Python Notes

Presenter

Rashid Hussain, PhD
Bioinformatician, Ayass Bioscience, USA
Web: rashid-bioinfo.github.io

Introduction

In the modern world, computers are everywhere — from smartphones and laptops to self-driving cars and smart appliances. But have you ever wondered how these machines know what to do?

The answer lies in programming.

Programming is the fundamental way through which we communicate with computers. Since computers do not understand human language naturally, we use programming languages to write instructions that computers can interpret and execute.

Without programming, computers would be useless pieces of hardware.

This chapter sets the stage for understanding what programming is and why it’s one of the most valuable skills in today’s digital world.

What is Programming?

Programming is the process of writing a set of instructions that a computer follows to perform a specific task. These instructions are written in programming languages like Python, C++, Java, etc.

Think of programming like writing a recipe. Just as a recipe contains step-by-step instructions for cooking a dish, a program contains step-by-step commands for the computer to execute.

Why is Programming Important?

A Simple Example

Here’s a very basic example of programming using Python — one of the most beginner-friendly programming languages:

a = 5
b = 7
print("The sum is:", a + b)

Output:

The sum is: 12

This simple program:

  1. Stores the value 5 in the variable a.
  2. Stores the value 7 in the variable b.
  3. Adds them together and prints the result.

Even though this is a small example, the same principles apply when you’re building more complex systems — like a web browser or a mobile app.

Real-World Applications of Programming

Summary

💡 Tip: Don’t worry if this feels overwhelming. Every great programmer started with the basics — one line of code at a time!

Chapter 1 - Modules, Comments and pip

In Python, code organization, readability, and reuse are essential. This chapter explores three important tools that help with these goals: Modules, Comments, and pip.

Modules

A module is a file containing Python definitions and statements. Modules allow you to organize code into separate files, making it more manageable and reusable.

Creating and Using a Module

You can create your own module by simply saving Python code in a .py file. For example, create a file called mymodule.py:

def greet(name):
    return f"Hello, {name}!"

You can use this module in another Python script by importing it:

import mymodule

print(mymodule.greet("Alice"))

Standard Library Modules

Python comes with a large collection of built-in modules like math, random, datetime, etc.

import math

print(math.sqrt(25))  # Output: 5.0

Comments

Comments help make code easier to understand. Python ignores comments during execution.

Single-line Comments

Start with #:

## This is a comment
x = 10  # This is an inline comment

Multi-line Comments

There’s no official multi-line comment syntax in Python, but you can use multi-line strings for block comments:

"""
This is a multi-line comment.
Python will ignore this as long as it's not assigned to a variable.
"""

pip – Python Package Installer

pip is a package manager used to install and manage external Python libraries that are not part of the standard library.

Installing a Package

pip install package_name

Example:

pip install requests

Using an Installed Package

import requests

response = requests.get("https://api.github.com")
print(response.status_code)

Listing Installed Packages

pip list

Uninstalling a Package

pip uninstall package_name

Summary

🧠 Tip: Mastering these tools will make your coding more professional and scalable!

Chapter 2 - Variables and Datatypes

Variables are used to store information in a program, and data types define what kind of data a variable holds.

Variables in Python

In Python, variables are created when you assign a value to them. You don’t need to declare their type.

Example

x = 10        # Integer
name = "Bob"  # String
price = 19.99 # Float

Python is dynamically typed, so you can change the type of a variable later:

x = 10
x = "Now I am a string"

Rules for Naming Variables

–>

Datatypes in Python

Python has several built-in data types. The most common are:

Numeric Types

a = 10       # int
b = 10.5     # float
c = 2 + 3j   # complex

String Type

message = "Hello, World!"

Boolean Type

is_active = True
is_logged_in = False

List Type

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

Tuple Type

coordinates = (10, 20)

Dictionary Type

student = {"name": "Alice", "age": 22}

Set Type

unique_numbers = {1, 2, 3}

Type Checking

You can check the type of any variable using type():

x = 42
print(type(x))  # Output: <class 'int'>

Summary

🧪 Practice Questions

Q1. What will be the output of the following code?

x = 5
x = "Hello"
print(x)

a) 5
b) Hello
c) Error
d) None

Q2. Which of the following is a valid variable name in Python?

a) 1name
b) my-name
c) my_name
d) class

Chapter 3 - Strings

Strings are sequences of characters used to store and represent text in Python. They are one of the most commonly used data types.

Creating Strings

Strings in Python can be created using single quotes ', double quotes ", or triple quotes ''' / """.

str1 = 'Hello'
str2 = "World"
str3 = '''This is
a multi-line string'''

String Indexing and Slicing

You can access characters in a string using indexing and extract parts of strings using slicing.

text = "Python"

print(text[0])    # Output: 'P'
print(text[-1])   # Output: 'n'

print(text[1:4])  # Output: 'yth'
print(text[:3])   # Output: 'Pyt'
print(text[3:])   # Output: 'hon'

String Methods

Python provides many built-in methods for string manipulation.

s = "hello world"

print(s.upper())         # HELLO WORLD
print(s.capitalize())    # Hello world
print(s.title())         # Hello World
print(s.count('l'))      # 3
print(s.replace('world', 'Python'))  # hello Python

String Formatting

There are three ways to format strings in Python.

Old Style

name = "Alice"
print("Hello %s" % name)

str.format()

print("Hello, {}".format("Bob"))

f-Strings (Python 3.6+)

name = "Charlie"
print(f"Hello, {name}")

Escape Characters

Escape characters are used to insert characters that are illegal in a string.

print("He said \"Hello\"")  # He said "Hello"
print("Line1\nLine2")          # Line1
Line2

Useful String Operations

### Checking membership
print("Py" in "Python")  # True

### Joining strings
words = ["Python", "is", "fun"]
print(" ".join(words))   # Python is fun

### Splitting strings
sentence = "one,two,three"
print(sentence.split(','))  # ['one', 'two', 'three']

Summary

🧪 Practice Questions

Q1. What is the output of the following code?

x = "Python"
print(x[2:5])

a) tho  
b) yth  
c) tho  
d) ytho

Q2. Which of the following is the correct way to join this list into a string with commas?

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

a) "+".join(words)  
b) " ".join(words)  
c) ",".join(words)  
d) "join".words(',')

Chapter 4 - Lists and Tuples

Lists and tuples are data structures used to store multiple values in a single variable. Both are sequence types, meaning their elements are ordered and can be accessed by index.

Lists

A list is a mutable (changeable) ordered collection of items. Lists are defined using square brackets [].

Creating Lists

fruits = ["apple", "banana", "cherry"]
numbers = [1, 2, 3, 4, 5]
mixed = ["Alice", 25, True]

Accessing List Elements

print(fruits[0])      # Output: apple
print(fruits[-1])     # Output: cherry

Modifying Lists

fruits[1] = "blueberry"
print(fruits)         # ['apple', 'blueberry', 'cherry']

List Methods

fruits.append("orange")       # Add item to the end
fruits.insert(1, "kiwi")      # Insert at index
fruits.remove("apple")        # Remove specific item
popped = fruits.pop()         # Remove and return last item
print(fruits.index("kiwi"))   # Find index of item
print(len(fruits))            # Length of the list

Iterating Through a List

for fruit in fruits:
    print(fruit)

Tuples

A tuple is an immutable (unchangeable) ordered collection of items. Tuples are defined using parentheses ().

Creating Tuples

coordinates = (10, 20)
colors = ("red", "green", "blue")

Accessing Tuple Elements

print(coordinates[0])  # Output: 10

Tuple Unpacking

x, y = coordinates
print(x)  # Output: 10
print(y)  # Output: 20




## Key Differences: List vs Tuple

| Feature       | List        | Tuple        |
|---------------|-------------|--------------|
| Syntax        | `[]`        | `()`         |
| Mutable       | Yes         | No           |
| Methods       | Many        | Fewer        |
| Performance   | Slower      | Faster       |

-->

## Summary

- **Lists** are ordered, mutable collections.
- **Tuples** are ordered, immutable collections.
- Use lists when you need to modify data, and tuples when the data should remain constant.



## 🧪 Practice Questions

#### Q1. What will be the output of the following code?

```python
fruits = ["apple", "banana", "cherry"]
fruits[1] = "kiwi"
print(fruits)

a) ['apple', 'kiwi', 'cherry']  
b) ['apple', 'banana', 'cherry']  
c) ['kiwi', 'banana', 'cherry']  
d) Error

Q2. Which of the following defines an immutable collection?

a) mydata = [1, 2, 3]  
b) mydata = {1, 2, 3}  
c) mydata = (1, 2, 3)  
d) mydata = {"a": 1, "b": 2}

Chapter 5 - Dictionary and Sets

Dictionaries and sets are two important built-in data types in Python used to store collections of data.

Dictionaries

A dictionary is an unordered, mutable collection of key-value pairs. It is defined using curly braces {}.

Creating Dictionaries

student = {
    "name": "Alice",
    "age": 21,
    "major": "Computer Science"
}

Accessing and Modifying Values

print(student["name"])       # Output: Alice
student["age"] = 22
print(student["age"])        # Output: 22

Dictionary Methods

student["grade"] = "A"         # Add new key-value pair
print(student.get("major"))    # Safe access to a key
student.pop("grade")           # Remove key-value pair
print(student.keys())          # All keys
print(student.values())        # All values
print(student.items())         # All key-value pairs

Looping through a Dictionary

for key, value in student.items():
    print(key, ":", value)

–>

Sets

A set is an unordered collection of unique elements. Sets are also defined using curly braces {} but only hold values, not key-value pairs.

Creating Sets

numbers = {1, 2, 3, 4, 5}
duplicates = {1, 2, 2, 3}  # Will automatically remove duplicate 2

Set Operations

a = {1, 2, 3}
b = {3, 4, 5}

print(a.union(b))         # {1, 2, 3, 4, 5}
print(a.intersection(b))  # {3}
print(a.difference(b))    # {1, 2}

Modifying Sets

a.add(6)
a.remove(1)
a.discard(10)  # No error if element not found

Summary

🧪 Practice Questions

Q1. What is the output of the following code?

info = {"name": "Tom", "age": 30}
print(info.get("age"))

a) 30  
b) "age"  
c) Error  
d) None

Q2. What is the result of the following set operation?

a = {1, 2, 3}
b = {2, 3, 4}
print(a & b)

a) {1, 4}  
b) {2, 3}  
c) {1, 2, 3, 4}  
d) {2, 4}

Chapter 6 - Conditional Expressions

Conditional expressions are used to make decisions in Python programs. They allow a program to execute certain blocks of code based on whether a condition is true or false.

The if Statement

The if statement is used to execute a block of code if a condition is true.

age = 18

if age >= 18:
    print("You are eligible to vote.")

if-else Statement

The else block runs if the condition is false.

num = 10

if num % 2 == 0:
    print("Even number")
else:
    print("Odd number")

if-elif-else Chain

You can check multiple conditions using elif.

score = 85

if score >= 90:
    print("Grade: A")
elif score >= 80:
    print("Grade: B")
elif score >= 70:
    print("Grade: C")
else:
    print("Grade: F")

Nested Conditions

Conditions can be nested inside each other.

x = 15

if x > 10:
    if x < 20:
        print("x is between 10 and 20")

The Ternary Operator

Python supports a short form for if-else, called a ternary expression:

a = 5
b = 10

min_val = a if a < b else b
print("Minimum is:", min_val)

Boolean Expressions

You can combine multiple conditions using logical operators:

x = 5

if x > 0 and x < 10:
    print("x is a positive single-digit number")

if x == 5 or x == 10:
    print("x is either 5 or 10")

🧪 Practice Questions

Q1. What is the output of the following code?

x = 20

if x < 10:
    print("Small")
elif x < 30:
    print("Medium")
else:
    print("Large")

a) Small  
b) Medium  
c) Large  
d) Error

Q2. What is the result of the following expression?

a = 5
b = 7
print("Smaller" if a < b else "Greater")

a) Greater  
b) Smaller  
c) Error  
d) None

Chapter 7 - Loops in Python

Loops are used to execute a block of code repeatedly. Python supports two types of loops: for and while.

The while Loop

The while loop runs as long as a condition is True.

Example

i = 1

while i <= 5:
    print(i)
    i += 1

Loop Control Statements

Python provides three keywords to control the flow of loops:

break

Exits the loop prematurely.

for i in range(10):
    if i == 5:
        break
    print(i)

continue

Skips the current iteration.

for i in range(5):
    if i == 2:
        continue
    print(i)

else with Loops

The else block runs after the loop finishes naturally (not by break).

for i in range(3):
    print(i)
else:
    print("Loop completed")

–>

Nested Loops

You can use loops inside loops.

for i in range(1, 4):
    for j in range(1, 3):
        print(i, j)

Summary

–>

🧪 Practice Questions

Q1. How many times will “Python” be printed?

for i in range(3):
    print("Python")

a) 2  
b) 3  
c) 4  
d) Infinite

Q2. What is the output of this code?

i = 1
while i < 5:
    if i == 3:
        break
    print(i)
    i += 1

a) 1 2 3  
b) 1 2  
c) 1 2 3 4  
d) 1 2 3 4 5

Chapter 8 - Functions and Recursions

Functions are reusable blocks of code that perform a specific task. Recursion is a technique where a function calls itself to solve smaller instances of a problem.

Handling File Paths

Use raw strings (r"...") for Windows paths to avoid escape sequences.

file = open(r"C:\Users\Name\Documents\file.txt", "r")

Summary

🧪 Practice Questions

Q1. What will happen if you open a file in 'w' mode and write to it?

file = open("data.txt", "w")
file.write("Hello")
file.close()

a) Data is appended to the file  
b) Data is read from the file  
c) Existing data is preserved  
d) Existing data is deleted and new data is written

Q2. Which of the following ensures that a file is properly closed after reading?

a) close(file)  
b) file.close()  
c) using with open(...)  
d) open(file).read()

Chapter 10 - Object Oriented Programming

Object Oriented Programming (OOP) is a programming paradigm based on the concept of objects, which contain data and methods. Python supports OOP features such as classes, objects, inheritance, encapsulation, and polymorphism.

Classes and Objects

Defining a Class

class Person:
    def __init__(self, name, age):
        self.name = name
        self.age = age

    def greet(self):
        print(f"Hello, my name is {self.name} and I am {self.age} years old.")

Creating Objects

p1 = Person("Alice", 30)
p1.greet()  # Output: Hello, my name is Alice and I am 30 years old.

–>

The __init__ Method

The __init__ method is a special method that runs as soon as an object is created. It is commonly used to initialize object attributes.

Instance Variables and Methods

–>

Inheritance

Inheritance allows one class to inherit the attributes and methods of another.

class Animal:
    def speak(self):
        print("Animal speaks")

class Dog(Animal):
    def bark(self):
        print("Dog barks")

d = Dog()
d.speak()  # Inherited method
d.bark()   # Own method

Method Overriding

Child classes can override parent class methods.

class Animal:
    def speak(self):
        print("Animal speaks")

class Cat(Animal):
    def speak(self):
        print("Cat meows")

c = Cat()
c.speak()  # Output: Cat meows

–>

Encapsulation

Encapsulation restricts direct access to some of an object’s components.

class BankAccount:
    def __init__(self, balance):
        self.__balance = balance

    def get_balance(self):
        return self.__balance

The double underscore __ makes the variable private.

Summary

–>

🧪 Practice Questions

Q1. What will be the output of the following code?

class A:
    def __init__(self):
        print("A")

class B(A):
    def __init__(self):
        super().__init__()
        print("B")

b = B()

a) A  
b) B  
c) A B  
d) B A

Q2. Which of the following best defines encapsulation in OOP?

a) Grouping functions together  
b) Hiding data and providing access through methods  
c) Creating functions outside of class  
d) Overriding methods in subclasses

Chapter 11 - Inheritance

Inheritance is one of the core principles of Object Oriented Programming (OOP). It allows one class (child or derived class) to inherit attributes and methods from another class (parent or base class), promoting code reusability.

Basic Inheritance

Example

class Animal:
    def speak(self):
        print("Animal speaks")

class Dog(Animal):
    def bark(self):
        print("Dog barks")

d = Dog()
d.speak()  # Inherited from Animal
d.bark()   # Defined in Dog

–>

The super() Function

The super() function allows access to methods from the parent class.

class Animal:
    def __init__(self, name):
        self.name = name

    def speak(self):
        print(f"{self.name} makes a sound")

class Cat(Animal):
    def __init__(self, name):
        super().__init__(name)

    def speak(self):
        print(f"{self.name} meows")

c = Cat("Whiskers")
c.speak()  # Output: Whiskers meows

Multi-Level Inheritance

Inheritance can go more than one level deep.

class A:
    def show(self):
        print("Class A")

class B(A):
    pass

class C(B):
    pass

obj = C()
obj.show()  # Output: Class A

Multiple Inheritance

A class can inherit from multiple classes.

class Father:
    def skills(self):
        print("Gardening, Programming")

class Mother:
    def skills(self):
        print("Cooking")

class Child(Father, Mother):
    def skills(self):
        super().skills()
        print("Drawing")

c = Child()
c.skills()

–>

Summary

🧪 Practice Questions

Q1. What is the output of the following code?

class Parent:
    def show(self):
        print("Parent")

class Child(Parent):
    def show(self):
        print("Child")

c = Child()
c.show()

a) Parent  
b) Child  
c) Parent Child  
d) Error

Q2. Which of the following statements is TRUE about super()?

a) It creates a new class  
b) It initializes private variables  
c) It accesses methods from the base class  
d) It returns the child object

Chapter 12 - Exception Handling in Python

In Python, exceptions are errors that occur during the execution of a program. Exception handling allows you to manage these errors gracefully without crashing the program.

What is an Exception?

An exception is an unwanted event that can occur during program execution, such as dividing by zero or accessing a file that doesn’t exist.

–>

The try-except Block

The most common way to handle exceptions is using the try-except block.

try:
    x = 10 / 0
except ZeroDivisionError:
    print("Cannot divide by zero!")

Catching Multiple Exceptions

You can handle multiple types of exceptions.

try:
    num = int(input("Enter a number: "))
    result = 10 / num
except ValueError:
    print("Invalid input. Please enter a number.")
except ZeroDivisionError:
    print("Cannot divide by zero.")

–>

The else Block

The else block runs if no exceptions occur.

try:
    x = 5
    y = 2
    result = x / y
except ZeroDivisionError:
    print("Error: Division by zero")
else:
    print("Result is", result)

The finally Block

The finally block always runs, regardless of whether an exception occurred or not.

try:
    file = open("test.txt", "r")
except FileNotFoundError:
    print("File not found")
finally:
    print("Execution complete")

–>

Raising Exceptions

You can raise exceptions manually using raise.

age = -1
if age < 0:
    raise ValueError("Age cannot be negative")

🧪 Practice Questions

Q1. What is the output of this code?

try:
    print(1 / 0)
except ZeroDivisionError:
    print("Caught ZeroDivisionError")

a) 0  
b) 1  
c) Caught ZeroDivisionError  
d) Error

Q2. What does the finally block do in exception handling?

a) Runs only if an exception is raised  
b) Runs only if no exception is raised  
c) Always runs regardless of exceptions  
d) Prevents errors from occurring

Chapter 13 - Virtual Environment

A virtual environment in Python is a self-contained directory that contains a Python installation for a particular version, plus a number of additional packages. It helps to keep dependencies required by different projects separate.

Why Use Virtual Environments?

–>

Creating a Virtual Environment

Use the venv module to create a virtual environment:

python -m venv myenv

This creates a directory called myenv with a local Python interpreter and installation paths.

Activating the Virtual Environment

On Windows:

myenv\Scripts\activate

On macOS/Linux:

source myenv/bin/activate

Once activated, your shell prompt will change, indicating you’re inside the virtual environment.

–>

Installing Packages in Virtual Environment

You can now install packages using pip without affecting the global Python setup:

pip install requests

Deactivating the Virtual Environment

To deactivate and return to the global environment:

deactivate

–>

Deleting a Virtual Environment

Simply delete the virtual environment directory:

rm -r myenv  # or use File Explorer to delete on Windows

Summary

–>

🧪 Practice Questions

Q1. What is the command to create a virtual environment named env?

a) python create env  
b) python -m venv env  
c) pip venv install env  
d) virtualenv env create

Q2. What does the deactivate command do?

a) Deletes the virtual environment  
b) Uninstalls packages  
c) Exits the virtual environment  
d) Closes the terminal