Optimisation Techniques

The bitstring module aims to be as fast as reasonably possible, and since version 4.1 has used the bitarray C extension to power its core.

There are however some pointers you should follow to make your code efficient, so if you need things to run faster then this is the section for you.

Use combined read and interpretation

When parsing a bitstring one way to write code is in the following style:

width = s.read(12).uint
height = s.read(12).uint
flags = s.read(4).bin

This works fine, but is not very quick. The problem is that the call to read constructs and returns a new bitstring, which then has to be interpreted. The new bitstring isn’t used for anything else and so creating it is wasted effort. Instead it is better to use a string parameter that does the read and interpretation together:

width = s.read('uint12')
height = s.read('uint12')
flags = s.read('bin4')

This is much faster, although probably not as fast as the combined call:

width, height, flags = s.readlist('uint12, uint12, bin4')

Choose the simplest class you can

If you don’t need to modify your bitstring after creation then prefer the immutable Bits over the mutable BitArray. This is typically the case when parsing, or when creating directly from files.

The speed difference between the classes is noticeable, and there are also memory usage optimisations that are made if objects are known to be immutable.

You should also prefer ConstBitStream to BitStream if you won’t need to modify any bits.

One anti-pattern to watch out for is using += on a Bits object. For example, don’t do this:

s = Bits()
for i in range(1000):
    s += '0xab'

Now this is inefficient for a few reasons, but the one I’m highlighting is that as the immutable bitstring doesn’t have an __iadd__ special method the ordinary __add__ gets used instead. In other words s += '0xab' gets converted to s = s + '0xab', which creates a new Bits from the old on every iteration. This isn’t what you’d want or possibly expect. If s had been a BitArray then the addition would have been done in-place, and have been much more efficient.

Another problem is that the string 0xab needs to be converted to a bitstring on every iteration. There are cacheing mechanisms that will make this faster after the first time, but if there is a constant conversion happening in a loop like this it is better to hoist it out of the loop by declaring ab = Bits('0xab') first and then adding this object instead of the string.

Use dedicated functions for bit setting and checking

If you need to set or check individual bits then there are special functions for this. For example one way to set bits would be:

s = BitArray(1000)
for p in [14, 34, 501]:
    s[p] = '0b1'

This creates a 1000 bit bitstring and sets three of the bits to ‘1’. Unfortunately the crucial line spends most of its time creating a new bitstring from the ‘0b1’ string. You could make it slightly quicker by using s[p] = True, but it is much faster (and I mean at least an order of magnitude) to use the set method:

s = BitArray(1000)
s.set(True, [14, 34, 501])

As well as set and invert there are also checking methods all and any. So rather than using

if s[100] and s[200]:

it’s better to say

if s.all(True, (100, 200)):

If the pattern of setting or getting can be expressed as a range then it is much faster to pass in the range object so that it can be used to optimize the pattern. For example, instead of

for i in range(0, len(s), 2):
    s.set(True, i)

you should just write

s.set(True, range(0, len(s), 2))