|logo| tractor
: next-gen Python parallelism
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tractor
is a structured concurrent
, multi-processing runtime
built on trio_.
Fundamentally, tractor
gives you parallelism via
trio
-"actors": independent Python processes (aka
non-shared-memory threads) which maintain structured
concurrency (SC) end-to-end inside a supervision tree.
Cross-process (and thus cross-host) SC is accomplished through the
combined use of our "actor nurseries_" and an "SC-transitive IPC
protocol" constructed on top of multiple Pythons each running a trio
scheduled runtime - a call to trio.run()
.
We believe the system adheres to the 3 axioms
of an "actor model
"
but likely does not look like what you probably think an "actor
model" looks like, and that's intentional.
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
.
trio
APIpdbp
(a fork & fix of
pdb++
thanks to @mdmintz!)msgspec
_), communications protocols, and environment specific IPC
primitivesasyncio
actors via "infected asyncio
" modestructured chadcurrency
_ from the ground upUse trio
's style of focussing on tasks as functions:
.. code:: python
"""
Run with a process monitor from a terminal using::
$TERM -e watch -n 0.1 "pstree -a $$" \
& python examples/parallelism/single_func.py \
&& kill $!
"""
import os
import tractor
import trio
async def burn_cpu():
pid = os.getpid()
# burn a core @ ~ 50kHz
for _ in range(50000):
await trio.sleep(1/50000/50)
return os.getpid()
async def main():
async with tractor.open_nursery() as n:
portal = await n.run_in_actor(burn_cpu)
# burn rubber in the parent too
await burn_cpu()
# wait on result from target function
pid = await portal.result()
# end of nursery block
print(f"Collected subproc {pid}")
if __name__ == '__main__':
trio.run(main)
This runs burn_cpu()
in a new process and reaps it on completion
of the nursery block.
If you only need to run a sync function and retreive a single result, you
might want to check out trio-parallel
_.
tractor
tries to protect you from zombies, no matter what.
.. code:: python
"""
Run with a process monitor from a terminal using::
$TERM -e watch -n 0.1 "pstree -a $$" \
& 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)
# raise an error in root actor/process and trigger
# reaping of all minions
raise Exception('Self Destructed')
if __name__ == '__main__':
try:
trio.run(main)
except Exception:
print('Zombies Contained')
If you can create zombie child processes (without using a system signal) it is a bug.
Using the magic of pdbp
_ and our internal IPC, we've
been able to create a native feeling debugging experience for
any (sub-)process in your tractor
tree.
.. code:: python
from os import getpid
import tractor
import trio
async def breakpoint_forever():
"Indefinitely re-enter debugger in child actor."
while True:
yield 'yo'
await tractor.breakpoint()
async def name_error():
"Raise a ``NameError``"
getattr(doggypants)
async def main():
"""Test breakpoint in a streaming actor.
"""
async with tractor.open_nursery(
debug_mode=True,
loglevel='error',
) as n:
p0 = await n.start_actor('bp_forever', enable_modules=[__name__])
p1 = await n.start_actor('name_error', enable_modules=[__name__])
# retreive results
stream = await p0.run(breakpoint_forever)
await p1.run(name_error)
if __name__ == '__main__':
trio.run(main)
You can run this with::
>>> python examples/debugging/multi_daemon_subactors.py
And, yes, there's a built-in crash handling mode B)
We're hoping to add a respawn-from-repl system soon!
Yes, you saw it here first; we provide 2-way streams with reliable, transitive setup/teardown semantics.
Our nascent api is remniscent of trio.Nursery.start()
style invocation:
.. code:: python
import trio
import tractor
@tractor.context
async def simple_rpc(
ctx: tractor.Context,
data: int,
) -> None:
'''Test a small ping-pong 2-way streaming server.
'''
# signal to parent that we're up much like
# ``trio_typing.TaskStatus.started()``
await ctx.started(data + 1)
async with ctx.open_stream() as stream:
count = 0
async for msg in stream:
assert msg == 'ping'
await stream.send('pong')
count += 1
else:
assert count == 10
async def main() -> None:
async with tractor.open_nursery() as n:
portal = await n.start_actor(
'rpc_server',
enable_modules=[__name__],
)
# XXX: this syntax requires py3.9
async with (
portal.open_context(
simple_rpc,
data=10,
) as (ctx, sent),
ctx.open_stream() as stream,
):
assert sent == 11
count = 0
# receive msgs using async for style
await stream.send('ping')
async for msg in stream:
assert msg == 'pong'
await stream.send('ping')
count += 1
if count >= 9:
break
# explicitly teardown the daemon-actor
await portal.cancel_actor()
if __name__ == '__main__':
trio.run(main)
See original proposal and discussion in #53
as well
as follow up improvements in #223
that we'd love to
hear your thoughts on!
.. #53: https://github.com/goodboy/tractor/issues/53 .. #223: https://github.com/goodboy/tractor/issues/223
The initial ask from most new users is "how do I make a worker pool thing?".
tractor
is built to handle any SC (structured concurrent) process
tree you can imagine; a "worker pool" pattern is a trivial special
case.
We have a full worker pool re-implementation
_ of the std-lib's
concurrent.futures.ProcessPoolExecutor
example for reference.
You can run it like so (from this dir) to see the process tree in real time::
$TERM -e watch -n 0.1 "pstree -a $$" \
& python examples/parallelism/concurrent_actors_primes.py \
&& kill $!
This uses no extra threads, fancy semaphores or futures; all we need
is tractor
's IPC!
asyncio
" modeHave a bunch of asyncio
code you want to force to be SC at the process level?
Check out our experimental system for guest-mode
_ controlled
asyncio
actors:
.. code:: python
import asyncio
from statistics import mean
import time
import trio
import tractor
async def aio_echo_server(
to_trio: trio.MemorySendChannel,
from_trio: asyncio.Queue,
) -> None:
# a first message must be sent **from** this ``asyncio``
# task or the ``trio`` side will never unblock from
# ``tractor.to_asyncio.open_channel_from():``
to_trio.send_nowait('start')
# XXX: this uses an ``from_trio: asyncio.Queue`` currently but we
# should probably offer something better.
while True:
# echo the msg back
to_trio.send_nowait(await from_trio.get())
await asyncio.sleep(0)
@tractor.context
async def trio_to_aio_echo_server(
ctx: tractor.Context,
):
# this will block until the ``asyncio`` task sends a "first"
# message.
async with tractor.to_asyncio.open_channel_from(
aio_echo_server,
) as (first, chan):
assert first == 'start'
await ctx.started(first)
async with ctx.open_stream() as stream:
async for msg in stream:
await chan.send(msg)
out = await chan.receive()
# echo back to parent actor-task
await stream.send(out)
async def main():
async with tractor.open_nursery() as n:
p = await n.start_actor(
'aio_server',
enable_modules=[__name__],
infect_asyncio=True,
)
async with p.open_context(
trio_to_aio_echo_server,
) as (ctx, first):
assert first == 'start'
count = 0
async with ctx.open_stream() as stream:
delays = []
send = time.time()
await stream.send(count)
async for msg in stream:
recv = time.time()
delays.append(recv - send)
assert msg == count
count += 1
send = time.time()
await stream.send(count)
if count >= 1e3:
break
print(f'mean round trip rate (Hz): {1/mean(delays)}')
await p.cancel_actor()
if __name__ == '__main__':
trio.run(main)
Yes, we spawn a python process, run asyncio
, start trio
on the
asyncio
loop, then send commands to the trio
scheduled tasks to
tell asyncio
tasks what to do XD
We need help refining the asyncio
-side channel API to be more
trio
-like. Feel free to sling your opinion in #273
_!
.. _#273: https://github.com/goodboy/tractor/issues/273
To be extra terse the tractor
devs have started hacking some "higher
level" APIs for managing actor trees/clusters. These interfaces should
generally be condsidered provisional for now but we encourage you to try
them and provide feedback. Here's a new API that let's you quickly
spawn a flat cluster:
.. code:: python
import trio
import tractor
async def sleepy_jane():
uid = tractor.current_actor().uid
print(f'Yo i am actor {uid}')
await trio.sleep_forever()
async def main():
'''
Spawn a flat actor cluster, with one process per
detected core.
'''
portal_map: dict[str, tractor.Portal]
results: dict[str, str]
# look at this hip new syntax!
async with (
tractor.open_actor_cluster(
modules=[__name__]
) as portal_map,
trio.open_nursery() as n,
):
for (name, portal) in portal_map.items():
n.start_soon(portal.run, sleepy_jane)
await trio.sleep(0.5)
# kill the cluster with a cancel
raise KeyboardInterrupt
if __name__ == '__main__':
try:
trio.run(main)
except KeyboardInterrupt:
pass
.. _full worker pool re-implementation: https://github.com/goodboy/tractor/blob/master/examples/parallelism/concurrent_actors_primes.py
From PyPi::
pip install tractor
From git::
pip install git+git://github.com/goodboy/tractor.git
tractor
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 streaming IPC.
If you understand how to work with trio
, tractor
will give you
the parallelism you may have been needing.
Wait, huh?! I thought "actors" have messages, and mailboxes and stuff?!
Let's stop and ask how many canon actor model papers have you actually read ;)
From our experience many "actor systems" aren't really "actor models"
since they don't adhere to the 3 axioms
_ and pay even less
attention to the problem of unbounded non-determinism (which was the
whole point for creation of the model in the first place).
From the author's mouth, the only thing required is adherance to
the 3 axioms
, and that's it.
tractor
adheres to said base requirements of an "actor model"::
In response to a message, an actor may:
- send a finite number of new messages
- create a finite number of new actors
- designate a new behavior to process subsequent messages
and requires no further api changes to accomplish this.
If you want do debate this further please feel free to chime in on our chat or discuss on one of the following issues after you've read everything in them:
Let's clarify our parlance
Whether or not tractor
has "actors" underneath should be mostly
irrelevant to users other then for referring to the interactions of our
primary runtime primitives: each Python process + trio.run()
The main goal of tractor
is is to allow for highly distributed
software that, through the adherence to structured concurrency,
results in systems which fail in predictable, recoverable and maybe even
understandable ways; being an "actor model" is just one way to describe
properties of the system.
Help us push toward the future of distributed Python
.
#22 <https://github.com/goodboy/tractor/issues/22>
_)msgspec.Struct
, see #36 <https://github.com/goodboy/tractor/issues/36>
_)#196 <https://github.com/goodboy/tractor/issues/196>
with draft work
started in #311 <https://github.com/goodboy/tractor/pull/311>
)#327 <https://github.com/goodboy/tractor/pull/327>
_). We do have windows
support (and have for quite a while) but since no active hacker
exists in the user-base to help test on that OS, for now we're not
actively maintaining testing due to the added hassle and general
latency..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
!
.. _structured concurrent: https://trio.discourse.group/t/concise-definition-of-structured-concurrency/228 .. _multi-processing: https://en.wikipedia.org/wiki/Multiprocessing .. _trio: https://github.com/python-trio/trio .. _nurseries: https://vorpus.org/blog/notes-on-structured-concurrency-or-go-statement-considered-harmful/#nurseries-a-structured-replacement-for-go-statements .. _actor model: https://en.wikipedia.org/wiki/Actor_model .. _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 .. _3 axioms: https://www.youtube.com/watch?v=7erJ1DV_Tlo&t=162s .. .. _3 axioms: https://en.wikipedia.org/wiki/Actor_model#Fundamental_concepts .. _adherance to: https://www.youtube.com/watch?v=7erJ1DV_Tlo&t=1821s .. _trio gitter channel: https://gitter.im/python-trio/general .. _matrix channel: https://matrix.to/#/!tractor:matrix.org .. _pdbp: https://github.com/mdmintz/pdbp .. _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 .. _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://en.wikipedia.org/wiki/Structured_concurrency .. _structured chadcurrency: https://en.wikipedia.org/wiki/Structured_concurrency .. _structured concurrency: https://en.wikipedia.org/wiki/Structured_concurrency .. _unrequirements: https://en.wikipedia.org/wiki/Actor_model#Direct_communication_and_asynchrony .. _async generators: https://www.python.org/dev/peps/pep-0525/ .. _trio-parallel: https://github.com/richardsheridan/trio-parallel .. _msgspec: https://jcristharif.com/msgspec/ .. _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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