Metadata-Version: 1.0
Name: lupa
Version: 0.18
Summary: Python wrapper around LuaJIT
Home-page: http://pypi.python.org/pypi/lupa
Author: Lupa-dev mailing list
Author-email: lupa-dev@freelists.org
License: Copyright (c) 2010 Stefan Behnel. All rights reserved.

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Download-URL: http://pypi.python.org/packages/source/l/lupa/lupa-0.18.tar.gz
Description: Lupa
        =====
        
        Lupa integrates the LuaJIT2_ runtime into CPython.  It is a partial
        rewrite of LunaticPython_ in Cython_ with some additional features
        such as proper coroutine support.
        
        .. _LuaJIT2: http://luajit.org/
        .. _LunaticPython: http://labix.org/lunatic-python
        .. _Cython: http://cython.org
        
        For questions not answered here, please contact the `Lupa mailing list`_.
        
        .. _`Lupa mailing list`: http://www.freelists.org/list/lupa-dev
        
        
        Major features
        ---------------
        
        * separate Lua runtime states through a ``LuaRuntime`` class
        
        * Python coroutine wrapper for Lua coroutines
        
        * iteration support for Python objects in Lua and Lua objects in
          Python
        
        * proper encoding and decoding of strings (configurable per runtime,
          UTF-8 by default)
        
        * frees the GIL and supports threading in separate runtimes when
          calling into Lua
        
        * supports Python 2.x and 3.x, potentially starting with Python 2.3
          (currently untested)
        
        * written for LuaJIT2 (tested with LuaJIT 2.0.0-beta5), but reportedly
          works with the normal Lua interpreter (5.1+)
        
        * easy to hack on and extend as it is written in Cython, not C
        
        
        Why use it?
        ------------
        
        It complements Python very well.  Lua is a language as dynamic as
        Python, but LuaJIT compiles it to very fast machine code, sometimes
        `faster than many other compiled languages`_ for computational code.
        The language runtime is extremely small and carefully designed for
        embedding.  The complete binary module of Lupa, including a statically
        linked LuaJIT2 runtime, is only some 500KB on a 64 bit machine.
        
        .. _`faster than many other compiled languages`: http://shootout.alioth.debian.org/u64/performance.php?test=mandelbrot
        
        However, the Lua ecosystem lacks many of the batteries that Python
        readily includes, either directly in its standard library or as third
        party packages. This makes real-world Lua applications harder to write
        than equivalent Python applications. Lua is therefore not commonly
        used as primary language for large applications, but it makes for a
        fast, high-level and resource-friendly backup language inside of
        Python when raw speed is required and the edit-compile-run cycle of
        binary extension modules is too heavy and too static for agile
        development or hot-deployment.
        
        Lupa is a very fast and thin wrapper around LuaJIT.  It makes it easy
        to write dynamic Lua code that accompanies dynamic Python code by
        switching between the two languages at runtime, based on the tradeoff
        between simplicity and speed.
        
        ..
              >>> import sys
              >>> try:
              ...     orig_dlflags = sys.getdlopenflags()
              ...     sys.setdlopenflags(258)
              ...     import lupa
              ...     sys.setdlopenflags(orig_dlflags)
              ... except: pass
        
        
        Examples
        ---------
        
        ..
              ## doctest helpers:
              >>> try: _ = sorted
              ... except NameError:
              ...     def sorted(seq):
              ...         l = list(seq)
              ...         l.sort()
              ...         return l
        
        ::
        
              >>> import lupa
              >>> from lupa import LuaRuntime
              >>> lua = LuaRuntime()
        
              >>> lua.eval('1+1')
              2
        
              >>> lua_func = lua.eval('function(f, n) return f(n) end')
        
              >>> def py_add1(n): return n+1
              >>> lua_func(py_add1, 2)
              3
        
              >>> lua.eval('python.eval(" 2 ** 2 ")') == 4
              True
              >>> lua.eval('python.builtins.str(4)') == '4'
              True
        
        
        Python objects in Lua
        ----------------------
        
        Python objects are either converted when passed into Lua (e.g.
        numbers and strings) or passed as wrapped object references.
        
        ::
        
              >>> lua_type = lua.globals().type   # Lua's type() function
              >>> lua_type(1) == 'number'
              True
              >>> lua_type('abc') == 'string'
              True
        
        Wrapped Lua objects get unwrapped when they are passed back into Lua,
        and arbitrary Python objects get wrapped in different ways::
        
              >>> lua_type(lua_type) == 'function'  # unwrapped Lua function
              True
              >>> lua_type(eval) == 'userdata'      # wrapped Python function
              True
              >>> lua_type([]) == 'userdata'        # wrapped Python object
              True
        
        Lua supports two main protocols on objects: calling and indexing.  It
        does not distinguish between attribute access and item access like
        Python does, so the Lua operations ``obj[x]`` and ``obj.x`` both map
        to indexing.  To decide which Python protocol to use for Lua wrapped
        objects, Lupa employs a simple heuristic.
        
        Pratically all Python objects allow attribute access, so if the object
        also has a ``__getitem__`` method, it is preferred when turning it
        into an indexable Lua object.  Otherwise, it becomes a simple object
        that uses attribute access for indexing from inside Lua.
        
        Obviously, this heuristic will fail to provide the required behaviour
        in many cases, e.g. when attribute access is required to an object
        that happens to support item access.  To be explicit about the
        protocol that should be used, Lupa provides the helper functions
        ``as_attrgetter()`` and ``as_itemgetter()`` that restrict the view on
        an object to a certain protocol, both from Python and from inside
        Lua::
        
              >>> lua_func = lua.eval('function(obj) return obj["get"] end')
              >>> d = {'get' : 'got'}
        
              >>> value = lua_func(d)
              >>> value == 'got'
              True
        
              >>> dict_get = lua_func( lupa.as_attrgetter(d) )
              >>> dict_get('get') == 'got'
              True
        
              >>> lua_func = lua.eval(
              ...     'function(obj) return python.as_attrgetter(obj)["get"] end')
              >>> dict_get = lua_func(d)
              >>> dict_get('get') == 'got'
              True
        
        Note that unlike Lua function objects, callable Python objects are
        indexable::
        
              >>> def py_func(): pass
              >>> py_func.ATTR = 2
              >>> lua_func = lua.eval('function(obj) return obj.ATTR end')
              >>> lua_func(py_func)
              2
              >>> lua_func = lua.eval(
              ...     'function(obj) return python.as_attrgetter(obj).ATTR end')
              >>> lua_func(py_func)
              2
              >>> lua_func = lua.eval(
              ...     'function(obj) return python.as_attrgetter(obj)["ATTR"] end')
              >>> lua_func(py_func)
              2
        
        
        Iteration in Lua
        -----------------
        
        Iteration over Python objects from Lua's for-loop is fully supported.
        However, Python iterables need to be converted using one of the
        utility functions which are described here.  This is similar to the
        functions like ``pairs()`` in Lua.
        
        To iterate over a plain Python iterable, use the ``python.iter()``
        function.  For example, you can manually copy a Python list into a Lua
        table like this::
        
              >>> lua_copy = lua.eval('''
              ...     function(L)
              ...         local t, i = {}, 1
              ...         for item in python.iter(L) do
              ...             t[i] = item
              ...             i = i + 1
              ...         end
              ...         return t
              ...     end
              ... ''')
        
              >>> table = lua_copy([1,2,3,4])
              >>> len(table)
              4
              >>> table[1]   # Lua indexing
              1
        
        Python's ``enumerate()`` function is also supported, so the above
        could be simplified to::
        
              >>> lua_copy = lua.eval('''
              ...     function(L)
              ...         local t = {}
              ...         for index, item in python.enumerate(L) do
              ...             t[ index+1 ] = item
              ...         end
              ...         return t
              ...     end
              ... ''')
        
              >>> table = lua_copy([1,2,3,4])
              >>> len(table)
              4
              >>> table[1]   # Lua indexing
              1
        
        For iterators that return tuples, such as ``dict.iteritems()``, it is
        convenient to use the special ``python.iterex()`` function that
        automatically explodes the tuple items into separate Lua arguments::
        
              >>> lua_copy = lua.eval('''
              ...     function(d)
              ...         local t = {}
              ...         for key, value in python.iterex(d.items()) do
              ...             t[key] = value
              ...         end
              ...         return t
              ...     end
              ... ''')
        
              >>> d = dict(a=1, b=2, c=3)
              >>> table = lua_copy( lupa.as_attrgetter(d) )
              >>> table['b']
              2
        
        Note that accessing the ``d.items`` method from Lua requires passing
        the dict as ``attrgetter``.  Otherwise, attribute access in Lua would
        use the ``getitem`` protocol of Python dicts.
        
        
        Lua Tables
        -----------
        
        Lua tables mimic Python's mapping protocol.  For the special case of
        array tables, Lua automatically inserts integer indices as keys into
        the table.  Therefore, indexing starts from 1 as in Lua instead of 0
        as in Python.  For the same reason, negative indexing does not work.
        It is best to think of Lua tables as mappings rather than arrays, even
        for plain array tables.
        
        ::
        
              >>> table = lua.eval('{10,20,30,40}')
              >>> table[1]
              10
              >>> table[4]
              40
              >>> list(table)
              [1, 2, 3, 4]
              >>> list(table.values())
              [10, 20, 30, 40]
              >>> len(table)
              4
        
              >>> mapping = lua.eval('{ [1] = -1 }')
              >>> list(mapping)
              [1]
        
              >>> mapping = lua.eval('{ [20] = -20; [3] = -3 }')
              >>> mapping[20]
              -20
              >>> mapping[3]
              -3
              >>> sorted(mapping.values())
              [-20, -3]
              >>> sorted(mapping.items())
              [(3, -3), (20, -20)]
        
              >>> mapping[-3] = 3     # -3 used as key, not index!
              >>> mapping[-3]
              3
              >>> sorted(mapping)
              [-3, 3, 20]
              >>> sorted(mapping.items())
              [(-3, 3), (3, -3), (20, -20)]
        
        A lookup of nonexisting keys or indices returns None (actually ``nil``
        inside of Lua).  A lookup is therefore more similar to the ``.get()``
        method of Python dicts than to a mapping lookup in Python.
        
        ::
        
              >>> table[1000000] is None
              True
              >>> table['no such key'] is None
              True
              >>> mapping['no such key'] is None
              True
        
        Note that ``len()`` does the right thing for array tables but does not
        work on mappings::
        
              >>> len(table)
              4
              >>> len(mapping)
              0
        
        This is because ``len()`` is based on the ``#`` (length) operator in
        Lua and because of the way Lua defines the length of a table.
        Remember that unset table indices always return ``nil``, including
        indices outside of the table size.  Thus, Lua basically looks for an
        index that returns ``nil`` and returns the index before that.  This
        works well for array tables that do not contain ``nil`` values, gives
        barely predictable results for tables with 'holes' and does not work
        at all for mapping tables.  For tables with both sequential and
        mapping content, this ignores the mapping part completely.
        
        Note that it is best not to rely on the behaviour of len() for
        mappings.  It might change in a later version of Lupa.
        
        Similar to the table interface provided by Lua, Lupa also supports
        attribute access to table members::
        
              >>> table = lua.eval('{ a=1, b=2 }')
              >>> table.a, table.b
              (1, 2)
              >>> table.a == table['a']
              True
        
        This enables access to Lua 'methods' that are associated with a table,
        as used by the standard library modules::
        
              >>> string = lua.eval('string')    # get the 'string' library table
              >>> print( string.lower('A') )
              a
        
        
        Lua Coroutines
        ---------------
        
        The next is an example of Lua coroutines.  A wrapped Lua coroutine
        behaves exactly like a Python coroutine.  It needs to get created at
        the beginning, either by using the ``.coroutine()`` method of a
        function or by creating it in Lua code.  Then, values can be sent into
        it using the ``.send()`` method or it can be iterated over.  Note that
        the ``.throw()`` method is not supported, though.
        
        ::
        
              >>> lua_code = '''\
              ...     function(N)
              ...         for i=0,N do
              ...             coroutine.yield( i%2 )
              ...         end
              ...     end
              ... '''
              >>> lua = LuaRuntime()
              >>> f = lua.eval(lua_code)
        
              >>> gen = f.coroutine(4)
              >>> list(enumerate(gen))
              [(0, 0), (1, 1), (2, 0), (3, 1), (4, 0)]
        
        An example where values are passed into the coroutine using its
        ``.send()`` method::
        
              >>> lua_code = '''\
              ...     function()
              ...         local t,i = {},0
              ...         local value = coroutine.yield()
              ...         while value do
              ...             t[i] = value
              ...             i = i + 1
              ...             value = coroutine.yield()
              ...         end
              ...         return t
              ...     end
              ... '''
              >>> f = lua.eval(lua_code)
        
              >>> co = f.coroutine()   # create coroutine
              >>> co.send(None)        # start coroutine (stops at first yield)
        
              >>> for i in range(3):
              ...     co.send(i*2)
        
              >>> mapping = co.send(None)   # loop termination signal
              >>> list(mapping.items())
              [(0, 0), (1, 2), (2, 4)]
        
        It also works to create coroutines in Lua and to pass them back into
        Python space::
        
              >>> lua_code = '''\
              ...   function f(N)
              ...         for i=0,N do
              ...             coroutine.yield( i%2 )
              ...         end
              ...   end ;
              ...   co1 = coroutine.create(f) ;
              ...   co2 = coroutine.create(f) ;
              ...
              ...   status, first_result = coroutine.resume(co2, 2) ;   -- starting!
              ...
              ...   return f, co1, co2, status, first_result
              ... '''
        
              >>> lua = LuaRuntime()
              >>> f, co, lua_gen, status, first_result = lua.execute(lua_code)
        
              >>> # a running coroutine:
        
              >>> status
              True
              >>> first_result
              0
              >>> list(lua_gen)
              [1, 0]
              >>> list(lua_gen)
              []
        
              >>> # an uninitialised coroutine:
        
              >>> gen = co(4)
              >>> list(enumerate(gen))
              [(0, 0), (1, 1), (2, 0), (3, 1), (4, 0)]
        
              >>> gen = co(2)
              >>> list(enumerate(gen))
              [(0, 0), (1, 1), (2, 0)]
        
              >>> # a plain function:
        
              >>> gen = f.coroutine(4)
              >>> list(enumerate(gen))
              [(0, 0), (1, 1), (2, 0), (3, 1), (4, 0)]
        
        
        Threading
        ----------
        
        The following example calculates a mandelbrot image in parallel
        threads and displays the result in PIL. It is based on a `benchmark
        implementation`_ for the `Computer Language Benchmarks Game`_.
        
        .. _`Computer Language Benchmarks Game`: http://shootout.alioth.debian.org/u64/benchmark.php?test=all&lang=luajit&lang2=python3
        .. _`benchmark implementation`: http://shootout.alioth.debian.org/u64/program.php?test=mandelbrot&lang=luajit&id=1
        
        ::
        
                lua_code = '''\
                    function(N, i, total)
                        local char, unpack = string.char, unpack
                        local result = ""
                        local M, ba, bb, buf = 2/N, 2^(N%8+1)-1, 2^(8-N%8), {}
                        local start_line, end_line = N/total * (i-1), N/total * i - 1
                        for y=start_line,end_line do
                            local Ci, b, p = y*M-1, 1, 0
                            for x=0,N-1 do
                                local Cr = x*M-1.5
                                local Zr, Zi, Zrq, Ziq = Cr, Ci, Cr*Cr, Ci*Ci
                                b = b + b
                                for i=1,49 do
                                    Zi = Zr*Zi*2 + Ci
                                    Zr = Zrq-Ziq + Cr
                                    Ziq = Zi*Zi
                                    Zrq = Zr*Zr
                                    if Zrq+Ziq > 4.0 then b = b + 1; break; end
                                end
                                if b >= 256 then p = p + 1; buf[p] = 511 - b; b = 1; end
                            end
                            if b ~= 1 then p = p + 1; buf[p] = (ba-b)*bb; end
                            result = result .. char(unpack(buf, 1, p))
                        end
                        return result
                    end
                '''
        
                image_size = 1280   # == 1280 x 1280
                thread_count = 8
        
                from lupa import LuaRuntime
                lua_funcs = [ LuaRuntime(encoding=None).eval(lua_code)
                              for _ in range(thread_count) ]
        
                results = [None] * thread_count
                def mandelbrot(i, lua_func):
                    results[i] = lua_func(image_size, i+1, thread_count)
        
        	import threading
                threads = [ threading.Thread(target=mandelbrot, args=(i,lua_func))
                            for i, lua_func in enumerate(lua_funcs) ]
        	for thread in threads:
                    thread.start()
        	for thread in threads:
                    thread.join()
        
                result_buffer = b''.join(results)
        
        	# use PIL to display the image
        	import Image
                image = Image.fromstring('1', (image_size, image_size), result_buffer)
                image.show()
        
        Note how the example creates a separate ``LuaRuntime`` for each thread
        to enable parallel execution.  Each ``LuaRuntime`` is protected by a
        global lock that prevents concurrent access to it.  The low memory
        footprint of Lua makes it reasonable to use multiple runtimes, but
        this setup also means that values cannot easily be exchanged between
        threads inside of Lua.  They must either get copied through Python
        space (passing table references will not work, either) or use some Lua
        mechanism for explicit communication, such as a pipe or some kind of
        shared memory setup.
        
        
        Importing Lua binary modules
        -----------------------------
        
        To use binary modules in Lua, you need to compile them against the
        header files of the LuaJIT sources that you used to build Lupa, but do
        not link them against the LuaJIT library.
        
        Furthermore, CPython needs to enable global symbol visibility for
        shared libraries before loading the Lupa module.  This can be done by
        calling ``sys.setdlopenflags(flag_values)``.  Importing the ``lupa``
        module will automatically try to set up the correct ``dlopen`` flags
        if it can find the platform specific ``DLFCN`` Python module that
        defines the necessary flag constants.  In that case, using binary
        modules in Lua should work out of the box.
        
        If this setup fails, however, you have to set the flags manually.
        When using the above configuration call, the argument ``flag_values``
        must represent the sum of your system's values for ``RTLD_NEW`` and
        ``RTLD_GLOBAL``.  If ``RTLD_NEW`` is 2 and ``RTLD_GLOBAL`` is 256, you
        need to call ``sys.setdlopenflags(258)``.
        
        Assuming that the Lua luaposix_ (``posix``) module is available, the
        following should work on a Linux system::
        
              >>> import sys
              >>> orig_dlflags = sys.getdlopenflags()
              >>> sys.setdlopenflags(258)
              >>> import lupa
              >>> sys.setdlopenflags(orig_dlflags)
        
              >>> lua = lupa.LuaRuntime()
              >>> posix_module = lua.require('posix')     # doctest: +SKIP
        
        .. _luaposix: http://git.alpinelinux.org/cgit/luaposix
        
        
        Installing lupa
        ================
        
        #) Download and unpack lupa
        
           http://pypi.python.org/pypi/lupa
        
        #) Download LuaJIT2
        
           http://luajit.org/download.html
        
        #) Unpack the archive into the lupa base directory, e.g.::
        
             .../lupa-0.1/LuaJIT-2.0.0-beta4
        
        #) Build LuaJIT::
        
             cd LuaJIT-2.0.0-beta4
             make
             cd ..
        
           If you need specific C compiler flags, pass them to ``make`` as follows::
        
             make CFLAGS="..."
        
        #) Build lupa::
        
             python setup.py build
        
        
        
        Lupa change log
        ================
        
        0.18 (2010-11-06)
        ------------------
        
        * fix iteration by returning ``Py_None`` object for ``None`` instead
          of ``nil``, which would terminate the iteration
        
        * when converting Python values to Lua, represent ``None`` as a
          ``Py_None`` object in places where ``nil`` has a special meaning,
          but leave it as ``nil`` where it doesn't hurt
        
        * support for counter start value in ``python.enumerate()``
        
        * native implementation for ``python.enumerate()`` that is several
          times faster
        
        * much faster Lua iteration over Python objects
        
        
        0.17 (2010-11-05)
        ------------------
        
        * new helper function ``python.enumerate()`` in Lua that returns a Lua
          iterator for a Python object and adds the 0-based index to each
          item.
        
        * new helper function ``python.iterex()`` in Lua that returns a Lua
          iterator for a Python object and unpacks any tuples that the
          iterator yields.
        
        * new helper function ``python.iter()`` in Lua that returns a Lua
          iterator for a Python object.
        
        * reestablished the ``python.as_function()`` helper function for Lua
          code as it can be needed in cases where Lua cannot determine how to
          run a Python function.
        
        
        0.16 (2010-09-03)
        ------------------
        
        * dropped ``python.as_function()`` helper function for Lua as all
          Python objects are callable from Lua now (potentially raising a
          ``TypeError`` at call time if they are not callable)
        
        * fix regression in 0.13 and later where ordinary Lua functions failed
          to print due to an accidentally used meta table
        
        * fix crash when calling ``str()`` on wrapped Lua objects without
          metatable
        
        
        0.15 (2010-09-02)
        ------------------
        
        * support for loading binary Lua modules on systems that support it
        
        
        0.14 (2010-08-31)
        ------------------
        
        * relicensed to the MIT license used by LuaJIT2 to simplify licensing
          considerations
        
        
        0.13.1 (2010-08-30)
        --------------------
        
        * fix Cython generated C file using Cython 0.13
        
        
        0.13 (2010-08-29)
        ------------------
        
        * fixed undefined behaviour on ``str(lua_object)`` when the object's
          ``__tostring()`` meta method fails
        
        * removed redundant "error:" prefix from ``LuaError`` messages
        
        * access to Python's ``python.builtins`` from Lua code
        
        * more generic wrapping rules for Python objects based on supported
          protocols (callable, getitem, getattr)
        
        * new helper functions ``as_attrgetter()`` and ``as_itemgetter()`` to
          specify the Python object protocol used by Lua indexing when
          wrapping Python objects in Python code
        
        * new helper functions ``python.as_attrgetter()``,
          ``python.as_itemgetter()`` and ``python.as_function()`` to specify
          the Python object protocol used by Lua indexing of Python objects in
          Lua code
        
        * item and attribute access for Python objects from Lua code
        
        
        0.12 (2010-08-16)
        ------------------
        
        * fix Lua stack leak during table iteration
        
        * fix lost Lua object reference after iteration
        
        
        0.11 (2010-08-07)
        ------------------
        
        * error reporting on Lua syntax errors failed to clean up the stack so
          that errors could leak into the next Lua run
        
        * Lua error messages were not properly decoded
        
        
        0.10 (2010-07-27)
        ------------------
        
        * much faster locking of the LuaRuntime, especially in the single
          threaded case (see
          http://code.activestate.com/recipes/577336-fast-re-entrant-optimistic-lock-implemented-in-cyt/)
        
        * fixed several error handling problems when executing Python code
          inside of Lua
        
        
        0.9 (2010-07-23)
        -----------------
        
        * fixed Python special double-underscore method access on LuaObject
          instances
        
        * Lua coroutine support through dedicated wrapper classes, including
          Python iteration support.  In Python space, Lua coroutines behave
          exactly like Python generators.
        
        
        0.8 (2010-07-21)
        -----------------
        
        * support for returning multiple values from Lua evaluation
        
        * ``repr()`` support for Lua objects
        
        * ``LuaRuntime.table()`` method for creating Lua tables from Python
          space
        
        * encoding fix for ``str(LuaObject)``
        
        
        0.7 (2010-07-18)
        -----------------
        
        * ``LuaRuntime.require()`` and ``LuaRuntime.globals()`` methods
        
        * renamed ``LuaRuntime.run()`` to ``LuaRuntime.execute()``
        
        * support for ``len()``, ``setattr()`` and subscripting of Lua objects
        
        * provide all built-in Lua libraries in ``LuaRuntime``, including
          support for library loading
        
        * fixed a thread locking issue
        
        * fix passing Lua objects back into the runtime from Python space
        
        
        0.6 (2010-07-18)
        -----------------
        
        * Python iteration support for Lua objects (e.g. tables)
        
        * threading fixes
        
        * fix compile warnings
        
        
        0.5 (2010-07-14)
        -----------------
        
        * explicit encoding options per LuaRuntime instance to decode/encode
          strings and Lua code
        
        
        0.4 (2010-07-14)
        -----------------
        
        * attribute read access on Lua objects, e.g. to read Lua table values
          from Python
        
        * str() on Lua objects
        
        * include .hg repository in source downloads
        
        * added missing files to source distribution
        
        
        0.3 (2010-07-13)
        -----------------
        
        * fix several threading issues
        
        * safely free the GIL when calling into Lua
        
        
        0.2 (2010-07-13)
        -----------------
        
        * propagate Python exceptions through Lua calls
        
        
        0.1 (2010-07-12)
        -----------------
        
        * first public release
        
Platform: UNKNOWN
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Information Technology
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Cython
Classifier: Programming Language :: Python :: 2
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Other Scripting Engines
Classifier: Operating System :: OS Independent
Classifier: Topic :: Software Development
