Python for Computer Science

1. Why Python?

Python is the dominant language in Data Science, AI, and backend development due to its simplicity and vast ecosystem.

2. Advanced Python Concepts

List Comprehensions

Concise way to create lists.

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

Decorators

Modifying functions or methods.

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_whee():
    print("Whee!")

Generators

Iterators that yield results one by one.

def count_up_to(n):
    count = 1
    while count <= n:
        yield count
        count += 1

3. Essential Libraries

• NumPy: Numerical computing.
• Pandas: Data manipulation and analysis.
• Matplotlib / Seaborn: Data visualization.
• Scikit-learn: Machine learning algorithms.
• PyTorch / TensorFlow: Deep learning frameworks.

4. Type Hinting (Modern Python)

def greeting(name: str) -> str:
    return 'Hello ' + name