Fast way of counting non-zero bits in positive integer

Question

For arbitrary-length integers, bin(n).count("1") is the fastest I could find in pure Python.

I tried adapting Óscar's and Adam's solutions to process the integer in 64-bit and 32-bit chunks, respectively. Both were at least ten times slower than bin(n).count("1") (the 32-bit version took about half again as much time).

On the other hand, gmpy popcount() took about 1/20th of the time of bin(n).count("1"). So if you can install gmpy, use that.

To answer a question in the comments, for bytes I'd use a lookup table. You can generate it at runtime:

counts = bytes(bin(x).count("1") for x in range(256))  # py2: use bytearray

Or just define it literally:

counts = (b'\x00\x01\x01\x02\x01\x02\x02\x03\x01\x02\x02\x03\x02\x03\x03\x04'
          b'\x01\x02\x02\x03\x02\x03\x03\x04\x02\x03\x03\x04\x03\x04\x04\x05'
          b'\x01\x02\x02\x03\x02\x03\x03\x04\x02\x03\x03\x04\x03\x04\x04\x05'
          b'\x02\x03\x03\x04\x03\x04\x04\x05\x03\x04\x04\x05\x04\x05\x05\x06'
          b'\x01\x02\x02\x03\x02\x03\x03\x04\x02\x03\x03\x04\x03\x04\x04\x05'
          b'\x02\x03\x03\x04\x03\x04\x04\x05\x03\x04\x04\x05\x04\x05\x05\x06'
          b'\x02\x03\x03\x04\x03\x04\x04\x05\x03\x04\x04\x05\x04\x05\x05\x06'
          b'\x03\x04\x04\x05\x04\x05\x05\x06\x04\x05\x05\x06\x05\x06\x06\x07'
          b'\x01\x02\x02\x03\x02\x03\x03\x04\x02\x03\x03\x04\x03\x04\x04\x05'
          b'\x02\x03\x03\x04\x03\x04\x04\x05\x03\x04\x04\x05\x04\x05\x05\x06'
          b'\x02\x03\x03\x04\x03\x04\x04\x05\x03\x04\x04\x05\x04\x05\x05\x06'
          b'\x03\x04\x04\x05\x04\x05\x05\x06\x04\x05\x05\x06\x05\x06\x06\x07'
          b'\x02\x03\x03\x04\x03\x04\x04\x05\x03\x04\x04\x05\x04\x05\x05\x06'
          b'\x03\x04\x04\x05\x04\x05\x05\x06\x04\x05\x05\x06\x05\x06\x06\x07'
          b'\x03\x04\x04\x05\x04\x05\x05\x06\x04\x05\x05\x06\x05\x06\x06\x07'
          b'\x04\x05\x05\x06\x05\x06\x06\x07\x05\x06\x06\x07\x06\x07\x07\x08')

Then it's counts[x] to get the number of 1 bits in x where 0 ≤ x ≤ 255.

Python 3.10 introduces int.bit_count():

>>> n = 19
>>> bin(n)
'0b10011'
>>> n.bit_count()
3
>>> (-n).bit_count()
3

This is functionally equivalent to bin(n).count("1") but should be ~6 times faster. See also Issue29882.

You can adapt the following algorithm:

def CountBits(n):
  n = (n & 0x5555555555555555) + ((n & 0xAAAAAAAAAAAAAAAA) >> 1)
  n = (n & 0x3333333333333333) + ((n & 0xCCCCCCCCCCCCCCCC) >> 2)
  n = (n & 0x0F0F0F0F0F0F0F0F) + ((n & 0xF0F0F0F0F0F0F0F0) >> 4)
  n = (n & 0x00FF00FF00FF00FF) + ((n & 0xFF00FF00FF00FF00) >> 8)
  n = (n & 0x0000FFFF0000FFFF) + ((n & 0xFFFF0000FFFF0000) >> 16)
  n = (n & 0x00000000FFFFFFFF) + ((n & 0xFFFFFFFF00000000) >> 32) # This last & isn't strictly necessary.
  return n

This works for 64-bit positive numbers, but it's easily extendable and the number of operations growth with the logarithm of the argument (i.e. linearly with the bit-size of the argument).

In order to understand how this works imagine that you divide the entire 64-bit string into 64 1-bit buckets. Each bucket's value is equal to the number of bits set in the bucket (0 if no bits are set and 1 if one bit is set). The first transformation results in an analogous state, but with 32 buckets each 2-bit long. This is achieved by appropriately shifting the buckets and adding their values (one addition takes care of all buckets since no carry can occur across buckets - n-bit number is always long enough to encode number n). Further transformations lead to states with exponentially decreasing number of buckets of exponentially growing size until we arrive at one 64-bit long bucket. This gives the number of bits set in the original argument.

Here's a Python implementation of the population count algorithm, as explained in this post:

def numberOfSetBits(i):
    i = i - ((i >> 1) & 0x55555555)
    i = (i & 0x33333333) + ((i >> 2) & 0x33333333)
    return (((i + (i >> 4) & 0xF0F0F0F) * 0x1010101) & 0xffffffff) >> 24

It will work for 0 <= i < 0x100000000.