Python vs Golang vs Rust

Photo by Michelle Moody on Unsplash

Python vs Golang vs Rust

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

Soumendra kumar sahoo
·May 17, 2022·

2 min read

Subscribe to my newsletter and never miss my upcoming articles

Play this article

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]


2 <= nums.length <= 104
-109 <= nums[i] <= 109
-109 <= target <= 109
Only one valid answer exists.


I have used a hash map to solve this problem across all three languages.


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]
                hash_table[target_num] = i
        return None

Python stats

  • Run time: 40ms
  • Memory usage: 14.5 MB


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


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


  • As per the results, Rust took the least memory and was the fastest of all three.

For more such insights follow me on Twitter.

Did you find this article valuable?

Support Soumendra kumar sahoo by becoming a sponsor. Any amount is appreciated!

See recent sponsors Learn more about Hashnode Sponsors
Share this


Views are my own and not represent of my employer.
All articles and images are CC-BY-SA-4.0 licensed unless or until explicitly specified.