commit
08fa55a8c3
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@ -313,9 +313,62 @@ real time::
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This uses no extra threads, fancy semaphores or futures; all we need
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is ``tractor``'s IPC!
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To be extra terse the ``tractor`` devs have started hacking some "higher
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level" APIs for managing actor trees/clusters. These interfaces should
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generally be condsidered provisional for now but we encourage you to try
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them and provide feedback. Here's a new API that let's you quickly
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spawn a flat cluster:
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.. code:: python
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import trio
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import tractor
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async def sleepy_jane():
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uid = tractor.current_actor().uid
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print(f'Yo i am actor {uid}')
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await trio.sleep_forever()
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async def main():
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'''
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Spawn a flat actor cluster, with one process per
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detected core.
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'''
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portal_map: dict[str, tractor.Portal]
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results: dict[str, str]
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# look at this hip new syntax!
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async with (
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tractor.open_actor_cluster(
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modules=[__name__]
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) as portal_map,
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trio.open_nursery() as n,
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):
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for (name, portal) in portal_map.items():
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n.start_soon(portal.run, sleepy_jane)
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await trio.sleep(0.5)
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# kill the cluster with a cancel
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raise KeyboardInterrupt
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if __name__ == '__main__':
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try:
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trio.run(main)
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except KeyboardInterrupt:
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pass
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.. _full worker pool re-implementation: https://github.com/goodboy/tractor/blob/master/examples/parallelism/concurrent_actors_primes.py
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Install
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-------
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From PyPi::
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@ -0,0 +1,40 @@
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Hot tips for ``tractor`` hackers
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================================
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This is a WIP guide for newcomers to the project mostly to do with
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dev, testing, CI and release gotchas, reminders and best practises.
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``tractor`` is a fairly novel project compared to most since it is
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effectively a new way of doing distributed computing in Python and is
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much closer to working with an "application level runtime" (like erlang
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OTP or scala's akka project) then it is a traditional Python library.
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As such, having an arsenal of tools and recipes for figuring out the
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right way to debug problems when they do arise is somewhat of
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a necessity.
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Making a Release
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----------------
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We currently do nothing special here except the traditional
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PyPa release recipe as in `documented by twine`_. I personally
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create sub-dirs within the generated `dist/` with an explicit
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release name such as `alpha3/` when there's been a sequence of
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releases I've made, but it really is up to you how you like to
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organize generated sdists locally.
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.. _documented by twine: https://twine.readthedocs.io/en/latest/#using-twine
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Debugging and monitoring actor trees
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------------------------------------
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TODO: but there are tips in the readme for some terminal commands
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which can be used to see the process trees easily on Linux.
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Using the log system to trace `trio` task flow
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----------------------------------------------
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TODO: the logging system is meant to be oriented around
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stack "layers" of the runtime such that you can track
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"logical abstraction layers" in the code such as errors, cancellation,
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IPC and streaming, and the low level transport and wire protocols.
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@ -0,0 +1,44 @@
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import trio
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import tractor
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async def sleepy_jane():
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uid = tractor.current_actor().uid
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print(f'Yo i am actor {uid}')
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await trio.sleep_forever()
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async def main():
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'''
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Spawn a flat actor cluster, with one process per
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detected core.
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'''
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portal_map: dict[str, tractor.Portal]
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results: dict[str, str]
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# look at this hip new syntax!
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async with (
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tractor.open_actor_cluster(
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modules=[__name__]
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) as portal_map,
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trio.open_nursery() as n,
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):
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for (name, portal) in portal_map.items():
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n.start_soon(portal.run, sleepy_jane)
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await trio.sleep(0.5)
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# kill the cluster with a cancel
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raise KeyboardInterrupt
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if __name__ == '__main__':
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try:
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trio.run(main)
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except KeyboardInterrupt:
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pass
|
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@ -38,7 +38,7 @@ async def open_actor_cluster(
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uid = tractor.current_actor().uid
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async def _start(name: str) -> None:
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name = f'{name}.{uid}'
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name = f'{uid[0]}.{name}'
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portals[name] = await an.start_actor(
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enable_modules=modules,
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name=name,
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|
|
Loading…
Reference in New Issue