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Python Functions → inner functions

Python Functions

inner functions

In Python, you can define a function inside another function. These are called inner functions, nested functions, or closure functions. They offer a powerful way to organize code, enhance readability, and create specialized functionalities. Let's explore this concept with detailed explanations and diverse examples.

1. Basic Structure and Access

An inner function is simply a function defined within the body of another function (the outer function). The inner function has access to: Its own local variables: Variables defined within the inner function itself. Variables of the enclosing (outer) function: This is a crucial aspect of closures. Variables in the global scope: But only if they aren't shadowed by local or enclosing variables.
Python inner functions(function inside function) def outer_function(x): """Outer function demonstrating an inner function.""" y = 10 # Variable accessible to the inner function def inner_function(z): """Inner function accessing variables from its scope and outer scope.""" result = x + y + z # Accesses x from outer, y from outer, and z from inner return result return inner_function #returns the inner function # Example usage: my_inner_func = outer_function(5) #outer_function returns inner_function print(my_inner_func(3))

Output

18
In this example, `inner_function` has access to `x` (from `outer_function`) and `y` (also from `outer_function`). The outer function *returns* the inner function, allowing us to call it later.

2. Closures

A key feature of inner functions is the creation of closures. A closure is an inner function that remembers and has access to variables in its surrounding scope, even after the outer function has finished executing.
Python closures example def counter(): count = 0 def increment(): nonlocal count # Crucial: Tells Python to modify the count in the enclosing scope count += 1 return count return increment my_counter = counter() print(my_counter()) print(my_counter()) print(my_counter())

Output

1 2 3
Here, `increment` is a closure. Even though `counter()` has finished executing, `increment` still "remembers" the `count` variable. The `nonlocal` keyword is essential; without it, Python would create a new local `count` inside `increment`, preventing the counter from working correctly.

3. Decorators (Advanced Application)

Closures are the foundation of decorators, a powerful Python feature for modifying or enhancing functions.
Decorators in python def my_decorator(func): def wrapper(): print("Before function execution") func() print("After function execution") return wrapper @my_decorator # This is syntactic sugar for: greet = my_decorator(greet) def greet(): print("Hello!") greet()

Output

Before function execution Hello! After function execution
`my_decorator` takes a function (`func`) as input, creates a wrapper function that adds extra behavior (printing messages before and after), and returns the wrapper. The `@` syntax makes using decorators concise and elegant.

4. Encapsulation and Code Organization

Inner functions help encapsulate code, making it more modular and readable. They can hide implementation details and prevent accidental modification of variables.
Python Inner function example def calculate_stats(data): def mean(data): return sum(data) / len(data) def variance(data): avg = mean(data) return sum([(x - avg)**2 for x in data]) / len(data) return mean(data), variance(data) #returns a tuple data = [1, 2, 3, 4, 5] avg, var = calculate_stats(data) print(f"Mean: {avg}, Variance: {var}")

Output

Mean: 3.0, Variance: 2.0
The `mean` and `variance` functions are only relevant within the context of `calculate_stats`, making it cleaner to define them internally.

5. Partial Function Application (using functools.partial)

While not strictly an inner function feature, it demonstrates how inner functions can be used in conjunction with other Python features for powerful effects.
Python Partial Function example from functools import partial def add(x, y, z): return x + y + z add_five = partial(add, 5) # create a new function which always has 5 as first argument print(add_five(2,3))

Output

10
Here `partial` creates a new function that has some of the arguments pre-filled making our function calls cleaner and concise. In summary, inner functions in Python offer a powerful combination of code organization, closure capabilities, and the ability to create advanced features like decorators. They are a valuable tool in any Python programmer's arsenal for building robust and maintainable applications.

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