy, SciPy, Pandas, and matplotlib. Many recipes that require other modules come with the appropriate installation instructions.

We highly recommend that you use an all-in-one Python distribution like Anaconda. This distribution comes with an excellent package manager named conda. It lets you install easily many modules on most platforms (Windows, Linux, Mac OS X), in 64-bit (recommended if you have a 64-bit OS) or 32-bit.

The recipes are written for Python 3 first, but they also work with Python 2. Please favor Python 3 over Python 2 if you can.

Cloning the repository

You need git, a distributed versioning system, to download a local copy of this repository. Open a terminal and type:

git clone https://github.com/ipython-books/cookbook-code.git

This will copy the repository in a local folder named cookbook-code.

Running the examples

Launch the IPython notebook server with:

ipython notebook

In your browser, go to 127.0.0.1:8888. You can navigate in the repository and open the notebooks.

Contribute

You are welcome to contribute to this repository. You can use the issue tracker to report any problem. You can also propose a pull request (PR) to fix an error, to add some information, or even propose a brand new recipe in the guests/ folder!