Say you have an array 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: 7

Explanation: 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: 4

Explanation: 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: 0

Explanation: In this case, no transaction is done, i.e. max profit = 0.

## Solution

```
from typing import List
class Solution:
def maxProfit(self, prices: List[int]) -> int:
profit = 0
for i in range(1, len(prices)):
if prices[i] > prices[i-1]:
profit += prices[i] - prices[i-1]
return profit
```

## Test Cases

```
test = Solution()
answer = test.maxProfit([7,1,5,3,6,4])
assert answer == 7
answer = test.maxProfit([1,2,3,4,5])
assert answer == 4
print('All Passed!')
```

## Big O Analysis

**Space Complexity**: O(1)

**Time Complexity**: O(N)