They aren’t talking about using recursion instead of loops. They are talking about the map method for iterators. For each element yielded by the iterator, map applies a specified function/closure and collects the results in a new iterator (usually a list). This is a functional programming pattern that’s common in many languages including Python and Rust.
This pattern has no risk of stack overflow since each invocation of the function is completed before the next invocation. The construct does expand to some sort of loop during execution. The only possible overhead is a single function call within the loop (whereas you could have written it as the loop body). However, that won’t be a problem if the compiler can inline the function.
The fact that this is functional programming creates additional avenues to optimize the program. For example, a chain of maps (or other iterator adaptors) can be intelligently combined into a single loop. In practice, this pattern is as fast as hand written loops.
A great point in favour of maps is that each iteration is independent, so could theoretically be executed in parallel. This heavily depends on the language implementation, though.
Imperative for loops have no guarantee at all that iterations could be executed in parallel.
You can do some (usually expensive, and never complete) analysis to find some cases, but smart compilers tend to work the best the dumbest you need them to be. Having a loop that you can just blindly parallelize will some times lead to it being parallel in practice, while having a loop where a PhD knows how to decide if you can parallelize will lead to sequential programs in practice.
They aren’t talking about using recursion instead of loops. They are talking about the map method for iterators. For each element yielded by the iterator, map applies a specified function/closure and collects the results in a new iterator (usually a list). This is a functional programming pattern that’s common in many languages including Python and Rust.
This pattern has no risk of stack overflow since each invocation of the function is completed before the next invocation. The construct does expand to some sort of loop during execution. The only possible overhead is a single function call within the loop (whereas you could have written it as the loop body). However, that won’t be a problem if the compiler can inline the function.
The fact that this is functional programming creates additional avenues to optimize the program. For example, a chain of maps (or other iterator adaptors) can be intelligently combined into a single loop. In practice, this pattern is as fast as hand written loops.
A great point in favour of maps is that each iteration is independent, so could theoretically be executed in parallel. This heavily depends on the language implementation, though.
Technically this is also possible with for loops, like with OpenMP
Imperative for loops have no guarantee at all that iterations could be executed in parallel.
You can do some (usually expensive, and never complete) analysis to find some cases, but smart compilers tend to work the best the dumbest you need them to be. Having a loop that you can just blindly parallelize will some times lead to it being parallel in practice, while having a loop where a PhD knows how to decide if you can parallelize will lead to sequential programs in practice.
While you do have a fair point, I was referring to the case where one is basically implementing a map operation as a for loop.