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12.7. Type Annotations¶
In the previous section, we discussed the decoding work that is required when you look at a function and are trying to determine the types of its parameters. In this section, we’ll introduce a feature that can help reduce the amount of sleuthing that is needed.
Consider the following function definition:
def duplicate(msg): """Returns a string containing two copies of `msg`""" return msg + msg
This function is intended to duplicate a message; if called with the value ‘Hello’, it returns the value
‘HelloHello’. If called with other types of data, however, it will not work properly. (What will the
function do if given an
int or a
Python allows you to indicate the intended type of the function parameters and the type of the function return value in a function definition using a special notation demonstrated in this example:
This definition of
duplicate makes use of type annotations that indicate the function’s parameter type and return
type. A type annotation, sometimes called a type hint, is an optional notation that specifies the type of a parameter or function result. It
tells the programmer using the function what kind of data to pass to the function, and what kind of data to expect when
the function returns a value.
In the definition above, the annotation
: str in
msg: str indicates that the caller should pass a
str value as an argument.
-> str indicates that the function will produce a
Here are some more examples of functions with type annotations:
It’s important to understand that adding type annotations to a function definition does not cause the Python interpreter
to check that the values passed to a function are the expected types, or cause the returned value to be converted to the
expected type. For example, if the function
add in the example above is called like this:
result = add('5', '15')
the function will receive two string values, concatenate them, and return the resulting string ‘515’. The
annotations are completely ignored by the Python interpreter. Think of type annotations as a kind of function
documentation, and remember that they have no effect on the program’s behavior.
Type annotations are an optional aspect of documenting functions. Still, type annotations are an important tool to increase the readability of your code, and you should use them in your programs.
Although type annotations are ignored by the Python interpreter, there are tools such as mypy that can analyze your code containing type annotations and flag potential problems.
Type hints can be especially useful for container types, like lists and dictionaries. When type hinting was first introduced into python, in version 3.5, it was possible to specify them, but a little clunky. Later versions made it a little easier.
For example, in the following code, which is valid in python version 3.10, the count_words function takes a string as input and returns a dictionary. That dictionary’s keys should all be strings and the value associated with every key should be an integer.
In the code below, the function add_em_up takes an input that is expected to be a list of numbers. It returns the sum of all of them.
Actually, this code should work just fine if the inputs are either integers or floats. If any are floats, then the return value will be a float. The more recent versions of type annotations in python allow the use the | symbol (pronounced “pipe”) to specify a union, that either of two types is permitted. You may find that it’s not permitted in the current runestone interpreter, though.
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