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

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README 

        
IPython Cookbook

================



This repository contains the recipes of the [IPython Cookbook](http://ipython-books.github.io), the definitive guide to **high-performance scientific computing** and **data science** in Python, by [Dr. Cyrille Rossant](http://cyrille.rossant.net), Packt Publishing, 500 pages, September 2014.



[Follow me on Twitter to get all updates](https://twitter.com/cyrillerossant)



## Featured recipes



A selection of free recipes from the book:



1. [Getting the best performance out of NumPy](http://ipython-books.github.io/featured-01/)

2. [Simulating a physical system by minimizing an energy](http://ipython-books.github.io/featured-02/)

3. [Creating a route planner for road network](http://ipython-books.github.io/featured-03/)

4. [Introduction to machine learning in Python with scikit-learn](http://ipython-books.github.io/featured-04/)

5. [Simulating a partial differential equation: reaction-diffusion systems and Turing patterns](http://ipython-books.github.io/featured-05/)

6. [Getting started with Vispy](http://ipython-books.github.io/featured-06/)

* more coming soon...



## Table of contents



* [See the full table of contents here](toc.md)



## Errata



You can report inaccuracies or errors in the [GitHub issue tracker](https://github.com/ipython-books/cookbook-code/issues). Even better, propose your own corrections by submitting a pull request!



* [See the list of errata here](errata.md)



## Example data



[You will find the data used in the recipes here](https://github.com/ipython-books/cookbook-data).



## 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](http://continuum.io/downloads). 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](http://git-scm.com/), 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!