4.7. More on Defining Functions

It is also possible to define functions with a variable number of arguments. There are three forms, which can be combined.

4.7.1. Default Argument Values

The most useful form is to specify a default value for one or more arguments. This creates a function that can be called with fewer arguments than it is defined to allow. For example:

def ask_ok(prompt, retries=4, complaint='Yes or no, please!'):
    while True:
        ok = raw_input(prompt)
        if ok in ('y', 'ye', 'yes'):
            return True
        if ok in ('n', 'no', 'nop', 'nope'):
            return False
        retries = retries - 1
        if retries < 0:
            raise IOError('refusenik user')
        print complaint

This function can be called in several ways:

• giving only the mandatory argument: ask_ok('Do you really want to quit?')
• giving one of the optional arguments: ask_ok('OK to overwrite the file?', 2)
• or even giving all arguments: ask_ok('OK to overwrite the file?', 2, 'Come on, only yes or no!')

This example also introduces the in keyword. This tests whether or not a sequence contains a certain value.

The default values are evaluated at the point of function definition in the defining scope, so that

i = 5

def f(arg=i):
    print arg

i = 6
f()

will print 5.

Important warning: The default value is evaluated only once. This makes a difference when the default is a mutable object such as a list, dictionary, or instances of most classes. For example, the following function accumulates the arguments passed to it on subsequent calls:

def f(a, L=[]):
    L.append(a)
    return L

print f(1)
print f(2)
print f(3)

This will print

[1]
[1, 2]
[1, 2, 3]

If you don’t want the default to be shared between subsequent calls, you can write the function like this instead:

def f(a, L=None):
    if L is None:
        L = []
    L.append(a)
    return L

4.7.2. Keyword Arguments

Functions can also be called using keyword arguments of the form keyword = value. For instance, the following function:

def parrot(voltage, state='a stiff', action='voom', type='Norwegian Blue'):
    print "-- This parrot wouldn't", action,
    print "if you put", voltage, "volts through it."
    print "-- Lovely plumage, the", type
    print "-- It's", state, "!"

could be called in any of the following ways:

parrot(1000)
parrot(action = 'VOOOOOM', voltage = 1000000)
parrot('a thousand', state = 'pushing up the daisies')
parrot('a million', 'bereft of life', 'jump')

but the following calls would all be invalid:

parrot()                     # required argument missing
parrot(voltage=5.0, 'dead')  # non-keyword argument following keyword
parrot(110, voltage=220)     # duplicate value for argument
parrot(actor='John Cleese')  # unknown keyword

In general, an argument list must have any positional arguments followed by any keyword arguments, where the keywords must be chosen from the formal parameter names. It’s not important whether a formal parameter has a default value or not. No argument may receive a value more than once — formal parameter names corresponding to positional arguments cannot be used as keywords in the same calls. Here’s an example that fails due to this restriction:

>>> def function(a):
...     pass
...
>>> function(0, a=0)
Traceback (most recent call last):
  File "<stdin>", line 1, in ?
TypeError: function() got multiple values for keyword argument 'a'

When a final formal parameter of the form **name is present, it receives a dictionary (see Mapping Types — dict) containing all keyword arguments except for those corresponding to a formal parameter. This may be combined with a formal parameter of the form *name (described in the next subsection) which receives a tuple containing the positional arguments beyond the formal parameter list. (*name must occur before **name.) For example, if we define a function like this:

def cheeseshop(kind, *arguments, **keywords):
    print "-- Do you have any", kind, "?"
    print "-- I'm sorry, we're all out of", kind
    for arg in arguments:
        print arg
    print "-" * 40
    keys = sorted(keywords.keys())
    for kw in keys:
        print kw, ":", keywords[kw]

It could be called like this:

cheeseshop("Limburger", "It's very runny, sir.",
           "It's really very, VERY runny, sir.",
           shopkeeper='Michael Palin',
           client="John Cleese",
           sketch="Cheese Shop Sketch")

and of course it would print:

-- Do you have any Limburger ?
-- I'm sorry, we're all out of Limburger
It's very runny, sir.
It's really very, VERY runny, sir.
----------------------------------------
client : John Cleese
shopkeeper : Michael Palin
sketch : Cheese Shop Sketch

Note that the list of keyword argument names is created by sorting the result of the keywords dictionary’s keys() method before printing its contents; if this is not done, the order in which the arguments are printed is undefined.

4.7.3. Arbitrary Argument Lists

Finally, the least frequently used option is to specify that a function can be called with an arbitrary number of arguments. These arguments will be wrapped up in a tuple (see Tuples and Sequences). Before the variable number of arguments, zero or more normal arguments may occur.

def write_multiple_items(file, separator, *args):
    file.write(separator.join(args))

4.7.4. Unpacking Argument Lists

The reverse situation occurs when the arguments are already in a list or tuple but need to be unpacked for a function call requiring separate positional arguments. For instance, the built-inrange() function expects separate start and stop arguments. If they are not available separately, write the function call with the *-operator to unpack the arguments out of a list or tuple:

>>> range(3, 6)             # normal call with separate arguments
[3, 4, 5]
>>> args = [3, 6]
>>> range(*args)            # call with arguments unpacked from a list
[3, 4, 5]

In the same fashion, dictionaries can deliver keyword arguments with the **-operator:

>>> def parrot(voltage, state='a stiff', action='voom'):
...     print "-- This parrot wouldn't", action,
...     print "if you put", voltage, "volts through it.",
...     print "E's", state, "!"
...
>>> d = {"voltage": "four million", "state": "bleedin' demised", "action": "VOOM"}
>>> parrot(**d)
-- This parrot wouldn't VOOM if you put four million volts through it. E's bleedin' demised !

4.7.5. Lambda Forms

By popular demand, a few features commonly found in functional programming languages like Lisp have been added to Python. With the lambda keyword, small anonymous functions can be created. Here’s a function that returns the sum of its two arguments: lambda a, b: a+b. Lambda forms can be used wherever function objects are required. They are syntactically restricted to a single expression. Semantically, they are just syntactic sugar for a normal function definition. Like nested function definitions, lambda forms can reference variables from the containing scope:

>>> def make_incrementor(n):
...     return lambda x: x + n
...
>>> f = make_incrementor(42)
>>> f(0)
42
>>> f(1)
43

4.7.6. Documentation Strings

There are emerging conventions about the content and formatting of documentation strings.

The first line should always be a short, concise summary of the object’s purpose. For brevity, it should not explicitly state the object’s name or type, since these are available by other means (except if the name happens to be a verb describing a function’s operation). This line should begin with a capital letter and end with a period.

If there are more lines in the documentation string, the second line should be blank, visually separating the summary from the rest of the description. The following lines should be one or more paragraphs describing the object’s calling conventions, its side effects, etc.

The Python parser does not strip indentation from multi-line string literals in Python, so tools that process documentation have to strip indentation if desired. This is done using the following convention. The first non-blank line after the first line of the string determines the amount of indentation for the entire documentation string. (We can’t use the first line since it is generally adjacent to the string’s opening quotes so its indentation is not apparent in the string literal.) Whitespace “equivalent” to this indentation is then stripped from the start of all lines of the string. Lines that are indented less should not occur, but if they occur all their leading whitespace should be stripped. Equivalence of whitespace should be tested after expansion of tabs (to 8 spaces, normally).

Here is an example of a multi-line docstring:

>>> def my_function():
...     """Do nothing, but document it.
...
...     No, really, it doesn't do anything.
...     """
...     pass
...
>>> print my_function.__doc__
Do nothing, but document it.

    No, really, it doesn't do anything.

4.8. Intermezzo: Coding Style

Now that you are about to write longer, more complex pieces of Python, it is a good time to talk about coding style. Most languages can be written (or more concise, formatted) in different styles; some are more readable than others. Making it easy for others to read your code is always a good idea, and adopting a nice coding style helps tremendously for that.

For Python, PEP 8 has emerged as the style guide that most projects adhere to; it promotes a very readable and eye-pleasing coding style. Every Python developer should read it at some point; here are the most important points extracted for you:

• Use 4-space indentation, and no tabs.
  4 spaces are a good compromise between small indentation (allows greater nesting depth) and large indentation (easier to read). Tabs introduce confusion, and are best left out.
• Wrap lines so that they don’t exceed 79 characters.
  This helps users with small displays and makes it possible to have several code files side-by-side on larger displays.
• Use blank lines to separate functions and classes, and larger blocks of code inside functions.
• When possible, put comments on a line of their own.
• Use docstrings.
• Use spaces around operators and after commas, but not directly inside bracketing constructs: a = f(1, 2) + g(3, 4).
• Name your classes and functions consistently; the convention is to use CamelCase for classes and lower_case_with_underscores for functions and methods. Always use self as the name for the first method argument (see A First Look at Classes for more on classes and methods).
• Don’t use fancy encodings if your code is meant to be used in international environments. Plain ASCII works best in any case.

Footnotes

[1]	Actually, call by object reference would be a better description, since if a mutable object is passed, the caller will see any changes the callee makes to it (items inserted into a list).