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  • + 0 comments

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  • + 2 comments

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    • + 0 comments

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    • + 0 comments

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  • + 1 comment

    Note: time complexity is O(1), not O(log n) as stated in the editorial.
    (Given that python's "bit_length()" is O(1).)

    • + 1 comment

      Lol. With that reasoning you may say that every question is because of the limits on . BIt length is considered as .

      Moreover, python integers are not limited. Check this:

          a = 10000
          b = a ** a
          print(b)
      
      • + 1 comment

        Thanks for your comment, however I fear you've got some things wrong (no offense intended) :-)

        • "limits of N .": never part of my arguing, what do you mean?
        • "python integers not limited": (except by memory) sure, aware of this, so what??
        • "Bit length considered ": now that is interesting:

        In general I would agree with you, however (implementation dependant) python exploits its integer data structure for a retrieval in O(1), compare here.
        Also you may be aware of different definitions of 'complexity': the optimization guys prefer to give it as function of input length, so you would find O(n) as result here ;-))

        • + 0 comments

          Oh, you are right, I misunderstood you. The bit length of a given integer is , while the calculation of bit length is implementation dependent. It seems Python remembers/calculates the number of digits while creating the big integers, so it is easier for Python to calculate the bit length.

          Thanks for the clarification.

  • + 0 comments

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  • + 0 comments

    I have not understood the problem