This begins the move to dropping support for `tractor.run()` which we
don't really need since the runtime is started (as it always has been)
from a new sub-task / nursery. Instead this introduces starting the
actor tree through a `open_root_actor()` async context manager which
we'll likely implicitly call (from the root) on the first use of an
actor nursery.
Drop `_actor._start_actor()` and factor its contents into this new api.
Make `run()` and `run_daemon()` use `open_root_actor()` until we decide
to remove them.
Relates to #168 and #177
This resolves and completes #69 allowing all RPC invocation APIs to pass
function references directly instead of explicit `str` names for the
target namespace and function (this is still done implicitly
underneath). This brings us closer to `trio`'s task running API as well
as acknowledges that any inter-host RPC system (and API) will likely
need to be implemented on top of local RPC primitives anyway. Even if
this ends up **not** being true we can always go to "function stubs" as
part of our IAC protocol or, add a new method to do explicit namespace
calls: `.run_from_module()` or whatever everyone votes on.
Resolves#69
Further, this commit drops `Actor.statespace` from the entire system
since a user can easily get this same functionality using module
level variables. Fix docs to match all these changes (luckily mostly
already done due to example scripts referencing).
Turns out this is a lower level issue in terms of the stdlib's default
`pdb.Pdb` settings and how they conflict with `trio`s cancellation and
KBI handling. The details are hashed out more thoroughly in
python-trio/trio#1155. Maybe we can get a fix in trio so things are
solved under our feet :)
Set `trio-run-in-process` as the default on *nix systems and
`multiprocessing`'s spawn method on Windows. Enable overriding the
default choice using `tractor._spawn.try_set_start_method()`. Allows
for easy runs of the test suite using a user chosen backend.
Add `@tractor.stream` which must be used to denote non async generator
streaming functions which use the `tractor.Context` API to push values.
This enforces a more explicit denotation as well as allows enforcing the
declaration of the `ctx` argument in definitions.
Add full support for using the "spawn" process starting method as per:
https://docs.python.org/3/library/multiprocessing.html#contexts-and-start-methods
Add a `spawn_method` argument to `tractor.run()` for specifying the
desired method explicitly. By default use the "fastest" method available.
On *nix systems this is the original "forkserver" method.
This should be the solution to getting windows support!
Resolves#60
Add a draft pub-sub API `@tractor.msg.pub` which allows
for decorating an asyn generator which can stream topic keyed
dictionaries for delivery to multiple calling / consuming tasks.
RPC module/function lookups should not cause the target actor to crash.
This change instead ships the error back to the calling actor allowing
for the remote actor to continue running depending on the caller's
error handling logic. Adds a new `ModuleNotExposed` error to accommodate.
Use the new custom error types throughout the actor and portal
primitives and set a few new rules:
- internal errors are any error not raised by an rpc task and are
**not** forwarded to portals but instead are raised directly in
the msg loop.
- portals always re-raise a "main task" error for every call to
``Portal.result()``.
This is purely for documentation purposes for now as it should be
obvious a bunch of the signatures aren't using the correct "generics"
syntax (i.e. the use of `(str, int)` instead of `typing.Tuple[str, int])`)
in a bunch of places. We're also not using a type checker yet and besides,
`trio` doesn't really expose a lot of its internal types very well.
2SQASH
Allows for waiting on another actor (by name) to register with the
arbiter. This makes synchronized actor spawning and consecutive task
coordination easier to accomplish from within sub-actors.
Resolves#31
Stop worrying about a "main task" in each actor and instead add an
additional `ActorNursery.run_in_actor()` method which wraps calls
to create an actor and run a lone RPC task inside it. Note this
adjusts the public API of `ActorNursery.start_actor()` to drop
its `main` kwarg.
The dirty deats of making this possible:
- each spawned RPC task is now tracked with a specific cancel scope such
that when the actor is cancelled all ongoing responders are cancelled
before any IPC/channel machinery is closed (turns out that spawning
new actors from `outlive_main=True` actors was probably borked before
finally getting this working).
- make each initial RPC response be a packet which describes the
`functype` (eg. `{'functype': 'asyncfunction'}`) allowing for async
calls/submissions by client actors (this was required to make
`run_in_actor()` work - `Portal._submit()` is the new async method).
- hooray we can stop faking "main task" results for daemon actors
- add better handling/raising of internal errors caught in the bowels of
the `Actor` itself.
- drop the rpc spawning nursery; just use the `Actor._root_nursery`
- only wait on `_no_more_peers` if there are existing peer channels that
are actually still connected.
- an `ActorNursery.__aexit__()` now implicitly waits on `Portal.result()` on close
for each `run_in_actor()` spawned actor.
- handle cancelling partial started actors which haven't yet connected
back to the parent
Resolves#24
Take @njsmith's advice and properly close actor invoked async generators
using `async_generator.aclosing()` instead of hacking it (as previous)
with a shielded cancel scope.
Cancellation requires that each actor cancel it's spawned subactors
before cancelling its own root (nursery's) cancel scope to avoid breaking
channel connections before kill commands (`Actor.cancel()`) have been sent
off to peers. To solve this, ensure each main task is cancelled to
completion first (which will guarantee that all actor nurseries have
completed their cancellation steps) before cancelling the actor's "core"
tasks under the "root" scope.
Here is a bunch of code tightening to make sure cancellation works even
if recently spawned actors haven't fully started up and the parent is
cancelled.
The fixes include:
- passing the arbiter socket address to each actor
- ensure all spawned actors respect the spawner's log level
- handle process versus final `portal.result()` teardown in multiple
tasks such that if a proc dies before shipping a result we don't wait
- more detailed debug logging in teardown code paths
- don't store peer connected events in the same `dict` as the peer channels
- if necessary fake main task results on peer channel disconnect
- warn when a `trio.Cancelled` is what causes a nursery to bail
otherwise error
- store the subactor portal in the nursery for teardown purposes
- add dedicated `Portal.cancel_actor()` which acts as a "hard cancel"
and never blocks (indefinitely)
- add `Arbiter.unregister_actor()` it's more explicit what's being
requested
- Allow passing in a program-wide `loglevel`
- Add detailed debug logging particularly to do with channel msg processing
and connection handling
- Don't daemonize subprocesses for now as it prevents use of
sub-sub-actors (need to solve #6 first)
- Add a `Portal.close()` which just tells the remote actor to tear down
the channel (for now)
- Add a message to signal the remote `StopAsyncIteration` from an async
gen such that the client side terminates properly as well
- Make `Actor.cancel()` cancel the channel server first
- Actors *must* complete the arbiter registeration steps before moving
on with their main taks and rpc handling
- When delivering rpc responses (using the local per caller queue) use
the blocking interface (`trio.Queue.put()`) to get backpressure
- Properly detect an `partial` wrapped async generators in `_invoke`
Fix quite a few little bugs:
- async gen func detection in `_invoke()`
- always cancel channel server on main task exit
- wait for remaining channel peers after unsub from arbiter
- return result from main task(s) all the way up to `tractor.run()`
Also add a `Portal.result()` for getting the final result(s) from the
actor's main task and fix up a bunch of docs.
Tyler Goodlet
Tyler Goodlet