In Python, you can deduplicate lists in a memory-efficient way by utilizing a combination of built-in data structures like sets and dictionary comprehensions. This approach ensures that duplicates are removed while keeping the original order of elements intact.
def deduplicate_list(original_list):
seen = set()
return [x for x in original_list if not (x in seen or seen.add(x))]
# Example usage
my_list = [1, 2, 2, 3, 4, 4, 5]
deduplicated_list = deduplicate_list(my_list)
print(deduplicated_list) # Output: [1, 2, 3, 4, 5]
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?