Repository files navigation

tractor: next-gen Python parallelism

tractor is astructured concurrent,multi-processing runtimebuilt ontrio.

Fundamentally,tractor gives you parallelism viatrio-"actors": independent Python processes (akanon-shared-memory threads) which maintain structuredconcurrency (SC)end-to-end inside asupervision tree.

Cross-process (and thus cross-host) SC is accomplished through thecombined use of our "actornurseries" and an "SC-transitive IPCprotocol" constructed on top of multiple Pythons each running atrioscheduled runtime - a call totrio.run().

We believe the system adheres to the3 axioms of an "actor model"but likelydoes not look like whatyou probably think an "actormodel" looks like, and that'sintentional.

The first step to groktractor is to get the basics oftrio down.A great place to start is thetrio docs and thisblog post.

• It's just atrio API
• Infinitely nesteable process trees
• Builtin IPC streaming APIs with task fan-out broadcasting
• A "native" multi-core debugger REPL usingpdbp (a fork & fix ofpdb++ thanks to @mdmintz!)
• Support for a swappable, OS specific, process spawning layer
• A modular transport stack, allowing for custom serialization (eg. withmsgspec), communications protocols, and environment specific IPCprimitives
• Support for spawning process-level-SC, inter-loop one-to-one-task orientedasyncio actors via "infectedasyncio" mode
• structured chadcurrency from the ground up

Usetrio's style of focussing ontasks as functions:

"""Run with a process monitor from a terminal using::    $TERM -e watch -n 0.1  "pstree -a $$"\        & python examples/parallelism/single_func.py\        && kill $!"""importosimporttractorimporttrioasyncdefburn_cpu():pid=os.getpid()# burn a core @ ~ 50kHzfor_inrange(50000):awaittrio.sleep(1/50000/50)returnos.getpid()asyncdefmain():asyncwithtractor.open_nursery()asn:portal=awaitn.run_in_actor(burn_cpu)#  burn rubber in the parent tooawaitburn_cpu()# wait on result from target functionpid=awaitportal.result()# end of nursery blockprint(f"Collected subproc{pid}")if__name__=='__main__':trio.run(main)

This runsburn_cpu() in a new process and reaps it on completionof the nursery block.

If you only need to run a sync function and retreive a single result, youmight want to check outtrio-parallel.

tractor tries to protect you from zombies, no matter what.

"""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 $!"""frommultiprocessingimportcpu_countimportosimporttractorimporttrioasyncdeftarget():print(f"Yo, i'm '{tractor.current_actor().name}' "f"running in pid{os.getpid()}"    )awaittrio.sleep_forever()asyncdefmain():asyncwithtractor.open_nursery()asn:foriinrange(cpu_count()):awaitn.run_in_actor(target,name=f'worker_{i}')print('This process tree will self-destruct in 1 sec...')awaittrio.sleep(1)# raise an error in root actor/process and trigger# reaping of all minionsraiseException('Self Destructed')if__name__=='__main__':try:trio.run(main)exceptException:print('Zombies Contained')

If you can create zombie child processes (without using a system signal)itis a bug.

Using the magic ofpdbp and our internal IPC, we'vebeen able to create a native feeling debugging experience forany (sub-)process in yourtractor tree.

fromosimportgetpidimporttractorimporttrioasyncdefbreakpoint_forever():"Indefinitely re-enter debugger in child actor."whileTrue:yield'yo'awaittractor.breakpoint()asyncdefname_error():"Raise a ``NameError``"getattr(doggypants)asyncdefmain():"""Test breakpoint in a streaming actor.    """asyncwithtractor.open_nursery(debug_mode=True,loglevel='error',    )asn:p0=awaitn.start_actor('bp_forever',enable_modules=[__name__])p1=awaitn.start_actor('name_error',enable_modules=[__name__])# retreive resultsstream=awaitp0.run(breakpoint_forever)awaitp1.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 streamswith reliable, transitive setup/teardown semantics.

Our nascent api is remniscent oftrio.Nursery.start()style invocation:

importtrioimporttractor@tractor.contextasyncdefsimple_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()``awaitctx.started(data+1)asyncwithctx.open_stream()asstream:count=0asyncformsginstream:assertmsg=='ping'awaitstream.send('pong')count+=1else:assertcount==10asyncdefmain()->None:asyncwithtractor.open_nursery()asn:portal=awaitn.start_actor('rpc_server',enable_modules=[__name__],        )# XXX: this syntax requires py3.9asyncwith (portal.open_context(simple_rpc,data=10,            )as (ctx,sent),ctx.open_stream()asstream,        ):assertsent==11count=0# receive msgs using async for styleawaitstream.send('ping')asyncformsginstream:assertmsg=='pong'awaitstream.send('ping')count+=1ifcount>=9:break# explicitly teardown the daemon-actorawaitportal.cancel_actor()if__name__=='__main__':trio.run(main)

See original proposal and discussion in#53 as wellas follow up improvements in#223 that we'd love tohear your thoughts on!

The initial ask from most new users is"how do I make a workerpool thing?".

tractor is built to handle any SC (structured concurrent) processtree you can imagine; a "worker pool" pattern is a trivial specialcase.

We have afull worker pool re-implementation of the std-lib'sconcurrent.futures.ProcessPoolExecutor example for reference.

You can run it like so (from this dir) to see the process tree inreal 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 needistractor's IPC!

Have a bunch ofasyncio code you want to force to be SC at the process level?

Check out our experimental system forguest-mode controlledasyncio actors:

importasynciofromstatisticsimportmeanimporttimeimporttrioimporttractorasyncdefaio_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.whileTrue:# echo the msg backto_trio.send_nowait(awaitfrom_trio.get())awaitasyncio.sleep(0)@tractor.contextasyncdeftrio_to_aio_echo_server(ctx:tractor.Context,):# this will block until the ``asyncio`` task sends a "first"# message.asyncwithtractor.to_asyncio.open_channel_from(aio_echo_server,    )as (first,chan):assertfirst=='start'awaitctx.started(first)asyncwithctx.open_stream()asstream:asyncformsginstream:awaitchan.send(msg)out=awaitchan.receive()# echo back to parent actor-taskawaitstream.send(out)asyncdefmain():asyncwithtractor.open_nursery()asn:p=awaitn.start_actor('aio_server',enable_modules=[__name__],infect_asyncio=True,        )asyncwithp.open_context(trio_to_aio_echo_server,        )as (ctx,first):assertfirst=='start'count=0asyncwithctx.open_stream()asstream:delays= []send=time.time()awaitstream.send(count)asyncformsginstream:recv=time.time()delays.append(recv-send)assertmsg==countcount+=1send=time.time()awaitstream.send(count)ifcount>=1e3:breakprint(f'mean round trip rate (Hz):{1/mean(delays)}')awaitp.cancel_actor()if__name__=='__main__':trio.run(main)

Yes, we spawn a python process, runasyncio, starttrio on theasyncio loop, then send commands to thetrio scheduled tasks totellasyncio tasks what to do XD

We need help refining the asyncio-side channel API to be moretrio-like. Feel free to sling your opinion in#273!

To be extra terse thetractor devs have started hacking some "higherlevel" APIs for managing actor trees/clusters. These interfaces shouldgenerally be condsidered provisional for now but we encourage you to trythem and provide feedback. Here's a new API that let's you quicklyspawn a flat cluster:

importtrioimporttractorasyncdefsleepy_jane():uid=tractor.current_actor().uidprint(f'Yo i am actor{uid}')awaittrio.sleep_forever()asyncdefmain():'''    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!asyncwith (tractor.open_actor_cluster(modules=[__name__]        )asportal_map,trio.open_nursery()asn,    ):for (name,portal)inportal_map.items():n.start_soon(portal.run,sleepy_jane)awaittrio.sleep(0.5)# kill the cluster with a cancelraiseKeyboardInterruptif__name__=='__main__':try:trio.run(main)exceptKeyboardInterrupt:pass

From PyPi:

pip install tractor

From git:

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

tractor is an attempt to pairtrionicstructured concurrency withdistributed Python. You can think of it as atrio-across-processes or simply as an opinionated replacement for thestdlib'smultiprocessing but built on async programming primitivesfrom the ground up.

Don't be scared off by this description.tractoris justtriobut with nurseries for process management and cancel-able streaming IPC.If you understand how to work withtrio,tractor will give youthe parallelism you may have been needing.

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 theydon't adhere to the3 axioms and pay even lessattention to the problem ofunbounded non-determinism (which was thewhole point for creation of the model in the first place).

From the author's mouth,the only thing required isadherance tothe3 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 requiresno further api changes to accomplish this.

If you want do debate this further please feel free to chime in on ourchat or discuss on one of the following issuesafter you've readeverything in them:

• #210
• #18

Whether or nottractor has "actors" underneath should be mostlyirrelevant to users other then for referring to the interactions of ourprimary runtime primitives: each Python process +trio.run()+ surrounding IPC machinery. These are our high level, baseruntime-units-of-abstraction which bothare (as much as they canbe in Python) and will be referred to as our"actors".

The main goal oftractor is is to allow for highly distributedsoftware that, through the adherence tostructured concurrency,results in systems which fail in predictable, recoverable and maybe evenunderstandable ways; being an "actor model" is just one way to describeproperties of the system.

Help us push toward the future of distributed Python.

• Erlang-style supervisors via composed context managers (see#22)
• Typed messaging protocols (ex. viamsgspec.Struct, see#36)
• Typed capability-based (dialog) protocols ( see#196 with draft workstarted in#311)
• Werecently disabled CI-testing on windows and need help gettingit running again! (see#327).We do have windowssupport (and have for quite a while) but since no active hackerexists in the user-base to help test on that OS, for now we're notactively maintaining testing due to the added hassle and generallatency..

This project is very much coupled to the ongoing development oftrio (i.e.tractor gets most of its ideas from that brilliantcommunity). If you want to help, have suggestions or just want tosay hi, please feel free to reach us in ourmatrix channel. Ifmatrix seems too hip, we're also mostly all in the thetrio gitterchannel!