When an `asyncio` side task errors or is cancelled we now explicitly
report the traceback and task name if possible as well as the source
reason for the error (some come from the `trio` side).
Further, properly set any `trio` side exception (after unwrapping it
from the `outcome.Error`) on the future that runs the `trio` guest run.
Python 3.9's new object resolver + a `str` is much simpler then mucking
with tuples (and easier to serialize). Include a `.to_tuple()` formatter
since we still are passing the module namespace and function name
separately inside the runtime's message format but in theory we might be
able to simplify this depending on how we would change the support for
`enable_modules:list[str]` in the spawn API.
Thanks to @Fuyukai for pointing `resolve_name()` which I didn't know
about before!
Adjust the `soft_wait()` strategy to avoid sending needless cancel
requests if it is known that a child process is already terminated or
does so before the cancel request times out. This should be no slower
and should avoid needless waits on either closure-in-progress or already
closed channels.
Basic strategy is,
- request child actor to cancel
- if process termination is detected, cancel the cancel
- if the process is still alive after a cancel request timeout warn the
user and yield back to the hard reap handling
Better encapsulate all the mem-chan, Queue, sync-primitives inside our
linked task channel in order to avoid `mypy`'s complaints about monkey
patching. This also sets footing for adding an `asyncio`-side channel
API that can be used more like this `trio`-side API.
For whatever reason `trio` seems to be swallowing this exception when
raised in the `trio` task so instead wrap it in our own non-base
exception type: `AsyncioCancelled` and raise that when the `asyncio`
task cancels itself internally using `raise <err> from <src_err>` style.
Further don't bother cancelling the `trio` task (via cancel scope)
since we we can just use the recv mem chan closure error as a signal
and explicitly lookup any set asyncio error.
Wraps the pairs of underlying `trio` mem chans and the `asyncio.Queue`
with this new composite which will be delivered from `open_channel_from()`.
This allows for both sending and receiving values from the `asyncio`
task (2 way msg passing) as well controls for cancelling or waiting on
the task.
Factor `asyncio` translation and re-raising logic into a new closure
which is run on both `trio` side error handling as well as on normal
termination to avoid missing `asyncio` errors even when `trio` task
cancellation is handled first.
Only close the `trio` mem chans on `trio` task termination *iff*
the task was spawned using `open_channel_from()`:
- on `open_channel_from()` exit, mem chan closure is the desired semantic
- on `run_task()` we normally only return a single value or error and
if the channel is closed before the error is raised we may propagate
a `trio.EndOfChannel` instead of the desired underlying `asyncio`
task's error
Pull the common `asyncio` -> `trio` error translation logic into
a common context manager and don't expect a final result to be captured
when using `open_channel_from()` since it's a manager interface and it
would be clunky to try and deliver some "final result" after exit.
Close the mem chan before cancelling the `trio` task in order to ensure
we retrieve whatever error is shuttled from `asyncio` before the channel
read is potentially cancelled (previously a race?).
Handle `asyncio.CancelledError` specially such that we raise it directly
(instead of `raise aio_cancelled from other_err`) since it *is* the
source error in the case where the cancellation is `asyncio` internal.
Clearly this wasn't developed against a task that spawned just an async
func in `asyncio`.. Fix all that and remove a bunch of unnecessary func
layers. Add provisional support for the target receiving the `to_trio`
and `from_trio` channels and for the @tractor.stream marker.
This should mostly maintain top level SC principles for any task spawned
using `tractor.to_asyncio.run()`. When the `asyncio` task completes make
sure to cancel the pertaining `trio` cancel scope and raise any error
that may have resulted. This interface uses `trio`'s "guest-mode" to run
`asyncio` loop using a special entrypoint which is handed to Python
during process spawn.
If the one side of an inter-actor context cancels the other then that
side should always expect back a `ContextCancelled` message. However we
should not set this error in this case (where the cancel request was
sent and a `ContextCancelled` msg was received back) since it may
override some other error that caused the cancellation request to be
sent out in the first place. As an example when a context opens another
context to a peer and some error happens which causes the second peer
context to be cancelled but we want to propagate the original error.
Fixes the issue found in https://github.com/pikers/piker/issues/244
After more extensive testing I realized that keying on the context
manager *instance id* isn't going to work since each entering task is
going to create a unique key XD
Instead pass the manager function as `acm_func` and optionally allow
keying the resource on the passed `kwargs` (if hashable) or the
`key:str`. Further, pass the key to the enterer task and avoid
a separate keying scheme for the manager versus the value it delivers.
Don't bother with checking and releasing the lock in `finally:` block,
it should be an error if it's still locked.
Without this wakeup you can have tasks which re-enter `.receive()`
and get stuck waiting on the wakeup event indefinitely. Whenever
a ``trio.EndOfChannel`` arrives we want to make sure all consumers
at least know about it and don't block. This previous behaviour was
basically a bug.
Add some state flags for tracking if the broadcaster was either
cancelled or terminated via EOC mostly for testing and debugging
purposes though this info might be useful if we decide to offer
a `.statistics()` like API in the future.
This commit obviously denotes a re-license of all applicable parts of
the code base. Acknowledgement of this change was completed in #274 by
the majority of the current set of contributors. From here henceforth
all changes will be AGPL licensed and distributed. This is purely an
effort to maintain the same copy-left policy whilst closing the
(perceived) SaaS loophole the GPL allows for. It is merely for this
loophole: to avoid code hiding by any potential "network providers" who
are attempting to use the project to make a profit without either
compensating the authors or re-distributing their changes.
I thought quite a bit about this change and can't see a reason not to
close the SaaS loophole in our current license. We still are (hard)
copy-left and I plan to keep the code base this way for a couple
reasons:
- The code base produces income/profit through parent projects and is
demonstrably of high value.
- I believe firms should not get free lunch for the sake of
"contributions from their employees" or "usage as a service" which
I have found to be a dubious argument at best.
- If a firm who intends to profit from the code base wants to use it
they can propose a secondary commercial license to purchase with the
proceeds going to the project's authors under some form of well
defined contract.
- Many successful projects like Qt use this model; I see no reason it
can't work in this case until such a time as the authors feel it
should be loosened.
There has been detailed discussion in #103 on licensing alternatives.
The main point of this AGPL change is to protect the code base for the
time being from exploitation while it grows and as we move into the next
phase of development which will include extension into the multi-host
distributed software space.
If we make it too fast a nursery with debug mode children can cancel
too fast and causes some test failures. It's likely not a huge deal
anyway since the purpose of this poll/check is for human interaction
and the current delay isn't really that noticeable.
Decrease log levels in the debug module to avoid console noise when in
use. Toss in some more detailed comments around the new debugger lock
points.
A context method handling all this logic makes the most sense since it
contains all the state related to whether the error should be raised in
a nursery scope or is expected to be raised by a consumer task which
reads and processes the msg directly (via a `Portal` API call). This
also makes it easy to always process remote errors even when there is no
(stream) overrun condition.
A context stream overrun should normally never take place since if
a stream is opened (via ``Context.open_stream()``) backpressure is
applied on the message buffer (unless explicitly disabled by the
``backpressure=False`` flag) such that an overrun on the receiving task
should result in blocking the (remote) sender task (eventually depending
on the underlying ``MsgStream`` transport).
Here we add a special error message that reports if one side never
opened a stream and let's the user know in the overrun error message
that they may be trying to push messages to a task that isn't ready to
receive them.
Further fixes / details:
- pop any `Context` at the end of any `_invoke()` task that creates
one and registers with the runtime.
- ignore but warn about messages received for a context that either
no longer exists or is unknown (guarding against crashes by malicious
packets in the latter case)
Keeping it disabled on context open will help with detecting any stream
connection which was never opened on one side of the task pair. In that
case we can report that there was an overrun **and** a stream wasn't
opened versus if the stream is explicitly configured not to use bp then
we throw the standard overflow.
Use `trio.Nursery._closed` to detect "closure" XD since it seems to be
the most reliable way to determine if a spawn call will trigger
a runtime error.
Half of portal API usage requires a 1 message response (`.run()`,
`.run_in_actor()`) and the streaming APIs should probably be explicitly
enabled for backpressure if desired by the user. This makes more sense
in (psuedo) realtime systems where it's better to notify on a block then
freeze without notice. Make this default behaviour with a new error to
be raised: `tractor._exceptions.StreamOverrun` when a sender overruns
a stream by the default size (2**6 for now). The old behavior can be
enabled with `Context.open_stream(backpressure=True)` but now with
warning log messages when there are overruns.
Add task-linked-context error propagation using a "nursery raising"
technique such that if either end of context linked pair of tasks
errors, that error can be relayed to other side and raised as a form of
interrupt at the receiving task's next `trio` checkpoint. This enables
reliable error relay without expecting the (error) receiving task to
call an API which would raise the remote exception (which it might never
currently if using `tractor.MsgStream` APIs).
Further internal implementation details:
- define the default msg buffer size as `Actor.msg_buffer_size`
- expose a `msg_buffer_size: int` kwarg from `Actor.get_context()`
- maybe raise aforementioned context errors using
`Context._maybe_error_from_remote_msg()` inside `Actor._push_result()`
- support optional backpressure on a stream when pushing messages
in `Actor._push_result()`
- in `_invote()` handle multierrors raised from a `@tractor.context`
entrypoint as being potentially caused by a relayed error from the
remote caller task, if `Context._error` has been set then raise that
error inside the `RemoteActorError` that will be relayed back to that
caller more or less proxying through the source side error back to its
origin.
In preparation for supporting both backpressure detection (through an
optional error) as well as control over the msg channel buffer size, add
internal configuration flags for both to contexts. Also adjust
`Context._err_on_from_remote_msg()` -> `._maybe..` such that it can be
called and will only raise if a scope nursery has been set. Add
a `Context._error` for stashing the remote task's error that may be
delivered in an `'error'` message.
Tyler Goodlet