This module provides an object type which efficiently represents an array of booleans. Bitarrays are sequence types and behave very much like usual lists. Eight bits are represented by one byte in a contiguous block of memory. The user can select between two representations: little-endian and big-endian. All of the functionality is implemented in C. Methods for accessing the machine representation are provided. This can be useful when bit level access to binary files is required, such as portable bitmap image files (.pbm). Also, when dealing with compressed data which uses variable bit length encoding, you may find this module useful.
&, |,
^, &=, |=, ^=,
~Bitarray can be installed from source:
$ tar xzf bitarray-1.6.3.tar.gz
$ cd bitarray-1.6.3
$ python setup.py installOn Unix systems, the latter command may have to be executed with root
privileges. You can also pip install bitarray. Please note that you need
a working C compiler to run the python setup.py install
command. If you rather want to use precompiled binaries, you can:
pip install bitarray-hardbyte (this PyPI package
contains Python wheels for Linux, MaxOSX and Windows and all common
Python versions)conda install bitarray (both the default Anaconda
repository as well as conda-forge support bitarray)Once you have installed the package, you may want to test it:
$ python -c 'import bitarray; bitarray.test()'
bitarray is installed in: /usr/local/lib/python2.7/site-packages/bitarray
bitarray version: 1.6.3
3.7.4 (r271:86832, Dec 29 2018) [GCC 4.2.1 (SUSE Linux)]
.........................................................................
.........................................................................
..............................
----------------------------------------------------------------------
Ran 257 tests in 0.921s
OKYou can always import the function test, and
test().wasSuccessful() will return True when
the test went well.
As mentioned above, bitarray objects behave very much like lists, so there is not too much to learn. The biggest difference from list objects (except that bitarray are obviously homogeneous) is the ability to access the machine representation of the object. When doing so, the bit endianness is of importance; this issue is explained in detail in the section below. Here, we demonstrate the basic usage of bitarray objects:
>>> from bitarray import bitarray
>>> a = bitarray() # create empty bitarray
>>> a.append(True)
>>> a.extend([False, True, True])
>>> a
bitarray('1011')Bitarray objects can be instantiated in different ways:
>>> a = bitarray(2**20) # bitarray of length 1048576 (uninitialized)
>>> bitarray('1001011') # from a string
bitarray('1001011')
>>> lst = [True, False, False, True, False, True, True]
>>> bitarray(lst) # from list, tuple, iterable
bitarray('1001011')Bits can be assigned from any Python object, if the value can be interpreted as a truth value. You can think of this as Python's built-in function bool() being applied, whenever casting an object:
>>> a = bitarray([42, '', True, {}, 'foo', None])
>>> a
bitarray('101010')
>>> a.append(a) # note that bool(a) is True
>>> a.count(42) # counts occurrences of True (not 42)
4
>>> a.remove('') # removes first occurrence of False
>>> a
bitarray('110101')Like lists, bitarray objects support slice assignment and deletion:
>>> a = bitarray(50)
>>> a.setall(False)
>>> a[11:37:3] = 9 * bitarray([True])
>>> a
bitarray('00000000000100100100100100100100100100000000000000')
>>> del a[12::3]
>>> a
bitarray('0000000000010101010101010101000000000')
>>> a[-6:] = bitarray('10011')
>>> a
bitarray('000000000001010101010101010100010011')
>>> a += bitarray('000111')
>>> a[9:]
bitarray('001010101010101010100010011000111')In addition, slices can be assigned to booleans, which is easier (and faster) than assigning to a bitarray in which all values are the same:
>>> a = 20 * bitarray('0')
>>> a[1:15:3] = True
>>> a
bitarray('01001001001001000000')This is easier and faster than:
>>> a = 20 * bitarray('0')
>>> a[1:15:3] = 5 * bitarray('1')
>>> a
bitarray('01001001001001000000')Note that in the latter we have to create a temporary bitarray whose length must be known or calculated.
Since a bitarray allows addressing of individual bits, where the machine represents 8 bits in one byte, there are two obvious choices for this mapping: little- and big-endian. When creating a new bitarray object, the endianness can always be specified explicitly:
>>> a = bitarray(endian='little')
>>> a.frombytes(b'A')
>>> a
bitarray('10000010')
>>> b = bitarray('11000010', endian='little')
>>> b.tobytes()
b'C'Here, the low-bit comes first because little-endian means that
increasing numeric significance corresponds to an increasing address
(index). So a[0] is the lowest and least significant bit,
and a[7] is the highest and most significant bit.
>>> a = bitarray(endian='big')
>>> a.frombytes(b'A')
>>> a
bitarray('01000001')
>>> a[6] = 1
>>> a.tobytes()
b'C'Here, the high-bit comes first because big-endian means
"most-significant first". So a[0] is now the lowest and
most significant bit, and a[7] is the highest and least
significant bit.
The bit endianness is a property attached to each bitarray object. When comparing bitarray objects, the endianness (and hence the machine representation) is irrelevant; what matters is the mapping from indices to bits:
>>> bitarray('11001', endian='big') == bitarray('11001', endian='little')
TrueBitwise operations (&, |,
^, &=, |=, ^=,
~) are implemented efficiently using the corresponding byte
operations in C, i.e. the operators act on the machine representation of
the bitarray objects. Therefore, one has to be cautious when applying
the operation to bitarrays with different endianness.
When converting to and from machine representation, using the
tobytes, frombytes, tofile and
fromfile methods, the endianness matters:
>>> a = bitarray(endian='little')
>>> a.frombytes(b'\x01')
>>> a
bitarray('10000000')
>>> b = bitarray(endian='big')
>>> b.frombytes(b'\x80')
>>> b
bitarray('10000000')
>>> a == b
True
>>> a.tobytes() == b.tobytes()
FalseThe endianness can not be changed once an object is created. However, since creating a bitarray from another bitarray just copies the memory representing the data, you can create a new bitarray with different endianness:
>>> a = bitarray('11100000', endian='little')
>>> a
bitarray('11100000')
>>> b = bitarray(a, endian='big')
>>> b
bitarray('00000111')
>>> a == b
False
>>> a.tobytes() == b.tobytes()
TrueThe default bit endianness is currently big-endian, however this may change in the future, and when dealing with the machine representation of bitarray objects, it is recommended to always explicitly specify the endianness.
Unless explicitly converting to machine representation, using the
tobytes, frombytes, tofile and
fromfile methods, the bit endianness will have no effect on
any computation, and one can safely ignore setting the endianness, and
other details of this section.
Python 2.7 provides memoryview objects, which allow Python code to access the internal data of an object that supports the buffer protocol without copying. Bitarray objects support this protocol, with the memory being interpreted as simple bytes.
>>> a = bitarray('01000001' '01000010' '01000011', endian='big')
>>> v = memoryview(a)
>>> len(v)
3
>>> v[-1]
67
>>> v[:2].tobytes()
b'AB'
>>> v.readonly # changing a bitarray's memory is also possible
False
>>> v[1] = 111
>>> a
bitarray('010000010110111101000011')The method encode takes a dictionary mapping symbols to
bitarrays and an iterable, and extends the bitarray object with the
encoded symbols found while iterating. For example:
>>> d = {'H':bitarray('111'), 'e':bitarray('0'),
... 'l':bitarray('110'), 'o':bitarray('10')}
...
>>> a = bitarray()
>>> a.encode(d, 'Hello')
>>> a
bitarray('111011011010')Note that the string 'Hello' is an iterable, but the
symbols are not limited to characters, in fact any immutable Python
object can be a symbol. Taking the same dictionary, we can apply the
decode method which will return a list of the symbols:
>>> a.decode(d)
['H', 'e', 'l', 'l', 'o']
>>> ''.join(a.decode(d))
'Hello'Since symbols are not limited to being characters, it is necessary to return them as elements of a list, rather than simply returning the joined string.
When the codes are large, and you have many decode calls, most time
will be spent creating the (same) internal decode tree objects. In this
case, it will be much faster to create a decodetree object
(which is initialized with a prefix code dictionary), and can be passed
to bitarray's .decode() and .iterdecode()
methods, instead of passing the prefix code dictionary to those methods
itself.
The above dictionary d can be efficiently constructed
using the function bitarray.util.huffman_code(). I also
wrote Huffman coding
in Python using bitarray for more background information.
bitarray(initializer=0, /, endian='big') ->
bitarray
Return a new bitarray object whose items are bits initialized from the optional initial object, and endianness. The initializer may be of the following types:
int: Create a bitarray of given integer length. The
initial values are arbitrary. If you want all values to be set, use the
.setall() method.
str: Create bitarray from a string of 0 and
1.
list, tuple, iterable: Create
bitarray from a sequence, each element in the sequence is converted to a
bit using its truth value.
bitarray: Create bitarray from another bitarray. This is
done by copying the buffer holding the bitarray data, and is hence very
fast.
The optional keyword arguments endian specifies the bit
endianness of the created bitarray object. Allowed values are the
strings big and little (default is
big).
Note that setting the bit endianness only has an effect when accessing the machine representation of the bitarray, i.e. when using the methods: tofile, fromfile, tobytes, frombytes.
A bitarray object supports the following methods:
all() -> bool
Returns True when all bits in the array are True.
any() -> bool
Returns True when any bit in the array is True.
append(item, /)
Append the truth value bool(item) to the end of the
bitarray.
buffer_info() -> tuple
Return a tuple (address, size, endianness, unused, allocated) giving the memory address of the bitarray's buffer, the buffer size (in bytes), the bit endianness as a string, the number of unused bits within the last byte, and the allocated memory for the buffer (in bytes).
bytereverse()
For all bytes representing the bitarray, reverse the bit order (in-place). Note: This method changes the actual machine values representing the bitarray; it does not change the endianness of the bitarray object.
clear()
Remove all items from the bitarray.
copy() -> bitarray
Return a copy of the bitarray.
count(value=True, start=0, stop=<end of array>, /)
-> int
Count the number of occurrences of bool(value) in the bitarray.
decode(code, /) -> list
Given a prefix code (a dict mapping symbols to bitarrays, or
decodetree object), decode the content of the bitarray and
return it as a list of symbols.
encode(code, iterable, /)
Given a prefix code (a dict mapping symbols to bitarrays), iterate over the iterable object with symbols, and extend the bitarray with the corresponding bitarray for each symbol.
endian() -> str
Return the bit endianness of the bitarray as a string
(little or big).
extend(iterable or string, /)
Extend bitarray by appending the truth value of each element given by
iterable. If a string is provided, each 0 and
1 are appended as bits.
fill() -> int
Adds zeros to the end of the bitarray, such that the length of the bitarray will be a multiple of 8. Returns the number of bits added (0..7).
frombytes(bytes, /)
Extend bitarray with raw bytes. That is, each append byte will add eight bits to the bitarray.
fromfile(f, n=-1, /)
Extend bitarray with up to n bytes read from the file object f. When n is omitted or negative, reads all data until EOF. When n is provided and positions but exceeds the data available, EOFError is raised (but the available data is still read and appended.
index(value, start=0, stop=<end of array>, /)
-> int
Return index of the first occurrence of bool(value) in
the bitarray. Raises ValueError if the value is not
present.
insert(index, value, /)
Insert bool(value) into the bitarray before index.
invert(index=<all bits>)
Invert all bits in the array (in-place). When the optional
index is given, only invert the single bit at index.
iterdecode(code, /) -> iterator
Given a prefix code (a dict mapping symbols to bitarrays, or
decodetree object), decode the content of the bitarray and
return an iterator over the symbols.
itersearch(bitarray, /) -> iterator
Searches for the given a bitarray in self, and return an iterator over the start positions where bitarray matches self.
length() -> int
Return the length - a.length() is the same as len(a). Deprecated since 1.5.1, use len().
pack(bytes, /)
Extend the bitarray from bytes, where each byte corresponds to a
single bit. The byte b'\x00' maps to bit 0 and all other
characters map to bit 1. This method, as well as the unpack method, are
meant for efficient transfer of data between bitarray objects to other
python objects (for example NumPy's ndarray object) which have a
different memory view.
pop(index=-1, /) -> item
Return the i-th (default last) element and delete it from the
bitarray. Raises IndexError if bitarray is empty or index
is out of range.
remove(value, /)
Remove the first occurrence of bool(value) in the
bitarray. Raises ValueError if item is not present.
reverse()
Reverse the order of bits in the array (in-place).
search(bitarray, limit=<none>, /) -> list
Searches for the given bitarray in self, and return the list of start positions. The optional argument limits the number of search results to the integer specified. By default, all search results are returned.
setall(value, /)
Set all bits in the bitarray to bool(value).
sort(reverse=False)
Sort the bits in the array (in-place).
to01() -> str
Return a string containing '0's and '1's, representing the bits in the bitarray object.
tobytes() -> bytes
Return the byte representation of the bitarray. When the length of the bitarray is not a multiple of 8, the few remaining bits (1..7) are considered to be 0.
tofile(f, /)
Write the byte representation of the bitarray to the file object f. When the length of the bitarray is not a multiple of 8, the remaining bits (1..7) are set to 0.
tolist(as_ints=False, /) -> list
Return a list with the items (False or True) in the bitarray. The optional parameter, changes the items in the list to integers (0 or 1). Note that the list object being created will require 32 or 64 times more memory (depending on the machine architecture) than the bitarray object, which may cause a memory error if the bitarray is very large.
unpack(zero=b'\x00', one=b'\xff') -> bytes
Return bytes containing one character for each bit in the bitarray, using the specified mapping.
This object is very similar to the bitarray object. The difference is that this a frozenbitarray is immutable, and hashable:
>>> from bitarray import frozenbitarray
>>> a = frozenbitarray('1100011')
>>> a[3] = 1
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "bitarray/__init__.py", line 40, in __delitem__
raise TypeError("'frozenbitarray' is immutable")
TypeError: 'frozenbitarray' is immutable
>>> {a: 'some value'}
{frozenbitarray('1100011'): 'some value'}frozenbitarray(initializer=0, /, endian='big') ->
frozenbitarray
Return a frozenbitarray object, which is initialized the same way a bitarray object is initialized. A frozenbitarray is immutable and hashable. Its contents cannot be altered after it is created; however, it can be used as a dictionary key.
This (immutable and unhashable) object stores a binary tree
initialized from a prefix code dictionary. It's sole purpose is to be
passed to bitarray's .decode() and
.iterdecode() methods, instead of passing the prefix code
dictionary to those methods directly:
>>> from bitarray import bitarray, decodetree
>>> t = decodetree({'a': bitarray('0'), 'b': bitarray('1')})
>>> a = bitarray('0110')
>>> a.decode(t)
['a', 'b', 'b', 'a']
>>> ''.join(a.iterdecode(t))
'abba'decodetree(code, /) -> decodetree
Given a prefix code (a dict mapping symbols to bitarrays), create a
binary tree object to be passed to .decode() or
.iterdecode().
bitarray module:test(verbosity=1, repeat=1) -> TextTestResult
Run self-test, and return unittest.runner.TextTestResult object.
bits2bytes(n, /) -> int
Return the number of bytes necessary to store n bits.
get_default_endian() -> string
Return the default endianness for new bitarray objects being created.
Under normal circumstances, the return value is big.
bitarray.util module:zeros(length, /, endian=None) -> bitarray
Create a bitarray of length, with all values 0, and optional endianness, which may be 'big', 'little'.
make_endian(bitarray, endian, /) -> bitarray
When the endianness of the given bitarray is different from
endian, return a new bitarray, with endianness
endian and the same elements as the original bitarray, i.e.
even though the binary representation of the new bitarray will be
different, the returned bitarray will equal the original one. Otherwise
(endianness is already endian) the original bitarray is
returned unchanged.
rindex(bitarray, value=True, /) -> int
Return the rightmost index of bool(value) in bitarray.
Raises ValueError if the value is not present.
strip(bitarray, mode='right', /) -> bitarray
Strip zeros from left, right or both ends. Allowed values for mode
are the strings: left, right,
both
count_n(a, n, /) -> int
Find the smallest index i for which
a[:i].count() == n. Raises ValueError, when n
exceeds total count (a.count()).
count_and(a, b, /) -> int
Returns (a & b).count(), but is more memory
efficient, as no intermediate bitarray object gets created.
count_or(a, b, /) -> int
Returns (a | b).count(), but is more memory efficient,
as no intermediate bitarray object gets created.
count_xor(a, b, /) -> int
Returns (a ^ b).count(), but is more memory efficient,
as no intermediate bitarray object gets created.
subset(a, b, /) -> bool
Return True if bitarray a is a subset of bitarray
b (False otherwise). subset(a, b) is
equivalent to (a & b).count() == a.count() but is more
efficient since we can stop as soon as one mismatch is found, and no
intermediate bitarray object gets created.
ba2hex(bitarray, /) -> hexstr
Return a string containing with hexadecimal representation of the bitarray (which has to be multiple of 4 in length).
hex2ba(hexstr, /, endian=None) -> bitarray
Bitarray of hexadecimal representation. hexstr may contain any number of hex digits (upper or lower case).
ba2int(bitarray, /, signed=False) -> int
Convert the given bitarray into an integer. The bit-endianness of the
bitarray is respected. signed indicates whether two's
complement is used to represent the integer.
int2ba(int, /, length=None, endian=None, signed=False)
-> bitarray
Convert the given integer to a bitarray (with given endianness, and
no leading (big-endian) / trailing (little-endian) zeros), unless the
length of the bitarray is provided. An
OverflowError is raised if the integer is not representable
with the given number of bits. signed determines whether
two's complement is used to represent the integer, and requires
length to be provided. If signed is False and a negative
integer is given, an OverflowError is raised.
huffman_code(dict, /, endian=None) -> dict
Given a frequency map, a dictionary mapping symbols to their
frequency, calculate the Huffman code, i.e. a dict mapping those symbols
to bitarrays (with given endianness). Note that the symbols may be any
hashable object (including None).
1.6.3 (2021-01-20):
1.6.2 (2021-01-20):
Py_SET_TYPE() and Py_SET_SIZE() for
Python 3.10, #1091.6.1 (2020-11-05):
1.6.0 (2020-10-17):
decodetree object, for speeding up consecutive
calls to .decode() and .iterdecode(), in
particular when dealing with large prefix codes, see #103.tolist() which changes the
items in the returned list to integers (0 or 1), as opposed to
Booleansbitdiff(), which has been deprecated
since version 1.2.0, use bitarray.util.count_xor()
instead1.5.3 (2020-08-24):
.index() to invert
single bitsys.getsizeof(bitarray) by adding
.__sizeof__(), see issue #1001.5.2 (2020-08-16):
1.5.1 (2020-08-10):
util.ba2int() and
util.int2ba(), see issue #85.length() in favor of len()1.5.0 (2020-08-05):
Py_ssize_t for bitarray index. This means that on
32bit systems, the maximun number of elements in a bitarray is 2 GBits.
We used to have a special 64bit index type for all architectures, but
this prevented us from using Python's sequence, mapping and number
methods, and made those method lookups slow.&,
|, ^, &=, |=,
^=. This should have always been the case but was
overlooked in the past.Please find the complete change log here.