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11
PROGRAMMING WITH PYTHON -I
Unit Structure
1.1 Objective
1.2 Reasons for Python as the learner’ s first programming language.
1.3 Introduction to the IDLE interpreter (shell) and its documentation.
Expression evaluation: similarities and differenc es compared to a
calculator; expressions and operators of types int, float,boolean.
1.4 Built -in function type.
1.5 Operator precedence
1.6 Summary
1.7 Reference for further reading
1.8 Unit End Exercises
1.1OBJECTIVE
1.Understand the fundamentals of writing Python scripts
2.Learn core Python scripting elements such as variables, expression ,
and operators
3.Use Python to input and output function
4.Understand the Built -in Functions
1.2REASONS FOR PYTHON AS THE LEARNER ’S
FIRST PROGRAMMING LANGUAGE
1. Reasons for Python are the learner's first programming language
are:
1. Presence of Third Party Modules:
The Python Package Index (PyPI) contains numerous third -party
modules that make Python capable of interacting with most of the other
languages and platforms.
2. Extensive Support Libraries:
Python provides a large stand ard library that includes areas like
internet protocols, string operations, web service tools ,and operating
system interfaces. Many high lyusedprogramming tasks have already
been scripted in to the standard libraries which reduces thelength of code
to be written significantly.munotes.in
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23. Open Source and Community Development:
Python language is developed under an OSI -approved open source
license, which makes it free to use and distribute, for commercial purposes
also.
4. Learning Ease and Support Available:
Python offers excellent readability and uncluttered simple -to-learn
syntax which helps beginners to easily use this programming language.
5. User -friendly Data Structures:
Python has built -in list and dictionary data structures thatcan be
used to constr uct fast runtime data structures. Further, Python also
provides anoption of dynamic high -level data typing which reduces the
length of support code .
6. Productivity and Speed:
Python supportsthe object -oriented design, provides enhanced
process control c apabilities, and possesses strong integration and text
processing capabilities and ,aunit testing framework all of which
contribute to increasing its speed and productivity.
Applications of Python
GUI based desktop applications
oImage processing and graphic design applications
oScientific and computational applications
oGames
Web frameworks and web applications
Enterprise and business applications
Operating systems
Language development
Prototyping
1.3INTRODUCTION TO THE IDLE INTERPRET ER
(SHELL) AND ITS DOCUMENTATION.
Introduction to the IDLE interpreter (shell) and its documentation
IDLE has the following features:
a.coded in 100% pure Python, using the Tkinter GUI toolkit
b.cross -platform: works mostly same on Windows, Unix, and
macOS
c.Python shell window (interactive interpreter) with colorizing code
input, output, and error messages
d.multi -window text editor with multiple undo, Python colorizing,
smart indent, call tips, auto-completion , and other featuresmunotes.in
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3e.search within any window, repl ace within editor windows and
search through multiple files (grep)
f.debugger with persistent breakpoints, stepping, and viewing of
global and local namespaces configuration, browsers, and other
dialogs
Menus
IDLE has two main window types, the Shell window ,and the Editor
window. It is possible to have multiple editor windows
simultaneously. On Windows and Linux, each has its top menu. Each
menu documented below indicates which window type it is associated
with.
Output windows, such as used for Edit => Find in Files, are a subtype
of editor window. They currently have the same top menu but a
different default title and context menu.
On macOS, there is one application menu. It dynamically changes
according to the window currently selected. It has an IDLE menu ,a n d
some entries described below are moved around to conform to Apple
guidelines.
File menu
New File
Create a new file editing window.
Open…
Open an existing file with an Open dialog.
Recent Files
Open a list of recent files. Click one to open it.
Open Module…
Open an existing module (searches sys.path).
Class Browser
Show functions, classes, and methods in the current Editor file in a tree
structure. In the shell, open a module first.
Path Browser
Show sys.path directories, modules, functions, classes and methods in
a tree structure.
Save
Save the current window to the associated file, if there is one.
Close
Close the current window (ask to save if unsaved).
Exit
Close all windows and quit IDLE (as k to save unsaved windows).
Edit menu (Shell and Editor)
Undo
Undo the last change to the current window. A maximum of 1000
changes may be undone.
Redomunotes.in
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4Redo the last undone change to the current window.
Cut
Copy selection into the system -wide clipboard; t hen delete the
selection.
Copy
Copy selection into the system -wide clipboard.
Format menu (Editor window only)
Indent Region
Shift selected lines right by the indent width (default 4 spaces).
Dedent Region
Shift selected lines left by the indent width (de fault 4 spaces).
Comment Out Region
Insert ## in front of selected lines.
Uncomment Region
Remove leading # or ## from selected lines.
Run menu (Editor window only)
Run Module
Do Check Module. If no error, restart the shell to clean the
environment, then execute the module. Output is displayed in the Shell
window. Note that output requires use of print or write. When
execution is complete, the Shell retains focus and displays a prompt.
At this point, one may interactively explore the result of execution.
This is similar to executing a file with python -i file at a command
line.
Run… Customized
Same as Run Module, but run the module with customized settings.
Command Line Arguments extend sys.argv as if passed on a command
line. The module can be run in the Shell without restarting.
Check Module
Check the syntax of the module currently open in the Editor window.
If the module has not been saved IDLE will either prompt the user to
save or autosave, as selected in the General tab of the Idle Settings
dialog. If there is a syntax error, the approximate location is indicated
in the Editor window.
Python Shell
Open or wake up the Python Shell window.
2Expression evaluation: similarities a nd differences compared to a
calculator; expressions and operators of types int, float, boolean.
3. Expression evaluation:
Python’s eval() allows to evaluate arbitrary Python expressions
from a string -based or a compiled code object input . This function can bemunotes.in
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5used to dynamically evaluate Python expressions from any input that
comes as a string or a compiled code object.
The eval() is defined as :
eval(expression[, globals[, locals]])
The function takes three arguments. The function takes a first
argument, called expression, which holds the expression that you need to
evaluate. eval() also takes two optional arguments:
1. globals
2. locals
The First Argument: expression
The first argument to eval() is called expression. It’s a required
argument that holds the string -based or compiled -code-based input to the
function. When eval() function call , the content of expression is evaluated
as a Python expression.
>>>eval("90 + 1 0")
100
>>>eval("sum([10, 50, 25])")
85
>>> x = 50
>>>eval("x * 2")
100
To evaluate a string -based expression, Python’s eval() runs the
following steps:
1. Parse expression
2. Compile it to bytecode
3. Evaluate it as a Python expression
4. Return the result of the evaluation
The Second Argument: globals
The second argument to eval() is called globals. It’s optional and
holds a dictionary that provides a global namespace to eval(). With
globals, you can tell eval() which global names to use while evaluating
expression. Global names are all those names that are available in your
current global scope or namespace. All the names passed to globals in a
dictionary will be available to eval() at execution time.
Python
>>>x1 = 100 # A global var iable
>>>eval("x1 + 100", {"x1": x1})
200
>>> y1 = 200 # Another global variablemunotes.in
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6>>>eval("x1 + y1", {"x1": x1})
Traceback (most recent call last):
File "", line 1, in
File "", line 1, in
NameError: name 'y1' is not defined
If you supply a custom dictionary to the globals argument of
eval(), then eval() will take only those names as globals. Any global
names defined outside of this custom dictionary won’t be accessible from
inside eval(). That’s why Python raises a N ameError when you try to
access y1 in the above code: The dictionary passed to globals doesn’t
include y1.
You can insert names into globals by listing them in your
dictionary, and then those names will be available during the evaluation
process. For example, if you insert y1 into globals, then the evaluation of
"x1 + y1" in the above example will work as expected:
Python
>>>eval("x1 + y1", {"x1": x1, "y1": y1})
300
Since you add y1 to your custom globals dictionary, the evalu ation of "x1
+ y1" is successful and you get the expected return value of 300.
The following examples show that even though you supply an empty
dictionary to globals, the call to eval() will still have access to Python’s
built-in names:
Python
>>>eval("s um([13, 12, 25])", {})
50
>>>eval("min([19, 55, 12])", {})
12
>>>eval("pow(10, 2)", {})
100
In the above code, you supply an empty dictionary ({}) to globals.
Since that dictionary doesn’t contain a key called "__builtins__", Python
automatically inserts one with a reference to the names in builtins. This
way, eval() has full access to all of Python’s built -in names when it parses
expression.
If eval() is call without passing a custom dictionary to globals, then
the argument will default to the dictionary returned by globals() in the
environment where eval() is called:munotes.in
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7Python
>>>x1 = 10
>>> y1 = 20
>>>eval("x1 + y1") # Access global variables
30
When eval() is call edwithout supplying a globals argument, the
function evaluates expression using th e dictionary returned by globals() as
its global namespace. So, in the above example, you can freely access x1
and y1 because they’re global variables included in your current global
scope.
The Third Argument: locals
Python’s eval() takes a third argumen t called locals. This is another
optional argument that holds a dictionary. In this case, the dictionary
contains the variables that eval() uses as local names when evaluating
expression.
Local names are those names (variables, functions, classes, and so
on) that you define inside a given function. Local names are visible only
from inside the enclosing function. You define these kinds of names when
you’re writing a function.
Since eval() is already written, you can’t add local names to its
code . However , you can pass a dictionary to locals, and eval() will treat
those names as local names:
>>>eval("x1 + 100", {}, {"x1": 100})
200
Evaluating Expressions With Python’s eval()
Python’s eval() can beusedto evaluate Boolean, math, and
general -purpose Pytho n expressions.
Boolean Expressions
Boolean expressions are Python expressions that return a True or
False when the interpreter evaluates them. They’re commonly used in if
statements to check if some condition is true or false.
Python
>>>x1 = 100
>>> y 1=1 0 0
>>>eval("x1 != y1")
Falsemunotes.in
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8>>>eval("x1< 300 and y1> 100")
False
>>>eval("x1 is y1")
True
>>>eval("x1 in {155, 100, 180, 190}")
True
eval()can be use dwith Boolean expressions that use any of the following
Python operators:
Value comparison operators: <, >, <=, >=, ==, !=
Logical (Boolean) operators: and, or, not
Membership test operators: in, not in
Identity operators: is, is not
Math Expressions
One common use case of Python’s eval() is to evaluate math expressions
from a string -based input.
The following examples show how you can use eval() along with math to
perform math operations:
>>> import math
>>> # Area of a circle
>>>eval("math.pi * pow(2, 2)")
12.56
General -Purpose Expressions
eval() can beusedwith more complex Python expressions that incorporate
function calls, object creation, attribute access, comprehensions, and so
on.
For example, you can call a built -in function or one that you’ve
imported with a standard or third -party module:
>>> impo rt subprocess
>>>eval("subprocess.getoutput('echo Hi, Friends')")
'Hi, Friends'
Operators
Operators are special symbols in Python that carry out arithmetic
or logical computation. The value that the operator operates on is called
the operand.
For example :
>>>12+93
115munotes.in
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9Here, + is the operator that performs addition. 12 and 93 are the operands
and 115 is the output of the operation.
Arithmetic operators:
Arithmetic operators are used to perform mathematical operations
like addition, subtraction, multiplication, etc.
Operator Meaning Example
+ Add two operands or
unary plusx+y +2
- Subtract right operand
from the left or unary
minusx-y-2
* Multiply two operands x*y
/ Divide left operand by
the right one (always
results into float)x/y
% Modulus -remainder of
the division of left
operand by the rightx % y (remainder of
x/y)
// Floor division -division
that results into whole
number adjusted to the
left in the number linex//y
** Exponent -left operand
raised to the power of
rightx**y (x to the power y)
Example 1: Arithmetic operators in Python
x=1 5
y=4
print('x + y =',x+y)
# Output: x + y = 19
print('x -y= ' , x -y)
# Output: x -y=1 1
print('x * y =',x*y)
#Output: x * y = 60
print('x / y =',x/y)
# Output: x / y = 3.75
print('x // y =',x//y)
# Output: x // y = 3munotes.in
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10print('x ** y =',x**y)
# Output: x ** y = 50625
Comparison operators:
Comparison operators are used to compare values. The comparison
operators are also known as relational operator. It returns either True or
False according to the condition.
Operator Meaning Syntax
> Greater than :-True if the
left operand is greater than
the righta>b
< Less than :-True if theleft
operand is less than the
righta== Equal to :-True if both
operands are equala= =b
!= Not equal to :-True if
operands are not equala! =b
>= Greater than or equal to :-
True if theleft operand is
greater than or equal to the
righta> =b
<= Less than or equal to :-True
iftheleft operand is less
than or equal to the righta< =b
a=1 0 0
b=1 1 2
print('a> bis',a>b)
Output: a > b is False
print('aOutput: a < b is True
print('a == b is',a==b)
Output: a == b is False
print('a != b is',a!=b)
Output: a != b is True
print('a >= b is',a>=b)
Output: a>= b is False
print('a <= b is',a<=b)
Output: a<= b is Truemunotes.in
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11Logical operators
Logical operators are and, or, not operators.
Operator Meaning
and if both the operands are true then condition become true.
or if either of the operands is true then condition become true.
not Used to reverse the logical state of its operand.
a=T r u e
b = False
print('a and bis',a and b)
print('a or bis',x or y)
print('not ais',nota)
Output
aand b is False
ao rbi sT r u e
nota is False
Bitwise operators
Bitwise operator works on bits and performs bit by bit operation.
& Binary AND Operator This Operator is used to copy a bit to the
result if it exists in both operands.
| Binary OR Operator It copies a bit if it exists in any operand.
^ Binary XOR Operator It copies a bit if it is set in one operand
but not both.
~ Binary ones
Complement OperatorItis unary and will flip the bits, so 1 will
become 0 , and 0 will become 1.
<< Binary Left Shift
OperatorIt shifts the value of the left operand to
left by the number of bits given by the
right operand.
>> Binary Right Shift
OperatorIt shifts the value of the left operand to
right by the number of bits given by the
right operand.munotes.in
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12Assignment operators
Assignment operators are used to assigning values to variables.
= These operators are used to assign the values for the
right side operands to theleft side operand.a=2 5
+= These operators are used to add theright operand to
the left operand and theresult is a assign to the left
operand.a+ =1 0
a=a+1 0
-= The right operand gets subtracted from theleft
operand and the result is assigned to the left
operand.a-=1 0
a=a -10
*= The right op erand gets mu ltiplied with the left
operand and the result is assigned to the left
operand.a* =1 0
a=a*1 0
/= The l eft operand is divided by the right operand and
theresult is assigned to the left operand.a /= 10
a=a/1 0
%= It performs the modulus operation and theresult is
assigned to the left operand.a %= 10
a=a%1 0
a = 25 is a simple assignment operator that assigns the value 25 on the
right to the variable aon the left.
a=25
a+ =1 0
print(“ a is : ”,a)
#output:a is : 35
a-=1 0
print(“ a is : ”,a)
#output:a is : 15
a* =2
print(“ a is : ”,a)
#output:a is : 50
a /= 5
print(“ a is : ”,a)
#Output:a is : 5
a %= 4
print(“ a is : ”,a)
#output:a is : 1munotes.in
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13Special operators
Python language offers some special types of operators like the identity
operator or the membership operator.
Identity operators
Identity operators are used to compare the memory location sof
two objects.
is True -If the variable on either side of the operator point
to the same object
False -If the variable on either side of the operator does
not point to the same object
isn o t False -if the variable on either side of the operator point
to the same object.
True -if the variable on either side of the operator point
to the different object.
Example:
p=50
q=50
print(‘p =’,p,’:’,id(p))
#output: -p=50 : 80983211
print(‘q =’,p,’:’,id(q))
#output: -q=50 : 80983211
if(p is q) :
print(‘p and q have same identity’)
else:
print(‘p and q do not have same identity’)
#output: -p and q have same identity
if(id(p) ==id(q)) :
print(‘p and q have same identity’)
else:
print(‘p and q do not have same identity’)
#output: -p and q have same identity
if(p is not q) :
print(‘p and q do not have same identity’)
else:
print(‘p and q have same identity’)
#output:p and q do not have same identitymunotes.in
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14Membership operators
There are two membership operators in Python (in and not in).
They are used to test for membership in a sequence(string, list, tuple and
dictionary) .
in Evaluates to true if it finds a variable in the sequence and
return false if it does not find a variable in the sequence
not in Evaluates to false if it finds a variable in the sequence
and return true if it does not find a variable in the
sequence
p=60
q=30
list1=[10,30,50,66]
example 1:
if(p in list 1):
print(‘p is in the list’)
else:
print(‘p is not in the list’)
#output: -p is not in the list
example 2:
if(p not in list 1):
print(‘p is not in the list’)
else:
print(‘p is in the list’)
#output: -p is not in the list
example 3:
if(q in list 1):
print(‘q is in the list’)
else:
print(‘q is not in the list’)
#output: -q is in the list
3Built -in function type.
type() function in python returns the data type of the object which is
passes as an argument in this function. It is basically used for debugging
process.
syntax
type(object)
type(name, bases, dict)
a.object –for which type needs to be returned
b.name –name of the class
c.bases –a tuple of classes
d.dict–dictionary that holds namespace for the classmunotes.in
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15>>>print(type([1,2,3]))
#output : -
>>>print(type((1,2,3)))
#output : -
>>>print(type({1:’a’,2:’b’,3:’c’}))
#output : -
>>>print(type(“Good”))
#output : -
>>>print(type(1))
#output : -
>>>print(type(3.14))
#output : -
>>>print(type(True))
#output : -
4Operator precedence.
The order of the operation me ans the operator precedence to evaluate
an expression. The operator will help to evaluate the expression.
Following table shows alloperator sthat hashighest prec edence to lowest.
Operator Description
() Parentheses
** Exponent
+a,-a, ~a Unary plus, Unary minus, Bitwise NOT
*, /, //, % Multiplication, Division, Floor division, Modulus
+,- Addition, Subtraction
<<, >> Bitwise shift operator
& Bitwise and
^ Bitwise XOR
| Bitwise or
==, !=, >, >=, <, <= Comparisons operator
Not Logical NOT
And Logical AND
Or Logical OR
Operators with the highest precedence appear at the top of the table
Example:
>>> 5*2+10
20munotes.in
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16In this example the first precedence is given to the multiplication
then addition operator.
>>>5*(2+10)
60
In this example the first precedence is given to the parenthesis then
multiplication operator.
>>>10/5+10
12
In this example the first precedence is given to the division then addition
operator.
1.6SUMMARY
a. We learn tReasons for Python as the learner’ s first programming
language.
b. We have studied IDLE interpreter (shell) and its documentation.
c. W e learn tsyntax of expression evaluation: similarities and differences
compared to a Calculator
d. We used different types of expressions and operators.
e. W ea l s ou s e dBuilt -in function type & operator precedence in python
programs.
1.7REFERENCE FOR FURTHER READING
a. Charles Dierbach, Introduction to Computer Science using Python,
Wiley, 2013
b. Paul Gries , Jennifer Campbell, Jason Montojo, Practical Programming:
An Introduction to Computer Science Using Python 3, Pragmatic
Bookshelf, 2/E 2014
1.8 UNIT END EXERCISES
1.What are the feature softhepython programming language?
2.Explain Expression evaluation in python.
3.Explain various operator su s e d in python.
4.Write a python program using Math Expressions.
5.Explain the use of Built -intype function with an example.
6.Explain operator precedence with anexample.
munotes.in
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172
PROGRAMMING WITH PYTHON -II
Unit Structure
2.1 Objective
2.2 Enumeration of simple and compound statements.
2.3 The expression statement. Theassert statement,
2.4 Boolean expression (values true or false).
2.5 The assignment statement, dynamic binding of names to values,
(type is associated with data and not with names); automatic and
implicit declaration of varia ble names with the assignment
statement; assigning the value None to a name.
2.6 The del (delete)statement.
2.7 Input/output with print and input functions.
2.8 A statement list ( semicolon -separated list of simple statements on a
single line) as a single interpreter command.
2.9 The import statement for already defined functions and constants.
2.10 The augmented assignment statement.
2.11 The built -inhelp() function.
2.12 Summary
2.13 Reference for further reading
2.14 Unit End Exercises
2.1OBJECTIVE
1.Understand the simple statements
2.Understand the compound statements
3.Use Python to delete thestatement
4.Understand print and input function sin python.
5.Understand the built -inhelpFunctions
2.2ENUMERATION OF SIMPLE AND COMPOUND
STATEMENTS.
ASimple statement in python:
As the name suggests, simple statement sare comprised in one
single line.These types of statements will never affect theflow of a
program.munotes.in
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18There are many simple statements like assert, break, continue,
pass, del,import, return, etc.
The syntax for simple statement is:
simple_stmt ::= expression_stmt
| assert_stmt
| assignment_stmt
| augmented_assignment_stmt
|annotated_assignment_stmt
|p a s s _ s t m t
| del_stmt
| return_stmt
| yield_stmt
| raise_stmt
|b r e a k _ s t m t
| continue_stmt
| import_stmt
| future_stmt
| global_stmt
| nonlocal_stmt
Compound statements in python:
A compound statement is defined as a group of statements that
affect or control the execution of other statements in some way. Python
programming language provides different ways to construct or write
compound statements. These are mainly defined as:
If Statement:
This statement is used for conditional execution.
The syntax of the statement is as follows: -
if expres sion: suite
elif expression: suite
else: suite
while Statement :
While statement is used to execute a block of statements repeatedly
until a given condition is fulfilled. Syntax of the statement is as follows
while expression:
statement(s)
for sta tement:
for statement is used to traverse a list or string or array in a
sequential manner for example
print("List Iteration")
li1= ["python", "for", "programmers"]
fori in l i1:
print(i)munotes.in
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19Try statement:
The try statement specifies exc eption handlers and/or cleanup code
for a group of statements.
With statement:
The with statement is used to wrap the execution of a block with
methods defined by a context manager where a context manager is an
object that defines the runtime context to b e established.
2.3THE EXPRESSION STATEMENT, ASSIGNMENT
STATEMENT, THE ASSERT STATEMENT,
2.3.1 The expression statement.
These types of statements are formed using operators, variables or
values which create one mathematical expression.
Example:
>>>i=5
>>> v=i -2
>>>v
3
>>> z=i**2
>>>z
25
2.3.2 Assignment Statement:
In this type of statement ,we assign value to a variable. This
statement has one equal (=) sign. We cannot set keywords as a variable
name.
Example:
>>>i=5
>>> a=10
>>> #keyword can not be used in as signment
>>>for=5
SyntaxError: invalid syntax
2.3.2The assert statement
Assert statements:
Assert statements are a convenient way to insert debugging assertions
into a program:
assert_stmt ::= "assert" expression ["," expression]
The simple form, assert expression, is equivalent to
if __debug__:
if not expression: raise AssertionError
The extended form, assert expression1, expression2, is equivalent tomunotes.in
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20if __debug__:
if not expression1: raise AssertionError(expression2)
These equiv alences assume that __debug__ and AssertionError refer s
to the built -in variables with those names. In the current
implementation, the built -in variable __debug__ is True under normal
circumstances, False when opt imization is requested (command -line
option -O). The current code generator emits no code for an assert
statement when optimization is requested at compile time. Note that it
is unnecessary to include the source code for the expression that failed
in the error message; it will be displayed as part of the stack trace.
Assignments to __debug__ are illegal. The value for the built -in
variable is determined when the interpreter starts.
2.4BOOLEAN EXPRESSION (VALUES TRUE OR
FALSE).
A boolean expression is an expr ession that yields just the two
outcomes: true or false. When we work with multiple boolean expressions
or perform some action son them, we make use of the boolean operators.
Since the boolean expression reveals true or false, the operations on these
expre ssions also result in either “true” or “false“. Consequently, there are
three types of boolean operators:
1. The AND operator (&& or “and”)
2. The OR operator (|| or “or”)
3. The NOT operator (not)
1. AND Boolean Operator in Python
The AND boolean operator is similar to the bitwise AND operator
where the operator analyzes the expressions written on both sides and
returns the output.munotes.in
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21True and True = True
True and False = False
False and True = False
False and False = False
In python, you can directly use the word “and ” instead of “&&” to
denote the “and ” boolean operator while for other languages, you need to
put “&&” instead.
a=3 0
b=4 5
if(a > 30 and b == 45):
print("True")
else:
print("False")
Output: -False
2.OR Boolean Operator in Python
The OR operator is similar to the OR bitwise operator. In the
bitwise OR, we were focu sing on either of the bit being 1. Here, we take
into account if either of the expression is true or not. If at least one
expression is true , consequently, the result is true.
True or True = True
True or False = True
False or True = True
False or False = False
a=2 5
b=3 0
if(a > 30 or b < 45):
print("True")
else:
print("False")
Output: -True
3.NOT Boolean Operator in Python
The NOT operator reverses the result of the boolean expression
that follows the operator. It is important to note that the NOT operator will
only reverse the final result of the expression that immediately follows.
Moreover, the NOT operator is denoted by the keyword “not“ .
a=2
b=2
if(not(a == b)):
print("If Executed")
else:
print("Else Executed")
Output: -Else Executedmunotes.in
Page 22
222.5DYNAMIC BINDING OF NAMES TO VALUES,
(TYPE IS ASSOCIATED WITH DATA AND NOT WITH
NAMES); AUTOMATIC AND IMPLICIT
DECLARATION OF VARIABLE NAMES WITH THE
ASSIGNMENT STATEMEN T;ASSIGNING THE
VALUENONE TO A NAME.
2.5.1 Python is a dynamically typed language. It doesn’t know about the
type of th e variable until the code is executed .S ovariable declaration is of
no use. What it does is store that value at some memory location and then
bind that variable name to that memory container. And makes the contents
of the container accessible through that variable name. So the data type
does not matter. As it will get to know the type of the value at run -time.
Example:
#This will store 99 in the memory and bind the name x to it. After it
execute s,thetype of x will be int.
x=9 9
print(type(x))
# This will st ore 'India' at some location in the mem ory and binds name x
to it. After it runs type of x will be str.
x = 'India'
print(type(x))
Output:
Variables
As the name implies, a variable is something thatcan change. A
variable is a way of referring to a mem ory location used by a computer
program. A variable is a symbolic name for this physical location. This
memory location contains values, like numbers, string setc.
A variable can be seen as a container to store values. While the
program is running, variab les are accessed and sometimes changed, i.e. a
new value will be assigned to the variable.
One of the main differences between Python and other
programming language sis the way it deals with types. In strongly -typed
languages ,every variable must have a u nique data type. E.g. if a variable
is of type integer, solely integers can be saved in the variable. In Java or C,
every variable has to be declared before it can be used.
Declaration of variables is not required in Python. If there is aneed
fora varia ble, you type a name and start using it as a variable.munotes.in
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23Another aspect of Python: Not only the value of a variable may
change during program execution but the type as well. You can assign a
float value to a variable, use it as afloat for a while and then assign a
string to the variable.
Example:
x=1 2 2
>>>print x
122
>>> x =”Mumbai”
>>>print x
Mumbai
x=8 2 # data type is integer
x=8 2+0 . 1 1 # data type is changed to float
x = "Mumbai" # and now it will be a string
Python automatically takes ca re of the physical representation for
the different data types, i.e. an integer value will be stored in a different
memory location than a float or a string.
Dynamic Typing vs Static Typing:
Dynamic Typing Static Typing
Variable type checking will happen
at runtime.Variable type checking will happen
at compile time.
As the typing checking happens in
runtime the dynamically typed code
can compile even it has some errors
which might lead logical issues.The statically ty ped code won't
compile if it has any error. In order
to run the code, we must fix the
error.
Dynamically typed languages don't
expect the variable declaration
before using them. The variable
declaration will happen
automatically when we assign
values to i t.Statically typed languages expect
the variable declaration before
assigning values to it.
Python, Perl, etc. C, Java, etc.
Assigning the valueNone to a name:
Python None Keyword:
Python has a set of keywords that are reserved words that cannot be used
as variable names, function names, or any other identifiers.
Keyword None: Represents a null value
Assign the value None to a variable:munotes.in
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24a=N o n e
print(a)
Definition and Usage
The None keyword is used to define a null value or no value at all.
None is not the same as 0 (Zero), False, or an empty string. None is a data
type of its own and only None can be None.
2.6THE DEL (DELETE) STATEMENT.
The del statement :
del〈object ,... 〉
Each object is any kind of Python object. Usually ,these a re
variables, but they can be functions, modules, classes.
The del statement works by unbinding the name, removing it from
the set of names known to the Python interpreter. If this variable was the
last remaining reference to an object, the object will be removed from
memory. If, on the other hand, other variables still refer to this object, the
object won't be deleted.
The del statement is typically used only in rare, specialized cases.
Ordinary namespace management and garbage collection are generally
sufficient for most purposes.
The del statement can be used to delete an item at a given index.
Also, it can be used to remove slices from a list.
List1 = [1, 2, 3, 4, 5, 6, 7, 8, 9]
# deleting the third item
del list1[2]
print(list1)
# Output: [1, 2, 4, 5, 6, 7, 8, 9]
# deleting items from 2nd to 4th
del list1[1:4]
print(list1)
# Output: [1, 6, 7, 8, 9]
# deleting all elements
del list1[:]
print(list 1)
# Output: []munotes.in
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252.7INPUT/OUTPUT WITH PRINT AND INPUT
FUNCTIONS.
Python provides numerous built -infunctions that are readily
available. Some of the functions like input() and print() are used for input
and output operations respectively.
Python Input:
In Python, input() function is used totake input from the user.
The syntax for input() is:
input([pro mpt])
>>>na = input('Enter your name: ')
Enter your name :Amit
>>>na
'Amit'
>>>num = int(input('Enter a number: '))
Enter a number: 10
>>>num
10
>>>num = float(input('Enter a number: '))
Enter a number: 10
>>>num
10.0
print() function is use dto output data to the output device.
print(' Python programming')
Output: -Python programming
a=5 6
print(‘a is', a)
Output :-a is 56
The syntax of the print() function :
print(*objects, sep=' ', end=' \n', file=sys.stdout)
objects is the value(s) to be printed.
The sep separator is used between the values.
Once all values are printed, end is printed. It defaults into a new line.
The file is the object where the values are printed and its default value is
sys.stdout.
print(11, 21, 31, 41)
print(11 ,2 1 ,3 1 ,4 1 ,s e p = ' $ ' )
print(11, 21, 31, 41, sep='@', end='#')munotes.in
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26Output
11 21 31 41
11$21$31$41
11@21@31@41#
2.8A STATEMENT LIST (SEMICOLON SEPARATED
LIST OF SIMPLE STATEMENTS ON A SINGLE
LINE) AS A SINGLE INTERPRETER COMMAND.
A statement list ( semicolon -separated list of simple statements on a
single line) as a single interpreter command
Each statement is written on aseparate physical line in the editor.
However, statements in a block can be written in one line if they are
separated bysemico lon.
Following is thecode of three statements written in separate lines
a=10
b=20
c=a*b
print (c)
These statements can very well be written in one line by putting a
semicolon in between.
a=10; b=20; c= a*b; print (c)
A new block of increased indent starts a fter : symbol as in case of
if, else, while, for, try statements. However, using syntax, statements in a
block can be written in one line by adding asemicolon.
Following is the example of a block of statements in a for loop
fori in range(4):
print ("Mum bai")
print ("i=",i)
This block can also be written in single line using :
fori in range(4): print ("Mumbai"); print ("i=",i)
2.9THE IMPORT STATEMENT FOR ALREADY -
DEFINED FUNCTIONS AND CONSTANTS.
The import statement for already -defined functio ns and constants
Any text file with the .py extension containing Python code is
basically a module. Different Python objects such as functions, classes,
variables, constants, etc., defined in one module can be made available tomunotes.in
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27an interpreter session or an other Python script by using the import
statement. Functions defined in built -in modules need to be imported
before use. On similar lines, a custom module may have one or more user -
defined Python objects in it. These objects can be imported into the
interp reter session or another script.
If the programming algorithm requires defining a lot of functions
and classes, they are logically organized in modules. One module stores
classes, functions ,and other resources of similar relevance. Such a
modular structu re of the code makes it easy to understand, use and
maintain.
Creating a Module
The definition of sum() function. It is saved as cal.py.
cal.py
def sum(x, y):
return x + y
Importing a Module
now import this module a nd execute the sum() function in Python.
Example:
>>> import c al
>>>cal.sum(55, 44)
99
The import statement for constants
Constant:
A constant value is similar to a variable, with the exception that it
cannot be changed once it is set. Constants have a variety of uses, from
setting static values to writing more semantic code.
create two files, constants1.py and main .py to demonstrate.
# constants1.py
No1 = 20
# main.py
import constants1
No2 = 170
total = No2 + constants1.No1
print("To tal is {total}")
Output:
Total is 190munotes.in
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282.10THE AUGMENTED ASSIGNMENT STATEMENT.
The augmented assignment statement :
unlike normal assignment operators, augmented assignment o perators are
used to replace those statements where binary opera tor takes two operands
says var1 1and var12 and then assigns a final result back to one of
operands i.e. var11 or var12.
For example: statement var11 = var11 + 5 is same as writing var11 += 5 in
python and this is known as augmented assignment operator. Such type of
operators are known a s augmented because their functionality is extended
or augmented to two operations at the same time.
List o f Augmented Assignment Operators in Python
Addition & Assignment (+=): x+=y is equivalent to x=x+y
# Addition
a=1 0
b=5
a+ =b
print('Addition = %d' %(a))
OUTPUT :-Addition = 15
Subtraction & Assignment ( -=): x -=y is equivalent to x=x -y
# Subtraction
a=1 0
b=5
a-=b
print('Subtraction = %d' %(a))
OUTPUT :-Subtraction = 5
Multiplication & Assignment (*=): x*=y is equivalent to x=x*y
#M u ltiplication
a=1 0
b=5
a* =b
print('Multiplication = %d' %(a))
OUTPUT :-Multiplication = 50
Division & Assignment (/=): x/=y is equivalent to x=x/y
# Division
a=2 3munotes.in
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29b=3
a /= b
print('Division = %f' %(a))
OUTPUT :-Division = 7.666667
Remainder(or Modulo) & Assignment (%=): x%=y is equivalent tox=x%y
# Remainder or Modulo
a=1 2
b=5
a %= b
print('Remainder or Modulo = %d' %(a))
OUTPUT :-Remainder or Modulo = 2
2.11THE BUILT -INHELP() FUNCTION.
The python help function is used to displa y the documentation of
modules, functions, classes, keywords etc.
The help function has the following syntax:
help(print)
It gives the following output:
Help on built -in function print in module built -ins:
print(...)
print(value, ..., sep=' ', end=' \n', file=sys.stdout)
Prints the values to a stream, or to sys.stdout by default.
Optional keyword arguments:
file: a file -like object (stream); defaults to the current sys.stdout.
sep: string inserted between values, default a space.
end: string append ed after the last value, default a newline.
2.12SUMMARY
a.In this chapter ,we learn theuse of Enumeration of simple and
compound statements .
b.Study of expression statement and t he assert statement.
c.We have studied Boolea n expression (values true or false). The
assignment statement, dynamic binding of names to values, (type is
associated with data and not with names); automatic and implicit
declaration of variable names with the assignment statement; assigning
the value No ne to a name.
d.Understood the concept of the del (delete) statement in python.munotes.in
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302.13REFERENCE FOR FURTHER READING
a.Charles Dierbach, Introduction to Computer Science using Python,
Wiley, 2013
b.Paul Gries , Jennifer Campbell, Jason Montojo, Practical Programming:
An Introduction to ComputerScience Using Python 3, Pragmatic
Bookshelf, 2/E 2014
2.14UNIT END EXERCISES
1Explain S imple statements .
2What is assigning the value None to a name ?
3Explain t he augmented assignment statement .
4Write a Python program for t he import statement for already -defined
functions .
5Explain C ompound statements .
6Write thedifference between Dynamic Typing and Static Typing
7Explain Assert statement .
munotes.in
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313
PROGRAMMING WITH PYTHON -III
Unit Structure
3.1 Objective
3.2 Interactive and script modes of IDLE, running a script, restarting
the shell.
3.3 The compound statement def to define functions; the role of
indentation for delimiting the body of a compound statement;
calling a previously defined function. Compound data types str,
tuple and list (enclosed in quotes, parentheses and brackets,
respectively). Indexing individual elements within these types.
Strings and tuples are immutable, lists are mutable.
3.4 Built -in functions min, max, sum.
3.5 Interactive solution of model problems, (e.g., finding the square
root of a number or zero of a function), by repeatedly executing the
body of a loop (where the body is a statement list).
3.6 Summary
3.7 Reference for further reading
3.8 Unit End Exercises
3.1 OBJECTIVE
1.Understand the IDLE
2.Learn use of user define function and its application
3.Understand the List, Tuple
4.Understand the mutable
3.2INTERACTIVE AND SCRIPT MODES OF IDLE,
RUNNING A SCRIPT, RESTARTING THE SHELL.
•Interactive Mode
Python provides Interactive Shell to execute code immediately and
produce instant output . To get into this shell, we have to write python
code in the command prompt and start working on it.munotes.in
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32
•Script Mode
Using Script Mode, we can write our Python code in a separate file of
any editor.
i) Click on Start button -> All Programs -> Python ->IDLE(Python GUI)
ii) Python Shell will be opened. Now click on File ->N e wW i n d o w .
•A new Editor will be opened. Write our Python code here.
To execute a file in IDLE, simply press the F5 key on your
keyboard. You can also select Run →Run Module from the menu bar.
Either option will restart the Python interpreter and then run the code th at
you've written with a fresh interpreter.
How to Use the Python IDLE Shell
The shell is the default mode of operation for Python IDLE. When
you click on the icon to open the program, the shell is the first thing that
you see:
You can restart the shell from this menu. If you select that option,
then you’ll clear the state of the shell. It will act as though you’ve started a
fresh instance of Python IDLE. The shell will forget about everything
from its previous state .munotes.in
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333.3THE COMPOUND STATEMENT DEF TO DEFINE
FUNCTIONS; THE ROLE OF INDENTATION FOR
DELIMITING THE BODY OF A COMPOUND
STATEMENT; CALLING A PREVIOUSLY
DEFINED FUNCTION.
What is a function in Python?
In Python, a function is a group of rela ted statements that performs
a specific task.
Functions help break our program into smaller and modular
chunks. As our program grows larger and larger, functions make it more
organized and manageable.
Furthermore, it avoids repetition and makes the c ode reusable.
Syntax of Function
deffunction_name(parameters):
"""docstring"""
statement(s)
Above shown is a function definition that consists of the following
components.
Keyword def that marks the start of the function header.
A function _name to uniquely identify the function. Function naming
follows the same rules of writing identifiers in Python.
Parameters (arguments) through which we pass values to a function.
A colon (:) to mark the end of the function header.
Optional documentation string (do cstring) to describe what the function
does.
One or more valid python statements that make up the function body.
Statements must have the same indentation level.
An optional return statement to return a value from the function.
Example of a function
defdi sp(name):
print("Hi, " + name + ". Good morning!")
How to call a function?
Once we defined a function, we can call it from another function,
program. To call a function type the function name with appropriate
parameters.
>>>disp('Raj')
Hi, Raj. Good morn ing!munotes.in
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34Although optional, documentation is a good programming practice.
In the above example, we have a docstring immediately below the
function header. We can generally use triple quotes so that docstring can
extend up to multiple lines. This string is ava ilable to us as the __doc__
attribute of the function.
For example:
>>>print(disp.__doc__)
This function greets tothe person passed in as a parameter
Role of indentation
Indentation , one of the important features of python, refers to the spaces at
the beginning of a code line.Python uses indentation to indicate a block of
code. It convey sa better structure of a program to the readers. It explains
relationship between control flow constructs such as conditions or loops,
andcode contained inside and outside of it.
Indentation makes our program : -
–Easy to read
–Easy to understand
–Easy to modify
–Easy to maintain
–Easy for code debugging
The return statement
The return statement is used to exit a function and go back to the
place from where it was called.
Syntax of return
return [expression_list]
This statement can contain an expression that gets evaluated and
the value is returned. If there is no expression in the statement or the
return statement itself is not present ins ide a function, then the function
will return the None object.
For example:
>>>print(disp("Deep"))
Hello, deep. Good morning!
None
Here, None is the returned value since disp() directly prints the name
and no return statement is used.
Example of return
defabsolute_value(num):
"""This function returns the
value of the entered number"""
if number >= 0:munotes.in
Page 35
35return number
else:
return -number
print(absolute_value(92))
print(absolute_value( -64))
Output
92
64
Types of Functions
Basically, we can divide f unctions into the following two types:
1)Built -in functions -Functions that are built into Python.
2)User -defined functions -Functions defined by the users
themselves.
The Python Square Root Function:
Python’s math module, in the standard library, this li brary can help
you work on math -related problems in code. It contains useful
functions, such as remainder() and factorial(). It also includes the
Python square root function, sqrt().
>>> import math #importing math module
You can now use math.sqrt() to ca lculate square roots.
>>>math.sqrt(49)
7.0
>>>math.sqrt(70.5)
8.396427811873332
4 Compound data types str, tuple and list (enclosed in quotes,
parentheses and brackets, respectively). Indexing individual
elements within these types. Strings and tuples are immutable,
lists are mutable
Compound data types in Python :
List
Dictionaries
Tuples
List:
A list is an array of objects. An object can be an
integer,astring,float or other things. List is a container which holds
the items or element. The elemen ts in the list not of the same type.
The element are separated by the comma in a square bracket.munotes.in
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36The list are mutable data type. Mutable means you can do changes
in the list elements after cr eating the list.
PYTHON LIST PROPERTIES
Lists are ordered.
Lists can contain any arbitrary objects.
List elements can be accessed by index.
Lists can be nested to arbitrary depth.
Lists are mutable.
Lists are dynamic.
Initializing Values of List:
>>> List1 = [“India”, “Maharashtra”, 81]
Empty List:
>>> List2=[]
List creation
>>>list=[13,66,88,45,76,77]
Indexing individual elements within list
The expression in brackets is called an index. The index indicates
which cha racter in the sequence you want to access. Index starts
with zero.
Accessing first element of the list: -
>>>list[0]
output : -13
>>>list[3]
Output : -45
Negative indexing returns last element of the list.
>>>list[ -1]
output : -77
>>>list[ -3]
output : -45
Mutable Concept:
The list are the mutable data type. Mutable means you can do
chan ges in the list elements after creating the list.
>>>print(“value of second index position ”,list[2])
88
>>list[2]=999
>>>print(“value of second index position ”,list[2])
999munotes.in
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37Initialize two Lists in a single line:
>>> L1, L2=[‘mango’,’apple’,’banana ’],[‘Raj’,’Deep’]
>>L2
[‘Raj’,’Deep’]
Delete element from list:
Del statement is use to delete the element from list.
>>>list=[10, 20, 30, 40, 50]
>>>del list[2]
>>print(list)
[10,20,40,50]
Built in function:
Min Function:
The min() function is used to find the minimum value from the list.
>>>list=[100, 20, 320, 140, 56]
>>min(list)
20
Max Function:
The max() function is used to find the maximum value from the
list.
>>>list=[100, 20, 320, 140, 56]
>>max (list)
320
Sum Fun ction:
Python provide san inbuilt function sum() which sums up the numbers
in the list.
Syntax:
sum(iterable, start)
iterable :iterable can be anything list , tuples or dictionaries ,but most
importantly it should be numbers.
start : this start is add ed to the sum of numbers in the iterable.
If start is not given in the syntax , it is assumed to be 0.
>>>numbers = [1,2,3,4,5,1,4,5]
>>>print( sum(numbers) )
List Operators:
There are two list operator s‘+’and ‘*’ use din python.
Operator ‘+’ isused f or concatenation and operator ‘*’ isused for
repetition.munotes.in
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38Example:
>>>x1=[11,33,55]
>>>x2=[67,87,92]
>>>x3=x1+x2
>>>x3
[11,33,55,67,87,92]
>>> x=[11,33,55]
>>>x*2
[11,33,55,11,33,55 ]
In Operator:
Operator ‘in’ i s used to checkwhether the given element is present
in the list or not .I fthegiven elementis present in the list it return s
true.
Example:
>>>x=[11,33,55,66,78,98,211]
>>>66 in x
True
>>>22in x
False
Tuple :
Tuples are the immutable sequence data type. Immutable means
once we create data types ,the contents of itcannot be changed.
Tuples are used to store the heterogeneous data.
Creating Tuple
>>> tuple1=(‘a’,’b’,’c’, ’d’)
>>>print(tuple1)
(‘a’,’b’, ’c’,’d’)
Accessing the elements in a tuple
>>> tuple1=(‘Deep’,’Raj’, ’Sam’, ’Geet’)
>>>print(“Name is: “,tuple1[0])
Name is : Deep
>>>print(“Name is: “,tuple1[2])
Name is : Sam
Min method:
The min() functio n is used to find the minimum value in the tuple.
>>>tuple2=(12,34,5,67,55)
>>>print(“Minimum value ”,min(tuple2))
5munotes.in
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39Max method:
The max() function is used to find maximum value in the tuple.
>>>tuple2=(12,34,5,67,55)
>>>print(“Maximum values”, max(tuple2))
67
Len Method:
The len() function is used to find the total number of elements in
the tuple.
>>>tuple2=(12,34,65, 67,55)
>>>len(tuple2)
5
Tuple Operators:
There are two operator s‘+’and ‘*’ use d in python.
Operator ‘+’ is used for concatenation and operator ‘*’ isused for
repetition.
Operator ‘+’
>>>x1=(1,3,5)
>>>x2=(67,87,92)
>>x3=x1+x2
>>>x 3
(1,3,5,67,87,92)
Operator ‘*’
>>> x=(1,3,5)
>>>x*2
(1,3,5,1,3,5)
In Operator:
Operator ‘in’is used to checkwhether the given element is present
in the tuple or not .I fthegiven element is present ,it return strue.
>>>x=(11,33,55,66,78,98,211)
>>> 66 in x
True
>>>22 in x
False
Dictionary :
Dictionaries are the mutable data types. Each key available in the
dictionary is separated from its values by using the colon(:). The
items of the dictionary are separated by using a comma(,) and the
entire thing is enclosed in curly braces.munotes.in
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40Dictionary creation
>>>mydict = {“name”:”Deep”, “surname”:”patil”, “age”:29}
Accessing the values in a Dictionary:
>>print(“Name is”,mydict([“name”])
Name is Deep
>>print(“Age is”,mydict([“age”])
Age is 29
Deleting Dictionary Elements:
The del() statement is used to delete the dictionary element.
>>>del(mydict([“name”] ))
>>>mydict
{“surname”:”patil”, “age”:29}
Built -in Dictionary Methods
There are several built -in methods that can be invoked on
dictionaries.
d.clear() :-empties dict ionary d with all key -value pairs:
>>> d1 = {'a1': 10, 'a2': 20, 'a3': 30}
>>> d1
{'a1': 10, 'a2': 20, 'a3': 30}
>>>d1.clear()
>>> d1
{}
d.get([, ]) -Returns the value for a key if it exists
in the dictionary.
d1.get() searches dictionary d for and returns the
associated value if it is found. If is not found, it returns
None.
>>> d1 = {'a1': 10, 'a2': 20, 'a3': 30}
>>>print(d.get('a2'))
20
>>>print(d.get('a8'))
None
d.items() -Returns a list of key -value p airs in a dictionary.
d1.items() returns a list of tuples containing the key -value pairs in
d. The first item in each tuple is the key, and the second item is the
key’s value:
>>> d1 = {'a1': 10, 'a2': 20, 'a3': 30}
>>> d1
{'a1': 10, 'a2': 20, 'a3': 30}
>>>list(d1.items())munotes.in
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41[('a1', 10), ('a2', 20), ('a3', 30)]
>>>list(d1.items())[1][1]
20
d.keys() -Returns a list of keys in a dictionary.
>>> d1 = {'a1': 10, 'a2': 20, 'a3': 30}
>>> d1
{'a1': 10, 'a2': 20, 'a3': 30}
>>>list(d1.keys())
['a1', 'a2', 'a3']
3.4BUILT -IN FUNCTIONS MIN, MAX, SUM.
INTERACTIVE SOLUTION OF MODEL PROBLEMS,
(E.G., FINDING THE SQUARE ROOT OF A NUMBER
OR ZERO OF A FUNCTION), BY REPEATEDLY
EXECUTING THE BODY OF A LOOP (WHERE THE
BODY IS A STATEMENT LIST).
The Python Square Root Function:
Python’s math module, in the standard library, can help you work on
math -related problems in code. It contains many useful functions, such
as remainder() and factorial(). It also includes the Python square root
function, sqrt().
You’ll begin by importing math:
>>> import math
You can now use math.sqrt() to calculate square roots.
The return value of sqrt() is the square root of x, as a floating point
number.
>>>math.sqrt(49)
7.0
>>>math.sqrt(70.5)
8.396427811873332
3.5SUMMARY
In this chapter we stud ied the use of Interactive and script modes
of IDLE, running a script, restarting the shell.The compound statement def
to define functions; the role of indentation for delimiting the body of a
compound statement; calling a previously defined function.Compo und
data types str, tuple and list (enclosed in quotes, parentheses and brackets,
respectively). Indexing individual elements within these types. Strings andmunotes.in
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42tuples are immutable, lists are mutable. Built -in functions min, max, sum.
Interactive solution of model problems, (e.g., finding the square root of a
number or zero of a function), by repeatedly executing the body of a loop
(where the body is a statement list).
3.6REFERENCE FOR FURTHER READING
1. Charles Dierbach, Introduction to Computer Science u sing Python,
Wiley, 2013
2. Paul Gries , Jennifer Campbell, Jason Montojo, Practical Programming:
An Introduction to ComputerScience Using Python 3, Pragmatic
Bookshelf, 2/E 2014
3.7UNIT END EXERCISES
1.What are two modes of working in IDLE?
2.What is list ? Explain with example?
3.Explain the function of tuple with example.
4.What is difference between mutable and immutable?
5.What is difference between list and tuple?
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FUNCTIONS
Unit Structure
4.1.1 Definition
4.1.2 Advantages
4.1.3 Function types
4.1.4 Parameters and arguments
4.1.5 Return statement
4.1.6 R ecursive function
4.1.7 Global and local variables
4.1.1 DEFINITION OF FUNCTION
A function is a blo ck of organized, reusable code.That means a
function created once and can be used multiple times.
4.1.2 ADVANTAGES OF USING FUNCTIONS
Use of functions makes the code shorter
Use of functions makes the code easier to understand
It reduces duplication of code
Code can be reused easily
Implements information hiding
Divides a larger problem into smaller parts
Improves modularity of code
4.1.3FUNCTION TYPES
Functions are divided into two categories :
Built -in functions
User -defined functions
Built -in functions
Afunction that is already defined in a program or programming
framework with a set of statements, which together performs a task is
called a Built -infunction. There is no need for a user to create these
functions and these can be used directly in their program or
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44The Python interpreter has a number of built-infunctions .
abs() -returns absolute value of a number
bin() -converts integer to binary string
dict() -Creates a Dictionary
float() -returns floating point number from number, string
help() -Invokes the built -in Help System
input() -reads and returns a line of string
int() -returns integer from a number or string
iter() -returns an iterator
len() -Returns Length of an Object
list() -creates a list in Python
max() -returns the largest item
min() -returns the smallest value
pow() -returns the power of a number
print() -Prints the Given Object
range() -return sequence of integers between start and stop
round() -rounds a number to specified decimals
sum() -Adds items of an Iterable
tuple() -Returns a tuple
type() -Returns the type of the object
User defined function
They are functions created by the user. They are defined once and
called multiple times.
Syntax: -
deffunctionname( parameters ):
block of stat ements
return [expression]
function call
function call
Example:
def display(name):
print(name)
return
display()
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454.1.4 PARAMETER AND ARGUMENT
A parameter is the variable listed inside the parentheses in the
function definition.
An argument is avalue that is sent to the function when it is called.
Types
Actual parameters
Here actual data is sent into a function
e.g add(10,20)
Formal parameters
A variable containing a value is passed
e.g add(x, y)
Actual parameters
Example:
Defadd(a,b):
print(a+b)
add(20,30)
output: 50
Formal parameters
Example
defcube( x):
return x*x*x
4.1.5 R ETURN STATEMENT
ThePython return statement is a special statement that you can use
inside a function or method to send the function's result back to the
caller. A return statement consists of the return keyword followed by
an optional return value. The return value of a Python function can be
anyPython object
Example: -
def add(a,b):
return(a+b)
print((“sum =”,add(10,20))
output:
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464.1.6 GLOBAL AND LOCAL VARIABLES
Global Variables
In Python, a variable declared outside of the function or in global
scope is known as a global variable. This means that a global va riable can
be accessed inside as well as outside of the function.
Example :
g="global"
defdisplay ():
print ("Global variable inside theFunction :",g)
display()
print ("Global variable outside theFunction:" ,g)
Local Variables
A variable declared inside the function's body or in the local scope is
known as a local variable.
Example :
def display():
l=”Local”
print(l)
display()
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475
CONDITIONAL STATEMENTS AND
LOOPS
Unit Structure
5.2.1 Range function
5.2.2 Iterative for statement
5.2.3 Conditional statements if, if…else, if…elif…else and Nested if
5.2.4 Loops
5.2.1 RANGE FUNCTION
Therange() function returns a sequence of numbers, starting from
0 by default, and increments by 1 (by default), and stops before a specified
number.
Syntax:
range(start,stop,step):
range() takes mainly three arguments.
start :i n t e g e rs t a r t i n gf r o mw h i c ht h es e q u e n c eo fi n t e g e r si st o
be returned
stop: integer before which the sequence of integers is to be
returned.
The range of integers end at stop –1.
step: integer value which determines the increment between each
integer i nt h es e q u e n c e
Some examples using the range function are given below:
Example 1:
fori in range(10):
print(i, end =" ")
Output:
0123456789
Example 2:
l=[ 1 0 ,2 0 ,3 0 ,4 0 ]
fori in range(len(l)):
print(l[i], end =" ")
Output:
10 20 30 40munotes.in
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48Example 3 :
fori in range( 3, 6):
print(i, end =" ")
Output:
345
Example 4:
fori in range( 2,10,2):
print(i, end =" ")
Output:
2468
5.2.2 ITERATIVE FOR STATEMENT
Aforloop is used for iterating over a sequence.
Example:
fruits = [ "apple" ,"banana" ,"cherry" ]
forxinfruits:
print (x)
forch in ‘FYCS’:
print(ch)
5.2.3CONDITIONAL STATEMENTS
Conditional Statements in Python perform different computations
or actions d epending on whether a specific Boolean constraint evaluates to
true or false. Conditional statements are handled by IF statements in
Python.
If statement
Python if Statement is used for decision -making operations. It
contains a body of code that runs only when the condition given in ‘if’
statement is true. If the condition is false, then the optional else statement
runs which contains some code for the else condition.
Syntax:
if expression :
Statement
else:
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49Example:
a=33
b=200
ifb>a :
print ("b is greater than a" )
Else
If the condition is false the block of else is executed. Else is optional
Syntax:
if test expression:
Body of if
else:
Body of else
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50Elif
If condition for if is false the conditions in elif are checked if the
conditions are true the blocks are ex ecuted. It allows us to check for
multiple expressions.
Syntax:
if test expression:
Body of if
elif test expression:
Body of elif
elif test expression:
Body of elif
else:
Body of else
Example
n = int(input(“Enter a number”))
f=1
if n < 0 :
print(“Factorial Does not exist”)
elif n == 0 :
print(“Factorial of 0 is 1”)
else:
fori in range(1,n + 1):
f=f*i
print(“factorial = “,f)
Python Nested if statements
We can have a ifstatement inside another ifstatement. Such
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51Example:
x=105
ifx>10:
print ("Above ten," )
ifx>100:
print ("and also above 100" )
else:
print ("but not above 20." )
5.2.4 LOOPS
A loop statement allows us to execute a statement or group of
statements multiple times
Python has two primitive loop commands:
while loop
forloop
The while Loop
The while loop is used to execute a set of statements as long as the
condition is true.
Syntax:
while expression:
Block of statements
Example:
i=1
while i<10:
print (i)
i+ = 1
While …else
While loops can also have a noptional else block .T h ee l s ep a r ti s
executed if the condition in thewhile loop is evaluated as false.
counter =0
while counter <5:
print ("Inside loop" )
counter =counter +1
else:
print ("Inside else" )
The Continue Statement
Thecontinue statement in Python returns the control to the
beginning of the while loop. The continue statement rejects all the
remaining statements in the current iteration of the loop and moves the
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52Syntax:
while expression:
Block of statements
If condition:
continue
Example:
forch in ‘Python’ :
ifch == ‘h’:
continue
print( “Current character : “, ch)
output : -
Current character : P
Current character :y
Current character :t
Current character :o
Current character :n
The break statement
Thebreak statement in Python terminates the current loop and
resumes execution at the next statement.
Syntax:
while expression:
Block of statements
If condition:
break
Example:
forch in ‘Python’ :
ifch == ‘h’:
break
print( “Current character : “, ch)
output : -
Current character : P
Current character : y
Current character : t
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DICTIONARIES
Unit Structure
6.3.1Dictionary
6.3.2Operations and functions of dictionary
A dictionary is a nunordered collection of key value pairs. It is
mutab leand does not allow duplicates. Creating a dictionary is as simple
as placing items inside curly braces {}separated by commas.
Key and values
An item has a key and a corresponding value that is expressed as a
pairand can be referred to by using the k ey name. Keys are unique within
a dictionary while values may not be.
Creating dictionary
Syntax:
Dictionary name={“key”:”value”}
Example:
studentinfo = {
"Name" :"John" ,
"Class" :"FYCS" ,
"Rollno" :01
}
Access ingvaluesin a dictionary
>>>print (studentinfo[‘Name’])
>>>print (studentinfo.get(‘Class’))
Adding an item to a dictionary
Adding an item to the dictionary is done by using a new index key
and assigning a value to it
Syntax:
Dictionary name[“Key”]=”value”
Example:
>>>studentinfo[ "DOB" ]="01/01/2020" #new item added
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54Updating Dictionary
Dictionaries are mutable. If the key is present then the corresponding
value gets updated.
>>>studentinfo[‘Rollno’] = 5
>>>print(studentinfo)
Deleting an item from a dictionary
Individual elements can be removed from a dictionary
Syntax:
deldictionary_name[item]
Example:
>>>del studentinfo[Rollno]
>>>print(studentinfo)
Deleting all elements
All the elements can be dele ted using clear()
Syntax:
Dictionary_name.clear();
Example:
>>>s tudentinfo.clear()
Deleting entire dictionary
An entire dictionary can be deleted by using del.
Syntax:
deldictionary _name;
Example:
delstudentinfo;
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ANONYMOUS FUNCTIONS
Unit Structure
7.1 Introduction to An onymous function
7.1.1 What are An onymous functions in Python?
7.1.2 Use of An onymous functions
7.1.3 How to use An onymous Functions in a Python program?
7.1.4 Using Anonymous functions with other built-in functions
7.1.5 Using Anonymous function with filter()
7.1.6 Using Anonymous function with map()
7.1 INTRODUCTI ON TO ANONYMOUS FUNCTION
7.1.1 What are An onymous functions in Python?
In Python, an anonymous function is a function that is defined without
an a m e .I tisthesame as a regular python function but can be defined
without a name.
While normal functions are defined using the defkeyword in Python,
anonymous functions are defined using the lambda keyword.
Hence, anonymous functions are also called lambda functions
7.1.1 Use of Anonymous functions
We use lambda functions when we require a nameless function for a
short period of time.
In Python, we generally use it as an argument to a higher -order
function
Lambda functions are used along with other built -in functions
7.1.2 How to use Anonymous Fun ctions in a Python program?
Syntax: Lambda arguments: Expression
Example:
l=lambda a:a+ 10
print(l(20))
output: 30munotes.in
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56Inthe above example lambda a:a+ 10is the lambda function , l is the
argument and a+10 is the expression that gets evaluated and returned.
7.1.3 Using Anonymous functions with other built-in functions
Anonymous or Lambda functions can be used effectively with other
functions
7.1.4 Using Anonymous function with filter()
Thefilter() function in Python takes in a function and a list as arguments.
The function is called with all the items in the list and a new list is
returned which contains items for which the function evaluates to True .
Example:
my_list =[ 1 0 ,1 5 ,2 0 ,2 5 ,3 0 ]
new_list = list(filter(lambda x: (x%2 == 0) , my_list))
print(new_list)
Output:
[10, 20, 30]
7.1.5 Using Anonymous function with map()
The map() function in Python takes in a function and a list.
The function is called with all the items in the list and a new list is
returned which contains items returned by that function for each item.
Here is an example of the use of map() function to double all the items in a
list.
EXAMPLE:
my_list = [1, 2, 3, 4, 5]
new_list = list(map(lambda x: x * 10 , my_list))
print(new_list)
OUTPUT:
[10, 20, 30, 40, 50]
Questions:
1. Explain the concept of Anonymous functions ?
2. Explain with example theuse ofAnonymous function with filter().
3. Explain with example theuseofAnonymous function with map().
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LIST COMPREHENSION
Unit Structure
8.2List Comprehension
8.2.1 What is list comprehension ?
8.2.2 Using list comprehension with a nexisting list
8.2.3 U sing list comprehension with r ange()
8.2 LIST COMPREHENSION
8.2.1What is list comprehension ?
List comprehension offers a shorter syntax when you want to
create a new list based on the values of an existing list.
List comprehension is considerably faster than processing a list
using for loop.
The list comprehension syntax contains three parts: an
expression, one or more for loop, and optionally, one or more if
conditions.
The list comprehension must be in the square brackets [].
The result of the first expres sion will be stored in the new list.
The for loop is used to iterate over the iterable object that optionally
includes the if condition.
8.2.2 Using List Comprehension with a nexisting list
Listcomprehension can be easily used with existing lists to crea te
a new list.
EXAMPLE:
>>>fruits = [ "apple" ,"banana" ,"cherry" ,"kiwi" ,"mango" ]
>>>newlist = []
forxinfruits:
if"a"inx:
newlist.append(x)
print(newlist)
OUTPUT:
["apple" ,"banana" ,"mango" ]
8.2.3 Using list comprehension with r ange()
List comprehension can be easily used with range ()to create a new list.munotes.in
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58EXAMPLE :
#list of even numbers with list comprehension
even_nums = [x for x in range(31) if x%2 == 0]
print(even_nums)
OUTPUT:
[0, 2, 4, 6, 8, 10, 12, 14, 16, 18, 20, 22, 24, 26, 28, 30]
Ques tions:
1.Explain list comprehension with an Example.
2.Explain with an example how list comprehensions can be used with an
existing list .
3.Explain with an example how list comprehensions can be used with
range().
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INTRODUCTION TO OBJECT ORIENTED
PROGRAMMING
Unit Structure
9.3Introduction to Object -Oriented Programming
9.3.1What is Object -oriented programming?
9.3.2 Major Python OOPs concept s
9.3.3Class
9.3.4 Object
9.3.5Method
9.3.6 Inheritance
9.3.7 Encapsulation
9.3.8 Polymorphism
9.3.9 Data Abstraction
9.4 Built -in function dir()
9.5 methods of strings, tuples, lists, dictionaries
9.3 INTRODUCTION TO OBJECT ORIENTED
PROGRAMMING
9.3.1What is Object oriented programming?
Object -oriented programming (OOP) is a programming model that
relies on the concept of classes and objects .
An object can be defined as a data field that has unique attributes and
behavior.
It is used to structure a software program into simp le, reusable pieces
of code, which are used to create individual instances of objects.
9.3.2Major Python OOPs concept
1.Class
2.Object
3.Method
4.Inheritance
5.Encapsulation
6.Polymorphism
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609.3.3Class
A class is a collection of objects.
Class creates a user-defined data structure , which holds its own data
members and member functions.
A class can be accessed and used by creating an instance of that class
which is an object
Classes are created by keyword class
Syntax:
classclassname:
stateme nts
Example:
classnewclass:
display():
print(“new class”)
9.3.4 Object
An object is as e l f -contained component which consists of methods
and properties to make a particular type of data useful.
An Object is an identifiable entity with some characteristics and
behavior
An Object is an instance of a Class.
When a class is defined, no memory is allocated but when an object is
created memory is allocated.
Syntax:
classclassname:
statements
Obje ct = classname()
Example:
classnewclass:
def display():
print(“new class”)
obj=newclass()
9.3.5 Methods in Python
Python method is like a Python function, but it must be called on
an object. And to create it, you must put it inside a class.
Syntax:
classclassname:
method(arguments):
Example:
classnewclass:
def display(a):
print(“new class”)
obj=newclass()
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619.3.6 Inheritance
Inheritance allows us to define a class that inherits all the methods
and properties from another class
Syntax:
Class Child_class(Parent_class)
Example:
classParent_class:
def display(a):
print(“new class”)
class Child_class(Parent_class):
obj= Child_class()
obj.display()
Types of inheritance
1. Single -When one class inherits members of just one class.
2. Multiple -When one class inherits members of multiple classes
Syntax:
Class Base1:
Body of the class
Class Base2:
Body of the class
Class Derived(Base1, Base2):
Body of the class
Example:
classParent_class:
def display(a):
print(“new class”)
class Parent_class2:
def display2(a):
print(“new class”)
class Child_class(Parent_class, Parent_class2):
obj= Child_class()
obj.display()
3. Multilevel
When there is inheritance at various levels
Syntax:
Class level1:
Body of the class
Class level2 (level1):
Body of the class
Class level3(level2):
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62Example:
Class level1:
def display(a):
print(“new class”)
Class level2(level1):
Class level3(level2):
obj=level3 ()
obj.display()
4. Hierarchical
When two or more classes inherit members of one class.
Class Base:
Body of the class
Class child1(base):
Body of the class
Class child2(base):
Body of the class
Example:
classParent_class:
def display(a):
print(“new class”)
class Child_class1(Parent_class):
class Chi ld_class2(Parent_class):
obj= Child_class1()
obj.display()
obj1= Child_class2()
obj1.display ()
5. Hybrid
When there is a mix of any of the above types
9.3.7 Encapsulation
Encapsulation refers to the bundling of data, along with the methods that
operate on that data, into a single unit.
9.3.8 Polymorphism
Polymorphism is one of the OOPs features that allow us to perform
a single action in different ways.
With polymorphism ,we can create multiple entities with thesame
name.
Example:
classnewclass:
defdisplay(a):
print(“new class”)
def display(a,b):
obj=newclass()
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639.3.9 Data Abstraction
Data abstraction hides the details and complexities of the program so the
user only has to know how to work with an object .
Questions:
1.State and explain various object -oriented concepts?
2.Explain class in python with an example.
3.Explain inheritance in python with an example.
4.State and explain various types of inheritance.
5.Explain Hierarchical inheritance with an example.
6.Define the terms encapsulation, poly morphism, abstraction.
9.4 BUILT -IN DIR() FUNCTION
9.4.1 What is dir() function?
dir() is a powerful built -infunction in Python3, which returns list of the
attributes and methods of any object
Thedir() function returns all properties and methods of the specified
object, without the values.
This function will return all the properties and methods, even built -in
properties which are default for all object s.
Syntax:
dir(object )
Example
import random
print(dir(random)) #lists all names of attributes in random function
9.5 METHODS
9.5.1 String for functions
Python has a set of built -in methods that you can use on strings.
Some of theimportant string functions are defined below:
format() : -Formats sp ecified values in a string
lower(): -Converts a string into lower case
upper(): -Converts a string into upper case
replace(): -Returns a string where a specified value is replaced with a
specified value
center(): -Returns a centered string
count(): -Returns the number of times a specified value occurs in a
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9.5.2 Methods for Tuples
Python has a set of built -in methods that you can use on tuples.
cmp(tuple1,tuple2): -Compares elements of both tuples
len(): -Gives the total length of the tuple.
max(): -Returns item from the tuple with max value.
min(): -Returns item from the tuple with min value.
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9.5.5 Methods of lists
Python has a set of built -in methods that you can use on lists
sort(): Sorts the list in ascending order.
type(list): It returns the class type of an object.
append(): Adds one element to a list.
extend(): Adds multiple elements to a list.munotes.in
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66index(): Returns the first appearance of a particular value.
max(list): It returns an item from the list with a max value.
min(list): It returns an i tem from the list with a min value.
len(list): It gives the overall length of the list.
clear(): Removes all the elements from the list.
insert(): Adds ac o m p o n e n t atthe required position.
count(): Returns the number of elements with the required value.
pop(): Removes the element at the required position.
remove(): Removes the primary item with the desired value.
reverse(): Reverses the order of the list.
copy(): Returns a duplicate of the list.
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9.5.6 methods of dictionaries
values(): -Returns a list of all the values in the dictionary
clear() Removes all the elements from the dictionary
update: -Updates the dictionary with the specified key -value pairs
copy()Returns a copy of the dictionary
fromkeys()Returns a dictionary with the specified keys and value
get(): -Returns the value of the specified key
items(): -Returns a list containing a tuple for each key value pair
keys(): -Returns a list containing the dictionary's keys
pop(): -Removes the element with the specified key
popitem(): -Removes the last inserted key -value pair
setdefault(): -Returns the value of the specified key. If the key does not
exist: insert the key, with the specified value
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Questions:
1.State and explain any 5 string functions.
2.State and explain any 5 tuple functions.
3.State and explain any 5 list functions.
4.State and explain any 5 dictionary functions.
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