很難抽象地描述這一點(diǎn)，所以讓我舉一個(gè)（簡化和摘錄的）示例：class ClassificationResults(object):  #####################################################################################################################  # These methods all represent aggregate metrics. They all follow the same interface: they return a tuple  # consisting of the numerator and denominator of a fraction, and a format string that describes the result in terms  # of that numerator, denominator, and the fraction itself.  #####################################################################################################################  metrics  = ['recall', 'precision', 'fmeasure', 'f2measure', 'accuracy']  # ...  def recall(self):    tpos, pos = 0, 0    for prediction in self.predictions:      if prediction.predicted_label == 1:        pos += 1        if prediction.true_label == 1:          tpos += 1    return tpos, pos, "{1} instances labelled positive. {0} of them correct (recall={2:.2})"  def precision(self):    tpos, true = 0, 0    for prediction in self.predictions:      if prediction.true_label == 1:        true += 1        if prediction.predicted_label == 1:          tpos += 1    return tpos, true, "{1} positive instances. We labelled {0} correctly (precision={2:.2})"  # ...  def printResults(self):    for methodname in self.metrics:      (num, denom, msg) = getattr(self, methodname)()      dec = num/float(denom)      print msg.format(num, denom, dec)有沒有更好的方法來表明這些方法都屬于同一個(gè)“族”，并允許它們?cè)谘h(huán)中被調(diào)用而無需每次都對(duì)其進(jìn)行命名？我過去做過的另一種方法是用通用前綴命名方法，例如  def metric_precision(self):    tpos, true = 0, 0    for prediction in self.predictions:      if prediction.true_label == 1:        true += 1        if prediction.predicted_label == 1:          tpos += 1    return tpos, true, "{1} positive instances. We labelled {0} correctly (precision={2:.2})"我還可以將每個(gè)方法都轉(zhuǎn)換為一個(gè)公共超類的實(shí)例，但是這感覺有點(diǎn)過頭了。