Alternatives to partition()

Are there any alternatives to using std::partition() or std::ranges::partition() that offer better performance or additional features?

While std::partition() and std::ranges::partition() are powerful tools for dividing collections, there are alternatives that might offer better performance or additional features depending on your specific needs.

1. Use stable_partition()

If you need to maintain the relative order of elements, std::ranges::stable_partition() is a better choice despite its higher complexity. It ensures the order of equivalent elements is preserved:

#include <algorithm>
#include <iostream>
#include <vector>

int main() {
  std::vector<int> A = {1, -6, 7, 2, 5, 4};

  auto isEven = [](int x) { return x % 2 == 0; };

  std::ranges::stable_partition(A, isEven);

  std::cout << "After stable_partition: ";
  for (int x : A) {
    std::cout << x << ", ";
  }
}
After stable_partition: -6, 2, 4, 1, 7, 5,

2. Parallel Algorithms

For large datasets, parallel algorithms can significantly speed up processing. The <execution> library in C++17 introduces parallel versions of many algorithms, including partition():

#include <algorithm>
#include <execution>
#include <iostream>
#include <vector>

int main() {
  std::vector<int> A = {1, -6, 7, 2, 5, 4};

  auto isEven = [](int x) { return x % 2 == 0; };

  std::partition(std::execution::par,
    A.begin(), A.end(), isEven);

  std::cout << "After parallel partition: ";
  for (int x : A) {
    std::cout << x << ", ";
  }
}
After parallel partition: -6, 2, 4, 1, 7, 5,

3. Custom Partitioning Functions

For specialized needs, custom partitioning functions can offer more control. You can implement a tailored partitioning algorithm optimized for your specific use case.

This might involve tweaking the logic for how elements are moved or adding additional processing steps. Here's a simple custom partition function:

#include <iostream>
#include <vector>
#include <algorithm>

template <typename Iterator, typename Predicate>
Iterator custom_partition(Iterator first,
  Iterator last, Predicate pred) {
  Iterator result = first;
  for (Iterator it = first; it != last; ++it) {
    if (pred(*it)) {
      std::iter_swap(it, result);
      ++result;
    }
  }
  return result;
}

int main() {
  std::vector<int> A = {1, -6, 7, 2, 5, 4};
  auto isEven = [](int x) { return x % 2 == 0; };

  auto partition_point = custom_partition(
    A.begin(), A.end(), isEven);

  std::cout << "After custom partition: ";
  for (int x : A) {
    std::cout << x << ", ";
  }
}
After custom partition: -6, 2, 4, 1, 7, 5,

4. Library-Specific Algorithms

Certain libraries offer enhanced partitioning functions. Libraries like Boost provide additional algorithms and data structures that might offer improved performance or flexibility for specific applications.

Conclusion

While std::partition() and std::ranges::partition() are versatile and efficient for many cases, exploring alternatives like stable_partition(), parallel algorithms, custom functions, or library-specific tools can provide better performance or additional features tailored to your needs.

Partition Algorithms

An introduction to partitions, and the C++ standard library algorithms that create them

Questions & Answers

Answers are generated by AI models and may not have been reviewed. Be mindful when running any code on your device.

Partition vs Stable Partition Performance
How does the partition() algorithm differ from the stable_partition() algorithm in terms of performance?
Partitioning Custom Data Types
Can the partition() function be used with custom data types, and if so, how?
Determining Partition Size
How can I determine the size of each partition after using the partition() function?
When to Use partition_copy()
What are the use cases for partition_copy() over partition() or stable_partition()?
Understanding partition_point()
How does the partition_point() algorithm determine the boundary between partitions?
Safe Iterator Handling in partition_point()
How can I handle the iterator returned by partition_point() to avoid dereferencing issues?
Partitioning Without Random Access Iterators
Is it possible to use the partition() algorithm with containers that do not support random access iterators?
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