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Merge pull request #67 from tgoodlet/docs_example_fixes 

Docs example fixes
ipc_iternals_renaming
tgoodlet 2019-03-11 16:10:00 -04:00 committed by GitHub
parent ddf467acf5 322145684b
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@ -159,7 +159,7 @@ Actor spawning and causality
``tractor`` tries to take ``trio``'s concept of causal task lifetimes ``tractor`` tries to take ``trio``'s concept of causal task lifetimes
to multi-process land. Accordingly, ``tractor``'s *actor nursery* behaves to multi-process land. Accordingly, ``tractor``'s *actor nursery* behaves
similar to ``trio``'s nursery_. That is, ``tractor.open_nursery()`` similar to ``trio``'s nursery_. That is, ``tractor.open_nursery()``
opens an ``ActorNursery`` which waits on spawned *actors* to complete opens an ``ActorNursery`` which **must** wait on spawned *actors* to complete
(or error) in the same causal_ way ``trio`` waits on spawned subtasks. (or error) in the same causal_ way ``trio`` waits on spawned subtasks.
This includes errors from any one actor causing all other actors This includes errors from any one actor causing all other actors
spawned by the same nursery to be cancelled_. spawned by the same nursery to be cancelled_.
@ -181,14 +181,13 @@ and use the ``run_in_actor()`` method:
""" """
async with tractor.open_nursery() as n: async with tractor.open_nursery() as n:
portal = await n.run_in_actor('teacher', cellar_door) portal = await n.run_in_actor('some_linguist', cellar_door)
# The ``async with`` will unblock here since the 'frank' # The ``async with`` will unblock here since the 'some_linguist'
# actor has completed its main task ``movie_theatre_question()``. # actor has completed its main task ``cellar_door``.
print(await portal.result()) print(await portal.result())
tractor.run(main) tractor.run(main)
@ -204,11 +203,11 @@ What's going on?
returned from ``nursery.run_in_actor()`` is used to communicate with returned from ``nursery.run_in_actor()`` is used to communicate with
the newly spawned *sub-actor* the newly spawned *sub-actor*
- the second actor, *frank*, in a new *process* running a new ``trio`` task_ - the second actor, *some_linguist*, in a new *process* running a new ``trio`` task_
then executes ``cellar_door()`` and returns its result over a *channel* back then executes ``cellar_door()`` and returns its result over a *channel* back
to the parent actor to the parent actor
- the parent actor retrieves the subactor's (*frank*) *final result* using ``portal.result()`` - the parent actor retrieves the subactor's *final result* using ``portal.result()``
much like you'd expect from a future_. much like you'd expect from a future_.
This ``run_in_actor()`` API should look very familiar to users of This ``run_in_actor()`` API should look very familiar to users of
@ -227,7 +226,7 @@ method:
method and act like an RPC daemon that runs indefinitely (the method and act like an RPC daemon that runs indefinitely (the
``with tractor.open_nursery()`` won't exit) until cancelled_ ``with tractor.open_nursery()`` won't exit) until cancelled_
Had we wanted the latter form in our example it would have looked like: Here is a similar example using the latter method:
.. code:: python .. code:: python
@ -584,7 +583,7 @@ find an actor's socket address by name use the ``find_actor()`` function:
print(f"my_service is found at {my_service}") print(f"my_service is found at {my_service}")
tractor.run(main, service_name) tractor.run(main, 'some_actor_name')
The ``name`` value you should pass to ``find_actor()`` is the one you passed as the The ``name`` value you should pass to ``find_actor()`` is the one you passed as the