cpy2py 0.13.0

.. # - # Copyright 2016 Max Fischer
.. # - #
.. # - # Licensed under the Apache License, Version 2.0 (the "License");
.. # - # you may not use this file except in compliance with the License.
.. # - # You may obtain a copy of the License at
.. # - #
.. # - # http://www.apache.org/licenses/LICENSE-2.0
.. # - #
.. # - # Unless required by applicable law or agreed to in writing, software
.. # - # distributed under the License is distributed on an "AS IS" BASIS,
.. # - # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
.. # - # See the License for the specific language governing permissions and
.. # - # limitations under the License.
CPy2Py
======

|Code Health| |Test Status|

Multi-intepreter execution environment

`cpy2py` allows multiple interpreters to act as one application in parallel
to the main interpreter, other interpreters may be run to execute parts of
the application.

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:target: https://landscape.io/github/maxfischer2781/cpy2py/master
:alt: Code Health

.. |Test Status| image:: https://travis-ci.org/maxfischer2781/cpy2py.svg?branch=master
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:alt: Test Health

Quick Guide
===========

Twinterpreters and TwinMasters
------------------------------

A twinterpreter is simply another interpreter running as a subprocess -
with some glue and magic sprinkled on it. You can control and create them
using a `cpy2py.TwinMaster`.

You should only ever worry about two methods: `TwinMaster.start`
launches the twinterpreter. `TwinMaster.execute` executes
an arbitrary callable in the twinterpreter.

.. code:: python

from my_module import my_function
twinterpreter = TwinMaster('pypy')
twinterpreter.start()
twinterpreter.execute(my_function, 1, 2, 3, 'ka-pow!', doctor="who?")

TwinObjects
-----------

The real power of `cpy2py` are Twins - objects living in one
twinterpreter and being represented by proxies in any other interpeter.
Using twins, you can seamlessly split your application across multiple
twins.

You create twins by inheriting from
`object` and
setting a ``__twin_id__``. That's it.

.. code:: python

from cpy2py import TwinObject
class SuperComputer(TwinObject):
__twin_id__ = 'pypy' # makes class native to pypy twinterpeter

def megaloop(self, x, y):
return sum(a+b for a in range(x) for b in range(y))

class CWrapper(TwinObject):
__twin_id__ = 'python' # makes class native to python twinterpeter

def callme(self, who, what="buy milk"):
return some_clib.c_fcn_cll_cplx_xmpl(who, what)

If you don't set ``__twin_id__`` on a child of
`cpy2py.TwinObject`,
the class will always be native to the main interpreter. Handy for all
the stuff that's needed everywhere but really doesn't belong anywhere.

:note: At the moment, you have to explicitly start a class's native
twinterpreter before instantiating the class. Only the main
interpreter is always available, of course.

Debugging
---------

The core of `logging` facilities.
All such loggers are children of the ``__cpy2py__`` logger. By default,
no active handlers are attached and propagation is disabled. If needed,
you reconfigure them like any other `logging` logger to suit your
needs.

For small scale debugging, one can set the environment variable
`CPY2PY_DEBUG`. If it is defined and not empty, logging output
is written to `stderr`.

Note that loggers are meant for development and only address the internal
state. Your application should not depend on this information. Unless
`cpy2py` misbehaves (or you suspect it to), ignore its logging.

Current Status
==============

CPy2Py is stable at its core, but still has some features missing.
What's there is more than sufficient to significantly enhance your applications.

Features
--------

* Any pickle'able callable can be dispatched to another interpreter.

* Object functionality is almost fully covered!

* Objects may reside in any interpreter and transparently interact.

* Both class and instance attributes work as expected.

* Methods, classmethods and staticmethods work transparently.

* Inheritance is fully supported, including multiple inheritance.
Affiliation to interpreters can be changed freely.

* A wide range of interpeters is supported.

* Pure python, no dependencies means perfect portability.

* Any interpeter compatible with python 2.6 to 3.5 is supported.

* Virtual Environments work out of the box.

* Tested with cpython and pypy, on Linux and Mac OSX.

Gotchas/Limitations
-------------------

* Calls across interpreters are blocking and not threadsafe.

* Module level settings are not synchronized. For example, configuration of `~cpy2py.twinterpreter.group_state.TwinGroupState`. See also issue #7.

* A `weakref` to objects only takes local references into account, not cross-interpreter references.