How to use the pyperformance.benchmarks.bm_deltablue.Variable function in pyperformance

def projection_test(n):
    """
    This test constructs a two sets of variables related to each
    other by a simple linear transformation (scale and offset). The
    time is measured to change a variable on either side of the
    mapping and to change the scale and offset factors.
    """
    global planner
    planner = Planner()
    scale = Variable("scale", 10)
    offset = Variable("offset", 1000)
    src = None

    dests = OrderedCollection()

    for i in range(n):
        src = Variable("src%s" % i, i)
        dst = Variable("dst%s" % i, i)
        dests.append(dst)
        StayConstraint(src, Strength.NORMAL)
        ScaleConstraint(src, scale, offset, dst, Strength.REQUIRED)

    change(src, 17)

    if dst.value != 1170:
        print("Projection 1 failed")

def projection_test(n):
    """
    This test constructs a two sets of variables related to each
    other by a simple linear transformation (scale and offset). The
    time is measured to change a variable on either side of the
    mapping and to change the scale and offset factors.
    """
    global planner
    planner = Planner()
    scale = Variable("scale", 10)
    offset = Variable("offset", 1000)
    src = None

    dests = OrderedCollection()

    for i in range(n):
        src = Variable("src%s" % i, i)
        dst = Variable("dst%s" % i, i)
        dests.append(dst)
        StayConstraint(src, Strength.NORMAL)
        ScaleConstraint(src, scale, offset, dst, Strength.REQUIRED)

    change(src, 17)

    if dst.value != 1170:
        print("Projection 1 failed")

"""
    This test constructs a two sets of variables related to each
    other by a simple linear transformation (scale and offset). The
    time is measured to change a variable on either side of the
    mapping and to change the scale and offset factors.
    """
    global planner
    planner = Planner()
    scale = Variable("scale", 10)
    offset = Variable("offset", 1000)
    src = None

    dests = OrderedCollection()

    for i in range(n):
        src = Variable("src%s" % i, i)
        dst = Variable("dst%s" % i, i)
        dests.append(dst)
        StayConstraint(src, Strength.NORMAL)
        ScaleConstraint(src, scale, offset, dst, Strength.REQUIRED)

    change(src, 17)

    if dst.value != 1170:
        print("Projection 1 failed")

    change(dst, 1050)

    if src.value != 5:
        print("Projection 2 failed")

    change(scale, 5)

This test constructs a two sets of variables related to each
    other by a simple linear transformation (scale and offset). The
    time is measured to change a variable on either side of the
    mapping and to change the scale and offset factors.
    """
    global planner
    planner = Planner()
    scale = Variable("scale", 10)
    offset = Variable("offset", 1000)
    src = None

    dests = OrderedCollection()

    for i in range(n):
        src = Variable("src%s" % i, i)
        dst = Variable("dst%s" % i, i)
        dests.append(dst)
        StayConstraint(src, Strength.NORMAL)
        ScaleConstraint(src, scale, offset, dst, Strength.REQUIRED)

    change(src, 17)

    if dst.value != 1170:
        print("Projection 1 failed")

    change(dst, 1050)

    if src.value != 5:
        print("Projection 2 failed")

    change(scale, 5)

and executing a constraint satisfaction plan. There are two cases.
    In case 1, the added constraint is stronger than the stay
    constraint and values must propagate down the entire length of the
    chain. In case 2, the added constraint is weaker than the stay
    constraint so it cannot be accomodated. The cost in this case is,
    of course, very low. Typical situations lie somewhere between these
    two extremes.
    """
    global planner
    planner = Planner()
    prev, first, last = None, None, None

    # We need to go up to n inclusively.
    for i in range(n + 1):
        name = "v%s" % i
        v = Variable(name)

        if prev is not None:
            EqualityConstraint(prev, v, Strength.REQUIRED)

        if i == 0:
            first = v

        if i == n:
            last = v

        prev = v

    StayConstraint(last, Strength.STRONG_DEFAULT)
    edit = EditConstraint(first, Strength.PREFERRED)
    edits = OrderedCollection()
    edits.append(edit)

def __init__(self, name, initial_value=0):
        super(Variable, self).__init__()
        self.name = name
        self.value = initial_value
        self.constraints = OrderedCollection()
        self.determined_by = None
        self.mark = 0
        self.walk_strength = Strength.WEAKEST
        self.stay = True