I adapted this code for using Google Cloud PubSub in Async Python: https://github.com/cloudfind/google-pubsub-asyncio
import asyncio
import datetime
import functools
import os
from google.cloud import pubsub
from google.gax.errors import RetryError
from grpc import StatusCode
async def message_producer():
""" Publish messages which consist of the current datetime """
while True:
await asyncio.sleep(0.1)
async def proc_message(message):
await asyncio.sleep(0.1)
print(message)
message.ack()
def main():
""" Main program """
loop = asyncio.get_event_loop()
topic = "projects/{project_id}/topics/{topic}".format(
project_id=PROJECT, topic=TOPIC)
subscription_name = "projects/{project_id}/subscriptions/{subscription}".format(
project_id=PROJECT, subscription=SUBSCRIPTION)
subscription = make_subscription(
topic, subscription_name)
def create_proc_message_task(message):
""" Callback handler for the subscription; schedule a task on the event loop """
print("Task created!")
task = loop.create_task(proc_message(message))
subscription.open(create_proc_message_task)
# Produce some messages to consume
loop.create_task(message_producer())
print("Subscribed, let's do this!")
loop.run_forever()
def make_subscription(topic, subscription_name):
""" Make a publisher and subscriber client, and create the necessary resources """
subscriber = pubsub.SubscriberClient()
try:
subscriber.create_subscription(subscription_name, topic)
except:
pass
subscription = subscriber.subscribe(subscription_name)
return subscription
if __name__ == "__main__":
main()
I basically removed the publishing code and only use the subscription code.
However, initially I did not include the loop.create_task(message_producer()) line. I figured that tasks were created as they were supposed to however they never actually run themselves. Only if I add said line the code properly executes and all created Tasks run. What causes this behaviour?
PubSub is calling the create_proc_message_task callback from a different thread. Since create_task is not thread-safe, it must only be called from the thread that runs the event loop (typically the main thread). To correct the issue, replace loop.create_task(proc_message(message)) with asyncio.run_coroutine_threadsafe(proc_message(message), loop) and message_producer will no longer be needed.
As for why message_producer appeared to fix the code, consider that run_coroutine_threadsafe does two additional things compared to create_task:
It operates in a thread-safe fashion, so the event loop data structures are not corrupted when this is done concurrently.
It ensures that the event loop wakes up at the soonest possible opportunity, so that it can process the new task.
In your case create_task added the task to the loop's runnable queue (without any locking), but failed to ensure the wakeup, because that is not needed when running in the event loop thread. The message_producer then served to force the loop to wake up in regular intervals, which is when it also checks and executes the runnable tasks.
Related
i have a program that basically does 2 things:
opens a websocket and remains on listening for messages and starting a video streaming in a forever loop.
I was trying to use multiprocess to manage both things but one piece stops the other from running.
The app is
if __name__ == '__main__':
loop = asyncio.get_event_loop()
loop.run_until_complete(start_client())
async def start_client():
async with WSClient() as client:
pass
class WSClient:
async def __aenter__(self):
async with websockets.connect(url,max_size= None) as websocket:
self.websocket = websocket
await self.on_open() ## it goes
p = Process(target = init(self)) # This is the streaming method
p.start()
async for message in websocket:
await on_message(message, websocket) ## listen for websocket messages
return self
the init method is
def init(ws):
logging.info('Firmware Version: ' + getVersion())
startStreaming(ws)
return
basically startStreaming has an infinite loop in it.
In this configuration, the stream starts but the on_message of the websocket it's not called because the Process function freezes the rest of the application.
How can I run both methods?
Thanks
In your code, you're telling multiprocessing.Process to take the function returned by init and call it in a new process. What you want is for the process to call init itself (with an argument). Here's how you can do that:
p = Process(target=init, args=(self,))
I have to note that you're passing an asynchronous websocket object to your init function. This will likely break as asyncio stuff aren't usually meant to be used in two threads, let alone two processes. Unless you're somehow recreating the websocket object in the new process and making a new loop there too, what you're actually looking for is how to create an asyncio task.
Assuming startStreaming is already an async function, you should change the init function to this:
async def init(ws): # note the async
logging.info('Firmware Version: ' + getVersion())
await startStreaming(ws) # note the await
return
and change the line creating and starting the process to this:
asyncio.create_task(init(self))
This will run your startStreaming function in a new task while you also read incoming messages at (basically) the same time.
Also, I'm not sure what you're trying to do with the async context manager as everything could be just in a normal async function. If you're interested in using one for learning purposes, I'd suggest you to check out contextlib.asynccontextmanager and have your message reading code inside the async with statement in start_client rather than inside __aenter__.
Objective
I am processing some files then uploading them to the cloud. My objective is to have an async producer and consumer. The producer copies data from a database, and compresses files, while the consumer uploads files to the cloud. My objective is to produce tasks as soon as they are available but only consume them one by one (I am trying to avoid sending too many files to s3 as I get throttled by aws).
What I have tried to do
I have successfully created a queue of a consumer and producer; however, my producer seems to be producing one item at a time. Here is the code I have tried (please let me know if I can add any further code):
import asyncio
import concurrent.futures
import logging
from asyncio import Queue
import aiobotocore
import asyncpg
import uvloop
from asyncpg.pool import Pool
from aws_async import upload_to_s3
from helpers import gather_with_concurrency, chunk_query, build_query, parquet_data
from pg_async import pg_copy
from resources.config import ARGS, PG_CONFIG, AWS_S3_CONFIG
# Defaults to CPU count and spawns up to 32 threads
EXECUTOR = concurrent.futures.ThreadPoolExecutor()
async def producer(query: str, pool: Pool, q: Queue):
# I expect all that loop to run async but it runs 1 by 1..
for qr in query:
# Process query and place (asynchronously) into queue
query_data = await pg_copy(pool, qr)
await q.put(query_data)
async def consume(queue, client, bucket):
while True:
item = await queue.get()
if item is None:
break
await upload_to_s3(client, bucket, item)
queue.task_done()
async def main():
# Define parameters based on parsed args
queries = build_query(ARGS.query, bool(ARGS.chunks), chunk_query, chunks=ARGS.chunks, chunk_col=ARGS.chunk_col)
# Define pool
pool = await asyncpg.create_pool(**PG_CONFIG)
# Define Aiobotocore async client
async with aiobotocore.get_session().create_client(**AWS_S3_CONFIG) as client:
# Prepare tasks from queries
queue = asyncio.Queue()
consumer = asyncio.create_task(consume(queue, client, bucket=ARGS.bucket))
await gather_with_concurrency(ARGS.parallelism, producer(queries, pool, queue))
# wait for the remaining tasks to be processed
await queue.join()
consumer.cancel()
uvloop.install()
asyncio.run(main())
Thanks to this answer, my gather_with_concurrency (which I use to throttle concurrent tasks running at a time) looks like:
async def gather_with_concurrency(n: int, *tasks):
semaphore = asyncio.Semaphore(n)
async def sem_task(task):
async with semaphore:
return await task
return await asyncio.gather(*(sem_task(task) for task in tasks))
What I am trying to achieve
The current behavior is that the producer is producing items 1 by 1. I want to have my producer processing all tasks asynchronously and place them into the queue as soon as they are made available (while still keeping the throttle that I have created), but my consumer consuming 1 task at a time.
Happy to add any further information if needed = )
Edit:
Thanks to dirn for helping me clarify my question earlier
I have subscribed to a MQ queue. Every time I get a message, I pass it a function that then performs a number of time-consuming I/O actions on it.
The issue is that everything happens serially.
A request comes in, it picks up the request, performs the action by calling the function, and then picks up the next request.
I want to do this asynchronously so that multiple requests can be dealt with in an async manner.
results = []
queue = queue.subscribe(name)
async for message in queue:
yield my_funcion(message)
The biggest issue is that my_function is slow because it calls external web services and I want my code to process other messages in the meantime.
I tried to implement it above but it doesn't work! I am not sure how to implement async here.
I can't create a task because I don't know how many requests will be received. It's a MQ which I have subscribed to. I loop over each message and perform an action. I don't want for the function to complete before I perform the action on the next message. I want it to happen asynchronously.
If I understand your request, what you need is a queue that your request handlers fill, and that you read from from the code that needs to do something with the results.
If you insist on an async iterator, it is straightforward to use a generator to expose the contents of a queue. For example:
def make_asyncgen():
queue = asyncio.Queue(1)
async def feed(item):
await queue.put(item)
async def exhaust():
while True:
item = await queue.get()
yield item
return feed, exhaust()
make_asyncgen returns two objects: an async function and an async generator. The two are connected in such a way that, when you call the function with an item, the item gets emitted by the generator. For example:
import random, asyncio
# Emulate a server that takes some time to process each message,
# and then provides a result. Here it takes an async function
# that it will call with the result.
async def serve(server_ident, on_message):
while True:
await asyncio.sleep(random.uniform(1, 5))
await on_message('%s %s' % (server_ident, random.random()))
async def main():
# create the feed function, and the generator
feed, get = make_asyncgen()
# subscribe to serve several requests in parallel
asyncio.create_task(serve('foo', feed))
asyncio.create_task(serve('bar', feed))
asyncio.create_task(serve('baz', feed))
# process results from all three servers as they arrive
async for msg in get:
print('received', msg)
asyncio.run(main())
I seem to be having a difficult time understanding pythons asyncio. I have not written any code, as all the examples I see are for one-off runs. Create a few coroutine's, add them to an event loop, then run the loop, they run the tasks switching between them, done. Which does not seem all that helpful for me.
I want to use asyncio to not interrupt the operation in my application (using pyqt5). I want to create some functions that when called run in the asyncio event loop, then when they are done they do a callback.
What I imagine is. Create a separate thread for asyncio, create the loop and run it forever. Create some functions getFile(url, fp), get(url), readFile(file), etc. Then in the UI, I have a text box with a submit button, user enters url, clicks submit, it downloads the file.
But, every example I see, I cannot see how to add a coroutine to a running loop. And I do not see how I could do what I want without adding to a running loop.
#!/bin/python3
import asyncio
import aiohttp
import threading
loop = asyncio.get_event_loop()
def async_in_thread(loop):
asyncio.set_event_loop(loop)
loop.run_forever()
async def _get(url, callback):
print("get: " + url)
async with aiohttp.ClientSession() as session:
async with session.get(url) as response:
result = await response.text()
callback(result)
return
def get(url, callback):
asyncio.ensure_future(_get(url, callback))
thread = threading.Thread(target=async_in_thread, args=(loop, ))
thread.start()
def stop():
loop.close()
def callme(data):
print(data)
stop()
get("http://google.com", callme)
thread.join()
This is what I imagine, but it does not work.
To add a coroutine to a loop running in a different thread, use asyncio.run_coroutine_threadsafe:
def get(url, callback):
asyncio.run_coroutine_threadsafe(_get(url, callback))
In general, when you are interacting with the event loop from outside the thread that runs it, you must run everything through either run_coroutine_threadsafe (for coroutines) or loop.call_soon_threadsafe (for functions). For example, to stop the loop, use loop.call_soon_threadsafe(loop.stop). Also note that loop.close() must not be invoked inside a loop callback, so you should place that call in async_in_thread, right after the call to run_forever(), at which point the loop has definitely stopped running.
Another thing with asyncio is that passing explicit when_done callbacks isn't idiomatic because asyncio exposes the concept of futures (akin to JavaScript promises), which allow attaching callbacks to a not-yet-available result. For example, one could write _get like this:
async def _get(url):
print("get: " + url)
async with aiohttp.ClientSession() as session:
async with session.get(url) as response:
return await response.text()
It doesn't need a callback argument because any interested party can convert it to a task using loop.create_task and use add_done_callback to be notified when the task is complete. For example:
def _get_with_callback(url, callback):
loop = asyncio.get_event_loop()
task = loop.create_task(_get(url))
task.add_done_callback(lambda _fut: callback(task.result()))
In your case you're not dealing with the task directly because your code aims to communicate with the event loop from another thread. However, run_coroutine_threadsafe returns a very useful value - a full-fledged concurrent.futures.Future which you can use to register done callbacks. Instead of accepting a callback argument, you can expose the future object to the caller:
def get(url):
return asyncio.run_coroutine_threadsafe(_get(url), loop)
Now the caller can choose a callback-based approach:
future = get(url)
# call me when done
future.add_done_callback(some_callback)
# ... proceed with other work ...
or, when appropriate, they can even wait for the result:
# give me the response, I'll wait for it
result = get(url).result()
The latter is by definition blocking, but since the event loop is safely running in a different thread, it is not affected by the blocking call.
Install QualMash to smooth integration between Qt and asyncio.
Example from the project's README gives an inspiration for how it looks like:
import sys
import asyncio
import time
from PyQt5.QtWidgets import QApplication, QProgressBar
from quamash import QEventLoop, QThreadExecutor
app = QApplication(sys.argv)
loop = QEventLoop(app)
asyncio.set_event_loop(loop) # NEW must set the event loop
progress = QProgressBar()
progress.setRange(0, 99)
progress.show()
async def master():
await first_50()
with QThreadExecutor(1) as exec:
await loop.run_in_executor(exec, last_50)
async def first_50():
for i in range(50):
progress.setValue(i)
await asyncio.sleep(.1)
def last_50():
for i in range(50,100):
loop.call_soon_threadsafe(progress.setValue, i)
time.sleep(.1)
with loop: ## context manager calls .close() when loop completes, and releases all resources
loop.run_until_complete(master())
I am pretty new with async programming and python in general but I want to implement an asynchronous function inside a state machine. The requirements are as follows:
The async task must be cancellable at any point in time
The async task must not block the main thread of execution
The async task must call a callback once it is done.
In order to achieve target 1 & 2, I have succesfully implemented my async routine to run inside an executor as stated here: asyncio: Is it possible to cancel a future been run by an Executor?. While debugging, I see that I also accomplish #2 because the original thread continues succesfully. However, I am having a hard time implementing the callback function. Please notice that this callback function must run on the original thread, since it will change the state of the object assigned to it. How can I accomplish this?
My code:
class Free(State):
def write(self, manager):
write_future = self.write_async(manager)
self.set_write_future(write_future)
self.change_state(manager, busy_state)
def write_async(self, manager):
event = threading.Event()
write_future = asyncio.get_event_loop().run_in_executor(None, self.async_write, 10, event)
write_future.add_done_callback(functools.partial(self.async_write_callback, manager))
return event
def async_write(self, seconds_to_block, event):
for i in range(seconds_to_block):
if event.is_set():
return
print('writing {}/{}'.format(i, seconds_to_block))
time.sleep(1)
print('done writing {}'.format(seconds_to_block))
def async_write_callback(self, manager):
#never gets called
self.terminate_future()
self.change_state(manager, free_state)