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Importing ModulesΒΆ

One of the strengths of Python is that there are many built-in add-ons - or modules - which allow you to do complex tasks in only a few lines of code. In addition, there are many other third-party modules (e.g. Numpy, Scipy, Matplotlib) that can be installed, and you can also develop your own modules that include functionalities you commonly use.

The built-in modules are referred to as the Standard Library, and you can find a full list of the available functionality in the Python Documentation.

To use modules in your Python session or script, you need to import them. The following example shows how to import the built-in os module, which contains amongst other things many useful functions relating to files and paths:

>>> import os

This will give you access to functions available within this module, which you can now access if you use the module name as a prefix. For example, if we want to check if a file data/m31.fits exists, we can use the os.path.exists function:

>>> os.path.exists('data/m31.fits')

In this case, we can use the function in an if statement, since it returns a boolean:

>>> if os.path.exists('data/m31.fits'):
...     print "The file exists"
... else:
...     print "The file does not exist"
The file does not exist


As with objects in Python, once you have imported a module, you can (in IPython) type the name of the module, followed by ., then press TAB to see the available functions!

If a module name is too long to be conveniently written each time you want to use a function, you can define a shortcut when you import it:

>>> import matplotlib.pyplot as plt
>>> fig = plt.figure()

In the following workshops we will look a number of third-party modules in more detail, such as numpy for creating and manipulating high performance arrays, scipy for scientific computing and matplotlib.pyplot for plotting.