67
1 = 0b1 -> 1
5 = 0b101 -> 3
10 = 0b1010 -> 4
100 = 0b1100100 -> 7
1000 = 0b1111101000 -> 10
…

How can I get the bit length of an integer, i.e. the number of bits that are necessary to represent a positive integer in Python?

0

7 Answers 7

209

In python 2.7+ there is a int.bit_length() method:

>>> a = 100
>>> a.bit_length()
7
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4 Comments

Curiously, you can't call bit_length() on an integer literal.
@EricWalker Sure you can. You can call a method on any object that has it. There's no exception for literals. You do need to use correct syntax: if you write 2., it's a floating point literal, not an integer literal followed by the field access operator. Put a space 2 .bit_length() or use parentheses (2).bit_length().
@Gilles'SO-stopbeingevil' thank you for the helpful clarification.
You can use bit_length() method in python 3 too !
23
>>> len(bin(1000))-2
10
>>> len(bin(100))-2
7
>>> len(bin(10))-2
4

Note: will not work for negative numbers, may be need to substract 3 instead of 2

5 Comments

This will not work with negative numbers though (while it also won't fail on it, opposed to the log-versions)
If you care about negative numbers, do len(bin(abs(n)))-2
More importantly, this fails for 0.
Another way is to do len("{:b}".format(x)) to avoid having to do the subtraction.
According to the Python Documentation, bin(n).lstrip('-0b') works fine for negative numbers, which is equivalent to bit_length.
8

If your Python version has it (≥2.7 for Python 2, ≥3.1 for Python 3), use the bit_length method from the standard library.

Otherwise, len(bin(n))-2 as suggested by YOU is fast (because it's implemented in Python). Note that this returns 1 for 0.

Otherwise, a simple method is to repeatedly divide by 2 (which is a straightforward bit shift), and count how long it takes to reach 0.

def bit_length(n): # return the bit size of a non-negative integer
    bits = 0
    while n >> bits: bits += 1
    return bits

It is significantly faster (at least for large numbers — a quick benchmarks says more than 10 times faster for 1000 digits) to shift by whole words at a time, then go back and work on the bits of the last word.

def bit_length(n): # return the bit size of a non-negative integer
    if n == 0: return 0
    bits = -32
    m = 0
    while n:
        m = n
        n >>= 32; bits += 32
    while m: m >>= 1; bits += 1
    return bits

In my quick benchmark, len(bin(n)) came out significantly faster than even the word-sized chunk version. Although bin(n) builds a string that's discarded immediately, it comes out on top due to having an inner loop that's compiled to machine code. (math.log is even faster, but that's not important since it's wrong.)

4 Comments

@JonathanEunice Which implementation are you talking about, and why do you think it is incorrect? The bit length of 5 is 3.
My mistake! I misread the question (as "number of set bits in N" rather than "number of bits to represent N"). I withdraw the criticism.
I thought the same :P, it's good to know about bit_length though
For those seeing the above comments, the term for the number of raised bits in a number is called the population count, oftentimes abbreviated the popcount. This solution is not how to find the popcount - see here for how to do popcount in Python.
3

Here we can also use slicing.

For positive integers, we'd start from 2:

len(bin(1)[2:])
len(bin(5)[2:])
len(bin(10)[2:])
len(bin(100)[2:])
len(bin(1000)[2:])

which would print:

1
3
4
7
10

For negative integers, we'd start from 3:

len(bin(-1)[3:])
len(bin(-5)[3:])
len(bin(-10)[3:])
len(bin(-100)[3:])
len(bin(-1000)[3:])

which would print:

1
3
4
7
10

Comments

0
def bitcounter(n):
    return math.floor(math.log(n,2)) + 1

EDIT fixed so that it works with 1

6 Comments

This is off by one for powers of two.
@Ants Aasma: Are you sure about that? It looks fine to me, assuming that math.log(n, 2) gives a perfectly correct result.
@MarkDickinson: math.log(n, 2) does not give a perfectly correct result. math.log(2**29, 2) = 29.000000000000004, for instance.
@endolith: Yep; I'm scratching my head trying to figure out what on earth I was thinking when I wrote that comment. FWIW, there's math.log2 for Python 3, which does give exact results for floats that are exact powers of 2.
@endolith: Though interestingly, on my machine, I get log(2**n, 2) >= n for all non-negative n, so that math.floor(math.log(n, 2)) + 1 still gives the correct result for powers of 2. Though not, of course, for all n; n = 2**48 - 1 seems to be the smallest value for which it fails.
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0

Here is another way:

def number_of_bits(n):
    return len('{:b}'.format(n))

Not so efficient I suppose, but doesn't show up in any of the previous answers...

Comments

-2

This solution takes advantage of .bit_length() if available, and falls back to len(hex(a)) for older versions of Python. It has the advantage over bin that it creates a smaller temporary string, so it uses less memory.

Please note that it returns 1 for 0, but that's easy to change.

_HEX_BIT_COUNT_MAP = {
    '0': 0, '1': 1, '2': 2, '3': 2, '4': 3, '5': 3, '6': 3, '7': 3}

def bit_count(a):
  """Returns the number of bits needed to represent abs(a). Returns 1 for 0."""
  if not isinstance(a, (int, long)):
    raise TypeError
  if not a:
    return 1
  # Example: hex(-0xabc) == '-0xabc'. 'L' is appended for longs.
  s = hex(a)
  d = len(s)
  if s[-1] == 'L':
    d -= 1
  if s[0] == '-':
    d -= 4
    c = s[3]
  else:
    d -= 3
    c = s[2]
  return _HEX_BIT_COUNT_MAP.get(c, 4) + (d << 2)


# Use int.bit_length and long.bit_length introduced in Python 2.7 and 3.x.
if getattr(0, 'bit_length', None):
  __doc = bit_count.__doc__
  def bit_count(a):
    return a.bit_length() or 1
  bit_count.__doc__ = __doc

assert bit_count(0) == 1
assert bit_count(1) == 1
assert bit_count(2) == 2
assert bit_count(3) == 2
assert bit_count(63) == 6
assert bit_count(64) == 7
assert bit_count(75) == 7
assert bit_count(2047) == 11
assert bit_count(2048) == 12
assert bit_count(-4007) == 12
assert bit_count(4095) == 12
assert bit_count(4096) == 13
assert bit_count(1 << 1203) == 1204
assert bit_count(-(1 << 1203)) == 1204
assert bit_count(1 << 1204) == 1205
assert bit_count(1 << 1205) == 1206
assert bit_count(1 << 1206) == 1207

5 Comments

instead of checking if it has bit_length, you should just try to use it and then except AttributeError?
@endolith: Would it be a significant improvement of this code? In what way?
well it's more efficient if you're expecting bit_length to be available
@endolith: Are you sure it's more efficient? (Have you benchmarked it?) Is the difference significant in this case?
@pts Handling AttributeError is considered more Pythonic. e.g., stackoverflow.com/a/12265860/687467

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