Advanced Python Concepts

 

Advanced Python Concepts

Once you are comfortable with the basics, it's time to move on to more advanced topics that unlock Python's true power. Below are the key areas to focus on:

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1. Object-Oriented Programming (OOP)

Object-Oriented Programming allows you to create classes and objects that model real-world things.

python
class Animal:
    def __init__(self, name, species):
        self.name = name
        self.species = species
    
    def make_sound(self):
        print(f"{self.name} makes a sound.")

# Usage
dog = Animal("Buddy", "Dog")
dog.make_sound()

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2. Decorators

Decorators are a powerful feature that allows you to modify the behavior of functions or classes.

python
def logger(func):
    def wrapper(*args, **kwargs):
        print(f"Function '{func.__name__}' called with {args} {kwargs}")
        return func(*args, **kwargs)
    return wrapper

@logger
def add(a, b):
    return a + b

# Usage
print(add(3, 5))

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3. Generators

Generators allow you to iterate over data without storing it entirely in memory.

python
def fibonacci_sequence(limit):
    a, b = 0, 1
    while a < limit:
        yield a
        a, b = b, a + b

# Usage
for number in fibonacci_sequence(50):
    print(number)

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4. Multithreading and Multiprocessing

Handle multiple operations simultaneously to optimize performance.

python
import threading

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

thread = threading.Thread(target=print_numbers)
thread.start()
thread.join()

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5. Working with APIs

Integrate with external data sources through REST APIs.

python
import requests

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

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6. Context Managers

Automatically handle resource management (like opening and closing files).

python
with open('example.txt', 'r') as file:
    content = file.read()
    print(content)