python slides introduction interrupt.ppt

14. Python - Functions
• A function is a block of organized, reusable code that is used to
perform a single, related action. Functions provides better modularity
for your application and a high degree of code reusing.
• As you already know, Python gives you many built-in functions like
print() etc. but you can also create your own functions. These functions
are called user-defined functions.

Defining a Function
Here are simple rules to define a function in Python:
• Function blocks begin with the keyword def followed by the function
name and parentheses ( ( ) ).
• Any input parameters or arguments should be placed within these
parentheses. You can also define parameters inside these
parentheses.
• The first statement of a function can be an optional statement - the
documentation string of the function or docstring.
• The code block within every function starts with a colon (:) and is
indented.
• The statement return [expression] exits a function, optionally passing
back an expression to the caller. A return statement with no
arguments is the same as return None.
• Syntax:
• def functionname( parameters ):
• "function_docstring" function_suite return [expression]

• Syntax:
def functionname( parameters ):
"function_docstring"
function_suite
return [expression]
By default, parameters have a positional behavior, and you need
to inform them in the same order that they were defined.
• Example:
def printme( str ):
"This prints a passed string function"
print str
return

Calling a Function
• Following is the example to call printme() function:
def printme( str ): "This is a print function“
print str;
return;
printme("I'm first call to user defined function!");
printme("Again second call to the same function");
• This would produce following result:
I'm first call to user defined function!
Again second call to the same function

Pass by reference vs value
All parameters (arguments) in the Python language are passed by
reference. It means if you change what a parameter refers to within a
function, the change also reflects back in the calling function. For
example:
def changeme( mylist ): "This changes a passed list“
mylist.append([1,2,3,4]);
print "Values inside the function: ", mylist
return
mylist = [10,20,30];
changeme( mylist );
print "Values outside the function: ", mylist
• So this would produce following result:
Values inside the function: [10, 20, 30, [1, 2, 3, 4]]
Values outside the function: [10, 20, 30, [1, 2, 3, 4]]

There is one more example where argument is being passed by reference but
inside the function, but the reference is being over-written.
def changeme( mylist ): "This changes a passed list"
mylist = [1,2,3,4];
print "Values inside the function: ", mylist
return
mylist = [10,20,30];
changeme( mylist );
print "Values outside the function: ", mylist
• The parameter mylist is local to the function changeme. Changing mylist
within the function does not affect mylist. The function accomplishes
nothing and finally this would produce following result:
Values inside the function: [1, 2, 3, 4]
Values outside the function: [10, 20, 30]

Function Arguments:
A function by using the following types of formal arguments::
– Required arguments
– Keyword arguments
– Default arguments
– Variable-length arguments
Required arguments:
• Required arguments are the arguments passed to a function in correct
positional order.
def printme( str ): "This prints a passed string"
print str;
return;
printme();
Traceback (most recent call last):
File "test.py", line 11, in <module> printme();
TypeError: printme() takes exactly 1 argument (0 given)

Keyword arguments:
• Keyword arguments are related to the function calls. When you
use keyword arguments in a function call, the caller identifies
the arguments by the parameter name.
• This allows you to skip arguments or place them out of order
because the Python interpreter is able to use the keywords
provided to match the values with parameters.
def printme( str ): "This prints a passed string"
print str;
return;
printme( str = "My string");
My string

Following example gives more clear picture. Note, here order of
the parameter does not matter:
def printinfo( name, age ): "Test function"
print "Name: ", name;
print "Age ", age;
return;
printinfo( age=50, name="miki" );
Name: miki Age 50

Default arguments:
• A default argument is an argument that assumes a default
value if a value is not provided in the function call for that
argument.
• Following example gives idea on default arguments, it would
print default age if it is not passed:
def printinfo( name, age = 35 ): “Test function"
print "Name: ", name;
print "Age ", age;
return;
printinfo( age=50, name="miki" );
printinfo( name="miki" );
Name: miki Age 50 Name: miki Age 35

Variable-length arguments:
• You may need to process a function for more arguments than
you specified while defining the function. These arguments are
called variable-length arguments and are not named in the
function definition, unlike required and default arguments.
• The general syntax for a function with non-keyword variable
arguments is this:
def functionname([formal_args,] *var_args_tuple ):
"function_docstring"
function_suite
return [expression]

• An asterisk (*) is placed before the variable name that will hold the
values of all nonkeyword variable arguments. This tuple remains
empty if no additional arguments are specified during the function
call. For example:
def printinfo( arg1, *vartuple ):
"This is test"
print "Output is: "
print arg1
for var in vartuple:
print var
return;
printinfo( 10 );
printinfo( 70, 60, 50 );
Output is:
10
Output is:
70
60
50

The Anonymous Functions:
You can use the lambda keyword to create small anonymous functions.
These functions are called anonymous because they are not declared
in the standard manner by using the def keyword.
• Lambda forms can take any number of arguments but return just one
value in the form of an expression. They cannot contain commands or
multiple expressions.
• An anonymous function cannot be a direct call to print because
lambda requires an expression.
• Lambda functions have their own local namespace and cannot access
variables other than those in their parameter list and those in the
global namespace.
• Although it appears that lambda's are a one-line version of a function,
they are not equivalent to inline statements in C or C++, whose
purpose is by passing function stack allocation during invocation for
performance reasons.
• Syntax:
lambda [arg1 [,arg2,.....argn]]:expression

Example:
• Following is the example to show how lembda form of function
works:
sum = lambda arg1, arg2: arg1 + arg2;
print "Value of total : ", sum( 10, 20 )
print "Value of total : ", sum( 20, 20 )
Value of total : 30
Value of total : 40

Scope of Variables:
• All variables in a program may not be accessible at all locations in that
program. This depends on where you have declared a variable.
• The scope of a variable determines the portion of the program where
you can access a particular identifier. There are two basic scopes of
variables in Python:
Global variables
Local variables
• Global vs. Local variables:
• Variables that are defined inside a function body have a local scope,
and those defined outside have a global scope.
• This means that local variables can be accessed only inside the
function in which they are declared whereas global variables can be
accessed throughout the program body by all functions. When you call
a function, the variables declared inside it are brought into scope.

• Example:
total = 0; # This is global variable.
def sum( arg1, arg2 ):
"Add both the parameters"
total = arg1 + arg2;
print "Inside the function local total : ", total
return total;
# Now you can call sum function
sum( 10, 20 );
print "Outside the function global total : ", total
Inside the function local total : 30
Outside the function global total : 0

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