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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def basis_function_one(degree, knot_vector, span, knot):
 """ Computes the value of a basis function for a single parameter. Implementation of Algorithm 2.4 from The NURBS Book by Piegl & Tiller. :param degree: degree, :math:`p` :type degree: int :param knot_vector: knot vector :type knot_vector: list, tuple :param span: knot span, :math:`i` :type span: int :param knot: knot or parameter, :math:`u` :type knot: float :return: basis function, :math:`N_{i,p}` :rtype: float """

    # Special case at boundaries
    if (span == 0 and knot == knot_vector[0]) or \
            (span == len(knot_vector) - degree - 2) and knot == knot_vector[len(knot_vector) - 1]:
        return 1.0

    # Knot is outside of span range
    if knot < knot_vector[span] or knot >= knot_vector[span + degree + 1]:
        return 0.0

    N = [0.0 for _ in range(degree + span + 1)]

    # Initialize the zeroth degree basis functions
    for j in range(0, degree + 1):
        if knot_vector[span + j] <= knot < knot_vector[span + j + 1]:
            N[j] = 1.0

    # Computing triangular table of basis functions
    for k in range(1, degree + 1):
        # Detecting zeros saves computations
        saved = 0.0
        if N[0] != 0.0:
            saved = ((knot - knot_vector[span]) * N[0]) / (knot_vector[span + k] - knot_vector[span])

        for j in range(0, degree - k + 1):
            Uleft = knot_vector[span + j + 1]
            Uright = knot_vector[span + j + k + 1]

            # Zero detection
            if N[j + 1] == 0.0:
                N[j] = saved
                saved = 0.0
            else:
                temp = N[j + 1] / (Uright - Uleft)
                N[j] = saved + (Uright - knot) * temp
                saved = (knot - Uleft) * temp

    return N[0]