Chapter 14. Advanced Function Topics

This chapter introduces a collection of more advanced function-related topics: the lambda expression, functional programming tools such as map and list comprehensions, generators, and more. Part of the art of using functions lies in the interfaces between them, so we will also explore some general function design principles here. Because this is the last chapter in Part IV, we’ll close with the usual sets of gotchas and exercises to help you start coding the ideas you’ve read about.

Anonymous Functions: lambda

So far, we’ve seen what it takes to write our own functions in Python. The next sections turn to a few more advanced function-related ideas. Most of these are optional features, but can simplify your coding tasks when used well.

Besides the def statement, Python also provides an expression form that generates function objects. Because of its similarity to a tool in the LISP language, it’s called lambda. [1] Like def, this expression creates a function to be called later, but returns it instead of assigning it to a name. This is why lambdas are sometimes known as anonymous (i.e., unnamed) functions. In practice, they are often used as a way to inline a function definition, or defer execution of a piece of code.

lambda Expressions

The lambda’s general form is the keyword lambda, followed by one or more arguments (exactly like the arguments list you enclose in parenthesis in a def header), followed by an expression after a colon:

lambda argument1 ...

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