Functions

Functions are reusable pieces of programs. They allow you to give a name to a block of statements, allowing you to run that block using the specified name anywhere in your program and any number of times. This is known as calling the function. We have already used many built-in functions such as len and range.

What is the main purpose of functions in programming? To make code reusable and organizedTo make code longerTo make code harder to read

The function concept is probably the most important building block of any non-trivial software (in any programming language), so we will explore various aspects of functions in this chapter.

Functions are defined using the def keyword. After this keyword comes an identifier name for the function, followed by a pair of parentheses which may enclose some names of variables, and by the final colon that ends the line. Next follows the block of statements that are part of this function.

What keyword is used to define a function in Python?

Example (save as function1.py):

def say_hello():
    print("hello world")

# Now we can call the function
say_hello()
# We can call it again
say_hello()

Output:

hello world

hello world

How It Works

We define a function called sayhello using the syntax as explained above. This function takes no parameters and hence there are no variables declared in the parentheses. Parameters to functions are just input to the function so that we can pass in different values to it and get back corresponding results.

Identify which parts of code represent function definitions and which represent function calls:

Function Parameters

A function can take parameters, which are values you supply to the function so that the function can do something utilising those values. These parameters are just like variables except that the values of these variables are defined when we call the function and are already assigned values when the function runs.

Parameters are specified within the pair of parentheses in the function definition, separated by commas. When we call the function, we supply the values in the same way. Note the terminology used - the names given in the function definition are called parameters whereas the values you supply in the function call are called arguments.

Match these function concepts with their correct descriptions:

Example (save as function_param.py):

def print_max(a, b):
    if a > b:
        print(a, "is maximum")
    else:
        print(b, "is maximum")

# directly pass literal values
print_max(3, 4)

x = 5
y = 7
# pass variables as arguments
print_max(x, y)

What will be printed when we call print_max(3, 4)?

4 is maximum3 is maximumErrorNothing

How It Works

Here, we define a function called print_max that uses two parameters called a and b. We find out the greater number using a simple if..else statement and then print the bigger number.

The first time we call the function print_max, we directly supply the numbers as arguments. In the second case, we call the function with variables as arguments. print_max(x, y) causes the value of argument x to be assigned to parameter a and the value of argument y to be assigned to parameter b. The print_max function works the same way in both cases.

Local Variables

When you declare variables inside a function definition, they are not related in any way to other variables with the same names used outside the function - i.e. variable names are local to the function. This is called the scope of the variable.

Which statement about local variables is correct?

Variables inside functions are independent of variables outsideVariables inside and outside functions are always connectedFunctions cannot have local variables

Example (save as function_local.py):

x = 50

def func(x):
    print("x is", x)
    x = 2
    print("Changed local x to", x)

func(x)
print("x is still", x)

What will be the final value of x printed?

502NoneError

How It Works

The first time that we print the value of the name x with the first line in the function's body, Python uses the value of the parameter declared in the main block, above the function definition.

Next, we assign the value 2 to x. The name x is local to our function. So, when we change the value of x in the function, the x defined in the main block remains unaffected.

With the last print statement, we display the value of x as defined in the main block, thereby confirming that it is actually unaffected by the local assignment within the previously called function.

The global statement

If you want to assign a value to a name defined at the top level of the program (i.e. not inside any kind of scope such as functions or classes), then you have to tell Python that the name is not local, but it is global. We do this using the global statement.

You can use the values of such variables defined outside the function (assuming there is no variable with the same name within the function). However, this is not encouraged and should be avoided since it becomes unclear to the reader of the program as to where that variable's definition is. Using the global statement makes it amply clear that the variable is defined in an outermost block.

What does the global statement do? Allows modification of global variables inside functionsCreates new global variablesDeletes global variables

Example (save as function_global.py):

x = 50

def func():
    global x
    print("x is", x)
    x = 2
    print("Changed global x to", x)

func()
print("Value of x is", x)

After running this code, what will be the final value of x?

250NoneError

How It Works

The global statement is used to declare that x is a global variable - hence, when we assign a value to x inside the function, that change is reflected when we use the value of x in the main block.

You can specify more than one global variable using the same global statement e.g. global x, y, z.

Let us understand which variables are local and which are global:

Default Argument Values

For some functions, you may want to make some parameters optional and use default values in case the user does not want to provide values for them. This is done with the help of default argument values. You can specify default argument values for parameters by appending to the parameter name in the function definition the assignment operator (=) followed by the default value.

Note that the default argument value should be a constant. More precisely, the default argument value should be immutable - this is explained in detail in later chapters. For now, just remember this.

What happens if you call a function with a default parameter without providing an argument?

The default value is usedAn error occursThe parameter is set to None

Example (save as function_default.py):

def say(message, times=1):
    print(message * times)

say("Hello")
say("World", 5)

How It Works

The function named 'say' is used to print a string as many times as specified. If we don't supply a value, then by default, the string is printed just once. We achieve this by specifying a default argument value of '1' to the parameter 'times'.

In the first usage of 'say', we supply only the string and it prints the string once. In the second usage of 'say', we supply both the string and an argument '5' stating that we want to say the string message 5 times.

Keyword Arguments

If you have some functions with many parameters and you want to specify only some of them, then you can give values for such parameters by naming them - this is called keyword arguments - we use the name (keyword) instead of the position (which we have been using all along) to specify the arguments to the function.

There are two advantages - one, using the function is easier since we do not need to worry about the order of the arguments. Two, we can give values to only those parameters to which we want to, provided that the other parameters have default argument values.

Match these function calls with their descriptions:

Example (save as function_keyword.py):

def func(a, b=5, c=10):
    print("a is", a, "and b is", b, "and c is", c)

func(3, 7)
func(25, c=24)
func(c=50, a=100)

What will func(25, c=24) print?

a is 25 and b is 5 and c is 24a is 25 and b is 24 and c is 10Error: missing argumentsa is 24 and b is 5 and c is 25

How It Works

The function named func has one parameter without a default argument value, followed by two parameters with default argument values.

In the first usage, func(3, 7), the parameter a gets the value 3, the parameter b gets the value 7 and c gets the default value of 10.

In the second usage func(25, c=24), the variable a gets the value of 25 due to the position of the argument. Then, the parameter c gets the value of 24 due to naming i.e. keyword arguments. The variable b gets the default value of 5.

In the third usage func(c=50, a=100), we use keyword arguments for all specified values. Notice that we are specifying the value for parameter c before that for a even though a is defined before c in the function definition.

VarArgs parameters

Sometimes you might want to define a function that can take any number of parameters:

def total(a=5, *numbers, **phonebook):
    print('a', a)

    #iterate through all the items in tuple
    for single_item in numbers:
        print('single_item', single_item)

    #iterate through all the items in dictionary    
    for first_part, second_part in phonebook.items():
        print(first_part,second_part)

total(10,1,2,3,Jack=1123,John=2231,Inge=1560)

Output: ''' python function_varargs.py

a 10

single_item 1

single_item 2

single_item 3

Inge 1560

John 2231

Jack 1123

'''

How It Works

When we declare a starred parameter such as *param, then all the positional arguments from that point till the end are collected as a tuple called 'param'.

Similarly, when we declare a double-starred parameter such as **param, then all the keyword arguments from that point till the end are collected as a dictionary called 'param'.

We will explore tuples and dictionaries in a later chapter.

What do single and double asterisks mean in function parameters?

* collects positional arguments, ** collects keyword arguments* is for multiplication, ** is for power* creates a tuple, ** creates a list

The return statement

The return statement is used to return from a function i.e. break out of the function. We can optionally return a value from the function as well.

What happens if a function has no return statement?

It returns None implicitlyIt returns 0It causes an errorIt returns an empty string

Example (save as function_return.py):

def maximum(x, y):
    if x > y:
        return x
    elif x < y:
        return y
    else:
        return "equal"

print(maximum(2, 3))

Output:

''' '''

How It Works

The maximum function returns the maximum of the parameters, in this case the numbers supplied to the function. It uses a simple if..else statement to find the greater value and then returns that value.

Note that a return statement without a value is equivalent to returnNone. None is a special type in Python that represents nothingness. For example, it is used to indicate that a variable has no value if it has a value of None.

Every function implicitly contains a returnNone statement at the end unless you have written your own return statement. You can see this by running 'print(some_function()) where the function somefunction does not use the return statement such as:

def some_function():
    pass

The pass statement is used in Python to indicate an empty block of statements.

DocStrings

Python has a nifty feature called documentation strings, usually referred to by its shorter name docstrings. DocStrings are an important tool that you should make use of since it helps to document the program better and makes it easier to understand.

Where should a docstring be placed in a function?

On the first logical line after the function definitionAnywhere in the functionBefore the function definitionAfter the return statement

Example (save as function_docstring.py):

def print_max(x, y):
    """Prints the maximum of two numbers.

    The two values must be integers."""
    x = int(x)
    y = int(y)
    if x > y:
        print(x, "is maximum")
    else:
        print(y, "is maximum")

print_max(3, 5)
print(print_max.__doc__)

Output:

How It Works

A string on the first logical line of a function is the docstring for that function. Note that DocStrings also apply to modules and classes which we will learn about in the respective chapters.

The convention followed for a docstring is a multi-line string where the first line starts with a capital letter and ends with a dot. Then the second line is blank followed by any detailed explanation starting from the third line. You are strongly advised to follow this convention for all your docstrings for all your non-trivial functions.

We can access the docstring of the 'print_max' function using the 'doc' (notice the double underscores) attribute (name belonging to) of the function. Just remember that Python treats everything as an object and this includes functions. We'll learn more about objects in the chapter on classes.

If you have used 'help()' in Python, then you have already seen the usage of docstrings! What it does is just fetch the 'doc' attribute of that function and displays it in a neat manner for you. You can try it out on the function above - just include 'help(print_max)' in your program. Remember to press the 'q' key to exit 'help'.

Automated tools can retrieve the documentation from your program in this manner. Therefore, I strongly recommend that you use docstrings for any non-trivial function that you write. The 'pydoc' command that comes with your Python distribution works similarly to 'help()' using docstrings.

Let us identify proper docstring conventions:

Summary

Let us test your understanding of Python functions:

We have seen so many aspects of functions but note that we still have not covered all aspects of them. However, we have already covered most of what you will use regarding Python functions on an everyday basis.

Are you ready to test your function skills? Try creating a function that:

1. Takes any number of arguments
2. Has a default parameter
3. Includes a proper docstring
4. Returns a value

Next, we will see how to use as well as create Python modules.