Metadata-Version: 2.2
Name: lupa
Version: 2.4
Summary: Python wrapper around Lua and LuaJIT
Home-page: https://github.com/scoder/lupa
Author: Stefan Behnel
Author-email: stefan_ml@behnel.de
Maintainer: Lupa-dev mailing list
Maintainer-email: lupa-dev@freelists.org
License: MIT style
Classifier: Development Status :: 5 - Production/Stable
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Information Technology
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Cython
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Lua
Classifier: Programming Language :: Other Scripting Engines
Classifier: Operating System :: OS Independent
Classifier: Topic :: Software Development
License-File: LICENSE.txt
Dynamic: author
Dynamic: author-email
Dynamic: classifier
Dynamic: description
Dynamic: home-page
Dynamic: license
Dynamic: maintainer
Dynamic: maintainer-email
Dynamic: summary

Lupa
====

.. image:: logo/logo-220x200.png

Lupa integrates the runtimes of Lua_ or LuaJIT2_ into CPython.
It is a partial rewrite of LunaticPython_ in Cython_ with some
additional features such as proper coroutine support.

.. _Lua: http://lua.org/
.. _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

.. contents:: :local:


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

* tested with Python 2.7/3.6 and later

* ships with Lua 5.1, 5.2, 5.3 and 5.4
  as well as LuaJIT 2.0 and 2.1 on systems that support it.

* easy to hack on and extend as it is written in Cython, not C


Why the name?
-------------

In Latin, "lupa" is a female wolf, as elegant and wild as it sounds.
If you don't like this kind of straight forward allegory to an
endangered species, you may also happily assume it's just an
amalgamation of the phonetic sounds that start the words "Lua" and
"Python", two from each to keep the balance.


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 statically compiled languages for computational code.
The language runtime is very small and carefully designed for
embedding.  The complete binary module of Lupa, including a statically
linked LuaJIT2 runtime, only weighs some 800KB on a 64 bit machine.
With standard Lua 5.2, it's less than 600KB.

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 Lua or 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.


Which Lua version?
------------------

The binary wheels include different Lua versions as well as LuaJIT, if supported.
By default, ``import lupa`` uses the latest Lua version, but you can choose
a specific one via import:

.. code:: python

    try:
        import lupa.luajit21 as lupa
    except ImportError:
        try:
            import lupa.lua54 as lupa
        except ImportError:
            try:
                import lupa.lua53 as lupa
            except ImportError:
                import lupa

    print(f"Using {lupa.LuaRuntime().lua_implementation} (compiled with {lupa.LUA_VERSION})")


Examples
--------

..
      >>> import lupa.lua54 as lupa

      ## doctest helpers:
      >>> try: _ = sorted
      ... except NameError:
      ...     def sorted(seq):
      ...         l = list(seq)
      ...         l.sort()
      ...         return l

.. code:: python

      >>> from lupa.lua54 import LuaRuntime
      >>> lua = LuaRuntime(unpack_returned_tuples=True)

      >>> 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

The function ``lua_type(obj)`` can be used to find out the type of a
wrapped Lua object in Python code, as provided by Lua's ``type()``
function:

.. code:: python

      >>> lupa.lua_type(lua_func)
      'function'
      >>> lupa.lua_type(lua.eval('{}'))
      'table'

To help in distinguishing between wrapped Lua objects and normal
Python objects, it returns ``None`` for the latter:

.. code:: python

      >>> lupa.lua_type(123) is None
      True
      >>> lupa.lua_type('abc') is None
      True
      >>> lupa.lua_type({}) is None
      True

Note the flag ``unpack_returned_tuples=True`` that is passed to create
the Lua runtime.  It is new in Lupa 0.21 and changes the behaviour of
tuples that get returned by Python functions.  With this flag, they
explode into separate Lua values:

.. code:: python

      >>> lua.execute('a,b,c = python.eval("(1,2)")')
      >>> g = lua.globals()
      >>> g.a
      1
      >>> g.b
      2
      >>> g.c is None
      True

When set to False, functions that return a tuple pass it through to the
Lua code:

.. code:: python

      >>> non_explode_lua = lupa.LuaRuntime(unpack_returned_tuples=False)
      >>> non_explode_lua.execute('a,b,c = python.eval("(1,2)")')
      >>> g = non_explode_lua.globals()
      >>> g.a
      (1, 2)
      >>> g.b is None
      True
      >>> g.c is None
      True

Since the default behaviour (to not explode tuples) might change in a
later version of Lupa, it is best to always pass this flag explicitly.


Python objects in Lua
---------------------

Python objects are either converted when passed into Lua (e.g.
numbers and strings) or passed as wrapped object references.

.. code:: python

      >>> wrapped_type = lua.globals().type     # Lua's own type() function
      >>> wrapped_type(1) == 'number'
      True
      >>> wrapped_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:

.. code:: python

      >>> wrapped_type(wrapped_type) == 'function'  # unwrapped Lua function
      True
      >>> wrapped_type(len) == 'userdata'       # wrapped Python function
      True
      >>> wrapped_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:

.. code:: python

      >>> lua_func = lua.eval('function(obj) return obj["get"] end')
      >>> d = {'get' : 'value'}

      >>> value = lua_func(d)
      >>> value == d['get'] == 'value'
      True

      >>> value = lua_func( lupa.as_itemgetter(d) )
      >>> value == d['get'] == 'value'
      True

      >>> dict_get = lua_func( lupa.as_attrgetter(d) )
      >>> dict_get == d.get
      True
      >>> dict_get('get') == d.get('get') == 'value'
      True

      >>> lua_func = lua.eval(
      ...     'function(obj) return python.as_attrgetter(obj)["get"] end')
      >>> dict_get = lua_func(d)
      >>> dict_get('get') == d.get('get') == 'value'
      True

Note that unlike Lua function objects, callable Python objects support
indexing in Lua:

.. code:: python

      >>> 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:

.. code:: python

      >>> 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:

.. code:: python

      >>> 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:

.. code:: python

      >>> 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 and look up ``d['items']``
instead.


None vs. nil
------------

While ``None`` in Python and ``nil`` in Lua differ in their semantics, they
usually just mean the same thing: no value.  Lupa therefore tries to map one
directly to the other whenever possible:

.. code:: python

      >>> lua.eval('nil') is None
      True
      >>> is_nil = lua.eval('function(x) return x == nil end')
      >>> is_nil(None)
      True

The only place where this cannot work is during iteration, because Lua
considers a ``nil`` value the termination marker of iterators.  Therefore,
Lupa special cases ``None`` values here and replaces them by a constant
``python.none`` instead of returning ``nil``:

.. code:: python

      >>> _ = lua.require("table")
      >>> func = lua.eval('''
      ...     function(items)
      ...         local t = {}
      ...         for value in python.iter(items) do
      ...             table.insert(t, value == python.none)
      ...         end
      ...         return t
      ...     end
      ... ''')

      >>> items = [1, None ,2]
      >>> list(func(items).values())
      [False, True, False]

Lupa avoids this value escaping whenever it's obviously not necessary.
Thus, when unpacking tuples during iteration, only the first value will
be subject to ``python.none`` replacement, as Lua does not look at the
other items for loop termination anymore.  And on ``enumerate()``
iteration, the first value is known to be always a number and never None,
so no replacement is needed.

.. code:: python

      >>> func = lua.eval('''
      ...     function(items)
      ...         for a, b, c, d in python.iterex(items) do
      ...             return {a == python.none, a == nil,   -->  a == python.none
      ...                     b == python.none, b == nil,   -->  b == nil
      ...                     c == python.none, c == nil,   -->  c == nil
      ...                     d == python.none, d == nil}   -->  d == nil ...
      ...         end
      ...     end
      ... ''')

      >>> items = [(None, None, None, None)]
      >>> list(func(items).values())
      [True, False, False, True, False, True, False, True]

      >>> items = [(None, None)]   # note: no values for c/d => nil in Lua
      >>> list(func(items).values())
      [True, False, False, True, False, True, False, True]


Note that this behaviour changed in Lupa 1.0.  Previously, the ``python.none``
replacement was done in more places, which made it not always very predictable.


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.

.. code:: python

      >>> table = lua.eval('{10,20,30,40}')
      >>> table[1]
      10
      >>> table[4]
      40
      >>> list(table)
      [1, 2, 3, 4]
      >>> dict(table)
      {1: 10, 2: 20, 3: 30, 4: 40}
      >>> 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)]

To simplify the table creation from Python, the ``LuaRuntime`` comes with
a helper method that creates a Lua table from Python arguments:

.. code:: python

      >>> t = lua.table(10, 20, 30, 40)
      >>> lupa.lua_type(t)
      'table'
      >>> list(t)
      [1, 2, 3, 4]
      >>> list(t.values())
      [10, 20, 30, 40]

      >>> t = lua.table(10, 20, 30, 40, a=1, b=2)
      >>> t[3]
      30
      >>> t['b']
      2

A second helper method, ``.table_from()``, was added in Lupa 1.1 and accepts
any number of mappings and sequences/iterables as arguments.  It collects
all values and key-value pairs and builds a single Lua table from them.
Any keys that appear in multiple mappings get overwritten with their last
value (going from left to right).

.. code:: python

      >>> t = lua.table_from([10, 20, 30], {'a': 11, 'b': 22}, (40, 50), {'b': 42})
      >>> t['a']
      11
      >>> t['b']
      42
      >>> t[5]
      50
      >>> sorted(t.values())
      [10, 11, 20, 30, 40, 42, 50]

Since Lupa 2.1, passing ``recursive=True`` will map data structures recursively
to Lua tables.

.. code:: python

      >>> t = lua.table_from(
      ...     [
      ...         # t1:
      ...         [
      ...             [10, 20, 30],
      ...             {'a': 11, 'b': 22}
      ...         ],
      ...         # t2:
      ...         [
      ...             (40, 50),
      ...             {'b': 42}
      ...         ]
      ...     ],
      ...     recursive=True
      ... )
      >>> t1, t2 = t.values()
      >>> list(t1[1].values())
      [10, 20, 30]
      >>> t1[2]['a']
      11
      >>> t1[2]['b']
      22
      >>> t2[2]['b']
      42
      >>> list(t1[1].values())
      [10, 20, 30]
      >>> list(t2[1].values())
      [40, 50]

A lookup of non-existing 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.

.. code:: python

      >>> table = lua.table(10, 20, 30, 40)
      >>> table[1000000] is None
      True
      >>> table['no such key'] is None
      True

      >>> mapping = lua.eval('{ [20] = -20; [3] = -3 }')
      >>> mapping['no such key'] is None
      True

Note that ``len()`` does the right thing for array tables but does not
work on mappings:

.. code:: python

      >>> 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:

.. code:: python

      >>> 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:

.. code:: python

      >>> string = lua.eval('string')    # get the 'string' library table
      >>> print( string.lower('A') )
      a


Python Callables
----------------

As discussed earlier, Lupa allows Lua scripts to call Python functions
and methods:

.. code:: python

      >>> def add_one(num):
      ...     return num + 1
      >>> lua_func = lua.eval('function(num, py_func) return py_func(num) end')
      >>> lua_func(48, add_one)
      49

      >>> class MyClass():
      ...     def my_method(self):
      ...         return 345
      >>> obj = MyClass()
      >>> lua_func = lua.eval('function(py_obj) return py_obj:my_method() end')
      >>> lua_func(obj)
      345

Lua doesn't have a dedicated syntax for named arguments, so by default
Python callables can only be called using positional arguments.

A common pattern for implementing named arguments in Lua is passing them
in a table as the first and only function argument.  See
http://lua-users.org/wiki/NamedParameters for more details.  Lupa supports
this pattern by providing two decorators: ``lupa.unpacks_lua_table``
for Python functions and ``lupa.unpacks_lua_table_method`` for methods
of Python objects.

Python functions/methods wrapped in these decorators can be called from
Lua code as ``func(foo, bar)``, ``func{foo=foo, bar=bar}``
or ``func{foo, bar=bar}``.  Example:

.. code:: python

      >>> @lupa.unpacks_lua_table
      ... def add(a, b):
      ...     return a + b
      >>> lua_func = lua.eval('function(a, b, py_func) return py_func{a=a, b=b} end')
      >>> lua_func(5, 6, add)
      11
      >>> lua_func = lua.eval('function(a, b, py_func) return py_func{a, b=b} end')
      >>> lua_func(5, 6, add)
      11

If you do not control the function implementation, you can also just
manually wrap a callable object when passing it into Lupa:

.. code:: python

      >>> import operator
      >>> wrapped_py_add = lupa.unpacks_lua_table(operator.add)

      >>> lua_func = lua.eval('function(a, b, py_func) return py_func{a, b} end')
      >>> lua_func(5, 6, wrapped_py_add)
      11

There are some limitations:

1. Avoid using ``lupa.unpacks_lua_table`` and ``lupa.unpacks_lua_table_method``
   for functions where the first argument can be a Lua table.  In this case
   ``py_func{foo=bar}`` (which is the same as ``py_func({foo=bar})`` in Lua)
   becomes ambiguous: it could mean either "call ``py_func`` with a named
   ``foo`` argument" or "call ``py_func`` with a positional ``{foo=bar}``
   argument".

2. One should be careful with passing ``nil`` values to callables wrapped in
   ``lupa.unpacks_lua_table`` or ``lupa.unpacks_lua_table_method`` decorators.
   Depending on the context, passing ``nil`` as a parameter can mean either
   "omit a parameter" or "pass None".  This even depends on the Lua version.

   It is possible to use ``python.none`` instead of ``nil`` to pass None values
   robustly.  Arguments with ``nil`` values are also fine when standard braces
   ``func(a, b, c)`` syntax is used.

Because of these limitations lupa doesn't enable named arguments for all
Python callables automatically.  Decorators allow to enable named arguments
on a per-callable basis.


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.

.. code:: python

      >>> 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:

.. code:: python

      >>> 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
      >>> sorted(mapping.items())
      [(0, 0), (1, 2), (2, 4)]

It also works to create coroutines in Lua and to pass them back into
Python space:

.. code:: python

      >>> 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

.. code:: python

    lua_code = '''\
        function(N, i, total)
            local char, unpack = string.char, table.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 Pillow to display the image
    from PIL import Image
    image = Image.frombytes('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.


Restricting Lua access to Python objects
----------------------------------------

..
        >>> try: unicode = unicode
        ... except NameError: unicode = str

Lupa provides a simple mechanism to control access to Python objects.
Each attribute access can be passed through a filter function as
follows:

.. code:: python

        >>> def filter_attribute_access(obj, attr_name, is_setting):
        ...     if isinstance(attr_name, unicode):
        ...         if not attr_name.startswith('_'):
        ...             return attr_name
        ...     raise AttributeError('access denied')

        >>> lua = lupa.LuaRuntime(
        ...           register_eval=False,
        ...           attribute_filter=filter_attribute_access)
        >>> func = lua.eval('function(x) return x.__class__ end')
        >>> func(lua)
        Traceback (most recent call last):
         ...
        AttributeError: access denied

The ``is_setting`` flag indicates whether the attribute is being read
or set.

Note that the attributes of Python functions provide access to the
current ``globals()`` and therefore to the builtins etc.  If you want
to safely restrict access to a known set of Python objects, it is best
to work with a whitelist of safe attribute names.  One way to do that
could be to use a well selected list of dedicated API objects that you
provide to Lua code, and to only allow Python attribute access to the
set of public attribute/method names of these objects.

Since Lupa 1.0, you can alternatively provide dedicated getter and
setter function implementations for a ``LuaRuntime``:

.. code:: python

        >>> def getter(obj, attr_name):
        ...     if attr_name == 'yes':
        ...         return getattr(obj, attr_name)
        ...     raise AttributeError(
        ...         'not allowed to read attribute "%s"' % attr_name)

        >>> def setter(obj, attr_name, value):
        ...     if attr_name == 'put':
        ...         setattr(obj, attr_name, value)
        ...         return
        ...     raise AttributeError(
        ...         'not allowed to write attribute "%s"' % attr_name)

        >>> class X(object):
        ...     yes = 123
        ...     put = 'abc'
        ...     noway = 2.1

        >>> x = X()

        >>> lua = lupa.LuaRuntime(attribute_handlers=(getter, setter))
        >>> func = lua.eval('function(x) return x.yes end')
        >>> func(x)  # getting 'yes'
        123
        >>> func = lua.eval('function(x) x.put = "ABC"; end')
        >>> func(x)  # setting 'put'
        >>> print(x.put)
        ABC
        >>> func = lua.eval('function(x) x.noway = 42; end')
        >>> func(x)  # setting 'noway'
        Traceback (most recent call last):
         ...
        AttributeError: not allowed to write attribute "noway"


Restricting Lua Memory Usage
----------------------------

Lupa provides a simple mechanism to control the maximum memory
usage of the Lua Runtime since version 2.0.
By default Lupa does not interfere with Lua's memory allocation, to opt-in
you must set the ``max_memory`` when creating the LuaRuntime.

The ``LuaRuntime`` provides three methods for controlling and reading the
memory usage:

1. ``get_memory_used(total=False)`` to get the current memory
   usage of the LuaRuntime.

2. ``get_max_memory(total=False)`` to get the current memory limit.
   ``0`` means there is no memory limitation.

3. ``set_max_memory(max_memory, total=False)`` to change the memory limit.
   Values below or equal to 0 mean no limit.

There is always some memory used by the LuaRuntime itself (around ~20KiB,
depending on your lua version and other factors) which is excluded from all
calculations unless you specify ``total=True``.

.. code:: python

        >>> from lupa import lua52
        >>> lua = lua52.LuaRuntime(max_memory=0)  # 0 for unlimited, default is None
        >>> lua.get_memory_used()  # memory used by your code
        0
        >>> total_lua_memory = lua.get_memory_used(total=True)  # includes memory used by the runtime itself
        >>> assert total_lua_memory > 0  # exact amount depends on your lua version and other factors


Lua code hitting the memory limit will receive memory errors:

.. code:: python
      
        >>> lua.set_max_memory(100)
        >>> lua.eval("string.rep('a', 1000)")   # doctest: +IGNORE_EXCEPTION_DETAIL
        Traceback (most recent call last):
         ...
        lupa.LuaMemoryError: not enough memory

``LuaMemoryError`` inherits from ``LuaError`` and ``MemoryError``.


Importing Lua binary modules
----------------------------

**This will usually work as is**, but here are the details, in case
anything goes wrong for you.

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:

.. code:: python

      >>> 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


Building with different Lua versions
------------------------------------

The build is configured to automatically search for an installed version
of first LuaJIT and then Lua, and failing to find either, to use the bundled
LuaJIT or Lua version.

If you wish to build Lupa with a specific version of Lua, you can
configure the following options on setup:

.. list-table::
   :widths: 20 35
   :header-rows: 1

   * - Option
     - Description
   * - ``--lua-lib <libfile>``
     - Lua library file path, e.g. ``--lua-lib /usr/local/lib/lualib.a``
   * - ``--lua-includes <incdir>``
     - Lua include directory, e.g. ``--lua-includes /usr/local/include``
   * - ``--use-bundle``
     - Use bundled LuaJIT or Lua instead of searching for an installed version.
   * - ``--no-bundle``
     - Don't use the bundled LuaJIT/Lua, search for an installed version of LuaJIT or Lua,
       e.g. using ``pkg-config``.
   * - ``--no-lua-jit``
     - Don't use or search for LuaJIT, only use or search Lua instead.


Installing lupa
===============

Building with LuaJIT2
---------------------

#) 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-2.0.2

#) Build LuaJIT::

     cd LuaJIT-2.0.2
     make
     cd ..

   If you need specific C compiler flags, pass them to ``make`` as follows::

     make CFLAGS="..."

   For trickier target platforms like Windows and MacOS-X, please see
   the official `installation instructions for LuaJIT`_.

   NOTE: When building on Windows, make sure that lua51.lib is made in addition
   to lua51.dll. The MSVC build produces this file, MinGW does NOT.

#) Build lupa::

     python setup.py build_ext -i

   Or any other distutils target of your choice, such as ``build``
   or one of the ``bdist`` targets.  See the `distutils
   documentation`_ for help, also the `hints on building extension
   modules`_.

   Note that on 64bit MacOS-X installations, the following additional
   compiler flags are reportedly required due to the embedded LuaJIT::

     -pagezero_size 10000 -image_base 100000000

   You can find additional installation hints for MacOS-X in this
   `somewhat unclear blog post`_, which may or may not tell you at
   which point in the installation process to provide these flags.

   Also, on 64bit MacOS-X, you will typically have to set the
   environment variable ``ARCHFLAGS`` to make sure it only builds
   for your system instead of trying to generate a fat binary with
   both 32bit and 64bit support::

     export ARCHFLAGS="-arch x86_64"

   Note that this applies to both LuaJIT and Lupa, so make sure
   you try a clean build of everything if you forgot to set it
   initially.

.. _`installation instructions for LuaJIT`: http://luajit.org/install.html
.. _`somewhat unclear blog post`: http://t-p-j.blogspot.com/2010/11/lupa-on-os-x-with-macports-python-26.html
.. _`distutils documentation`: http://docs.python.org/install/index.html#install-index
.. _`hints on building extension modules`: http://docs.python.org/install/index.html#building-extensions-tips-and-tricks


Building with Lua 5.x
---------------------

It also works to use Lupa with the standard (non-JIT) Lua
runtime. The easiest way is to use the bundled lua submodule:

#) Clone the submodule::

     $ git submodule update --init third-party/lua
     
#) Build Lupa::

     $ python3 setup.py bdist_wheel --use-bundle --with-cython

You can also build it by installing a Lua 5.x package, including
any development packages (header files etc.). On systems that
use the "pkg-config" configuration mechanism, Lupa's
setup.py will pick up either LuaJIT2 or Lua automatically, with a
preference for LuaJIT2 if it is found.  Pass the ``--no-luajit`` option
to the setup.py script if you have both installed but do not want to
use LuaJIT2.

On other systems, you may have to supply the build parameters
externally, e.g. using environment variables or by changing the
setup.py script manually.  Pass the ``--no-luajit`` option to the
setup.py script in order to ignore the failure you get when neither
LuaJIT2 nor Lua are found automatically.

For further information, read this mailing list post:

https://www.freelists.org/post/lupa-dev/Lupa-with-normal-Lua-interpreter-Lua-51,2


Installing lupa from packages
=============================

Debian/Ubuntu + Lua 5.2
-----------------------

#) Install Lua 5.2 development package::

     $ apt-get install liblua5.2-dev

#) Install lupa::

     $ pip install lupa

Debian/Ubuntu + LuaJIT2
-----------------------

#) Install LuaJIT2 development package::

     $ apt-get install libluajit-5.1-dev

#) Install lupa::

     $ pip install lupa

Depending on OS version, you might get an older LuaJIT2 version.

OS X + Lua 5.2 + Homebrew
-------------------------

#) Install Lua::

     $ brew install lua

#) Install pkg-config::

     $ brew install pkg-config

#) Install lupa::

     $ pip install lupa


Lupa change log
===============

2.4 (2025-01-10)
----------------

* The windows wheels now bundle LuaJIT 2.0 and 2.1.
  (patch by Michal Plichta)

* Failures in the test suite didn't set a non-zero process exit value.


2.3 (2025-01-09)
----------------

* The bundled LuaJIT versions were updated to the latest git branches.

* The bundled Lua 5.4 was updated to 5.4.7.

* Removed support for Python 2.x.

* Built with Cython 3.0.11.


2.2 (2024-06-02)
----------------

* A new method ``LuaRuntime.gccollect()`` was added to trigger the Lua garbage collector.

* A new context manager ``LuaRuntime.nogc()`` was added to temporarily disable the Lua
  garbage collector.

* Freeing Python objects from a thread while running Lua code could run into a deadlock.

* The bundled LuaJIT versions were updated to the latest git branches.

* Built with Cython 3.0.10.


2.1 (2024-03-24)
----------------

* GH#199: The ``table_from()`` method gained a new keyword argument ``recursive=False``.
  If true, Python data structures will be recursively mapped to Lua tables,
  taking care of loops and duplicates via identity de-duplication.

* GH#248: The LuaRuntime methods "eval", "execute" and "compile" gained new
  keyword options ``mode`` and ``name`` that allow constraining the input type
  and modifying the (chunk) name shown in error messages, following similar
  arguments in the Lua ``load()`` function.
  See https://www.lua.org/manual/5.4/manual.html#pdf-load

* GH#246: Loading Lua modules did not work for the version specific Lua modules
  introduced in Lupa 2.0.  It turned out that it can only be enabled for
  one of them in a given Python run, so it is now left to users to enable it
  explicitly at need.
  (original patch by Richard Connon)

* GH#234: The bundled Lua 5.1 was updated to 5.1.5 and Lua 5.2 to 5.2.4.
  (patch by xxyzz)

* The bundled Lua 5.4 was updated to 5.4.6.

* The bundled LuaJIT versions were updated to the latest git branches.

* Built with Cython 3.0.9 for improved support of Python 3.12/13.


2.0 (2023-04-03)
----------------

* GH#217: Lua stack traces in Python exception messages are now reversed to
  match the order of Python stack traces.

* GH#196: Lupa now ships separate extension modules built with Lua 5.3,
  Lua 5.4, LuaJIT 2.0 and LuaJIT 2.1 beta.  Note that this is build specific
  and may depend on the platform.  A normal Python import cascade can be used.

* GH#211: A new option `max_memory` allows to limit the memory usage of Lua code.
  (patch by Leo Developer)

* GH#171: Python references in Lua are now more safely reference counted
  to prevent garbage collection glitches.
  (patch by Guilherme Dantas)

* GH#146: Lua integers in Lua 5.3+ are converted from and to Python integers.
  (patch by Guilherme Dantas)

* GH#180: The ``python.enumerate()`` function now returns indices as integers
  if supported by Lua.
  (patch by Guilherme Dantas)

* GH#178: The Lua integer limits can be read from the module as
  ``LUA_MAXINTEGER`` and ``LUA_MININTEGER``.
  (patch by Guilherme Dantas)

* GH#174: Failures while calling the ``__index`` method in Lua during a
  table index lookup from Python could crash Python.
  (patch by Guilherme Dantas)

* GH#137: Passing ``None`` as a dict key into ``table_from()`` crashed.
  (patch by Leo Developer)

* GH#176: A new function ``python.args(*args, **kwargs)`` was added
  to help with building Python argument tuples and keyword argument dicts
  for Python function calls from Lua code.

* GH#177: Tables that are not sequences raise ``IndexError`` when unpacking
  them.  Previously, non-sequential items were simply ignored.

* GH#179: Resolve some C compiler warnings about signed/unsigned comparisons.
  (patch by Guilherme Dantas)

* Built with Cython 0.29.34.


1.14.1 (2022-11-16)
-------------------

* Rebuild with Cython 0.29.32 to support Python 3.11.


1.13 (2022-03-01)
-----------------

* Bundled Lua source files were missing in the source distribution.


1.12 (2022-02-24)
-----------------

* GH#197: Some binary wheels in the last releases were not correctly linked with Lua.

* GH#194: An absolute file path appeared in the ``SOURCES.txt`` metadata
  of the source distribution.


1.11 (2022-02-23)
-----------------

* Use Lua 5.4.4 in binary wheels and as bundled Lua.

* Built with Cython 0.29.28 to support Python 3.10/11.


1.10 (2021-09-02)
-----------------

* GH#147: Lua 5.4 is supported.
  (patch by Russel Davis)

* The runtime version of the Lua library as a tuple (e.g. ``(5,3)``)
  is provided via ``lupa.LUA_VERSION`` and ``LuaRuntime.lua_version``.

* The Lua implementation name and version string is provided as
  ``LuaRuntime.lua_implementation``.

* ``setup.py`` accepts new command line arguments ``--lua-lib`` and ``--lua-includes``
  to specify the

* Use Lua 5.4.3 in binary wheels and as bundled Lua.

* Built with Cython 0.29.24 to support Python 3.9.


1.9 (2019-12-21)
----------------

* Build against Lua 5.3 if available.

* Use Lua 5.3.5 in binary wheels and as bundled Lua.

* GH#129: Fix Lua module loading in Python 3.x.

* GH#126: Fix build on Linux systems that install Lua as "lua52" package.

* Built with Cython 0.29.14 for better Py3.8 compatibility.


1.8 (2019-02-01)
----------------

* GH#107: Fix a deprecated import in Py3.

* Built with Cython 0.29.3 for better Py3.7 compatibility.


1.7 (2018-08-06)
----------------

* GH#103: Provide wheels for MS Windows and fix MSVC build on Py2.7.


1.6 (2017-12-15)
----------------

* GH#95: Improved compatibility with Lua 5.3.
  (patch by TitanSnow)


1.5 (2017-09-16)
----------------

* GH#93: New method ``LuaRuntime.compile()`` to compile Lua code
  without executing it.
  (patch by TitanSnow)

* GH#91: Lua 5.3 is bundled in the source distribution to simplify
  one-shot installs.
  (patch by TitanSnow)

* GH#87: Lua stack trace is included in output in debug mode.
  (patch by aaiyer)

* GH#78: Allow Lua code to intercept Python exceptions.
  (patch by Sergey Dobrov)

* Built with Cython 0.26.1.


1.4 (2016-12-10)
----------------

* GH#82: Lua coroutines were using the wrong runtime state
  (patch by Sergey Dobrov)

* GH#81: copy locally provided Lua DLL into installed package on Windows
  (patch by Gareth Coles)

* built with Cython 0.25.2


1.3 (2016-04-12)
----------------

* GH#70: ``eval()`` and ``execute()`` accept optional positional arguments
  (patch by John Vandenberg)

* GH#65: calling ``str()`` on a Python object from Lua could fail if the
  ``LuaRuntime`` is set up without auto-encoding (patch by Mikhail Korobov)

* GH#63: attribute/keyword names were not properly encoded if the
  ``LuaRuntime`` is set up without auto-encoding (patch by Mikhail Korobov)

* built with Cython 0.24


1.2 (2015-10-10)
----------------

* callbacks returned from Lua coroutines were incorrectly mixing
  coroutine state with global Lua state (patch by Mikhail Korobov)

* availability of ``python.builtins`` in Lua can be disabled via
  ``LuaRuntime`` option.

* built with Cython 0.23.4


1.1 (2014-11-21)
----------------

* new module function ``lupa.lua_type()`` that returns the Lua type of
  a wrapped object as string, or ``None`` for normal Python objects

* new helper method ``LuaRuntime.table_from(...)`` that creates a Lua
  table from one or more Python mappings and/or sequences

* new ``lupa.unpacks_lua_table`` and ``lupa.unpacks_lua_table_method``
  decorators to allow calling Python functions from Lua using named
  arguments

* fix a hang on shutdown where the LuaRuntime failed to deallocate due
  to reference cycles

* Lupa now plays more nicely with other Lua extensions that create
  userdata objects


1.0.1 (2014-10-11)
------------------

* fix a crash when requesting attributes of wrapped Lua coroutine objects

* looking up attributes on Lua objects that do not support it now always
  raises an AttributeError instead of sometimes raising a TypeError depending
  on the attribute name


1.0 (2014-09-28)
----------------

* NOTE: this release includes the major backwards incompatible changes listed
  below.  It is believed that they simplify the interaction between Python code
  and Lua code by more strongly following idiomatic Lua on the Lua side.

  * Instead of passing a wrapped ``python.none`` object into Lua, ``None``
    return values are now mapped to ``nil``, making them more straight forward
    to handle in Lua code.  This makes the behaviour more consistent, as it
    was previously somewhat arbitrary where ``none`` could appear and where a
    ``nil`` value was used.  The only remaining exception is during iteration,
    where the first returned value must not be ``nil`` in Lua, or otherwise
    the loop terminates prematurely.  To prevent this, any ``None`` value
    that the iterator returns, or any first item in exploded tuples that is
    ``None``, is still mapped to ``python.none``. Any further values
    returned in the same iteration will be mapped to ``nil`` if they are
    ``None``, not to ``none``.  This means that only the first argument
    needs to be manually checked for this special case.  For the
    ``enumerate()`` iterator, the counter is never ``None`` and thus the
    following unpacked items will never be mapped to ``python.none``.

  * When ``unpack_returned_tuples=True``, iteration now also unpacks tuple
    values, including ``enumerate()`` iteration, which yields a flat sequence
    of counter and unpacked values.

  * When calling bound Python methods from Lua as "obj:meth()", Lupa now
    prevents Python from prepending the self argument a second time, so that
    the Python method is now called as "obj.meth()".  Previously, it was called
    as "obj.meth(obj)".  Note that this can be undesired when the object itself
    is explicitly passed as first argument from Lua, e.g. when calling
    "func(obj)" where "func" is "obj.meth", but these constellations should be
    rare.  As a work-around for this case, user code can wrap the bound method
    in another function so that the final call comes from Python.

* garbage collection works for reference cycles that span both runtimes,
  Python and Lua

* calling from Python into Lua and back into Python did not clean up the
  Lua call arguments before the innermost call, so that they could leak
  into the nested Python call or its return arguments

* support for Lua 5.2 (in addition to Lua 5.1 and LuaJIT 2.0)

* Lua tables support Python's "del" statement for item deletion
  (patch by Jason Fried)

* Attribute lookup can use a more fine-grained control mechanism by
  implementing explicit getter and setter functions for a LuaRuntime
  (``attribute_handlers`` argument).  Patch by Brian Moe.

* item assignments/lookups on Lua objects from Python no longer
  special case double underscore names (as opposed to attribute lookups)


0.21 (2014-02-12)
-----------------

* some garbage collection issues were cleaned up using new Cython features

* new ``LuaRuntime`` option ``unpack_returned_tuples`` which automatically
  unpacks tuples returned from Python functions into separate Lua objects
  (instead of returning a single Python tuple object)

* some internal wrapper classes were removed from the module API

* Windows build fixes

* Py3.x build fixes

* support for building with Lua 5.1 instead of LuaJIT (setup.py --no-luajit)

* no longer uses Cython by default when building from released sources (pass
  ``--with-cython`` to explicitly request a rebuild)

* requires Cython 0.20+ when building from unreleased sources

* built with Cython 0.20.1


0.20 (2011-05-22)
-----------------

* fix "deallocating None" crash while iterating over Lua tables in
  Python code

* support for filtering attribute access to Python objects for Lua
  code

* fix: setting source encoding for Lua code was broken


0.19 (2011-03-06)
-----------------

* fix serious resource leak when creating multiple LuaRuntime instances

* portability fix for binary module importing


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


License
=======

Lupa
----

Copyright (c) 2010-2017 Stefan Behnel.  All rights reserved.

Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in
all copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT.  IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
THE SOFTWARE.

Lua
---

(See https://www.lua.org/license.html)

Copyright © 1994–2017 Lua.org, PUC-Rio.

Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in
all copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
THE SOFTWARE.