tractor
=======
The Python async-native multi-core system *you always wanted*.


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.. _actor model: https://en.wikipedia.org/wiki/Actor_model
.. _trio: https://github.com/python-trio/trio
.. _multi-processing: https://en.wikipedia.org/wiki/Multiprocessing
.. _trionic: https://trio.readthedocs.io/en/latest/design.html#high-level-design-principles
.. _async sandwich: https://trio.readthedocs.io/en/latest/tutorial.html#async-sandwich
.. _structured concurrent: https://trio.discourse.group/t/concise-definition-of-structured-concurrency/228


``tractor`` is a `structured concurrent`_ "`actor model`_" built on trio_ and multi-processing_.

It is an attempt to pair trionic_ `structured concurrency`_ with
distributed Python. You can think of it as a ``trio``
*-across-processes* or simply as an opinionated replacement for the
stdlib's ``multiprocessing`` but built on async programming primitives
from the ground up.

Don't be scared off by this description. ``tractor`` **is just ``trio``**
but with nurseries for process management and cancel-able IPC.
If you understand how to work with ``trio``, ``tractor`` will give you
the parallelism you've been missing.

``tractor``'s nurseries let you spawn ``trio`` *"actors"*: new Python
processes which each run a ``trio`` scheduled task tree (also known as
an `async sandwich`_ - a call to ``trio.run()``). That is, each
"*Actor*" is a new process plus a ``trio`` runtime.

"Actors" communicate by exchanging asynchronous messages_ and avoid
sharing state. The intention of this model is to allow for highly
distributed software that, through the adherence to *structured
concurrency*, results in systems which fail in predictable and
recoverable ways.

The first step to grok ``tractor`` is to get the basics of ``trio`` down.
A great place to start is the `trio docs`_ and this `blog post`_.

.. _messages: https://en.wikipedia.org/wiki/Message_passing
.. _trio docs: https://trio.readthedocs.io/en/latest/
.. _blog post: https://vorpus.org/blog/notes-on-structured-concurrency-or-go-statement-considered-harmful/
.. _structured concurrency: https://vorpus.org/blog/notes-on-structured-concurrency-or-go-statement-considered-harmful/
.. _3 axioms: https://en.wikipedia.org/wiki/Actor_model#Fundamental_concepts
.. _unrequirements: https://en.wikipedia.org/wiki/Actor_model#Direct_communication_and_asynchrony
.. _async generators: https://www.python.org/dev/peps/pep-0525/


Install
-------
No PyPi release yet!

::

    pip install git+git://github.com/goodboy/tractor.git


Alluring Features
-----------------
- **It's just** ``trio``, but with SC applied to processes (aka "actors")
- Infinitely nesteable process trees
- Built-in API for inter-process streaming
- A (first ever?) "native" multi-core debugger for Python using `pdb++`_
- (Soon to land) ``asyncio`` support allowing for "infected" actors where
  `trio` drives the `asyncio` scheduler via the astounding "`guest mode`_"


Example: self-destruct a process tree
-------------------------------------

.. code:: python

   """
   Run with a process monitor from a terminal using:
   $TERM -e watch -n 0.1  "pstree -a $$" & python examples/parallelism/we_are_processes.py && kill $!

   """
   from multiprocessing import cpu_count
   import os

   import tractor
   import trio


   async def target():
       print(f"Yo, i'm '{tractor.current_actor().name}' "
             f"running in pid {os.getpid()}")
       await trio.sleep_forever()


   async def main():

       async with tractor.open_nursery() as n:

           for i in range(cpu_count()):
               await n.run_in_actor(target, name=f'worker_{i}')

           print('This process tree will self-destruct in 1 sec...')
           await trio.sleep(1)

           # you could have done this yourself
           raise Exception('Self Destructed')


   if __name__ == '__main__':
       try:
           trio.run(main)
       except Exception:
           print('Zombies Contained')


The example you're probably after...
------------------------------------
It seems the initial query from most new users is "how do I make a worker
pool thing?".

``tractor`` is built to handle any SC process tree you can
imagine; the "worker pool" pattern is a trivial special case:

.. code:: python

   """
   Demonstration of the prime number detector example from the
   ``concurrent.futures`` docs:

   https://docs.python.org/3/library/concurrent.futures.html#processpoolexecutor-example

   This uses no extra threads, fancy semaphores or futures; all we need 
   is ``tractor``'s channels.

   """
   from contextlib import asynccontextmanager
   from typing import List, Callable
   import itertools
   import math
   import time

   import tractor
   import trio
   from async_generator import aclosing


   PRIMES = [
       112272535095293,
       112582705942171,
       112272535095293,
       115280095190773,
       115797848077099,
       1099726899285419,
   ]


   def is_prime(n):
       if n < 2:
           return False
       if n == 2:
           return True
       if n % 2 == 0:
           return False

       sqrt_n = int(math.floor(math.sqrt(n)))
       for i in range(3, sqrt_n + 1, 2):
           if n % i == 0:
               return False
       return True


   @asynccontextmanager
   async def worker_pool(workers=4):
       """Though it's a trivial special case for ``tractor``, the well
       known "worker pool" seems to be the defacto "but, I want this
       process pattern!" for most parallelism pilgrims.

       Yes, the workers stay alive (and ready for work) until you close
       the context.
       """
       async with tractor.open_nursery() as tn:

           portals = []
           snd_chan, recv_chan = trio.open_memory_channel(len(PRIMES))

           for i in range(workers):

               # this starts a new sub-actor (process + trio runtime) and
               # stores it's "portal" for later use to "submit jobs" (ugh).
               portals.append(
                   await tn.start_actor(
                       f'worker_{i}',
                       enable_modules=[__name__],
                   )
               )

           async def _map(
               worker_func: Callable[[int], bool],
               sequence: List[int]
           ) -> List[bool]:

               # define an async (local) task to collect results from workers
               async def send_result(func, value, portal):
                   await snd_chan.send((value, await portal.run(func, n=value)))

               async with trio.open_nursery() as n:

                   for value, portal in zip(sequence, itertools.cycle(portals)):
                       n.start_soon(
                           send_result,
                           worker_func,
                           value,
                           portal
                       )

                   # deliver results as they arrive
                   for _ in range(len(sequence)):
                       yield await recv_chan.receive()

           # deliver the parallel "worker mapper" to user code
           yield _map

           # tear down all "workers" on pool close
           await tn.cancel()


   async def main():

       async with worker_pool() as actor_map:

           start = time.time()

           async with aclosing(actor_map(is_prime, PRIMES)) as results:
               async for number, prime in results:

                   print(f'{number} is prime: {prime}')

           print(f'processing took {time.time() - start} seconds')


   if __name__ == '__main__':
       start = time.time()
       trio.run(main)
       print(f'script took {time.time() - start} seconds')


Feel like saying hi?
--------------------
This project is very much coupled to the ongoing development of
``trio`` (i.e. ``tractor`` gets most of its ideas from that brilliant
community). If you want to help, have suggestions or just want to
say hi, please feel free to reach us in our `matrix channel`_.  If
matrix seems too hip, we're also mostly all in the the `trio gitter
channel`_!

.. _trio gitter channel: https://gitter.im/python-trio/general
.. _matrix channel: https://matrix.to/#/!tractor:matrix.org
.. _pdb++: https://github.com/pdbpp/pdbpp
.. _guest mode: https://trio.readthedocs.io/en/stable/reference-lowlevel.html?highlight=guest%20mode#using-guest-mode-to-run-trio-on-top-of-other-event-loops


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