QBASIC Programming Solutions and SLC / SEE Computer Science Questions Solved Along PYTHON: 7. Programming Concept (Python)

7. Programming Concept (Python)

DOWNLOAD PDF

7.1 Introduction to programming languages

7.2 Types of programming languages

7.3 Programming tools: flowchart and algorithm

7.4 Introduction to coding, testing, and debugging

7.5 Compiler and interpreter

7.6 Introduction to python programming

7.7 Basic syntaxes

7.8 I/O statements and string formatting

7.9 Data types and variables

7.10 Concept of Type casting

7.11 Operators and expressions: Arithmetic, Relational, Logical, Assignment

7.12 Conditional statement (if, elseif, else)

7.13 Iteration (for and while)

7.14 List and Dictionary

7.15 Use library functions: String Functions (center, upper, lower, Len), Numeric and mathematical (sum, pow, round, abs, sqrt, Int)

7.1 Introduction to Programming Language

Programming Language

A programming language is a language used to write instructions that tell a computer to solve problems or perform specific tasks. Python, Java, PHP, C++, etc. are some examples of popular programming languages.

Programming

Programming is the process of providing step-by-step instructions to a computer to solve problems or perform specific tasks.

Programmer

A programmer is a person who writes computer programs using programming languages to solve problems or perform specific tasks.

Program

A program is a sequence of instructions that a computer executes to solve a problem or perform a specific task.

Syntax

Syntax is the set of rules that defines the correct structure of statements in a programming language.

7.2 Types of programming languages - High-level programming language and Low-level programming language

High-level programming language

A high-level programming language is a machine-independent language that uses English-like statements, making it easy for humans to write and understand programs, and it requires a compiler or interpreter to translate it into machine code. Examples: Python, Java, C++, PHP, JavaScript

Low-level programming language

A low-level programming language is a machine-dependent language that is very close to computer hardware and machine code. It is difficult for humans to understand but easy and fast for the computer to execute.

Types of low level programming language - Machine Level Language and Assembly Language.

Machine language is a low-level programming language which uses binary digits (0 and 1) that a computer can understand and execute directly without any translator.

Assembly language is a low-level programming language that uses mnemonics (e.g., MOV, ADD, SUB) instead of binary (0s and 1s), making it easier for humans to write programs, and it requires an assembler to translate it into machine language.

High level language Vs Low level language

Low-Level Language	High-Level Language
Difficult for humans to understand; close to hardware/machine code	Easy to understand; uses English-like statements
Machine dependent (not portable)	Machine independent (portable)
Machine language needs no translator; assembly language needs an assembler	Needs a compiler or interpreter
Examples: Machine language, Assembly language	Examples: Python, Java, JavaScript

7.3 Programming tools: Flowchart and Algorithm

Algorithm

An algorithm is a finite set of clear, step-by-step instructions designed to solve a specific problem or perform a particular task. It is written in simple language and generally begins with Start and ends with Stop.

Flowchart

A flowchart is a diagrammatic (graphical) representation of an algorithm, using standard symbols and arrows to show the sequence of steps and the flow of control in solving a problem.

Algorithm	Flowchart
A step-by-step written procedure to solve a problem	A graphical/diagrammatic representation of an algorithm
Written in simple language	Drawn using standard symbols and arrows
Easy to write but may be harder to visualize	Easy to understand visually
No symbols are used	Uses standard symbols (oval, rectangle, diamond, etc.)
Easy to modify steps	Modification can be time-consuming
Takes less space	Takes more space

The table below shows shapes used in flowchart and their meaning:

Shape	Name	Meaning / Use
Oval	Terminator	Indicates Start and Stop (End) of the flowchart
Rectangle	Process	Represents a processing step such as calculation or assignment
Parallelogram	Input / Output	Used for input (read data) or output (display result)
Diamond	Decision	Used for decision making with Yes/No or True/False paths
Arrow	Flow line	Shows the direction and sequence of steps
Circle (small)	Connector	Connects different parts of a flowchart (avoids long lines or connects pages)

7.4 Coding, testing and debugging

Coding

Coding is the process of writing instructions (code) in a programming language to create a computer program. These instructions tell the computer what tasks to perform.

Testing

Testing is the process of executing a program with different inputs to check whether it works correctly and produces the expected output.

Debugging

Debugging is the process of identifying, locating, and correcting errors (bugs) in a program after testing to ensure it runs correctly and smoothly.

7.5 Compiler and Interpreter

Compiler

A compiler is a translator program that converts the entire high-level program into machine language in a single operation before execution. Examples: C, C++, FORTRAN.

Interpreter

An interpreter is a translator program that translates and executes a high-level program into machine language one line at a time. Examples: Python, Ruby, QBasic, JavaScript.

Compiler	Interpreter
Translates the entire program at once	Translates one line at a time
Program is executed after complete compilation	Each line is translated and executed immediately
Generates object code	Does not generate object code
Shows all errors after compilation	Shows errors one by one and stops at error
Faster execution (after compilation)	Slower execution
Requires more memory	Requires less memory
C, C++, FORTRAN	Python, JavaScript, Ruby

Assembler

An assembler is a translator program that converts programs written in assembly language into machine code that the computer can understand and execute.

7.6 Introduction to Python Programming

Python

Python is a high-level, interpreted programming language introduced by Guido van Rossum in 1991.
It is easy to learn and uses simple English-like syntax, which makes it suitable for beginners.
Python is widely used in areas such as web development, artificial intelligence (AI), data science, and automation.
It has a large number of built-in libraries and strong community support, which makes program development faster and easier.
Python uses indentation instead of braces { } to define blocks of code, which improves readability and makes programs easier to understand.

Features of Python

Features of Python (Exam-Type, Topper Level)

a) Easy to Read and Write - Python uses simple, English-like syntax, which makes programs easy to understand and write.

b) Versatile - Python can be used in many fields such as web development, data science, artificial intelligence, automation, and game development.

c) Beginner-Friendly - Python is easy to learn, allowing beginners to start programming with less effort.

d) Extensive Standard Library - Python provides a large number of built-in modules and functions, reducing the need to write code from scratch.

e) Platform Independent - Python programs can run on different operating systems like Windows, macOS, and Linux without modification.

f) Huge Community Support - Python has a large community that offers tutorials, documentation, and online support, making problem-solving easier.

Advantages of Python

Python is simple and easy to learn, making it suitable for beginners.
It is cross-platform, meaning the same program can run on Windows, Linux, and macOS.
Python is free and open-source and supported by a large global community.
Python programs are shorter and faster to develop, which saves time and effort.
Python is widely used in modern fields such as artificial intelligence, data science, automation, and web development.

Disadvantages of Python

Python is slower than compiled languages like C, C++ and Java because it is interpreted.
It is not ideal for mobile application development, where languages like Java or Kotlin are preferred.
Python programs generally require more memory, making them less efficient for large or resource-intensive applications.
Due to dynamic typing, some errors are detected only at runtime, which may cause issues if not properly tested.

Installation Process of Python

Step 1: Download Python

Go to the official Python website: www.python.org
Click on Download Python and choose the latest version suitable for your operating system (Windows / macOS / Linux).

Step 2: Run the Installer

Open the downloaded setup file.
Important: Check the box “Add Python to PATH” (students forget this and then panic later).
Click Install Now.

📌 PATH means the system can find Python easily from anywhere.

Step 3: Complete Installation

Wait for the installation process to finish.
Click Close after successful installation.

Step 4: Verify Installation

Open Command Prompt (Windows) or Terminal (macOS/Linux).
Type:
python --version
If the Python version appears, installation is successful.

Step 5: Run Python

Type python in Command Prompt/Terminal to enter the Python interpreter.
You can now start writing and executing Python programs.

Download and Install a Suitable IDE for Python

An IDE (Integrated Development Environment) is software that helps write, run, and debug programs easily. For Python, some popular IDEs are IDLE, PyCharm, VS Code, Jupyter Notebook.

Download and Install VS Code for Python

VS Code (Visual Studio Code) is a popular, free, and lightweight code editor used for Python programming.

Step 1: Download VS Code

Go to the official website: https://code.visualstudio.com
Click Download and choose the version for your operating system
(Windows / macOS / Linux).

Step 2: Install VS Code

Open the downloaded setup file.
Click Next and follow the on-screen instructions.
Check “Add to PATH” (recommended).
Click Install and wait for completion.

Step 3: Launch VS Code

Open Visual Studio Code from the Start menu or desktop.

Step 4: Install Python Extension

In VS Code, click on the Extensions icon (left side).
Search for Python.
Install the extension by Microsoft.

📌 This extension enables Python syntax highlighting, debugging, and running programs.

Step 5: Verify Python Setup

Make sure Python is already installed on your computer.
Open Terminal inside VS Code.
Type:
python --version
If the version appears, Python is ready to use.

Step 6: Run a Python Program

Create a new file and save it with .py extension.
Write Python code and click Run.

7.7 Basic Syntaxes in Python

Python syntax refers to the rules for writing Python programs correctly.

1) Indentation

Python uses indentation (spaces) to define blocks of code.
Curly braces { } are not used.

Example:

if a > b:

print("a is greater")

📌 Important: Wrong indentation = error.

2) Comments

Comments are used to explain code.
Python uses # for single-line comments.

Example:

# This is a comment

print("Hello")

3) Case Sensitivity

Python is case-sensitive.
name and Name are treated as different variables.

📌 Small letter, capital letter — Python notices everything.

4) Statements

Python statements usually end without semicolons (;).
One statement is written per line.

Example:

x = 10

y = 20

5) Variables

Variables are used to store data.
No need to declare data type explicitly.

Example:

x = 5

name = "Python"

6) Print Statement

print() is used to display output.

Example:

print("Hello World")

7) Input Statement

input() is used to take input from the user.

Example:

name = input("Enter name: ")

Comments in Python

Comments in Python are notes written using # or triple quotes to explain the code, and they are ignored by the Python interpreter.

Why Comments Are Used?

To explain code
To make programs easier to understand
To help debugging
To leave notes for other programmers

Types of Comments in Python

Single-line Comment - Begins with #.

Example:

# This is a single-line comment

print("Hello, World!") # This prints a message

Multi-line Comment - Written inside triple quotes ''' ''' or """ """.

Useful for writing long explanations or documentation.
Example:

'''This is a

multi-line

comment in Python'''

print("Welcome")

Keywords

Keywords are reserved words in Python that have special meanings and cannot be used as variable names, function names, or identifiers.

Python 3 has more than 35 keywords, which are reserved words such as if, else, while, def, class, True, False, and None, and they cannot be used as variable or function names.

7.8 I/O statements and string formatting

Input/Output statements (I/O)

I/O stands for Input and Output. Input statements are used to take data from the user, and output statements are used to display results.

Input Statement - input() is used to take input from the user.

Example: name = input("Enter name: ")

Output Statement - print() is used to display output.

Example: print(name)

String Formatting -String formatting is used to display variables along with strings in a proper format.

Different Ways of String Formatting

Using % Operator (Old Style) - This is the old style of string formatting, where we use % to insert values into a string.

Example:

name = "Charlie"

age = 22

message = "My name is %s and I am %d years old." % (name, age)

print(message)

Output - My name is Charlie and I am 22 years old.

Using format( ) Method (New-style formatting) - The format( ) method allows to insert values into a string using curly braces {} as placeholders.

Example 1:

name = "Bob"

age = 30

message = "My name is {} and I am {} years old.".format(name, age)

print(message)

Output

My name is Bob and I am 30 years old.

We can also use numbered or named placeholders

Example 2:

message = "My name is {0} and I am {1} years old.".format(name, age)

print(message)

Using commas in print( ) - Simple and beginner-friendly. Easiest method but adds spaces automatically.

Example:

name = "Alex"

age = 15

print("My name is", name, "and I am", age, "years old.")

Output:

My name is Alex and I am 15 years old.

Formatted string literals (Using f-strings - modern and easiest)

This is the most widely used method in string formatting in the current time. In formatted string literal we use ‘f’ before the string and embedding expressions inside { }. It is the most popular method of using string format. It was introduced in Python 3.6.

Example 1:

name = "Alice"

age = 25

message = f"My name is {name} and I am {age} years old."

print(message)

Output

My name is Alice and I am 25 years old.

7.9 Data types and variables

Data type

Data types are categories of data that specify the type of value a variable can store. In Python, the data type is automatically assigned to a variable when a value is stored in it.

Python supports several data types:

int (Integer) - Stores whole numbers without decimals. Example: 10, -25
float (Floating point) - Stores decimal numbers. Example: 3.14, -0.5
str (String) - Stores text or characters enclosed in single or double quotes. Example: "Hello", 'Python'
bool (Boolean) - Stores logical values True or False. It is often used in decision-making statements. Example: is_pass = True
List - Stores multiple values in a single variable using square brackets [ ].
Example: fruits = ["apple", "banana", "mango"]
Dictionary (dict) - Stores data in key–value pairs using curly braces { }.
Example: student = {"name": "Ram", "age": 14}

Identifier

An identifier is the name given to variables, functions, classes, or any other user-defined items in Python. It is used to identify different parts of a program.

Rules for Identifiers / variables in Python

An identifier must begin with a letter (A–Z or a–z) or an underscore (_).
It cannot start with a number.
It can contain letters, digits, and underscores only (e.g., student_1).
Keywords like if, else, class, def cannot be used as identifiers.
Python identifiers are case-sensitive (name, Name, and NAME are different).
Spaces are not allowed in identifiers.

Valid Identifiers - A1, B34, First_Name, x_1

Invalid Identifiers - 1A, 34BA, 198, int, first-name, def

Variables in Python

A variable is a named memory location used to store data in a program, and its value can change during program execution.

Variable Name	Data Type	Description	Python Representation
age	Integer (int)	Stores an integer value 15	age = 15
height	Float (float)	Stores a decimal value 5.7	height = 5.7
fname	String (str)	Stores a string value "Sanjog"	fname = "Sanjog"
is_student	Boolean (bool)	Stores a Boolean value True	is_student = True

7.10 Concept of Type Casting

Type Casting (Type Conversion)

Type casting is the process of converting one data type into another, such as converting strings into integers or floats in Python.

Types of casting

· Implicit casting

· Explicit casting

Implicit casting

Implicit casting is the automatic conversion of one data type into another by Python when necessary, without the programmer doing anything.

Examples:

x = 10 # integer

y = 5.5 # float

z = x + y # the integer ‘x’ is cast to a float for the addition.

print(z)

Explicit casting

Explicit casting is the manual conversion of one data type into another using functions like int(), float(), and str().

Common Casting Functions in Python

· int(): Converts a value to an integer.

· float(): Converts a value to a float.

· str(): Converts a value to a string.

· bool(): Converts a value to a boolean (True or False).

Example:

int(x): Converts x to an integer.

x = 3.14

y = int(x) # Converts float to int (removes decimal part)

print(y) # Output: 3

x = 25

y = str(x) # Converts integer to string

print(y) # Output: "25"

7.11 Operators and Expressions: Arithmetic, Relational, Logical, Assignment

Operators

An operator in Python is a symbol that is used to perform a specific operation on one or more operands to produce a result.

Example: 5 + 3

+ → operator
5, 3 → operands

Result → 8

Operands

Operands are the values, variables, or constants on which an operator performs an operation. For example, in x + y, the operands are x and y, while + is the operator.

Example: add = 5 + 3

Here, ‘5’ and ‘3’ are operands and ‘+’ is an operator, and it is performing an ‘addition’ operation.

Arithmetic Operators

An arithmetic operator in Python is a symbol that is used to perform basic mathematical operations such as addition, subtraction, multiplication, division, floor division, modulus, and exponentiation on numeric operands and returns a numeric result.

List of Arithmetic Operators

Operator	Name	Example	Result
+	Addition	10 + 3	13
-	Subtraction	10 - 3	7
*	Multiplication	10 * 3	30
/	Division	10 / 3	3.33
//	Floor Division	10 // 3	3
%	Modulus	10 % 3	1
**	Exponentiation	2 ** 3	8

Example:

Simple program to find the sum of the two number for the user input

num1 = float(input(“Enter first number: “))

num2 = float(input(“Enter second number: “))

sum = num1 + num2

print(“The sum of {0} and {1} is {2}”.format(num1, num2, sum))

Relational operator

A relational operator in Python is an operator used to compare two values and return a Boolean result, that is True or False.

List of Relational Operators

Operator	Meaning	Example	Result
>	Greater than	5 > 3	True
<	Less than	5 < 3	False
>=	Greater than or equal to	5 >= 5	True
<=	Less than or equal to	3 <= 5	True
==	Equal to	5 == 3	False
!=	Not equal to	5 != 3	True

Logical operator

A logical operator in Python is an operator used to combine two or more conditions and return a Boolean result, that is True or False. There are 3 main logical operators, ‘and’, ‘or’, and ‘not’.

Operator	Name	Meaning
and	Logical AND	True if both conditions are True
or	Logical OR	True if at least one condition is True
not	Logical NOT	Reverses the result

AND Operator

The AND operator in Python is a logical operator that returns True only when all the given conditions are True; otherwise, it returns False.

Example: x = (5<2) and (5>3)

Result: False

Truth Table for ‘and’ Operator

Condition A	Condition B	Result (A and B)
True	True	True
True	False	False
False	True	False
False	False	False

OR Operator

The OR operator in Python is a logical operator that returns True if at least one of the given conditions is True; it returns False only when all conditions are False.

Example: (5<2) or (5>3)

Result: True’

Truth Table for ‘or’ Operator

Condition A	Condition B	Result(A or B)
True	True	True
True	False	True
False	True	True
False	False	False

NOT Operator

The NOT operator in Python is a logical operator that reverses the Boolean value of a condition, changing True to False and False to True.

Example: not(5<2)

Result: True

Truth Table for not Operator

Condition A	Result(not A)
True	False
False	True

Assignment operator

An assignment operator in Python is an operator used to assign or update the value of a variable by performing an operation and storing the result in the same variable.

List of Assignment Operators

Operator	Name	Example	Meaning
=	Assignment	a = 5	Assigns 5 to a
+=	Add and assign	a += 3	a = a + 3
-=	Subtract and assign	a -= 2	a = a - 2
*=	Multiply and assign	a *= 2	a = a * 2
/=	Divide and assign	a /= 2	a = a / 2
//=	Floor divide and assign	a //= 3	a = a // 3
%=	Modulus and assign	a %= 3	a = a % 3
**=	Power and assign	a **= 2	a = a ** 2

Expression

An expression in Python is a combination of variables, constants, and operators that is evaluated to produce a single value.

Example:

x = 10

y = 5

z = x + y # arithmetic expression

print(z) # 15

x + y → is an expression.

The result is 15.

Other examples:

10 > 5 → relational expression → result: True
(5 > 3) and (2 < 7) → logical expression → result: True

Algebraic Expression (Maths)	Python Expression (Code)	Meaning / Example
( x + y )	x + y	Addition of two numbers
( x - y )	x - y	Subtraction of two numbers
( x × y )	x * y	Multiplication
x/y	x / y	Division (float result)
x\y	x // y	Floor division (quotient only)
( x mod y )	x % y	Modulus (remainder)
( x^y )	x ** y	Exponent (power)

Exam Tip:

In algebra, we use symbols like × and ^.
In Python, we use * for multiplication and ** for exponent.

7.12 Conditional statement (if, elif, else)

A conditional statement in Python is a control structure used for decision making. It allows a program to test a condition and execute a block of code if the condition is True, and optionally execute another block of code if the condition is False. The main conditional statements in Python are if, if–else, and if–elif–else.

For example:

if age >= 18:

print("Eligible to vote")

else:

print("Not eligible")

Types of Conditional Statements in Python

if statement - → Executes a block of code when a condition is True.

Syntax:

if condition:

# Code to execute if condition is true

Example:

age = 18

if age >= 18:

print("You are eligible to vote")

if–else statement - → Executes one block if the condition is True, otherwise executes another block.

Syntax:

if condition:

# Code to execute if condition is true

else:

# Code to execute if condition is false

Example:

age = 16

if age >= 18:

print("You can vote")

else:

print("You cannot vote")

if–elif–else statement: → Tests multiple conditions and executes the block of the first True condition.

Syntax:

if condition1:

# Code to execute if condition1 is true

elif condition2:

# Code to execute if condition2 is true

else:

# Code to execute if none of the conditions are true

Example:

Checking the number’s category, whether it is positive, negative or zero.

user_number = int(input(“Enter a number: “))

if user_number > 0:

print(“The number is positive.”)

elif user_number == 0:

print(“The number is zero.”)

else:

print(“The number is negative.”)

Nested if Statements: A nested if statement in Python is a conditional statement in which one if statement is placed inside another if or else block to test multiple conditions.

Syntax:

if condition1:

#code to be executed if condition1 is True

if condition2:

#code to be executed if condition 2 is True

else:

#code to be executed when condition2 is False

else:

#code to be executed when condition1 and condition2 are False

Example:

age = int(input(“Enter your age: “))

if age >= 16:

print(“You are eligible for citizenship.”)

if age >= 18:

print(“You are eligible to cast a vote.”)

else:

print(“You are not eligible to cast vote.”)

else:

print(“You are a minor.”)

7.13 Iteration (for and while)

Iteration in Python is the process of repeatedly executing a block of code as long as a given condition is True. It is also called a loop.

The two main types are for loop (used when the number of iterations is known) and while loop (used when iterations depend on a condition). For example, for i in range(5): print(i) prints numbers from 0 to 4.

Types of iterations

· for loop

· while loop

For Loop

A for loop in Python is an iteration statement used to repeat a block of code for each element in a sequence such as a list, string, or range. It is mostly used when the number of repetitions is known.

Syntax:

for variable in sequence:

# Code to execute

Example:

# Iterating over a range of numbers from 0 to 4

for i in range(5):

print(i)

Example:

#Using for loop to print “jump” five times

for x in range(5):

print(“Jump!”)

Example:

# Iterating over a list

fruits = ["apple", "banana", "cherry"]

for fruit in fruits:

print(fruit)

While Loop

A while loop in Python is an iteration statement that repeats a block of code as long as a given condition remains True. It is mainly used when the number of iterations is not known in advance.

Syntax:

while condition:

# Code to execute

Example:

# Using while loop to print numbers from 0 to 4

i = 0

while i < 5:

print(i)

i += 1 # Incrementing the value of i to avoid infinite loop

Example 2 (infinite loop warning!):

while True:

print("This will run forever!")

Example 3:

x = 1

while x <= 5:

print(x)

x += 1

# prints numbers from 1 to 5.

Difference between for loop and while loop

for loop	while loop
Used when the number of iterations is known	Used when the number of iterations is not known
Iterates over a sequence (list, string, range)	Repeats based on a condition
Loop variable is automatically updated	Loop variable must be updated manually
Syntax is short and clean	Syntax is more flexible
Less chance of infinite loop	Higher chance of infinite loop
Example: for i in range(5):	Example: while i < 5:

pass Statement

The pass statement in Python is a null statement that does nothing and is used as a placeholder where a statement is syntactically required but no action is needed. For example, if x > 5: pass allows the program to run without producing an error even though the block is empty.

The pass statement in Python is a null statement.

Syntax:

if condition:

# Some code here

else:

pass # Nothing happens in the “else” case

Example:

for i in range(5):

if i == 2:

pass # Do nothing if i is 2

else:

print(i)

Output:

In this example, when i is equal to 2, the pass statement is executed, which does nothing, so the loop continues without printing 2.

continue Statement

The continue statement in Python is a loop control statement that skips the remaining code of the current iteration and immediately moves to the next iteration of the loop. For example, in a loop from 1 to 5, if continue is used when i == 3, the number 3 will be skipped from the output.

Example:

for i in range(5):

if i == 2:

continue # Skip the rest of the code when i is 2

print(i)

Output:

Here, when i == 2, the continue statement skips the print(i) and moves to the next iteration of the loop, so 2 is not printed.

break Statement

The break statement in Python is a loop control statement that terminates the loop immediately when it is encountered, and the control moves to the statement following the loop. For example, in a loop from 1 to 5, if break is used when i == 3, the loop will stop after printing 1 and 2.

Example:

for i in range(5):

if i == 3:

break # Exit the loop when i is 3

print(i)

Output:

In this case, when i == 3, the break statement causes the loop to terminate, and no further numbers are printed.

Comparison Table: break, continue, and pass

Feature	break	continue	pass
Type	Loop control statement	Loop control statement	Null statement
Function	Terminates the loop completely	Skips current iteration	Does nothing
Effect on loop	Loop ends immediately	Loop continues	Loop unaffected
Use in loops	Yes	Yes	Yes
Use outside loops	No	No	Yes
Purpose	Exit loop early	Skip unwanted iteration	Placeholder
Common use	Stop searching	Ignore certain values	Empty block

7.14 Lists and Dictionary

Python list

A list in Python is an ordered, mutable collection of elements that can store multiple values of different data types in a single variable. A list can store numbers, strings, or even mixed data types. Lists are indexed, meaning each item has a position starting from 0.

Features of Lists

Ordered → Elements have a fixed position (index) (index starts from 0).
Mutable → Values can be changed after creation
Can hold mixed data types (numbers, strings, booleans).
Allows duplicate values.

1. Creating a List

Using square brackets:

numbers = [1, 2, 3, 4, 5]

fruits = ["apple", "banana", "cherry"]

mixed = [1, "apple", 3.14, True]

empty = []

Using the list() constructor:

thislist = list(("apple", "banana", "cherry"))

2. Accessing Elements

Lists use indexing (starts at 0).

print(fruits[0]) # apple

print(fruits[-1]) # cherry (last element)

3. Modifying a List

Lists are mutable → items can be changed, added, or removed.

numbers[0] = 10

fruits.append("orange") # add at end

fruits.insert(1, "grape") # insert at position

fruits.remove("banana") # remove by value

removed = fruits.pop(2) # remove by index

4. List Length

print(len(fruits)) # number of elements

5. Looping Through a List

for fruit in fruits:

print(fruit)

6. List Slicing

fruits = ["apple", "grape", "cherry", "orange"]

print(fruits[1:3]) # ['grape', 'cherry']

print(fruits[:2]) # ['apple', 'grape']

print(fruits[2:]) # ['cherry', 'orange']

7. Concatenation & Repetition

list1 = [1, 2, 3]

list2 = [4, 5, 6]

print(list1 + list2) # [1,2,3,4,5,6]

print(list1 * 2) # [1,2,3,1,2,3]

8. List Comprehension

squares = [x**2 for x in range(5)]

print(squares) # [0, 1, 4, 9, 16]

evens = [x for x in range(10) if x % 2 == 0]

print(evens) # [0, 2, 4, 6, 8]

9. Nested Lists

nested = [1, [2, 3], 4, [5, 6]]

print(nested[1]) # [2, 3]

print(nested[1][0]) # 2

10. Common List Methods

Method	Use
append(x)	Add item at end
insert(i,x)	Insert at index
remove(x)	Remove item by value
pop(i)	Remove item by index
sort()	Sort list ascending
reverse()	Reverse list order
clear()	Remove all items

Python Dictionary

A dictionary in Python is an unordered, mutable collection of data that stores elements in the form of key–value pairs, written inside curly braces { }. Each element has a key and its associated value, and values are accessed using the keys.

1. Creating a Dictionary

# Syntax

my_dict = {key1: value1, key2: value2, key3: value3}

# Example

fruit_colors = {"apple": "red", "banana": "yellow", "cherry": "red"}

2. Accessing Values

print(fruit_colors["apple"]) # red

print(fruit_colors.get("orange", "Not found")) # Not found

3. Adding or Modifying Items

fruit_colors["orange"] = "orange" # Add new

fruit_colors["banana"] = "green" # Modify existing

4. Removing Items

del fruit_colors["cherry"] # delete by key

removed = fruit_colors.pop("apple") # removes and returns value

print(removed) # red

5. Dictionary Properties

Unordered → items have no fixed order.
Mutable → items can be added, changed, or deleted.
Keys must be unique.
Values can be of any data type.

6. Dictionary Methods

Method	Description
keys()	Returns all keys
values()	Returns all values
items()	Returns all key–value pairs
update()	Merges another dictionary
clear()	Removes all items
pop(key)	Removes and returns value by key
popitem()	Removes last inserted item

7. Dictionary Length

print(len(fruit_colors)) # Number of key–value pairs

8. Looping through a Dictionary

for key, value in fruit_colors.items():

print(key, ":", value)

9. Dictionary Comprehension

squares = {x: x**2 for x in range(5)}

print(squares) # {0:0, 1:1, 2:4, 3:9, 4:16}

10. Nested Dictionaries

students = {

"John": {"age": 25, "grade": "A"},

"Anna": {"age": 22, "grade": "B"}

}

print(students["Anna"]["grade"]) # B

11. Merging Dictionaries

dict1 = {"apple": "red", "banana": "yellow"}

dict2 = {"cherry": "red", "orange": "orange"}

dict1.update(dict2) # merge into dict1

Difference between List and Dictionary in Python

List	Dictionary
Ordered collection of elements stored inside square brackets [ ].	Unordered collection of key–value pairs stored inside curly braces { }.
Elements are accessed using index numbers (starting from 0).	Elements are accessed using keys.
Single collection of values.	Collection of key–value pairs.
Mutable (elements can be changed).	Mutable (items can be added, changed, or removed).
Allows duplicate elements.	Keys must be unique (values may repeat).
fruits = ["apple", "banana", "cherry"]	fruit_colors = {"apple": "red", "banana": "yellow"}

Features of List in Python

A list is an ordered collection of items.
Lists are created using square brackets [ ].
Lists support indexing and slicing, and indexing starts from 0.
Lists are mutable, which means elements can be changed after creation.
A list can store different data types such as numbers and strings in a single list.
Lists allow duplicate elements.
Lists support useful methods such as append(), insert(), remove(), sort(), etc.

Features of Dictionary in Python

A dictionary is an unordered collection of key–value pairs.
Dictionaries are created using curly braces { }.
Elements are accessed using keys, not index numbers.
Keys must be unique, but values can be repeated.
Dictionaries are mutable, which means key–value pairs can be added, modified, or removed.
A dictionary can store values of different data types.
Dictionaries support useful methods such as keys(), values(), items(), update(), pop(), etc.

7.15 Uses of Library functions : String Functions (center, upper, lower, Len), Numeric and mathematical (sum, pow, round, abs, sqrt, Int)

Function

A function in Python is a block of reusable code that performs a specific task and is executed only when it is called.

Types of Functions

1. Built-in Functions

Built-in functions are the functions that are already defined in Python and can be used directly without creating them.

Examples:

len() → returns length of a list or string
sum() → adds all numbers in a list
print() → displays output

numbers = [1, 2, 3]

print(len(numbers)) # 3

print(sum(numbers)) # 6

2. User-defined Functions

User-defined functions are the functions that are created by the programmer to perform a specific task and can be reused whenever required.

Example:

def square(x):

return x * x

print(square(4)) # 16

Difference between Built-in and User-defined Functions

Built-in Functions	User-defined Functions
Predefined functions that come with Python.	Functions created by the programmer using the def keyword.
Always available to use directly.	Available only after being defined in the program.
Saves time since no coding is required.	Gives flexibility to design your own logic.
print(), len(), sum(), abs().	def add(a, b): return a+b, def square(x): return x*x.

Library function

A library function in Python is a predefined function that is stored in a module (library) and can be used by importing that module into a program. They are used by importing the library and help programmers perform common tasks without writing code from scratch.

Example:

import math

print(math.sqrt(16))

String Function

String functions in Python are built-in methods used to perform operations on strings, such as changing case, searching text, and modifying content.

center(width, fillchar): Centers the string within the given width, padding it with a specified character (default is a space).

Example:

text = "Hello"

print(text.center(10, "*")) # Output: '**Hello***'

upper( ): Converts string to uppercase.

Example:

text = "hello"

print(text.upper( )) # Output: 'HELLO'

lower( ): Converts string to lowercase.

Example:

text = "hello"

print(text.lower( )) # Output: 'hello'

len(): Returns length of the string. (i.e., the number of characters).

Example:

text = "Hello"

print(len(text)) # Output: 5

Numeric Functions

Numeric functions in Python are built-in functions used to perform operations on numeric values such as finding maximum, minimum, absolute value, power, and type conversion.

sum(iterable): Returns the sum of all elements in an iterable (e.g., a list).

Example:

numbers = [1, 2, 3, 4, 5]

print(sum(numbers)) # Output: 15

abs(x): Returns the absolute value of a number.

Example:

print(abs(-5)) # Output: 5

print(abs(3.5)) # Output: 3.5

round(x, n): Rounds a number x to n decimal places (default is 0).

Example:

print(round(3.14159, 2)) # Output: 3.14

print(round(3.5)) # Output: 4

pow(x, y): Returns x raised to the power of y (i.e., x^y).

Example:

print(pow(2, 3)) # Output: 8 (2^3)

int(x): Converts a number or string to an integer.

Example:

print(int(3.7)) # Output: 3

print(int("42")) # Output: 42

min( ) and max( )Function: Returns the smallest (minimum) or largest(maximum) value from the given iterable or from multiple values passed as arguments.

Example:

numbers = [3, 1, 4, 1, 5, 9, 2, 6]

print(min(numbers)) # Output: 1

Mathematical Functions (from math module)

Mathematical functions are predefined functions provided by Python in the math module to perform advanced mathematical operations such as square root, power, trigonometry, and rounding.

math.sqrt(x): Returns the square root of x.

Example:

import math

print(math.sqrt(16)) # Output: 4.0

math.factorial(x) : Returns the factorial of a number x (i.e., x! = x * (x - 1) * (x - 2) * ... * 1).

Example:

import math

print(math.factorial(5)) # Output: 120 (5! = 5 * 4 * 3 * 2 * 1)

math.pi : Provides the mathematical constant π (approximately 3.14159).

Example:

import math

print(math.pi) # Output: 3.141592653589793

math.sin(x) and math.cos(x): Return the sine and cosine of x (where x is in radians).

Example:

import math

print(math.sin(math.radians(30))) # Output: 0.5

print(math.cos(math.radians(60))) # Output: 0.5

math.log(x, base): Returns the logarithm of x to the given base. If the base is not specified, it returns the natural logarithm (base e).

Example:

import math

print(math.log(10)) # Output: 2.302585092994046 (natural log of 10)

print(math.log(100, 10)) # Output: 2.0 (logarithm base 10 of 100)

QBASIC Programming Solutions and SLC / SEE Computer Science Questions Solved Along PYTHON

Thursday, January 1, 2026

7. Programming Concept (Python)

No comments:

Post a Comment