Create `/math/standard_deviation` resource

[neumannrf]

As a user I need to calculate the standard deviation of the elements in the list So that so that calculations can be automated.

Assumptions:

• There should be a main.py file with the following content.

@math_ns.route('/standard_deviation')
@math_ns.doc(description='Standard deviation of the list.')
class StandardDeviationList(Resource):
    def get(self):
        return ms.standard_deviation(my_list)

• The main.py file should include an external file above the from src import basic_services as bs line.

from src import math_services as ms

• The requirements.txt file should list numpy as a dependency.

• There should be a src/math_services.py file with the following content

import numpy as np


def standard_deviation(integer_list):
    """
    Calculates the standard deviation of the list of integers.

    Receives
    --------
    integer_list : list
        List of integers.

    Returns
    -------
    std : float
        Standard deviation of the list.
    """

    integer_array = np.array(integer_list, dtype=int)
    return np.std(integer_array).astype(float)

• There should be a test/math_test.py file with the following content.

from src import math_services as ms


def test_standard_deviation():
    assert ms.standard_deviation([1]) == 0.0
    assert ms.standard_deviation([2]) == 0.0
    assert ms.standard_deviation([1, 1]) == 0.0
    assert ms.standard_deviation([1, 2]) == 0.5
    assert ms.standard_deviation([1, 2, 3]) == 0.816496580927726
    assert ms.standard_deviation([0, 1, 2, 2]) == 0.82915619758885
    assert ms.standard_deviation([1, 1, 2, 3]) == 0.82915619758885
    assert ms.standard_deviation([1, 2, 4, 5]) == 1.5811388300841898
    assert ms.standard_deviation([1, 2, 3, 4, 5]) == 1.4142135623730951

Acceptance criteria:

Given that the application stores a list of integers
When this resource is called
Then the standard deviation of the list is calculated.