Learn Composing Functions | Functional Programming in Practice

Function composition is a foundational technique in functional programming that allows you to build complex operations by combining simpler ones. By composing functions, you can create reusable, modular code that is easier to understand and maintain. This approach not only simplifies logic but also enhances clarity, making your codebase more robust and flexible.


              12345678
            
# Define two simple functions
double <- function(x) {x * 2}

add_three <- function(x) {x + 3}

# Compose: double a number, then add three
result <- add_three(double(5))
print(result)  # Output: 13

In R, you can manually compose functions by nesting one function call inside another. The output of the inner function serves as the input for the outer function. This technique allows you to chain together multiple operations, each encapsulated in its own function, to achieve a desired result.


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double <- function(x) {x * 2}
add_three <- function(x) {x + 3}

# Create a compose function
compose <- function(f, g) {
  function(x) {
    f(g(x))
  }
}

# Compose add_three and double
add_three_after_double <- compose(add_three, double)
print(add_three_after_double(5))  # Output: 13

Function composition is especially valuable in data pipelines, where you often need to process data through a series of transformations. By composing small, single-purpose functions, you can build expressive and maintainable data workflows. This modular approach makes it easy to modify, extend, or debug each step in the pipeline without affecting the others.

To keep composed functions readable and debuggable, always give clear, descriptive names to your functions and avoid excessive nesting. Consider breaking down complex compositions into intermediate steps or using helper functions. This practice not only improves code clarity but also makes troubleshooting easier if something goes wrong.

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Section 3. Chapter 3

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              12345678
            
# Define two simple functions
double <- function(x) {x * 2}

add_three <- function(x) {x + 3}

# Compose: double a number, then add three
result <- add_three(double(5))
print(result)  # Output: 13


              12345678910111213
            
double <- function(x) {x * 2}
add_three <- function(x) {x + 3}

# Create a compose function
compose <- function(f, g) {
  function(x) {
    f(g(x))
  }
}

# Compose add_three and double
add_three_after_double <- compose(add_three, double)
print(add_three_after_double(5))  # Output: 13

Everything was clear?

Thanks for your feedback!

Section 3. Chapter 3

Composing Functions

1. What is function composition?

2. How can function composition improve code reuse?

3. What is a potential downside of deeply nested function compositions?

Composing Functions

1. What is function composition?

2. How can function composition improve code reuse?

3. What is a potential downside of deeply nested function compositions?