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  1. PO
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    <p>ok with the use of deque class, but for the requeriments of the question (average) this is my solution:</p> <pre><code>&gt;&gt;&gt; from collections import deque &gt;&gt;&gt; class CircularBuffer(deque): ... def __init__(self, size=0): ... super(CircularBuffer, self).__init__(maxlen=size) ... @property ... def average(self): # TODO: Make type check for integer or floats ... return sum(self)/len(self) ... &gt;&gt;&gt; &gt;&gt;&gt; cb = CircularBuffer(size=10) &gt;&gt;&gt; for i in range(20): ... cb.append(i) ... print "@%s, Average: %s" % (cb, cb.average) ... @deque([0], maxlen=10), Average: 0 @deque([0, 1], maxlen=10), Average: 0 @deque([0, 1, 2], maxlen=10), Average: 1 @deque([0, 1, 2, 3], maxlen=10), Average: 1 @deque([0, 1, 2, 3, 4], maxlen=10), Average: 2 @deque([0, 1, 2, 3, 4, 5], maxlen=10), Average: 2 @deque([0, 1, 2, 3, 4, 5, 6], maxlen=10), Average: 3 @deque([0, 1, 2, 3, 4, 5, 6, 7], maxlen=10), Average: 3 @deque([0, 1, 2, 3, 4, 5, 6, 7, 8], maxlen=10), Average: 4 @deque([0, 1, 2, 3, 4, 5, 6, 7, 8, 9], maxlen=10), Average: 4 @deque([1, 2, 3, 4, 5, 6, 7, 8, 9, 10], maxlen=10), Average: 5 @deque([2, 3, 4, 5, 6, 7, 8, 9, 10, 11], maxlen=10), Average: 6 @deque([3, 4, 5, 6, 7, 8, 9, 10, 11, 12], maxlen=10), Average: 7 @deque([4, 5, 6, 7, 8, 9, 10, 11, 12, 13], maxlen=10), Average: 8 @deque([5, 6, 7, 8, 9, 10, 11, 12, 13, 14], maxlen=10), Average: 9 @deque([6, 7, 8, 9, 10, 11, 12, 13, 14, 15], maxlen=10), Average: 10 @deque([7, 8, 9, 10, 11, 12, 13, 14, 15, 16], maxlen=10), Average: 11 @deque([8, 9, 10, 11, 12, 13, 14, 15, 16, 17], maxlen=10), Average: 12 @deque([9, 10, 11, 12, 13, 14, 15, 16, 17, 18], maxlen=10), Average: 13 @deque([10, 11, 12, 13, 14, 15, 16, 17, 18, 19], maxlen=10), Average: 14 </code></pre>
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    1. POefficient circular buffer?
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    1. PTAnswer
    1. USSmartElectron
    1. USSmartElectron
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      1. VTUpMod
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    1. COI get `TypeError: 'numpy.float64' object is not callable` when trying to call `average` method
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    2. COIs for my post?, the code don´t use numpy anywhere. ¿?
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    3. COYes... in fact I guess that deque uses numpy arrays internally (after removing @property it works fine)
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