Actor state via messages

examples/actors/mutate_remote_state.py

@@ -0,0 +1,64 @@
+from itertools import cycle
+from pprint import pformat
+from dataclasses import dataclass, field
+
+import trio
+import tractor
+
+
+@dataclass
+class MyProcessStateThing:
+    state: dict = field(default_factory=dict)
+
+    def update(self, msg: dict):
+        self.state.update(msg)
+
+
+_actor_state = MyProcessStateThing()
+
+
+async def update_local_state(msg: dict):
+    """Update process-local state from sent message and exit.
+
+    """
+    actor = tractor.current_actor()
+
+    global _actor_state
+
+
+    print(f'Yo we got a message {msg}')
+
+    # update the "actor state"
+    _actor_state.update(msg)
+
+    print(f'New local "state" for {actor.uid} is {pformat(_actor_state.state)}')
+
+    # we're done so exit this task running in the subactor
+
+
+async def main():
+    # Main process/thread that spawns one sub-actor and sends messages
+    # to it to update it's state.
+
+    actor_portals = []
+
+    # XXX: that subactor can **not** outlive it's parent, this is SC.
+    async with tractor.open_nursery() as tn:
+
+        portal = await tn.start_actor('even_boy', enable_modules=[__name__])
+        actor_portals.append(portal)
+
+        portal = await tn.start_actor('odd_boy', enable_modules=[__name__])
+        actor_portals.append(portal)
+
+        for i, (count, portal) in enumerate(
+            zip(range(100), cycle(actor_portals))
+        ):
+            await portal.run(update_local_state, msg={f'msg_{i}': count})
+
+    # blocks here indefinitely synce we spawned "daemon actors" using
+    # .start_actor()`, you'll need to control-c to cancel.
+
+
+if __name__ == '__main__':
+    trio.run(main)

examples/actors/ray_style_classes.py

@@ -0,0 +1,153 @@
+import inspect
+from typing import Any
+from functools import partial
+from contextlib import asynccontextmanager, AsyncExitStack
+from itertools import cycle
+from pprint import pformat
+
+import trio
+import tractor
+
+
+log = tractor.log.get_logger(__name__)
+
+
+class ActorState:
+    """Singlteton actor per process.
+
+    """
+    # this is a class defined variable and is thus both
+    # singleton across object instances and task safe.
+    state: dict = {}
+
+    def update(self, msg: dict) -> None:
+        _actor = tractor.current_actor()
+
+        print(f'Yo we got a message {msg}')
+        self.state.update(msg)
+
+        print(f'New local "state" for {_actor.uid} is {pformat(self.state)}')
+
+    def close(self):
+        # gives headers showing which process and task is active
+        log.info('Actor state is closing')
+
+    # if we wanted to support spawning or talking to other
+    # actors we can do that using a portal map collection?
+    # _portals: dict = {}
+
+
+async def _run_proxy_method(
+    meth: str,
+    msg: dict,
+) -> Any:
+    """Update process-local state from sent message and exit.
+
+    """
+    # Create a new actor instance per call.
+    # We can make this persistent by storing it either
+    # in a global var or are another clas scoped variable?
+    # If you want it somehow persisted in another namespace
+    # I'd be interested to know "where".
+    actor = ActorState()
+    if meth != 'close':
+        return getattr(actor, meth)(msg)
+    else:
+        actor.close()
+
+    # we're done so exit this task running in the subactor
+
+
+class MethodProxy:
+    def __init__(
+        self,
+        portal: tractor._portal.Portal
+    ) -> None:
+        self._portal = portal
+
+    async def _run_method(
+        self,
+        *,
+        meth: str,
+        msg: dict,
+    ) -> Any:
+        return await self._portal.run(
+            _run_proxy_method,
+            meth=meth,
+            msg=msg
+        )
+
+
+def get_method_proxy(portal, target=ActorState) -> MethodProxy:
+
+    proxy = MethodProxy(portal)
+
+    # mock all remote methods
+    for name, method in inspect.getmembers(
+        target, predicate=inspect.isfunction
+    ):
+        if '_' == name[0]:
+            # skip private methods
+            continue
+
+        else:
+            setattr(proxy, name, partial(proxy._run_method, meth=name))
+
+    return proxy
+
+
+@asynccontextmanager
+async def spawn_proxy_actor(name):
+
+    # XXX: that subactor can **not** outlive it's parent, this is SC.
+    async with tractor.open_nursery(
+        debug_mode=True,
+        # loglevel='info',
+    ) as tn:
+
+        portal = await tn.start_actor(name, enable_modules=[__name__])
+
+        proxy = get_method_proxy(portal)
+
+        yield proxy
+
+        await proxy.close(msg=None)
+
+
+async def main():
+    # Main process/thread that spawns one sub-actor and sends messages
+    # to it to update it's state.
+
+    try:
+        stack = AsyncExitStack()
+
+        actors = []
+        for name in ['even', 'odd']:
+
+            actor_proxy = await stack.enter_async_context(
+                    spawn_proxy_actor(name + '_boy')
+            )
+            actors.append(actor_proxy)
+
+        # spin through the actors and update their states
+        for i, (count, actor) in enumerate(
+            zip(range(100), cycle(actors))
+        ):
+            # Here we call the locally patched `.update()` method of the
+            # remote instance
+
+            # NOTE: the instance created each call here is currently
+            # a new object - to persist it across `portal.run()` calls
+            # we need to store it somewhere in memory for access by
+            # a new task spawned in the remote actor process.
+            await actor.update(msg={f'msg_{i}': count})
+
+    # blocks here indefinitely synce we spawned "daemon actors" using
+    # .start_actor()`, you'll need to control-c to cancel.
+
+    finally:
+        await stack.aclose()
+
+
+if __name__ == '__main__':
+    trio.run(main)

examples/parallelism/concurrent_actors_primes.py

@@ -0,0 +1,119 @@
+"""
+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')

examples/parallelism/concurrent_futures_primes.py

@@ -0,0 +1,40 @@
+import time
+import concurrent.futures
+import math
+
+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
+
+def main():
+    with concurrent.futures.ProcessPoolExecutor() as executor:
+        start = time.time()
+
+        for number, prime in zip(PRIMES, executor.map(is_prime, PRIMES)):
+            print('%d is prime: %s' % (number, prime))
+
+        print(f'processing took {time.time() - start} seconds')
+
+if __name__ == '__main__':
+
+    start = time.time()
+    main()
+    print(f'script took {time.time() - start} seconds')