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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 _jaccard_similarity(f1, f2, weight_func):
 """Calculate generalized Jaccard similarity of formulas. Returns the weighted similarity value or None if there is no overlap at all. If the union of the formulas has a weight of zero (i.e. the denominator in the Jaccard similarity is zero), a value of zero is returned. """

    elements = set(f1)
    elements.update(f2)

    count, w_count, w_total = 0, 0, 0
    for element in elements:
        mi = min(f1.get(element, 0), f2.get(element, 0))
        mx = max(f1.get(element, 0), f2.get(element, 0))
        count += mi
        w = weight_func(element)
        w_count += w * mi
        w_total += w * mx

    if count == 0:
        return None

    return 0.0 if w_total == 0.0 else w_count / w_total