Advanced Python Techniques

Python is a versatile programming language that has a wide range of advanced techniques. These techniques can help you write more efficient, readable, and maintainable code. Here are some of the key advanced Python techniques:

List Comprehensions

List comprehensions are a concise way to create lists. They are often faster than using loops and are more readable.

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

Generator Expressions

Generator expressions are similar to list comprehensions, but they generate items one at a time instead of creating a list in memory.

squares = (x**2 for x in range(10))

Decorators

Decorators are a powerful way to modify the behavior of functions or methods without changing their source code.

def my_decorator(func):
    def wrapper():
        print("Something is happening before the function is called.")
        func()
        print("Something is happening after the function is called.")
    return wrapper

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

say_hello()

Context Managers

Context managers are used to allocate and release resources precisely when you want to. The with statement is used to create a context manager.

with open("file.txt", "r") as file:
    content = file.read()

Async/Await

Async/await syntax is used to write asynchronous code that looks synchronous. This is particularly useful for I/O-bound and high-level structured network code.

async def main():
    print('Hello')
    await asyncio.sleep(1)
    print('World!')

# Python 3.7+
asyncio.run(main())