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IPython Notebook Essentials

By Luiz Felipe Martins
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About this book
Publication date:
November 2014
Publisher
Packt
Pages
190
ISBN
9781783988341

 

Chapter 1. A Tour of the IPython Notebook

This chapter gives a brief introduction to the IPython notebook and highlights some of its special features that make it a great tool for scientific and data-oriented computing. IPython notebooks use a standard text format that makes it easy to share results.

After the quick installation instructions, you will learn how to start the notebook and be able to immediately use IPython to perform computations. This simple, initial setup is all that is needed to take advantage of the many notebook features, such as interactively producing high quality graphs, performing advanced technical computations, and handling data with specialized libraries.

All examples are explained in detail in this book and available online. We do not expect the readers to have deep knowledge of Python, but readers unfamiliar with the Python syntax can consult Appendix B, A Brief Review of Python, for an introduction/refresher.

In this chapter, we will cover the following topics:

  • Getting started with Anaconda or Wakari

  • Creating notebooks and then learning about the basics of editing and executing statements

  • An applied example highlighting the notebook features

 

Getting started with Anaconda or Wakari


There are several approaches to setting up an IPython notebook environment. We suggest you use Anaconda, a free distribution designed for large-scale data processing, predictive analytics, and scientific computing. Alternatively, you can use Wakari, which is a web-based installation of Anaconda. Wakari has several levels of service, but the basic level is free and suitable for experimenting and learning.

Tip

We recommend that you set up both a Wakari account and a local Anaconda installation. Wakari has the functionality of easy sharing and publication. This local installation does not require an Internet connection and may be more responsive. Thus, you get the best of both worlds!

Installing Anaconda

To install Anaconda on your computer, perform the following steps:

  1. Download Anaconda for your platform from https://store.continuum.io/cshop/anaconda/.

  2. After the file is completely downloaded, install Anaconda:

    • Windows users can double-click on the installer and follow the on-screen instruction

    • Mac users can double-click the .pkg file and follow the instructions displayed on screen

    • Linux users can run the following command:

      bash <downloaded file>
      

Note

Anaconda supports several different versions of Python. This book assumes you are using Version 2.7, which is the standard version that comes with Anaconda. The most recent version of Python, Version 3.0, is significantly different and is just starting to gain popularity. Many Python packages are still only fully supported in Version 2.7.

 

Running the notebook


You are now ready to run the notebook. First, we create a directory named my_notebooks to hold your notebooks and open a terminal window at this directory. Different operating systems perform different steps.

Microsoft Windows users need to perform the following steps:

  1. Open Window Explorer.

  2. Navigate to the location where your notebooks are stored.

  3. Click on the New Folder button.

  4. Rename the folder my_notebooks.

  5. Right-click on the my_notebooks folder and select Open command window here from the context menu.

Mac OS X and other Unix-like systems' users need to perform the following steps:

  1. Open a terminal window.

  2. Run the following commands:

    mkdir my_notebooks
    cd my_notebooks
    
  3. Then, execute the following command on the terminal window:

    ipython notebook
    

After a while, your browser will automatically load the notebook dashboard as shown in the following screenshot. The dashboard is a mini filesystem where you can manage your notebooks. The notebooks listed in the dashboard correspond exactly to the files you have in the directory where the notebook server was launched.

Tip

Internet Explorer does not fully support all features in the IPython notebook. It is suggested that you use Chrome, Firefox, Safari, Opera, or another standards-conforming browser. If your default browser is one of those, you are ready to go. Alternatively, close the Internet Explorer notebook, open a compatible browser, and enter the notebook address given in the command window from which you started IPython. This will be something like http://127.0.0.1:8888 for the first notebook you open.

Creating a Wakari account

To access Wakari, simply go to https://www.wakari.io and create an account. After logging in, you will be automatically directed to an introduction to using the notebook interface in Wakari. This interface is shown in the following screenshot:

The interface elements as seen in the preceding screenshot are described as follows:

  • The section marked 1 shows the directory listing of your notebooks and files. On the top of this area, there is a toolbar with buttons to create new files and directories as well as download and upload files.

  • The section marked 2 shows the Welcome to Wakari notebook. This is the initial notebook with information about IPython and Wakari. The notebook interface is discussed in detail in Chapter 2, The Notebook Interface.

  • The section marked 3 shows the Wakari toolbar. This has the New Notebook button and drop-down menus with other tools.

Note

This book concentrates on using IPython through the notebook interface. However, it's worth mentioning the two other ways to run IPython.

The simplest way to run IPython is to issue the ipython command in a terminal window. This starts a command-line session of IPython. As the reader may have guessed, this is the original interface for IPython.

Alternatively, IPython can be started using the ipython qtconsole command. This starts an IPython session attached to a QT window. QT is a popular multiplatform windowing system that is bundled with the Anaconda distribution. These alternatives may be useful in systems that, for some reason, do not support the notebook interface.

Creating your first notebook

We are ready to create our first notebook! Simply click on the New Notebook button to create a new notebook.

  • In a local notebook installation, the New Notebook button appears in the upper-left corner of the dashboard.

  • In Wakari, the New Notebook button is at the top of the dashboard, in a distinct color. Do not use the Add File button.

Notice that the Wakari dashboard contains a directory list on the left. You can use this to organize your notebooks in any convenient way you choose. Wakari actually provides access to a fully working Linux shell.

We are now ready to start computing. The notebook interface is displayed in the following screenshot:

By default, new notebooks are named UntitledX, where X is a number. To change it, just click on the current title and edit the dialog that pops up.

At the top of the notebook, you will see an empty box with the In [ ]: text on the left-hand side. This box is called a code cell and it is where the IPython shell commands are entered. Usually, the first command we issue in a new notebook is %pylab inline. Go ahead and type this line in the code cell and then press Shift + Enter (this is the most usual way to execute commands. Simply pressing Enter will create a new line in the current cell.) Once executed, this command will issue a message as follows:

Populating the interactive namespace from numpy and matplotlib

This command makes several computational tools easily available and is the recommended way to use the IPython notebook for interactive computations. The inline directive tells IPython that we want graphics embedded in the notebook and not rendered with an external program.

Commands that start with % and %% are called magic commands and are used to set up configuration options and special features. The %pylab magic command imports a large collection of names into the IPython namespace. This command is usually frowned upon for causing namespace pollution. The recommended way to use libraries in scripts is to use the following command:

import numpy as np

Then, for example, to access the arange() function in the NumPy package, one uses np.arange(). The problem with this approach is that it becomes cumbersome to use common mathematical functions, such as sin(), cos(), and so on. These would have to be entered as np.sin(), np.cos(), and so on, which makes the notebook much less readable.

In this book, we adopt the following middle-of-the road convention: when doing interactive computations, we will use the %pylab directive to make it easier to type formulae. However, when using other libraries or writing scripts, we will use the recommended best practices to import libraries.

     
About the Author
  • Luiz Felipe Martins

    Luiz Felipe Martins holds a PhD in applied mathematics from Brown University and has worked as a researcher and educator for more than 20 years. His research is mainly in the field of applied probability. He has been involved in developing code for the open source homework system, WeBWorK, where he wrote a library for the visualization of systems of differential equations. He was supported by an NSF grant for this project. Currently, he is an Associate Professor in the Department of Mathematics at Cleveland State University, Cleveland, Ohio, where he has developed several courses in applied mathematics and scientific computing. His current duties include coordinating all first-year calculus sessions.

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Latest Reviews (3 reviews total)
This is the book for getting started in IPython Notebook. When you combine it with some of the other Packt books on IPython visualization, numpy, scipy, etc., you've a pretty full toolbox demonstrating and documenting data or model driven phenomena.
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