tractor/tractor/experimental/_pubsub.py

335 lines
12 KiB
Python
Raw Normal View History

Re-license code base for distribution under AGPL 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.
2021-12-13 18:08:32 +00:00
# tractor: structured concurrent "actors".
# Copyright 2018-eternity Tyler Goodlet.
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU Affero General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU Affero General Public License for more details.
# You should have received a copy of the GNU Affero General Public License
# along with this program. If not, see <https://www.gnu.org/licenses/>.
"""
2022-01-29 17:43:06 +00:00
Single target entrypoint, remote-task, dynamic (no push if no consumer)
pubsub API using async an generator which muli-plexes to consumers by
key.
NOTE: this module is likely deprecated by the new bi-directional streaming
support provided by ``tractor.Context.open_stream()`` and friends.
"""
from __future__ import annotations
import inspect
import typing
from typing import (
Any,
Callable,
)
from functools import partial
from async_generator import aclosing
import trio
import wrapt
from ..log import get_logger
from .._context import Context
__all__ = ['pub']
log = get_logger('messaging')
async def fan_out_to_ctxs(
pub_async_gen_func: typing.Callable, # it's an async gen ... gd mypy
topics2ctxs: dict[str, list],
packetizer: typing.Callable | None = None,
) -> None:
'''
Request and fan out quotes to each subscribed actor channel.
'''
def get_topics():
return tuple(topics2ctxs.keys())
agen = pub_async_gen_func(get_topics=get_topics)
2021-04-27 15:08:20 +00:00
async with aclosing(agen) as pub_gen:
2021-04-27 15:08:20 +00:00
async for published in pub_gen:
2021-04-27 15:08:20 +00:00
ctx_payloads: list[tuple[Context, Any]] = []
2021-04-27 15:08:20 +00:00
for topic, data in published.items():
log.debug(f"publishing {topic, data}")
# build a new dict packet or invoke provided packetizer
if packetizer is None:
packet = {topic: data}
else:
packet = packetizer(topic, data)
for ctx in topics2ctxs.get(topic, list()):
ctx_payloads.append((ctx, packet))
if not ctx_payloads:
log.debug(f"Unconsumed values:\n{published}")
# deliver to each subscriber (fan out)
if ctx_payloads:
for ctx, payload in ctx_payloads:
try:
await ctx.send_yield(payload)
except (
# That's right, anything you can think of...
trio.ClosedResourceError, ConnectionResetError,
ConnectionRefusedError,
):
log.warning(f"{ctx.chan} went down?")
for ctx_list in topics2ctxs.values():
try:
ctx_list.remove(ctx)
except ValueError:
continue
if not get_topics():
log.warning(f"No subscribers left for {pub_gen}")
break
def modify_subs(
topics2ctxs: dict[str, list[Context]],
topics: set[str],
ctx: Context,
) -> None:
"""Absolute symbol subscription list for each quote stream.
Effectively a symbol subscription api.
"""
log.info(f"{ctx.chan.uid} changed subscription to {topics}")
# update map from each symbol to requesting client's chan
2019-01-24 03:35:59 +00:00
for topic in topics:
topics2ctxs.setdefault(topic, list()).append(ctx)
# remove any existing symbol subscriptions if symbol is not
# found in ``symbols``
# TODO: this can likely be factored out into the pub-sub api
2019-01-24 03:35:59 +00:00
for topic in filter(
lambda topic: topic not in topics, topics2ctxs.copy()
):
ctx_list = topics2ctxs.get(topic)
if ctx_list:
try:
ctx_list.remove(ctx)
except ValueError:
pass
if not ctx_list:
# pop empty sets which will trigger bg quoter task termination
2019-01-24 03:35:59 +00:00
topics2ctxs.pop(topic)
_pub_state: dict[str, dict] = {}
_pubtask2lock: dict[str, trio.StrictFIFOLock] = {}
def pub(
wrapped: typing.Callable | None = None,
*,
tasks: set[str] = set(),
):
'''
Publisher async generator decorator.
A publisher can be called multiple times from different actors but
will only spawn a finite set of internal tasks to stream values to
each caller. The ``tasks: set[str]`` argument to the decorator
specifies the names of the mutex set of publisher tasks. When the
publisher function is called, an argument ``task_name`` must be
passed to specify which task (of the set named in ``tasks``) should
be used. This allows for using the same publisher with different
input (arguments) without allowing more concurrent tasks then
necessary.
Values yielded from the decorated async generator must be
``dict[str, dict[str, Any]]`` where the fist level key is the topic
string and determines which subscription the packet will be
delivered to and the value is a packet ``dict[str, Any]`` by default
of the form:
.. ::python
{topic: str: value: Any}
The caller can instead opt to pass a ``packetizer`` callback who's
return value will be delivered as the published response.
The decorated async generator function must accept an argument
:func:`get_topics` which dynamically returns the tuple of current
subscriber topics:
.. code:: python
from tractor.msg import pub
@pub(tasks={'source_1', 'source_2'})
async def pub_service(get_topics):
data = await web_request(endpoints=get_topics())
for item in data:
yield data['key'], data
The publisher must be called passing in the following arguments:
- ``topics: set[str]`` the topic sequence or "subscriptions"
- ``task_name: str`` the task to use (if ``tasks`` was passed)
- ``ctx: Context`` the tractor context (only needed if calling the
pub func without a nursery, otherwise this is provided implicitly)
- packetizer: ``Callable[[str, Any], Any]`` a callback who receives
the topic and value from the publisher function each ``yield`` such that
whatever is returned is sent as the published value to subscribers of
2020-08-09 02:29:57 +00:00
that topic. By default this is a dict ``{topic: str: value: Any}``.
As an example, to make a subscriber call the above function:
.. code:: python
from functools import partial
import tractor
async with tractor.open_nursery() as n:
portal = n.run_in_actor(
'publisher', # actor name
partial( # func to execute in it
pub_service,
topics=('clicks', 'users'),
task_name='source1',
)
)
2020-08-09 02:29:57 +00:00
async for value in await portal.result():
print(f"Subscriber received {value}")
Here, you don't need to provide the ``ctx`` argument since the
remote actor provides it automatically to the spawned task. If you
were to call ``pub_service()`` directly from a wrapping function you
would need to provide this explicitly.
Remember you only need this if you need *a finite set of tasks*
running in a single actor to stream data to an arbitrary number of
subscribers. If you are ok to have a new task running for every call
to ``pub_service()`` then probably don't need this.
'''
global _pubtask2lock
# handle the decorator not called with () case
if wrapped is None:
return partial(pub, tasks=tasks)
task2lock: dict[str, trio.StrictFIFOLock] = {}
for name in tasks:
task2lock[name] = trio.StrictFIFOLock()
@wrapt.decorator
async def wrapper(agen, instance, args, kwargs):
# XXX: this is used to extract arguments properly as per the
# `wrapt` docs
async def _execute(
ctx: Context,
topics: set[str],
*args,
# *,
task_name: str | None = None, # default: only one task allocated
packetizer: Callable | None = None,
**kwargs,
):
if task_name is None:
task_name = trio.lowlevel.current_task().name
if tasks and task_name not in tasks:
raise TypeError(
f"{agen} must be called with a `task_name` named "
f"argument with a value from {tasks}")
elif not tasks and not task2lock:
# add a default root-task lock if none defined
task2lock[task_name] = trio.StrictFIFOLock()
_pubtask2lock.update(task2lock)
2020-09-24 14:04:56 +00:00
topics = set(topics)
lock = _pubtask2lock[task_name]
all_subs = _pub_state.setdefault('_subs', {})
topics2ctxs = all_subs.setdefault(task_name, {})
try:
modify_subs(topics2ctxs, topics, ctx)
# block and let existing feed task deliver
# stream data until it is cancelled in which case
# the next waiting task will take over and spawn it again
async with lock:
# no data feeder task yet; so start one
respawn = True
while respawn:
respawn = False
log.info(
f"Spawning data feed task for {funcname}")
try:
# unblocks when no more symbols subscriptions exist
# and the streamer task terminates
await fan_out_to_ctxs(
pub_async_gen_func=partial(
agen, *args, **kwargs),
topics2ctxs=topics2ctxs,
packetizer=packetizer,
)
log.info(
f"Terminating stream task {task_name or ''}"
f" for {agen.__name__}")
except trio.BrokenResourceError:
log.exception("Respawning failed data feed task")
respawn = True
finally:
# remove all subs for this context
modify_subs(topics2ctxs, set(), ctx)
# if there are truly no more subscriptions with this broker
# drop from broker subs dict
if not any(topics2ctxs.values()):
log.info(
f"No more subscriptions for publisher {task_name}")
# invoke it
await _execute(*args, **kwargs)
funcname = wrapped.__name__
if not inspect.isasyncgenfunction(wrapped):
raise TypeError(
f"Publisher {funcname} must be an async generator function"
)
if 'get_topics' not in inspect.signature(wrapped).parameters:
raise TypeError(
f"Publisher async gen {funcname} must define a "
"`get_topics` argument"
)
# XXX: manually monkey the wrapped function since
# ``wrapt.decorator`` doesn't seem to want to play nice with its
# whole "adapter" thing...
wrapped._tractor_stream_function = True # type: ignore
2020-08-09 02:29:57 +00:00
return wrapper(wrapped)