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Understanding Channel Buffers
In your code, you observed that increasing the channel buffer size from 1 to 10 enhanced performance by reducing context switches. This concept is correct. A larger buffer allows the fibonacci goroutine to fill multiple spots in advance, reducing the need for constant communication between goroutines.
Channel Lifetime and Memory Management
However, a channel's lifetime is distinct from the goroutines that use it. In your original code, the fibonacci goroutine is not terminated, and the channel reference is retained in the main function. As such, the channel and its contents persist in memory, leading to a potential memory leak.
An Alternative Generator Implementation
To avoid memory leaks while still utilizing Python-style generators, you can implement a solution similar to the following:
package main import "fmt" func fib(n int) chan int { c := make(chan int) go func() { x, y := 0, 1 for i := 0; i <= n; i++ { c <- x x, y = y, x+y } close(c) }() return c } func main() { for i := range fib(10) { fmt.Println(i) } }
Explanation:
This approach ensures that the fibonacci goroutine terminates gracefully, preventing memory leaks and providing a clean and efficient generator implementation.
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