How to handle input and output in golang functional programming?

Functional programming uses pipes and goroutines to handle input and output. When processing input, use pipes and goroutines to process streaming data in parallel. When processing output, use pipes to pass data from one function to another. In the actual case, pipelines are used to connect the processing function and the output function to achieve input processing and output formatting. This approach offers scalability, concurrency, and testability advantages.

Handling input and output in Go functional programming

Functional programming focuses on using immutable data structures and pure functions to write logic. This approach has unique benefits when handling input and output.

Processing input

To process input, we can use pipes and goroutines to process streaming data in parallel. For example, we can use the following code to stream lines of text read from standard input into a pipe:

package main

import (
    "bufio"
    "fmt"
    "log"
    "os"
)

func main() {
    lines := make(chan string)

    go func() {
        s := bufio.NewScanner(os.Stdin)
        for s.Scan() {
            lines <- s.Text()
        }
        close(lines)
    }()

    for line := range lines {
        fmt.Println(line)
    }
}

Processing Output

For output, we can use Pipes to pass data from one function to another. For example, we can use the following code to stream some strings to standard output: Contains some data. We want to process the data in this list and output it in another format.

Using functional programming, we can decompose this task into two functions:

Processing function:

Output function:
• is responsible for outputting the processed data in the required format.
We can use pipes to connect the processing function and the output function as follows:

• package main
  
  import (
      "fmt"
      "log"
  )
  
  func main() {
      lines := []string{"line1", "line2", "line3"}
  
      ch := make(chan string)
  
      go func() {
          for _, line := range lines {
              ch <- line
          }
          close(ch)
      }()
  
      for line := range ch {
          fmt.Println(line)
      }
  }

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  This approach provides the following benefits: Extensibility: We can easily add or modify processing or output logic without modifying other parts.
  Concurrency: By using pipelines, we can process data in parallel.
  Testability: The processing and output functions are independent and therefore easy to test separately.

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