#asyncio.coroutine
def listener():
while True:
message = yield from websocket.recieve_message()
if message:
yield from handle(message)
loop = asyncio.get_event_loop()
loop.run_until_complete(listener())
Let's say i'm using websockets with asyncio. That means I recieve messages from websockets. And when I recieve a message, I want to handle the message but I'm loosing all the async thing with my code. Because the yield from handle(message) is definetly blocking... How could I find a way to make it non-blocking ? Like, handle multiple messages in the same time. Not having to wait the message to be handled before I can handle another message.
Thanks.
If you don't care about the return value from handle message, you can simply create a new Task for it, which will run in the event loop alongside your websocket reader. Here is a simple example:
#asyncio.coroutine
def listener():
while True:
message = yield from websocket.recieve_message()
if message:
asyncio.ensure_future(handle(message))
ensure_future will create a task and attach it to the default event loop. Since the loop is already running, it will get processed alongside your websocket reader in parallel. In fact, if it is a slow-running I/O blocked task (like sending an email), you could easily have a few dozen handle(message) tasks running at once. They are created dynamically when needed, and destroyed when finished (with much lower overhead than spawning threads).
If you want a bit more control, you could simply write to an asyncio.Queue in the reader and have a task pool of a fixed size that can consume the queue, a typical pattern in multi-threaded or multi-process programming.
#asyncio.coroutine
def consumer(queue):
while True:
message = yield from queue.get()
yield from handle(message)
#asyncio.coroutine
def listener(queue):
for i in range(5):
asyncio.ensure_future(consumer(queue))
while True:
message = yield from websocket.recieve_message()
if message:
yield from q.put(message)
q = asyncio.Queue()
loop = asyncio.get_event_loop()
loop.run_until_complete(listener(q))
Related
I have a TCP server running and have a handler function which needs to take the contents of the request, add it to an asyncio queue and reply with an OK status.
On the background I have an async coroutine running that detects when a new item is added and performs some processing.
How do I put items in the asyncio queue from the handler function, which isn't and can't be an async coroutine?
I am running a DICOM server pynetdicom which listens on port 104 for incoming TCP requests (DICOM C-STORE specifically).
I need to save the contents of the request to a queue and return a a 0x0000 response so that the listener is available to the network.
This is modeled by a producer-consumer pattern.
I have tried to define a consumer co-routine consume_dicom() that is currently stuck in await queue.get() since I can't properly define the producer.
The producer needs to simply invoke queue.put(produce_item) but this happens inside a handle_store(event) function which is not part of the event_loop but is called every time a request is received by the server.
import asyncio
from pynetdicom import (
AE, evt,
StoragePresentationContexts
)
class PacsServer():
def __init__(self, par, listen=True):
# Initialize other stuff...
# Initialize DICOM server
ae = AE(ae_title='DICOM-NODE')
ae.supported_contexts = StoragePresentationContexts
# When a C-STORE request comes, it will be passed to self.handle_store
handlers = [(evt.EVT_C_STORE, self.handle_store)]
# Define queue
loop = asyncio.get_event_loop()
self.queue = asyncio.Queue(loop=loop)
# Define consumer
loop.create_task(self.consume_dicom(self.queue))
# Start server in the background with specified handlers
self.scp = ae.start_server(('', 104), block=False, evt_handlers=handlers)
# Start async loop
self.loop.run_forever()
def handle_store(self, event):
# Request handling
ds = event.dataset
# Here I want to add to the queue but this is not an async method
await queue.put(ds)
return 0x0000
async def consume_dicom(self, queue):
while True:
print(f"AWAITING FROM QUEUE")
ds = await queue.get()
do_some_processing(ds)
I would like to find a way to add items to the queue and return the OK status in the handle_store() function.
Since handle_store is running in a different thread, it needs to tell the event loop to enqueue the item. This is done with call_soon_threadsafe:
self.loop.call_soon_threadsafe(queue.put_nowait, ds)
Note that you need to call queue.put_nowait instead of queue.put because the former is a function rather than a coroutine. The function will always succeed for unbounded queues (the default), otherwise it will raise an exception if the queue is full.
Trying to use pyserial with asyncio on a windows machine.
Inspired by https://stackoverflow.com/a/27927704/1629704 my code is constantly watching a serial port for incoming data.
# This coroutine is added as a task to the event loop.
#asyncio.coroutine
def get_from_serial_port(self):
while 1:
serial_data = yield from self.get_byte_async()
<doing other stuff with serial_data>
# The method which gets executed in the executor
def get_byte(self):
data = self.s.read(1)
time.sleep(0.5)
tst = self.s.read(self.s.inWaiting())
data += tst
return data
# Runs blocking function in executor, yielding the result
#asyncio.coroutine
def get_byte_async(self):
with concurrent.futures.ThreadPoolExecutor(max_workers=1) as executor:
res = yield from self.loop.run_in_executor(executor, self.get_byte)
return res
After serial data has been returned. the coroutine get_byte_async is called inside the while loop creating a new executor. I always learned creating a new thread is expensive so I feel I should take another approach, but I am not sure how to do that.
I've been reading this article https://hackernoon.com/threaded-asynchronous-magic-and-how-to-wield-it-bba9ed602c32#.964j4a5s7
And I guess I need to do the reading of the serial port in another thread. But how to get the serial data back to the "main" loop ?
You can either use the default executor and lock the access to get_byte with an asyncio lock:
async def get_byte_async(self):
async with self.lock:
return await self.loop.run_in_executor(None, self.get_byte)
Or simply create your own executor once:
async def get_byte_async(self):
if self.executor is None:
self.executor = concurrent.futures.ThreadPoolExecutor(max_workers=1)
return await self.loop.run_in_executor(self.executor, self.get_byte)
I'm using the websockets library to create a websocket server in Python 3.4. Here's a simple echo server:
import asyncio
import websockets
#asyncio.coroutine
def connection_handler(websocket, path):
while True:
msg = yield from websocket.recv()
if msg is None: # connection lost
break
yield from websocket.send(msg)
start_server = websockets.serve(connection_handler, 'localhost', 8000)
asyncio.get_event_loop().run_until_complete(start_server)
asyncio.get_event_loop().run_forever()
Let's say we – additionally – wanted to send a message to the client whenever some event happens. For simplicity, let's send a message periodically every 60 seconds. How would we do that? I mean, because connection_handler is constantly waiting for incoming messages, the server can only take action after it has received a message from the client, right? What am I missing here?
Maybe this scenario requires a framework based on events/callbacks rather than one based on coroutines? Tornado?
I'm surprised gather isn't mentioned.
From the Python documentation:
import asyncio
async def factorial(name, number):
f = 1
for i in range(2, number + 1):
print(f"Task {name}: Compute factorial({i})...")
await asyncio.sleep(1)
f *= i
print(f"Task {name}: factorial({number}) = {f}")
async def main():
# Schedule three calls *concurrently*:
await asyncio.gather(
factorial("A", 2),
factorial("B", 3),
factorial("C", 4),
)
asyncio.run(main())
# Expected output:
#
# Task A: Compute factorial(2)...
# Task B: Compute factorial(2)...
# Task C: Compute factorial(2)...
# Task A: factorial(2) = 2
# Task B: Compute factorial(3)...
# Task C: Compute factorial(3)...
# Task B: factorial(3) = 6
# Task C: Compute factorial(4)...
# Task C: factorial(4) = 24
TL;DR Use asyncio.ensure_future() to run several coroutines concurrently.
Maybe this scenario requires a framework based on events/callbacks rather than one based on coroutines? Tornado?
No, you don't need any other framework for this. The whole idea the asynchronous application vs synchronous is that it doesn't block, while waiting for result. It doesn't matter how it is implemented, using coroutines or callbacks.
I mean, because connection_handler is constantly waiting for incoming messages, the server can only take action after it has received a message from the client, right? What am I missing here?
In synchronous application you will write something like msg = websocket.recv(), which would block whole application until you receive message (as you described). But in the asynchronous application it's completely different.
When you do msg = yield from websocket.recv() you say something like: suspend execution of connection_handler() until websocket.recv() will produce something. Using yield from inside coroutine returns control back to the event loop, so some other code can be executed, while we're waiting for result of websocket.recv(). Please, refer to documentation to better understand how coroutines work.
Let's say we – additionally – wanted to send a message to the client whenever some event happens. For simplicity, let's send a message periodically every 60 seconds. How would we do that?
You can use asyncio.async() to run as many coroutines as you want, before executing blocking call for starting event loop.
import asyncio
import websockets
# here we'll store all active connections to use for sending periodic messages
connections = []
#asyncio.coroutine
def connection_handler(connection, path):
connections.append(connection) # add connection to pool
while True:
msg = yield from connection.recv()
if msg is None: # connection lost
connections.remove(connection) # remove connection from pool, when client disconnects
break
else:
print('< {}'.format(msg))
yield from connection.send(msg)
print('> {}'.format(msg))
#asyncio.coroutine
def send_periodically():
while True:
yield from asyncio.sleep(5) # switch to other code and continue execution in 5 seconds
for connection in connections:
print('> Periodic event happened.')
yield from connection.send('Periodic event happened.') # send message to each connected client
start_server = websockets.serve(connection_handler, 'localhost', 8000)
asyncio.get_event_loop().run_until_complete(start_server)
asyncio.async(send_periodically()) # before blocking call we schedule our coroutine for sending periodic messages
asyncio.get_event_loop().run_forever()
Here is an example client implementation. It asks you to enter name, receives it back from the echo server, waits for two more messages from server (which are our periodic messages) and closes connection.
import asyncio
import websockets
#asyncio.coroutine
def hello():
connection = yield from websockets.connect('ws://localhost:8000/')
name = input("What's your name? ")
yield from connection.send(name)
print("> {}".format(name))
for _ in range(3):
msg = yield from connection.recv()
print("< {}".format(msg))
yield from connection.close()
asyncio.get_event_loop().run_until_complete(hello())
Important points:
In Python 3.4.4 asyncio.async() was renamed to asyncio.ensure_future().
There are special methods for scheduling delayed calls, but they don't work with coroutines.
Same issue, can hardly got solution until I saw the perfect sample here: http://websockets.readthedocs.io/en/stable/intro.html#both
done, pending = await asyncio.wait(
[listener_task, producer_task],
return_when=asyncio.FIRST_COMPLETED) # Important
So, I can handle multi coroutine tasks such as heartbeat and redis subscribe.
If you are using Python 3.7 and later you can use asyncio.gather() and asyncio.run() as follows:
import asyncio
async def coro1():
for i in range(1, 6):
print(i)
await asyncio.sleep(0) # switches task every one iteration.
async def coro2():
for i in range(1, 6):
print(i * 10)
await asyncio.sleep(0) # switches task every one iteration.
async def main():
await asyncio.gather(
coro1(),
coro2(),
)
asyncio.run(main())
## Or instead of defining the main async function:
futures = [coro1(), coro2()]
await asyncio.gather(*futures)
Otherwise, if you are using Python 3.6 or 3.5 do as follows for the same result which you should handle the loop as well:
import asyncio
async def coro1():
for i in range(1, 6):
print(i)
await asyncio.sleep(0) # switches task every one iteration.
async def coro2():
for i in range(1, 6):
print(i * 10)
await asyncio.sleep(0) # switches task every one iteration.
loop = asyncio.get_event_loop()
futures = [
asyncio.ensure_future(coro1()),
asyncio.ensure_future(coro2())
]
loop.run_until_complete(asyncio.gather(*futures))
loop.close()
Out:
1
10
2
20
3
30
4
40
5
50
[UPDATE]:
With new syntax in Python 3.11 you don't need .gather():
async def main():
async with asyncio.TaskGroup() as tg:
tg.create_task(coro1())
tg.create_task(coro2())
asyncio.run(main())
I have a TCP server implemented in Python using asyncio's create_server.
I call the coroutine start_server with a connection_handler_cb.
Now my question is this: let's say my connection_handler_cb looks something
like this:
def connection_handler_cb(reader, writer):
while True:
yield from reader.read()
--do some computation--
I know that only the yield from coroutines are being run "concurrently" (I know it's not really concurrent), all the "--do some computation--" part is being called sequentially and is preventing everything else from running in the loop.
Let's say we are talking about a TCP server with multiple clients trying to send. Can this situation cause send timeout from the other side - the client side?
If your clients are waiting for a response from the server, and that response isn't sent until the computation is done, then it's possible the clients could eventually timeout, if the computations took long enough. More likely, though, is that the clients will just hang until the computations are done and the event loop gets unblocked.
In any case, if you're worried about timeouts or hangs, use loop.run_in_executor to run your computations in a background process (this is preferable), or thread (probably not a good choice since you're doing CPU-bound computations) without blocking the event loop:
import asyncio
import multiprocessing
from concurrent.futures import ProcessPoolExecutor
def comp_func(arg1, arg2):
# Do computation here
return output
def connection_handler_cb(reader, writer):
while True:
yield from reader.read()
# Do computation in a background process
# This won't block the event loop.
output = yield from loop.run_in_executor(None, comp_func, arg1, arg2) #
if __name__ == "__main__":
executor =
loop = asyncio.get_event_loop()
loop.set_default_executor(
ProcessPoolExecutor(multiprocessing.cpu_count()))
asyncio.async(asyncio.start_server(connect_handler_cb, ...))
loop.run_forever()
Using asyncio a coroutine can be executed with a timeout so it gets cancelled after the timeout:
#asyncio.coroutine
def coro():
yield from asyncio.sleep(10)
loop = asyncio.get_event_loop()
loop.run_until_complete(asyncio.wait_for(coro(), 5))
The above example works as expected (it times out after 5 seconds).
However, when the coroutine doesn't use asyncio.sleep() (or other asyncio coroutines) it doesn't seem to time out. Example:
#asyncio.coroutine
def coro():
import time
time.sleep(10)
loop = asyncio.get_event_loop()
loop.run_until_complete(asyncio.wait_for(coro(), 1))
This takes more than 10 seconds to run because the time.sleep(10) isn't cancelled. Is it possible to enforce the cancellation of the coroutine in such a case?
If asyncio should be used to solve this, how could I do that?
No, you can't interrupt a coroutine unless it yields control back to the event loop, which means it needs to be inside a yield from call. asyncio is single-threaded, so when you're blocking on the time.sleep(10) call in your second example, there's no way for the event loop to run. That means when the timeout you set using wait_for expires, the event loop won't be able to take action on it. The event loop doesn't get an opportunity to run again until coro exits, at which point its too late.
This is why in general, you should always avoid any blocking calls that aren't asynchronous; any time a call blocks without yielding to the event loop, nothing else in your program can execute, which is probably not what you want. If you really need to do a long, blocking operation, you should try to use BaseEventLoop.run_in_executor to run it in a thread or process pool, which will avoid blocking the event loop:
import asyncio
import time
from concurrent.futures import ProcessPoolExecutor
#asyncio.coroutine
def coro(loop):
ex = ProcessPoolExecutor(2)
yield from loop.run_in_executor(ex, time.sleep, 10) # This can be interrupted.
loop = asyncio.get_event_loop()
loop.run_until_complete(asyncio.wait_for(coro(loop), 1))
Thx #dano for your answer. If running a coroutine is not a hard requirement, here is a reworked, more compact version
import asyncio, time
timeout = 0.5
loop = asyncio.get_event_loop()
future = asyncio.wait_for(loop.run_in_executor(None, time.sleep, 2), timeout)
try:
loop.run_until_complete(future)
print('Thx for letting me sleep')
except asyncio.exceptions.TimeoutError:
print('I need more sleep !')
For the curious, a little debugging in my Python 3.8.2 showed that passing None as an executor results in the creation of a _default_executor, as follows:
self._default_executor = concurrent.futures.ThreadPoolExecutor()
The examples I've seen for timeout handling are very trivial. Given reality, my app is bit more complex. The sequence is:
When a client connects to server, have the server create another connection to internal server
When the internal server connection is ok, wait for the client to send data. Based on this data we may make a query to internal server.
When there is data to send to internal server, send it. Since internal server sometimes doesn't respond fast enough, wrap this request into a timeout.
If the operation times out, collapse all connections to signal the client about error
To achieve all of the above, while keeping the event loop running, the resulting code contains following code:
def connection_made(self, transport):
self.client_lock_coro = self.client_lock.acquire()
asyncio.ensure_future(self.client_lock_coro).add_done_callback(self._got_client_lock)
def _got_client_lock(self, task):
task.result() # True at this point, but call there will trigger any exceptions
coro = self.loop.create_connection(lambda: ClientProtocol(self),
self.connect_info[0], self.connect_info[1])
asyncio.ensure_future(asyncio.wait_for(coro,
self.client_connect_timeout
)).add_done_callback(self.connected_server)
def connected_server(self, task):
transport, client_object = task.result()
self.client_transport = transport
self.client_lock.release()
def data_received(self, data_in):
asyncio.ensure_future(self.send_to_real_server(message, self.client_send_timeout))
def send_to_real_server(self, message, timeout=5.0):
yield from self.client_lock.acquire()
asyncio.ensure_future(asyncio.wait_for(self._send_to_real_server(message),
timeout, loop=self.loop)
).add_done_callback(self.sent_to_real_server)
#asyncio.coroutine
def _send_to_real_server(self, message):
self.client_transport.write(message)
def sent_to_real_server(self, task):
task.result()
self.client_lock.release()