Why is “1000000000000000 in range(1000000000000001)” so fast in Python 3?

It is my understanding that the range() function, which is actually an object type in Python 3, generates its contents on the fly, similar to a generator.

This being the case, I would have expected the following line to take an inordinate amount of time because, in order to determine whether 1 quadrillion is in the range, a quadrillion values would have to be generated:

1_000_000_000_000_000 in range(1_000_000_000_000_001)

Furthermore: it seems that no matter how many zeroes I add on, the calculation more or less takes the same amount of time (basically instantaneous).

I have also tried things like this, but the calculation is still almost instant:

# count by tens
1_000_000_000_000_000_000_000 in range(0,1_000_000_000_000_000_000_001,10)

If I try to implement my own range function, the result is not so nice!

def my_crappy_range(N):
    i = 0
    while i < N:
        yield i
        i += 1
    return

What is the range() object doing under the hood that makes it so fast?


Martijn Pieters’s answer was chosen for its completeness, but also see abarnert’s first answer for a good discussion of what it means for range to be a full-fledged sequence in Python 3, and some information/warning regarding potential inconsistency for __contains__ function optimization across Python implementations. abarnert’s other answer goes into some more detail and provides links for those interested in the history behind the optimization in Python 3 (and lack of optimization of xrange in Python 2). by poke and by wim provide the relevant C source code and explanations for those who are interested.

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