Say you have an array `prices`

for which the *i*^{th} element is the price of a given stock on day *i*.

Design an algorithm to find the maximum profit. You may complete as many transactions as you like (i.e., buy one and sell one share of the stock multiple times).

**Note:** You may not engage in multiple transactions at the same time (i.e., you must sell the stock before you buy again).

**Example 1:**

Input:[7,1,5,3,6,4]Output:7Explanation:Buy on day 2 (price = 1) and sell on day 3 (price = 5), profit = 5-1 = 4. Then buy on day 4 (price = 3) and sell on day 5 (price = 6), profit = 6-3 = 3.

**Example 2:**

Input:[1,2,3,4,5]Output:4Explanation:Buy on day 1 (price = 1) and sell on day 5 (price = 5), profit = 5-1 = 4. Note that you cannot buy on day 1, buy on day 2 and sell them later, as you are engaging multiple transactions at the same time. You must sell before buying again.

**Example 3:**

Input:[7,6,4,3,1]Output:0Explanation:In this case, no transaction is done, i.e. max profit = 0.

**Constraints:**

`1 <= prices.length <= 3 * 10 ^ 4`

`0 <= prices[i] <= 10 ^ 4`

```
struct Solution;
impl Solution {
fn max_profit(prices: Vec<i32>) -> i32 {
let mut max = 0;
for i in 1..prices.len() {
if prices[i] > prices[i - 1] {
max += prices[i] - prices[i - 1]
}
}
max
}
}
#[test]
fn test() {
assert_eq!(Solution::max_profit(vec![7, 1, 5, 3, 6, 4]), 7);
assert_eq!(Solution::max_profit(vec![1, 2, 3, 4, 5]), 4);
assert_eq!(Solution::max_profit(vec![7, 6, 4, 3, 1]), 0);
}
```