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Python

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Basics​

Syntax and Variables​

Python uses simple, clean syntax. Variables don't need explicit declarations.

# Basic variables
x = 10
y = 3.14
name = "Alice"

# Printing values
print(x, y, name)

Control Flow​

# if-else example
x = 10
if x > 5:
    print("x is greater than 5")
else:
    print("x is 5 or less")

# for loop example
for i in range(5):
    print(i)

Functions​

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

print(greet("Alice"))

Data Structures​

Python has built-in data structures like lists, dictionaries, and sets

# List
numbers = [1, 2, 3, 4]
print(numbers)

# Tuple - ordered and unchangeable
ord_numbers = (1, 2, 3, 4)
print(ord_numbers)

# Dictionary
person = {"name": "Alice", "age": 25}
print(person["name"])

# Set
unique_values = {1, 2, 3, 3}
print(unique_values)

Error Handling​

Handle errors gracefully using try-except blocks.

try:
    x = int("not a number")
except ValueError as e:
    print(f"Error: {e}")

Object-Oriented Programming (OOP)​

Python supports OOP with classes and objects.

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'm {self.age} years old.")

person = Person("Alice", 25)
person.greet()

Modules and Packages​

You can import modules to reuse code across files.

# Importing a built-in module
import math
print(math.sqrt(16))

# Creating your own module (save as my_module.py)
def say_hello():
    return "Hello from the module!"

# In another file
from my_module import say_hello
print(say_hello())

File I/O​

Python makes file reading and writing simple.

# Writing to a file
with open("test.txt", "w") as file:
    file.write("Hello, World!")

# Reading from a file
with open("test.txt", "r") as file:
    content = file.read()
    print(content)

List Comprehensions and Lambda Functions​

List comprehensions provide a concise way to create lists.

# List comprehension
squares = [x**2 for x in range(5)]
print(squares)

# Lambda functions
double = lambda x: x * 2
print(double(5))

Advanced Python Concepts​

Iterators and Generators​

Iterators help in traversing through sequences, and generators lazily produce values.

# Iterator example
my_list = [1, 2, 3]
my_iter = iter(my_list)

print(next(my_iter))
print(next(my_iter))

# Generator example
def countdown(n):
    while n > 0:
        yield n
        n -= 1

for count in countdown(5):
    print(count)

Decorators​

Decorators modify the behavior of functions without changing their code.

def decorator(func):
    def wrapper():
        print("Before the function call")
        func()
        print("After the function call")
    return wrapper

@decorator
def say_hello():
    print("Hello!")

say_hello()

Context Managers​

Context managers ensure proper resource management (e.g., opening/closing files).

with open("file.txt", "w") as file:
    file.write("Writing with a context manager.")

Regular Expressions​

Regular expressions are used for string pattern matching.

import re

pattern = r"\d+"
text = "There are 123 apples"

match = re.findall(pattern, text)
print(match)  # Output: ['123']