This notebook was prepared by Donne Martin. Source and license info is on GitHub.

Challenge Notebook¶

Problem: Given a list of stock prices, find the max profit from 1 buy and 1 sell.¶

See the LeetCode problem page.

Constraints¶

Are all prices positive ints?
- Yes
Is the output an int?
- Yes
If profit is negative, do we return the smallest negative loss?
- Yes
If there are less than two prices, what do we return?
- Exception
Can we assume the inputs are valid?
- No
Can we assume this fits memory?
- Yes

Test Cases¶

None -> TypeError
Zero or one price -> ValueError
No profit
- [8, 5, 3, 2, 1] -> -1
General case
- [5, 3, 7, 4, 2, 6, 9] -> 7

Algorithm¶

Refer to the Solution Notebook. If you are stuck and need a hint, the solution notebook's algorithm discussion might be a good place to start.

Code¶

In [ ]:

class Solution(object):

    def find_max_profit(self, prices):
        # TODO: Implement me
        pass

Unit Test¶

The following unit test is expected to fail until you solve the challenge.

In [ ]:

# %load test_max_profit.py
import unittest


class TestMaxProfit(unittest.TestCase):

    def test_max_profit(self):
        solution = Solution()
        self.assertRaises(TypeError, solution.find_max_profit, None)
        self.assertRaises(ValueError, solution.find_max_profit, [])
        self.assertEqual(solution.find_max_profit([8, 5, 3, 2, 1]), -1)
        self.assertEqual(solution.find_max_profit([5, 3, 7, 4, 2, 6, 9]), 7)
        print('Success: test_max_profit')


def main():
    test = TestMaxProfit()
    test.test_max_profit()


if __name__ == '__main__':
    main()

Solution Notebook¶

Review the Solution Notebook for a discussion on algorithms and code solutions.