Book Image

IPython Interactive Computing and Visualization Cookbook

By : Cyrille Rossant
Book Image

IPython Interactive Computing and Visualization Cookbook

By: Cyrille Rossant

Overview of this book

Table of Contents (22 chapters)
IPython Interactive Computing and Visualization Cookbook
Credits
About the Author
About the Reviewers
www.PacktPub.com
Preface
Index

Mastering IPython's configuration system


IPython implements a truly powerful configuration system. This system is used throughout the project, but it can also be used by IPython extensions. It could even be used in entirely new applications.

In this recipe, we show how to use this system to write a configurable IPython extension. We will create a simple magic command that displays random numbers. This magic command comes with configurable parameters that can be set by the user in their IPython configuration file.

How to do it...

  1. We create an IPython extension in a random_magics.py file. Let's start by importing a few objects.

    Note

    Be sure to put the code in steps 1-5 in an external text file named random_magics.py, rather than in the notebook's input!

    from IPython.utils.traitlets import Int, Float, Unicode, Bool
    from IPython.core.magic import (Magics, magics_class, line_magic)
    import numpy as np
  2. We create a RandomMagics class deriving from Magics. This class contains a few configurable parameters:

    @magics_class
    class RandomMagics(Magics):
        text = Unicode(u'{n}', config=True)
        max = Int(1000, config=True)
        seed = Int(0, config=True)
  3. We need to call the parent's constructor. Then, we initialize a random number generator with a seed:

        def __init__(self, shell):
            super(RandomMagics, self).__init__(shell)
            self._rng = np.random.RandomState(self.seed or None)
  4. We create a %random line magic that displays a random number:

        @line_magic
        def random(self, line):
            return self.text.format(n=self._rng.randint(self.max))
  5. Finally, we register that magic when the extension is loaded:

    def load_ipython_extension(ipython):
        ipython.register_magics(RandomMagics)
  6. Let's test our extension in the notebook:

    In [1]: %load_ext random_magics
    In [2]: %random
    Out[2]: '635'
    In [3]: %random
    Out[3]: '47'
  7. Our magic command has a few configurable parameters. These variables are meant to be configured by the user in the IPython configuration file or in the console when starting IPython. To configure these variables in the terminal, we can type the following command in a system shell:

    ipython --RandomMagics.text='Your number is {n}.' --RandomMagics.max=10 --RandomMagics.seed=1
    

    In this session, we get the following behavior:

    In [1]: %load_ext random_magics
    In [2]: %random
    Out[2]: u'Your number is 5.'
    In [3]: %random
    Out[3]: u'Your number is 8.'
  8. To configure the variables in the IPython configuration file, we have to open the ~/.ipython/profile_default/ipython_config.py file and add the following line:

    c.RandomMagics.text = 'random {n}'

    After launching IPython, we get the following behavior:

    In [4]: %random
    Out[4]: 'random 652'

How it works...

IPython's configuration system defines several concepts:

  • A user profile is a set of parameters, logs, and command history, which are specific to a user. A user can have different profiles when working on different projects. A xxx profile is stored in ~/.ipython/profile_xxx, where ~ is the user's home directory.

    • On Linux, the path is generally /home/yourname/.ipython/profile_xxx

    • On Windows, the path is generally C:\Users\YourName\.ipython\profile_xxx

  • A configuration object, or Config, is a special Python dictionary that contains key-value pairs. The Config class derives from Python's dict.

  • The HasTraits class is a class that can have special trait attributes. Traits are sophisticated Python attributes that have a specific type and a default value. Additionally, when a trait's value changes, a callback function is automatically and transparently called. This mechanism allows a class to be notified whenever a trait attribute is changed.

  • A Configurable class is the base class of all classes that want to benefit from the configuration system. A Configurable class can have configurable attributes. These attributes have default values specified directly in the class definition. The main feature of Configurable classes is that the default values of the traits can be overridden by configuration files on a class-by-class basis. Then, instances of Configurables can change these values at leisure.

  • A configuration file is a Python or JSON file that contains the parameters of Configurable classes.

The Configurable classes and configuration files support an inheritance model. A Configurable class can derive from another Configurable class and override its parameters. Similarly, a configuration file can be included in another file.

Configurables

Here is a simple example of a Configurable class:

from IPython.config.configurable import Configurable
from IPython.utils.traitlets import Float

class MyConfigurable(Configurable):
    myvariable = Float(100.0, config=True)

By default, an instance of the MyConfigurable class will have its myvariable attribute equal to 100. Now, let's assume that our IPython configuration file contains the following lines:

c = get_config()
c.MyConfigurable.myvariable = 123.

Then, the myvariable attribute will default to 123. Instances are free to change this default value after they are instantiated.

The get_config() function is a special function that is available in any configuration file.

Additionally, Configurable parameters can be specified in the command-line interface, as we saw in this recipe.

This configuration system is used by all IPython applications (notably console, qtconsole, and notebook). These applications have many configurable attributes. You will find the list of these attributes in your profile's configuration files.

Magics

The Magics class derives from Configurable and can contain configurable attributes. Moreover, magic commands can be defined by methods decorated by @line_magic or @cell_magic. The advantage of defining class magics instead of function magics (as in the previous recipe) is that we can keep a state between multiple magic calls (because we are using a class instead of a function).

There's more...

Here are a few references:

See also

  • The Creating an IPython extension with custom magic commands recipe