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UNIT: III Functions and Modules Lectures:
08 Hrs
• Need for functions:
• Function: definition, call, variable scope and lifetime, the return statement.
• Defining functions, Lambda or anonymous function,
• documentation string,
• good programming practices.
• Introduction to modules,
• Introduction to packages in Python,
• Introduction to standard library modules.
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Function
A function is a block of organized, reusable code that is used to perform a single, related
action. Functions provide better modularity for your application and a high degree of code
reusing.
Defining a Function
•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 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.
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Function
Syntax:
def function_name (parameter) :
def marks the start of function
Function_name to uniquely identify a function.
Argument to pass a value in function
colon(:) to mark end of function header
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Function Type
THERE ARE TWO TYPES OF FUNCTION IN PYTHON
BUILT-IN FUNCTION:
Example: print(), input(), eval().
USERDEFINE FUNCTION:
Example: def my_addition(x,y):
sum = x + y
return sum
THERE ARE 68 BUILT-IN FUNCTION VERSION 3.4.
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Return Statement
It is statement to return from a function to its
previous function who called this function.
After return control goes out of the current
function.
All local variables which were allocated memory in
current function will be destroyed.
Return statement is optional in python.
Any function can return multiple arguments.
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Return Statement
Example
return #This returns none value
return None #This returns none value
return a, b #This returns two values
return a #This returns single value
These all are valid examples of a return statement.
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• Position
• Keyword
• Default
• Variable length
• lambda
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Anonymous Functions / Lambda Functions
Functions containing only single operation can be
converted into an anonymous function.
‘Lambda’ is the keyword used to create such anonymous
functions.
Syntax
Lambda < space > <parameter> : < operation >
Example
my_addition = lambda x, y : x + y
print(“addition is ”, my_addition(20, 30))
Output = 50
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Variable Scope and Lifetime
1. In functions, there are two kinds of variables, local and
global.
Local Variables / Objects :
2. Variables or objects which are used only within given
function are local variables or local objects.
3. Local objects include parameters and created in a given
function.
Example
In following code, mult() function has two local variables
Local variable ‘a’ and local variable ‘b’.
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Global variables / objects
1. Objects which can be accessed throughout the
script/program are global variables or objects.
2. Global variables or objects are created in python script
outside any function.
3. Global objects are available after “global” keyword
defined in the script.
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Global variables / objects
1. Reading Global variable value
Example
In following example global variable is accessed for
printing / reading purpose.
No modification to global variable is done here.
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Global variables / objects
#No modification in global variable id made
def add_gv(a,b):
c=a+b+gv
print("in function value of gv is =",gv)
print("The addition is :",c)
gv=100
print("The initial value of gv =", gv)
add_gv(10,20)
print("After function value of gv =",gv)
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Global variables / objects
Modification of Global Variable Value
‘global’ keyword is used to modify a global variable inside a
function.
Example
In following example “global” keyword is used inside the
function.
Now global variable can be modified within the function.
Modifications made in the function (after using “global”)
will stay after the function as well.
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Global variables / objects
#Modification in global variable is made
def add_gv(a,b):
global gv
gv=150
print(gv)
c=a+b+gv
return c
gv=100
print(gv)
x=add_gv(10,20)
print(x)
print(gv)
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Documentation String
In python, programmer can write a documentation
for every function.
This documentation can be accessed by other
functions.
Advantage of Document string
It is useful when we want to know about any
function in python.
Programmer can simply print the document string
of that function and can know what that function
does.
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Documentation String
def func( ):
"""Welcome to Coulomb"""
return
print(func.__doc__)
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Standard Libraries in Python
1. Math (import math)
This is a package for providing various functionalities
regarding mathematical operations.
2. Random (import random)
This is the module which supports various functions for
generation of random numbers and setting seed of random
number generator.
3. Numpy (import numpy)
This is a package in python which supports various
numeric operations. It supports multidimensional arrays or
matrices and their calculations.
4. Scipy (import scipy)
This is the package for various scientific computations.
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Introduction to Modules
Modules make python programs re-usable.
Every python code (.py) file can be treated as a
module.
A module can be accessed in other module using
import statement.
A single module can have multiple functions or
classes.
Each function or class can be accessed separately
in import statement.
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Introduction to Modules
Example to create your own module
Create a file named sample.py in your directory.
Write function add() in it. (as we have seen in
previous sections)
Now create another file trial.py in same directory
In trial.py write
import sample.add
print(“addition is “, sample.add(10,20))
Now run trial.py.
Now the output will be 30.
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