🧠 Python Higher-Order Functions – Functions That Work with Functions

🧲 Introduction – What Are Higher-Order Functions?

In Python, functions are first-class citizens. This means functions can be:

• Assigned to variables ✅
• Passed as arguments ✅
• Returned from other functions ✅

A Higher-Order Function (HOF) is any function that takes another function as an argument or returns a function as a result.

They are the foundation of functional programming in Python and are used in tools like map(), filter(), sorted(), decorators, and custom logic.

🎯 In this guide, you’ll learn:

• What higher-order functions are
• Common built-in HOFs (map, filter, reduce, sorted)
• How to create your own higher-order functions
• Real-world use cases and best practices

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🔧 What Is a Higher-Order Function?

A higher-order function is any function that does one or both of the following:

1. Accepts another function as an argument
2. Returns a function

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✅ Example 1: Function as Argument

def shout(text):
    return text.upper()

def greet(func):
    return func("hello")

print(greet(shout))  # Output: HELLO

📘 Explanation:
greet() takes another function (shout) as input and applies it to a string.

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✅ Example 2: Returning a Function

def outer(x):
    def inner(y):
        return x + y
    return inner

add_five = outer(5)
print(add_five(10))  # Output: 15

💡 Use Case: This is the foundation of closures and decorators.

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🔁 Common Built-In Higher-Order Functions

🔹 map()

Applies a function to every element in an iterable.

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

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🔹 filter()

Filters elements based on a condition.

evens = list(filter(lambda x: x % 2 == 0, range(10)))
print(evens)  # [0, 2, 4, 6, 8]

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🔹 reduce() (from functools)

Applies a rolling computation.

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

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🔹 sorted() with key

Sorts based on a custom function.

words = ['banana', 'apple', 'cherry']
print(sorted(words, key=lambda x: len(x)))  # ['apple', 'banana', 'cherry']

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🔧 Custom Higher-Order Function

def apply_twice(func, value):
    return func(func(value))

print(apply_twice(lambda x: x + 3, 7))  # Output: 13

📘 Explanation:
The function func is applied two times to the input value.

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💡 Best Practices

• ✅ Use HOFs to reduce duplication and abstract behavior
• ✅ Combine with lambda for simple one-off logic
• ✅ Use functools.wraps when writing function-returning decorators
• ⚠️ Avoid deep nesting of HOFs for readability

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📌 Summary – Recap & Next Steps

Python higher-order functions are functions that take other functions as arguments or return them. They form the basis for map-reduce, decorators, and functional abstraction in modern Python.

🔍 Key Takeaways:

• ✅ A higher-order function accepts or returns another function.
• ✅ Common HOFs: map(), filter(), reduce(), and sorted().
• ✅ You can create custom HOFs for reusable and composable code.
• ⚠️ Maintain readability when combining lambdas or multiple nested HOFs.

⚙️ Real-World Relevance:
Higher-order functions are widely used in data pipelines, API wrappers, web frameworks, and machine learning preprocessing, making them a vital tool in every Python developer’s toolkit.

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❓ FAQ Section – Python Higher-Order Functions

❓ What is a higher-order function in Python?

✅ A higher-order function is a function that accepts another function as a parameter or returns a function.

❓ Is map() a higher-order function?

✅ Yes. map() takes a function and an iterable, applying the function to each item.

❓ What’s the difference between a regular function and a higher-order function?

✅ A regular function performs computation directly, while a higher-order function works on other functions.

❓ Can I return a function from another function?

✅ Yes! This is the basis of closures and decorators.

❓ Are decorators higher-order functions?

✅ Absolutely. Decorators are one of the most common real-world examples of higher-order functions.

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