Introduction to Python

Introduction to Python: Comprehensive Notes

1. Introduction to Python

• Invented By: Python was created by Guido van Rossum.
• Year: Python was first released in 1991.
• Usage: Python is widely used in web development, data science, artificial intelligence, automation, and more.
• Why Python?
• Readability: Simple and clean syntax.
• Community Support: Extensive libraries and frameworks.
• Versatility: Used in various domains like web development, data science, etc.

2. Python Syntax

• Indentation: Python uses indentation (spaces or tabs) to define blocks of code.
• Example:

if True:
print(“This is indented”)

• Comments:
  Single-line:Use # for single-line comments.
  Multi-line: Use triple quotes (”’ or “””) for multi-line comments.

• Example:

# This is a single-line comment
“””
This is a
multi-line comment
“””

3. Data Types

• Numeric Types: int, float, complex
• Sequence Types: str, list, tuple
• Mapping Type: dict
• Set Types: set, frozenset
• Boolean Type: bool
• None Type: NoneType
• Example:

a = 10       # int
b = 3.14     # float
c = ‘Hello’  # str
d = True     # bool

4. Variables

• Declaration: Variables are created when you assign a value to them.
• Dynamic Typing: Python variables do not require an explicit declaration of type.
• Example:

x = 5        # Integer
y = “Hello”  # String
z = 3.14     # Float

5. Operators

• Arithmetic Operators: +, -, *, /, //, %, **
• Comparison Operators: ==, !=, >, <, >=, <=
• Logical Operators: and, or, not
• Membership Operators: in, not in
• Identity Operators: is, is not
• Example:

a = 10
b = 20
print(a == b)  # False
print(a is b)  # False

6. Control Flow and Looping Statements

• Conditional Statements:
• if, elif, else
• Example:

x = 10
if x > 0:
print(“Positive”)
elif x == 0:
print(“Zero”)
else:
print(“Negative”)

• Looping Statements:
• For Loop:

for i in range(5):
print(i)

• While Loop:

i = 0
while i < 5:
print(i)
i += 1

• Loop Control: break, continue, pass

7. Functions

• Introduction: Functions allow for code reuse and modularity.
• Syntax:

def function_name(parameters):
“””Docstring”””
statement(s)

Example:

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

print(greet(“Alice”))

• Arguments: Positional, keyword, default values.
• Return Statement: Used to return values from a function

8. Modules and Packages

• Modules: A Python file containing definitions and statements.
• Importing Modules:

import math
print(math.sqrt(16))

• Packages: A collection of modules in directories that include a special __init__.py file.
• Creating a Module: Any .py file can be used as a module.
• Example:

from math import pi
print(pi)

9. File Handling

• Reading and Writing Files:
• Open a file: open(filename, mode)
• Modes: r (read), w (write), a (append), b (binary mode)
• Example:

with open(‘file.txt’, ‘r’) as file:
content = file.read()
print(content)

• Writing to a File:

with open(‘file.txt’, ‘w’) as file:
file.write(“Hello, World!”)

10. Error Handling

• Try-Except Block:

try:
# Code that may throw an error
x = 1 / 0
except ZeroDivisionError:
print(“You cannot divide by zero!”)
finally:
print(“This runs no matter what.”)

• Multiple Exceptions: Handle multiple exceptions using tuples.

11. Object-Oriented Programming (OOP)

• Class and Objects:
• Class Definition:

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

def greet(self):
return f”Hello, {self.name}”

• Object Creation:

obj = MyClass(“Alice”)
print(obj.greet())

• Inheritance:Allows one class to inherit attributes and methods from another.

class Animal:
def sound(self):
return “Some sound”

class Dog(Animal):
def sound(self):
return “Bark”

dog = Dog()
print(dog.sound())  # Output: Bark

• Polymorphism: Same method name, different implementations.

12. List Comprehensions

• Syntax: [expression for item in iterable if condition]
• Example:

squares = [x**2 for x in range(10)]
print(squares)

• Output: [0, 1, 4, 9, 16, 25, 36, 49, 64, 81]

13. Lambda Functions

• Anonymous Functions: Created using the lambda keyword.
• Syntax: lambda arguments: expression
• Example:

add = lambda x, y: x + y
print(add(2, 3))  # Output: 5

14. Map, Filter, and Reduce

• Map: Applies a function to all items in an iterable.

nums = [1, 2, 3, 4]
squares = list(map(lambda x: x**2, nums))
print(squares)  # Output: [1, 4, 9, 16]

• Filter: Filters items based on a condition.

nums = [1, 2, 3, 4]
evens = list(filter(lambda x: x % 2 == 0, nums))
print(evens)  # Output: [2, 4]

• Reduce: Reduces a sequence to a single value.

from functools import reduce
nums = [1, 2, 3, 4]
product = reduce(lambda x, y: x * y, nums)
print(product)  # Output: 24

15. Common Built-in Functions

• Examples: len(), sum(), max(), min(), sorted(), type(), range()
• Example Usage:

numbers = [1, 2, 3, 4]
print(len(numbers))  # Output: 4
print(sum(numbers))  # Output: 10

16. Debugging

• Simple Debugging: Use print() statements to track variables.
• Python Debugger (pdb):

import pdb
pdb.set_trace()

• Setting Breakpoints: Can be used to pause execution and inspect code.

This comprehensive document covers the fundamental concepts of Python and provides clear examples for each topic.