Aprenda 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.


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# 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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Seção 3. Capítulo 3

Pergunte à IA

Pergunte o que quiser ou experimente uma das perguntas sugeridas para iniciar nosso bate-papo

Suggested prompts:

Can you explain how the compose function works in R?

What are some practical examples of function composition in data analysis?

How can I make my composed functions more readable and maintainable?

Deslize para mostrar o menu


              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

Tudo estava claro?

Obrigado pelo seu feedback!

Seção 3. Capítulo 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?