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.
This more formally declares the runtime's remote task startingn API
and uses it throughout all the dependent `Portal` API methods.
Allows dropping `Portal._submit()` and simplifying `.run_in_actor()`
style result waiting to be delegated to the context APIs at remote
task `return` response time. We now also track the remote entrypoint
"type` as `Context._remote_func_type`.
Instead of tracking feeder mem chans per RPC dialog, store `Context`
instances which (now) hold refs to the underlying RPC-task feeder chans
and track them inside a `Actor._contexts` map. This begins a transition
to making the "context" idea the primitive abstraction for representing
messaging dialogs between tasks in different memory domains (i.e.
usually separate processes).
A slew of changes made this possible:
- change `Actor.get_memchans()` -> `.get_context()`.
- Add new `Context._send_chan` and `._recv_chan` vars.
- implicitly create a new context on every `Actor.send_cmd()` call.
- use the context created by `.send_cmd()` in `Portal.open_context()`
instead of manually creating one.
- call `Actor.get_context()` inside tasks run from `._invoke()`
such that feeder chans are implicitly created for callee tasks
thus fixing the bug #265.
NB: We might change some of the internal semantics to do with *when* the
feeder chans are actually created to denote whether or not a far end
task is actually *read to receive* messages. For example, in the cases
where it **never** will be ready to receive messages (one-way streaming,
a context that never opens a stream, etc.) we will likely want some kind
of error or at least warning to the caller that messages can't be sent
(yet).
Previously we were ignoring a race where the callee an opened task
context could enter `Context.open_stream()` before calling `.started().
Disallow this as well as calling `.started()` more then once.
We don't need to any more presuming you get ideal remote cancellation
conditions where the remote actor should teardown and kill the streams
from its end.
On msg loop termination we now check and see if a channel is associated
with a child-actor registered in some local task's nursery. If so, we
attempt to wait on channel closure initiated from the child side (by
draining the underlying msg stream) so as to avoid closing it too early
resulting in the child not relaying its termination status response. This
means we now support the ideal case in 2-general's where we get back the
ack to the closure request instead of just ignoring it and timing out XD
The main implementation detail is that when `Portal.cancel_actor()`
remotely calls `Actor.cancel()` we actually wait for the RPC response
from that request before allowing the channel shutdown sequence to
engage. The new msg stream draining support enables this.
Also, factor child-to-parent error propagation logic into a helper func
and improve some docs (yeah yeah y'all don't like the ''', i don't
care - it makes my eyes not hurt).
Use a `trio.Event` to enable nursery closure detection such that core
runtime tasks can be notified when a local nursery exits and allow
shutdown protocols to operate without close-before-terminate issues
(such as IPC channel closure during remote peer cancellation).
Enables "draining" the last set of messages after a channel/stream has
been terminated mostly for the purposes of receiving a final ACK to
a remote cancel command. Also, add an internal `Channel._cancel_called`
flag which can be set by `Portal.cancel_actor()`.
It's definitely possible to have a nursery spawn task be cancelled
before a `trio.Process` handle is ever returned; we now handle this
case as a cancelled-during-spawn scenario. Zombie collection logic
also is bypassed in this case.
Thanks to @richardsheridan for pointing out the limitations of using
*any* kind of value as the result-cached-flag and how it might cause
problems for anyone returning pickled blob-data. This changes the
`Portal` internal result value tracking to stash the full message from
which the value can be retrieved by any `Portal.result()` caller.
The internal change is that `Portal._return_once()` now returns a tuple
of the message *and* its value.
Fixes the issue where if the main remote task returns `None`,
`Portal.result()` would erroneously wait again on the underlying feeder
mem chan since `None` was being used as the cache flag. Instead set the
flag as the channel uid and consider the result collected when set to
anything else (since it would be odd to return that value from a remote
task when you already can read it as part of portal/channel apis).
The api we've made here is actually closer to `asyncio.gather()` but
with opening async context managers instead of funcs. Use another event
to allow for graceful teardown of children on non-cancellation exits
and add a doc string.
Since it seems we're building out more and more higher level primitives
in order to support certain parallel style actor trees and messaging
patterns (eg. task broadcast channels), we might as well start a new
sub-package for purely `trio` constructions. We hereby dub this
the realm of `trionics` (like electronics but for trios instead of
electrons).
To kick things off, add an `async_enter_all()` concurrent
exit-stack-like context manager API which will concurrently spawn
a sequence of provided async context managers and deliver their ordered
results but with proper support for `trio` cancellation semantics.
The stdlib's `AsyncExitStack` is not compatible with nurseries not
`trio` tasks (which are cancelled) since as task will be suspended on
the stack after push and does not ever hit a checkpoint until the stack
is closed.
Tyler Goodlet
overclockworked64