How do I use views::iota, views::take, views::drop?

The C++ standard library offers a powerful set of tools for working with ranges, including views::iota, views::take, and views::drop. These views allow you to easily manipulate sequences of data in a lazy and efficient manner. Below is an example demonstrating how to use these views in your C++ code.

#include #include #include int main() { // Generate a range of integers [0, 1, 2, ..., 9] auto range = std::views::iota(0, 10); // Take the first 5 elements auto taken = range | std::views::take(5); // Print the taken elements std::cout << "Taken elements: "; for (int n : taken) { std::cout << n << ' '; } std::cout << std::endl; // Drop the first 3 elements auto dropped = range | std::views::drop(3); // Print the dropped elements std::cout << "Dropped elements: "; for (int n : dropped) { std::cout << n << ' '; } std::cout << std::endl; return 0; }

C++ views::iota views::take views::drop ranges standard library

Related Questions

How do I avoid rehashing overhead with std::set in multithreaded code?

How do I find elements with custom comparators with std::set for embedded targets?

How do I erase elements while iterating with std::set for embedded targets?

How do I provide stable iteration order with std::unordered_map for large datasets?

How do I reserve capacity ahead of time with std::unordered_map for large datasets?

How do I erase elements while iterating with std::unordered_map in multithreaded code?

How do I provide stable iteration order with std::map for embedded targets?

How do I provide stable iteration order with std::map in multithreaded code?

How do I avoid rehashing overhead with std::map in performance-sensitive code?

How do I merge two containers efficiently with std::map for embedded targets?