Complete practice algorithms from InterviewCake.com
While I've done these algorithms before, I'm preparing for an on-site with DeepMind, so I created a subdirectory called deepmind where I'm storing my second attempts at these problems. The idea of storing them in a second directory is to remove the urge to check my existing solutions that also exist in this repository.
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deepmind/stock-price.py
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51
deepmind/stock-price.py
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def get_max_profit(xs):
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best_profit = xs[1] - xs[0]
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lowest_buy = xs[0]
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for x in xs[1:]:
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best_profit = max(best_profit, x - lowest_buy)
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lowest_buy = min(lowest_buy, x)
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return best_profit
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# Tests
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import unittest
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class Test(unittest.TestCase):
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def test_price_goes_up_then_down(self):
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actual = get_max_profit([1, 5, 3, 2])
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expected = 4
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self.assertEqual(actual, expected)
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def test_price_goes_down_then_up(self):
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actual = get_max_profit([7, 2, 8, 9])
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expected = 7
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self.assertEqual(actual, expected)
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def test_price_goes_up_all_day(self):
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actual = get_max_profit([1, 6, 7, 9])
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expected = 8
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self.assertEqual(actual, expected)
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def test_price_goes_down_all_day(self):
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actual = get_max_profit([9, 7, 4, 1])
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expected = -2
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self.assertEqual(actual, expected)
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def test_price_stays_the_same_all_day(self):
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actual = get_max_profit([1, 1, 1, 1])
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expected = 0
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self.assertEqual(actual, expected)
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def test_error_with_empty_prices(self):
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with self.assertRaises(Exception):
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get_max_profit([])
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def test_error_with_one_price(self):
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with self.assertRaises(Exception):
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get_max_profit([1])
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unittest.main(verbosity=2)
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