Idea for production validation

validator.py

def validate(data, **kwargs):
    """
    Validates a production datapoint based on given constraints.
    By default this will change type values that are negative to None.
    If the datapoint is found to be invalid then the production key
    is changed to the following.

    data['production'] = None

    Optional Arguments:
    --
    missing (list)
    Generation types that must be present.
    If any of these types are None the datapoint will be invalidated.
    For example ['gas', 'hydro']
    Defaults to an empty list.
    --
    allow_negative (bool)
    Determines if negative generation values are allowed.
    Defaults to False.
    --
    reference (list)
    Checks production total against expected range.
    List is in form [reference value, low %, high %].
    If the total generation is outside this range the datapoint will be invalidated.
    For example [12000, 0.1, 1.4]
    Defaults to None.
    """

    missing = kwargs.pop('missing', [])
    allow_negative = kwargs.pop('allow_negative', False)
    reference = kwargs.pop('reference', None)
    if kwargs:
        raise TypeError('Unexpected **kwargs: %r' % kwargs)

    generation = data['production']
    if missing:
        for item in missing:
            if generation[item] == None:
                data['production'] = None
                return data

    if allow_negative == True:
        pass
    else:
        for k,v in generation.iteritems():
            if v < 0.0:
                generation[k] = None

    if reference:
        low = reference[0]*reference[1]
        high = reference[0]*reference[2]
        total = sum(v for k, v in generation.iteritems() if v != None)
        if low <= total <= high:
            pass
        else:
            generation = None

    data['production'] = generation

    return data