Unlocking the Power of Algorithms
When it comes to finding the student with the highest score in a large collection, we often rely on the max_element() function. However, what if we only want to consider students from a specific year? This is where things get tricky. We need to combine copy_if() and max_element() to achieve our goal, but unfortunately, the Algorithm library doesn’t allow us to compose algorithms.
A Custom Solution
One approach is to create a new container, copy the relevant students into it, and then iterate through the new container to find the maximum score. This can be done using the following code:
cpp
auto get_max_score(const std::vector<Student>& students, int year) {
auto by_year = [=](const auto& s) { return s.year_ == year; };
auto v = std::vector<Student>{};
std::ranges::copy_if(students, std::back_inserter(v), by_year);
auto it = std::ranges::max_element(v, std::less{}, &Student::score_);
return it!= v.end()? it->score_ : 0;
}
The Limitations of the Algorithm Library
While this solution works, it highlights one of the limitations of the Algorithm library: the inability to compose algorithms. This can lead to unnecessary container copies and inefficiencies. However, as we’ll see in the next chapter, there’s a better way to approach this problem.
The Benefits of Standard Algorithms
Despite the limitations, using the standard Algorithm library has its advantages. By leveraging these algorithms, we can optimize our code for later stages and avoid handwritten for-loops. We’ve also discussed the guarantees and trade-offs of standard algorithms, giving us the confidence to use them effectively.
Preparing for Parallelization
By using standard algorithms, our codebase is well-prepared for parallelization techniques that will be discussed in later chapters. However, the inability to compose algorithms remains a significant limitation.
Introducing the Ranges Library
In the next chapter, we’ll explore the Ranges library, which offers a powerful solution to this limitation. With views from the Ranges library, we can compose multiple transformations into a lazy-evaluated view over a sequence of elements. This allows us to overcome the limitations of standard algorithms and unlock new possibilities for efficient and effective coding.
What to Expect
In the next chapter, we’ll delve into the world of range views, covering topics such as:
- The composability of algorithms
- Range adaptors
- Materializing views into containers
- Generating, transforming, and sampling elements in a range
The Motivation Behind the Ranges Library
The Ranges library was introduced in C++20 to provide major improvements to how we benefit from the standard library when implementing algorithms. With features like concepts that define requirements on iterators and ranges, we can now better check these requirements during development and enjoy more help from the compiler.
Get ready to unlock the full potential of algorithms and take your coding skills to the next level!