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CHAPTER 6 ■ ABSTRACTION 137
As you can see, the left argument is always the largest number found so far, while the right
argument is the next number in the sequence.
■Note You have seen that reduce can be replaced by a for loop, but it cannot be reduced (pun intended)
to a list comprehension because it doesn’t return a list.
apply
Before leaving the subject of functional programming, I’ll touch upon the built-in function
apply. It takes a function as an argument and calls it. You may also optionally supply a tuple of
positional parameters and a dictionary of keyword arguments. You use this if you have a tuple
(or dictionary) of arguments and want to apply a function to it:
>>> def rectangleArea(width, height):
return width * height
>>> rectangle = 20, 30
>>> apply(rectangleArea, rectangle)
600
However, this function is a bit outdated now that you can simply use the nifty little stars to
unpack the arguments (as discussed earlier in this chapter, in the section “Collecting
Parameters”):
>>> rectangleArea(*rectangle)
600
Even though you’ll probably rarely use apply, it has been used extensively in older programs,
and you never know when you’ll have to read someone else’s code.
A Quick Summary
In this chapter, you’ve learned several things about abstraction in general, and functions in
particular:
Abstraction. Abstraction is the art of hiding unnecessary details. You can make your
program more abstract by defining functions that handle the details.
Function definition. Functions are defined with the def statement. They are blocks of
statements that receive values (parameters) from the “outside world” and may return one
or more values as the result of their computation.
Parameters. Functions receive what they need to know in the form of parameters—variables
that are set when the function is called. There are two types of parameters in Python,
positional parameters and keyword parameters. Parameters can be made optional by
giving them default values.