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Python vs Golang vs Rust

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Python vs Golang vs Rust

A short benchmarking between Python, Go, and Rust language.

Soumendra kumar sahoo's photo
Soumendra kumar sahoo
ยทMay 17, 2022ยท

2 min read

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Table of contents

  • Test scenario
  • Implementation
  • Conclusion

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.

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