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

# Challenge Notebook¶

## Constraints¶

• Can we assume the inputs are valid?
• No
• Is there a range of inputs?
• 0 <= item <= 100
• Should mean return a float?
• Yes
• Should the other results return an int?
• Yes
• If there are multiple modes, what do we return?
• Any of the modes
• Can we assume this fits memory?
• Yes

## Test Cases¶

• None -> TypeError
• [] -> ValueError
• [5, 2, 7, 9, 9, 2, 9, 4, 3, 3, 2]
• max: 9
• min: 2
• mean: 55
• mode: 9 or 2

## 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 __init__(self, upper_limit=100):
# TODO: Implement me
pass

def insert(self, val):
# TODO: Implement me
pass


## Unit Test¶

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

In [ ]:
# %load test_math_ops.py
import unittest

class TestMathOps(unittest.TestCase):

def test_math_ops(self):
solution = Solution()
self.assertRaises(TypeError, solution.insert, None)
solution.insert(5)
solution.insert(2)
solution.insert(7)
solution.insert(9)
solution.insert(9)
solution.insert(2)
solution.insert(9)
solution.insert(4)
solution.insert(3)
solution.insert(3)
solution.insert(2)
self.assertEqual(solution.max, 9)
self.assertEqual(solution.min, 2)
self.assertEqual(solution.mean, 5)
self.assertTrue(solution.mode in (2, 9))
print('Success: test_math_ops')

def main():
test = TestMathOps()
test.test_math_ops()

if __name__ == '__main__':
main()


## Solution Notebook¶

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