Natural Language Processing with Python

Functions: The Foundation of Structured Programming

Functions provide an effective way to package and reuse program code, as already explained in More Python: Reusing Code. For example, suppose we find that we often want to read text from an HTML file. This involves several steps: opening the file, reading it in, normalizing whitespace, and stripping HTML markup. We can collect these steps into a function, and give it a name such as get_text(), as shown in Example 4-1.

Example 4-1. Read text from a file.

import re
def get_text(file):
    """Read text from a file, normalizing whitespace and stripping HTML markup."""
    text = open(file).read()
    text = re.sub('\s+', ' ', text)
    text = re.sub(r'<.*?>', ' ', text)
    return text

Now, any time we want to get cleaned-up text from an HTML file, we can just call get_text() with the name of the file as its only argument. It will return a string, and we can assign this to a variable, e.g., contents = get_text("test.html"). Each time we want to use this series of steps, we only have to call the function.

Using functions has the benefit of saving space in our program. More importantly, our choice of name for the function helps make the program readable. In the case of the preceding example, whenever our program needs to read cleaned-up text from a file we don’t have to clutter the program with four lines of code; we simply need to call get_text(). This naming helps to provide some “semantic interpretation”—it helps a reader of our program to see what the program ...