A memory-efficient packed representation for bit arrays in pure Python
Consult the module API page at
for all information related to this module, including information regarding the latest changes to the code. The page at the URL shown above lists all of the module functionality you can invoke in your own code.
With regard to the basic purpose of the module, it defines the BitVector class as a memory-efficient packed representation for bit arrays. The class comes with a large number of methods for using the representation in diverse applications such as computer security, computer vision, etc.
Version 3.4.6 fixes what was hopefully the last remaining bug in using negative index values for slice assignments.
Version 3.4.5 fixes an important bug in the slice assignment code. The bug made itself evident when using negative start/stop values for slice assignment. This version also include a new method named min_canonical() that returns a canonical form of a bit pattern, which is a circularly shifted form of a bit pattern that has the maximum number of leading zeros. This method is useful in the “Local Binary Pattern” algorithm for characterizing image textures.
The class is provided with the following operators/methods:
- __eq__, __ne__, __lt__, __le__, __gt__, __ge__
- count_bits_sparse (faster for sparse bit vectors)
- gcd (for greatest common divisor)
- gf_divide_by_modulus (for modular divisions in GF(2^n))
- gf_MI (for multiplicative inverse in GF(2^n))
- gf_multiply (for multiplications in GF(2))
- gf_multiply_modular (for multiplications in GF(2^n))
- int_val (for returning the integer value)
- is_power_of_2_sparse (faster for sparse bit vectors)
- shift_left (for non-circular left shift)
- shift_right (for non-circular right shift)
Release history Release notifications | RSS feed
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.