Metadata-Version: 1.1
Name: bitstream
Version: 1.0.1
Summary: A Binary Data Type with a Stream Interface
Home-page: https://github.com/boisgera/bitstream
Author: Sébastien Boisgérault
Author-email: Sebastien.Boisgerault@mines-paristech.fr
License: MIT License
Description: **About this document.** It is originally a plain text file using the
        `Markdown <http://daringfireball.net/projects/markdown/>`__ syntax, but
        you may be reading a HTML, PDF or ReST version instead. In any case, the
        contents are subject to a `Creative Commons Attribution
        3.0 <http://creativecommons.org/licenses/by/3.0/>`__ license.
        
        What is Bitstream ?
        ===================
        
        Bitstream provides a binary data type with a stream interface for
        `Python <http://www.python.org/>`__.
        
        -  **Binary Data:** the ``BitStream`` class is a linearly ordered
           container of bits. The standard library is only convenient to manage
           binary data at the byte level. Consider using BitStream instead,
           especially you need to address the bit level.
        
        -  **Stream Interface:** you can only read data at the start of a stream
           and write data at its end. This is a very simple way to interact with
           binary data, but it is also the pattern that comes naturally in many
           applications. To manage binary codes and formats, in my experience,
           random data access is not a requirement.
        
        -  **Python and NumPy Types.** BitStream has built-in readers and
           writers for the common data types with a standard binary layout:
           bools, ASCII strings, fixed-size integers and floating-point
           integers.
        
        -  **User-Defined Types.** The list of supported types and binary
           representation may be enlarged at will: new readers and writers can
           be implemented and associated to specific data types.
        
        -  **Performance.** Bitstream is a Python C-extension module that has
           been optimized for the common use cases. Hopefully, it will be fast
           enough for your needs ! Under the hood, the
           `Cython <http://www.cython.org>`__ language and compiler are used to
           generate this extension module.
        
        -  **Open-Source:** the Bitstream software is distributed under a `MIT
           license <http://opensource.org/licenses/MIT>`__, its documentation
           under a `Creative Commons Attribution
           3.0 <http://creativecommons.org/licenses/by/3.0/>`__ license. The
           development takes place on
           `GitHub <https://github.com/boisgera/bitstream>`__ and releases are
           also available on `PyPi <https://pypi.python.org/pypi/bitstream/>`__.
        
        Requirements & Installation
        ===========================
        
        Bitstream targets `Python
        2.7 <http://www.python.org/download/releases/2.7>`__, you will need to
        install it first.
        
        **TODO:** move NumPy dependency here (? Dunno ...), talk about
        Linux-only platform.
        
        Then, several installation options are available: **TODO:** state
        clearly what one should do depending on the aim.
        
        -  **Easy install:** if the `pip <https://pypi.python.org/pypi/pip>`__
           package manager is available, execute the following command as root:
        
           ::
        
               $ pip install bitstream
        
           The dependencies of Bitstream will be handled automatically. If you
           don't have root privileges, use
           `virtualenv <https://pypi.python.org/pypi/virtualenv>`__.
        
        -  **Install from source:** the releases of Bitstream are available on
           the `Python Package Index
           (PyPi) <https://pypi.python.org/pypi/bitstream/>`__. Once you have
           downloaded and unpacked the archive, to build the Bitstream module,
           you need `setuptools <https://pypi.python.org/pypi/setuptools>`__.
           You also need to install the `NumPy <http://www.numpy.org/>`__
           package, version 1.6.1 or later.
        
           **TODO: test if numpy is automatically download if needed**.
        
           Then, as root, execute
        
           ::
        
               $ python setup.py install
        
        -  **Hack with git:** to experiment with the latest version of
           Bitstream, clone the GitHub repository:
        
           ::
        
               $ git clone git://github.com/boisgera/bitstream.git
        
           To actually build the module, you will need everything you need to
           build from source and will execute the same command. If in addition,
           you want to edit the source files, you will also need the
           `Cython <http://www.cython.org>`__ compiler, version 0.15.1 or later
           and will execute instead:
        
           ::
        
               $ python setup.py install --cython
        
        Getting Started
        ===============
        
        Most of the features of bitstream are available via the ``BitStream``
        class.
        
        ::
        
            >>> from bitstream import BitStream
        
        The module is tightly integrated with the
        `NumPy <http://www.numpy.org/>`__ library. For convenience, we import
        all symbols from its top-level module.
        
        ::
        
            >>> from numpy import *
        
        Overview of Bitstream Features
        ==============================
        
        ::
        
            >>> stream = BitStream()
            >>> stream
            <BLANKLINE>
            >>> stream.write(True, bool)
            >>> stream
            1
            >>> stream.write(False, bool)
            >>> stream
            10
            >>> stream.write(-128, int8)
            >>> stream
            1010000000
            >>> stream.write("AB", str)
            >>> stream
            10100000000100000101000010
            >>> stream.read(bool, 2)
            [True, False]
            >>> stream
            100000000100000101000010
            >>> stream.read(int8, 1)
            array([-128], dtype=int8)
            >>> stream
            0100000101000010
            >>> stream.read(str, 2)
            'AB'
            >>> stream
            <BLANKLINE>
        
        Built-in Readers and Writers
        ============================
        
        Bools
        -----
        
        Write single bits to a bitstream with the arguments ``True`` and
        ``False``:
        
        ::
        
            >>> stream = BitStream()
            >>> stream.write(False, bool)
            >>> stream.write(True , bool)
            >>> stream
            01
        
        Lists of booleans may be used too write multiple bits at once:
        
        ::
        
            >>> stream = BitStream()
            >>> stream.write([], bool)
            >>> stream
            <BLANKLINE>
            >>> stream.write([False], bool)
            >>> stream.write([True] , bool)
            >>> stream
            01
            >>> stream.write([False, True], bool)
            >>> stream
            0101
        
        The second argument to the ``write`` method -- the type information --
        can also be specified with the keyword argument ``type``:
        
        ::
        
            >>> stream = BitStream()
            >>> stream.write(False, type=bool)
            >>> stream.write(True , type=bool)
            >>> stream
            01
        
        For single bools or lists of bools, the type information is optional:
        
        ::
        
            >>> stream = BitStream()
            >>> stream.write(False)
            >>> stream.write(True)
            >>> stream.write([])
            >>> stream.write([False])
            >>> stream.write([True])
            >>> stream.write([False, True])
            >>> stream
            010101
        
        Numpy ``bool_`` scalars or one-dimensional arrays can be used instead:
        
        ::
        
            >>> bool_
            <type 'numpy.bool_'>
            >>> stream = BitStream()
            >>> stream.write(bool_(False)  , bool)
            >>> stream.write(bool_(True)   , bool)
            >>> stream
            01
        
            >>> stream = BitStream()
            >>> empty = array([], dtype=bool)
            >>> stream.write(empty, bool)
            >>> stream
            <BLANKLINE>
            >>> stream.write(array([False]), bool)
            >>> stream.write(array([True]) , bool)
            >>> stream.write(array([False, True]), bool)
            >>> stream
            0101
        
        For such data, the type information is also optional:
        
        ::
        
            >>> stream = BitStream()
            >>> stream.write(bool_(False))
            >>> stream.write(bool_(True))
            >>> stream.write(array([], dtype=bool))
            >>> stream.write(array([False]))
            >>> stream.write(array([True]))
            >>> stream.write(array([False, True]))
            >>> stream
            010101
        
        Python and Numpy numeric types are also valid arguments: zero is
        considered false and nonzero numbers are considered true.
        
        **Q:** Use a predicate instead (non-zero) ? and check iff ?
        
        ::
        
            >>> small_integers = range(0, 64)
            >>> stream = BitStream()
            >>> for integer in small_integers:
            ...     stream.write(integer, bool)
            >>> stream
            0111111111111111111111111111111111111111111111111111111111111111
            >>> stream = BitStream()
            >>> for integer in small_integers:
            ...     stream.write(-integer, bool)
            >>> stream
            0111111111111111111111111111111111111111111111111111111111111111
        
            >>> large_integers = [2**i for i in range(6, 64)]
            >>> stream = BitStream()
            >>> for integer in large_integers:
            ...     stream.write(integer, bool)
            >>> stream
            1111111111111111111111111111111111111111111111111111111111
            >>> stream = BitStream()
            >>> for integer in large_integers:
            ...     stream.write(-integer, bool)
            >>> stream
            1111111111111111111111111111111111111111111111111111111111
        
        **TODO:** use iinfo(type).min/max
        
        **TODO:** write ``sample(type, r)`` iterator.
        
        ::
        
            >>> def irange(start, stop, r=1.0):
            ...     i = 0
            ...     while i < stop:
            ...         yield i
            ...         i = max(i+1, int(i*r))
        
            >>> unsigned = [uint8, uint16, uint32]
            >>> for integer_type in unsigned:
            ...     _min, _max = iinfo(integer_type).min, iinfo(integer_type).max
            ...     for i in irange(_min, _max + 1, r=1.001):
            ...         integer = integer_type(i)
            ...         if integer and BitStream(integer, bool) != BitStream(True):
            ...             type_name = integer_type.__name__
            ...             print "Failure for {0}({1})".format(type_name, integer)
        
        
        
        
        
            >>> stream = BitStream()
            >>> stream.write(0.0, bool)
            >>> stream.write(1.0, bool)
            >>> stream.write(pi , bool)
            >>> stream.write(float64(0.0), bool)
            >>> stream.write(float64(1.0), bool)
            >>> stream.write(float64(pi) , bool)
            >>> stream
            011011
        
        **TODO:** arrays of numeric type (non-bools), written as bools
        
        --------------
        
        **TODO:** Mark all following behaviors as undefined ? Probably safer ...
        
        Actually, any single data written as a bool, is conceptually cast into a
        bool first, with the semantics of the ``bool`` constructor. List and
        one-dimensional numpy array arguments are considered holders of multiple
        data, each of which is converted to bool. Any other sequence type
        (strings, tuples, etc.) is considered single data.
        
        ::
        
            >>> bool("")
            False
            >>> bool(" ")
            True
            >>> bool("A")
            True
            >>> bool("AAA")
            True
        
            >>> stream = BitStream()
            >>> stream.write("", bool)
            >>> stream.write(" ", bool)
            >>> stream.write("A", bool)
            >>> stream.write("AAA", bool)
            >>> stream
            0111
            >>> stream = BitStream()
            >>> stream.write(["", " " , "A", "AAA"], bool)
            >>> stream
            0111
            >>> stream = BitStream()
            >>> stream.write(array(["", " " , "A", "AAA"]), bool)
            >>> stream
            0111
        
            >>> stream = BitStream()
            >>> stream.write(    (), bool)
            >>> stream.write(  (0,), bool)
            >>> stream.write((0, 0), bool)
            >>> stream
            011
        
            >>> stream = BitStream()
            >>> stream.write([[], [0], [0, 0]], bool)
            >>> stream
            011
        
            >>> class BoolLike(object):
            ...     def __init__(self, value):
            ...         self.value = bool(value)
            ...     def __nonzero__(self):
            ...         return self.value
            >>> false = BoolLike(False)
            >>> true = BoolLike(True)
            >>> stream = BitStream()
            >>> stream.write(false, bool)
            >>> stream.write(true, bool)
            >>> stream.write([false, true], bool)
            >>> stream
            0101
        
        TODO:
        
        -  direct call to ``write_bool`` (import the symbol first)
        -  reader tests
        
        Integers
        --------
        
        **TODO**
        
        Floating-Point Numbers
        ----------------------
        
        ::
        
            >>> import struct
            >>> struct.pack(">d", pi)
            '@\t!\xfbTD-\x18'
        
            >>> stream = BitStream()
            >>> stream.write(0.0)
            >>> stream.write([1.0, 2.0, 3.0])
            >>> stream.write(arange(4.0, 10.0))
            >>> len(stream)
            640
            >>> output = stream.read(float, 10)
            >>> type(output)
            <type 'numpy.ndarray'>
            >>> all(output == arange(10.0))
            True
        
            >>> BitStream(1.0) == BitStream(1.0, float) == BitStream(1.0, float64)
            True
            >>> BitStream(1.0) == BitStream([1.0]) == BitStream(ones(1))
            True
        
        The byte order is big endian:
        
        ::
        
            >>> BitStream(struct.pack(">d", pi)) == BitStream(pi)
            True
        
        Extra Methods
        =============
        
        **TODO:**:
        
        -  length
        
        -  str, repr
        
        -  \_extend ? Make it public ? This is low-level ... but may be
           necesssary to implement new readers/writers. Don't specify it now, as
           we don't specify the offsets / stream state, let the user only rely
           on the high-level methods.
        
        -  copy
        
        -  hash, comparison.
        
        Custom Writers and Readers
        ==========================
        
        ::
        
            >>> import bitstream
        
        Definition and Registration of Writers and Readers
        --------------------------------------------------
        
        Let's define a writer for the binary representation of natural numbers:
        
        ::
        
            >>> def write_integer(stream, data):
            ...     if isinstance(data, list):
            ...         for integer in data:
            ...             write_integer(stream, integer)
            ...     else:
            ...         integer = int(data)
            ...         if integer < 0:
            ...             error = "negative integers cannot be encoded"
            ...             raise ValueError(error)
            ...         bools = []
            ...         while integer:
            ...             bools.append(integer & 1)
            ...             integer = integer >> 1
            ...         bools.reverse()
            ...         stream.write(bools, bool)
        
        We can check that this writer behaves as expected:
        
        ::
        
            >>> stream = BitStream()
            >>> write_integer(stream, 42)
            >>> stream
            101010
            >>> write_integer(stream, [1, 2, 3])
            >>> stream
            10101011011
        
        Then, we can associate it to the type ``int``:
        
        ::
        
            >>> bitstream.register(int, writer=write_integer)
        
        After this step, ``BitStream`` will redirect all data of type ``int`` to
        this writer:
        
        ::
        
            >>> BitStream(42)
            101010
            >>> BitStream([1, 2, 3])
            11011
        
        If the type information is explicit, other kind of data can use this
        writer too:
        
        ::
        
            >>> BitStream(uint8(42), int)
            101010
            >>> BitStream("42", int)
            101010
        
        A possible implementation of the corresponding reader is given by:
        
        ::
        
            >>> def read_integer(stream, n=None):
            ...     if n is not None:
            ...         error = "unsupported argument n"
            ...         raise NotImplementedError(error)
            ...     else:
            ...         integer = 0
            ...         for _ in range(len(stream)):
            ...             integer = integer << 1
            ...             if stream.read(bool):
            ...                 integer += 1
            ...     return integer
        
            >>> read_integer(BitStream(42))
            42
        
        Once this reader is registered with
        
        ::
        
            >>> bitstream.register(int, reader=read_integer)
        
        the calls to ``read_integer`` can be made through the ``read`` method of
        ``BitStream``.
        
        ::
        
            >>> BitStream(42).read(int)
            42
        
        In all readers, the second argument of readers, named ``n``, represents
        the number of values to read from the stream. Here, this argument is not
        supported, instead any call to this reader interprets the complete
        stream content as a single value.
        
        Writer and Reader Factories
        ---------------------------
        
        We actually had a legitimate reason not to support the number of values
        argument in the binary representation reader. Indeed, when the binary
        representation is used to code sequence of integers instead of a single
        integer, it becomes ambiguous: the same bitstream may represent several
        sequences of integers. For example, we have:
        
        ::
        
            >>> BitStream(255)
            11111111
            >>> BitStream([15, 15])
            11111111
            >>> BitStream([3, 7, 3, 1])
            11111111
            >>> BitStream([3, 3, 3, 3])
            11111111
        
        We say that this code is not *self-delimiting*, as there is no way to
        know where is the boundary between the bits coding for different
        integers.
        
        For natural numbers with known bounds, we may solve this problem by
        setting a number of bits to be used for each integer. However, to do
        that, we would have to define and register a new writer for every
        possible number of bits. Instead, we register a single but configurable
        writer, defined by a writer factory.
        
        Let's define a type tag ``uint`` whose instances hold a number of bits:
        
        ::
        
            >>> class uint(object):
            ...     def __init__(self, num_bits):
            ...         self.num_bits = num_bits
        
        Then, we define a factory that given a ``uint`` instance, returns a
        stream writer:
        
        ::
        
            >>> def write_uint_factory(instance):
            ...     num_bits = instance.num_bits
            ...     def write_uint(stream, data):
            ...         if isinstance(data, list):
            ...             for integer in data:
            ...                 write_uint(stream, integer)
            ...         else:
            ...             integer = int(data)
            ...             if integer < 0:
            ...                 error = "negative integers cannot be encoded"
            ...                 raise ValueError(error)
            ...             bools = []
            ...             for _ in range(num_bits):
            ...                 bools.append(integer & 1)
            ...                 integer = integer >> 1
            ...             bools.reverse()
            ...             stream.write(bools, bool)
            ...     return write_uint
        
        Finally, we register this writer factory with ``bitstream``:
        
        ::
        
            >>> bitstream.register(uint, writer=write_uint_factory)
        
        To select a writer, we use the proper instance of type tag:
        
        ::
        
            >>> BitStream(255, uint(8))
            11111111
            >>> BitStream(255, uint(16))
            0000000011111111
            >>> BitStream(42, uint(8))
            00101010
            >>> BitStream(0, uint(16))
            0000000000000000
        
        **TODO: reader, give details, comment.**
        
        ::
        
            >>> def read_uint_factory(instance): # use the name factory ?
            ...     num_bits = instance.num_bits
            ...     def read_uint(stream, n=None):
            ...         if n is None:
            ...             integer = 0
            ...             for _ in range(num_bits):
            ...                 integer = integer << 1
            ...                 if stream.read(bool):
            ...                     integer += 1
            ...             return integer
            ...         else:
            ...             integers = [read_uint(stream) for _ in range(n)]
            ...             return integers
            ...     return read_uint
        
            >>> bitstream.register(uint, reader=read_uint_factory)
        
            >>> stream = BitStream([0, 1, 2, 3, 4], uint(8))
            >>> stream.read(uint(8))
            0
            >>> stream.read(uint(8), 1)
            [1]
            >>> stream.read(uint(8), 3)
            [2, 3, 4]
        
        Unit Tests
        ==========
        
        The text version of the document you are reading is also an executable
        specification. Check that the code examples produce the expected results
        with
        
        ::
        
            $ python -m doctest -v manual.txt
        
        Examples
        ========
        
        Unary coder / Rice coder ? Huffman tree/table coder ?
        
Platform: UNKNOWN
Classifier: Development Status :: 3 - Alpha
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: POSIX :: Linux
Classifier: Programming Language :: Python :: 2.7
Classifier: Programming Language :: Cython
