Test scenario
I have taken the Two sum problem from Leetcode.
The problem statement:
Given an array of integers nums and an integer target, return indices of the two numbers such that they add up to target.
You may assume that each input would have exactly one solution, and you may not use the same element twice.
You can return the answer in any order.
Example 1:
Input: nums = [2,7,11,15], target = 9
Output: [0,1]
Explanation: Because nums[0] + nums[1] == 9, we return [0, 1].Example 2:
Input: nums = [3,2,4], target = 6
Output: [1,2]Example 3:
Input: nums = [3,3], target = 6
Output: [0,1]Constraints:
2 <= nums.length <= 104 -109 <= nums[i] <= 109 -109 <= target <= 109 Only one valid answer exists.
Implementation
I have used a hash map to solve this problem across all three languages.
Python
class Solution:
def twoSum(self, nums: List[int], target: int) -> List[int]:
hash_table = {}
for i, num in enumerate(nums):
target_num = target - num
if num in hash_table:
return i, hash_table[num]
else:
hash_table[target_num] = i
return None
Python stats
- Run time: 40ms
- Memory usage: 14.5 MB
Golang
func twoSum(nums []int, target int) []int {
hashMap := make(map[int] int)
for i := 0; i < len(nums); i++{
if _, found := hashMap[nums[i]]; found {
ans := []int{i, hashMap[nums[i]]}
return ans
} else {
hashMap[target- nums[i]]= i
}
}
return nil
}
Golang stats
- Run time: 4ms
- Memory usage: 4.3 MB
Rust
use std::collections::HashMap;
impl Solution {
pub fn two_sum(nums: Vec<i32>, target: i32) -> Vec<i32> {
let mut hash_table: HashMap<i32, i32> = HashMap::new();
for i in 0..nums.len() {
// println!("Processing number: {}", nums[i]);
match hash_table.get(&nums[i]){
Some(&x) => return vec![x, i as i32],
None => hash_table.insert(target - nums[i], i as i32),
};
};
return vec![-1, -1]
}
}
Rust stats
- Run time: 2ms
- Memory usage: 2.2 MB
Conclusion
- As per the results, Rust took the least memory and was the fastest of all three.