I'm trying to display an interactive mesh visualizer based on Three.js inside a Jupyter cell. The workflow is the following:
The user launches a Jupyter notebook, and open the viewer in a cell
Using Python commands, the user can manually add meshes and animate them interactively
In practice, the main thread is sending requests to a server via ZMQ sockets (every request needs a single reply), then the server sends back the desired data to the main thread using other socket pairs (many "request", very few replies expected), which finally uses communication through ipython kernel to send the data to the Javascript frontend. So far so good, and it works properly because the messages are all flowing in the same direction:
Main thread (Python command) [ZMQ REQ] -> [ZMQ REP] Server (Data) [ZMQ XREQ] -> [ZMQ XREQ] Main thread (Data) [IPykernel Comm] -> [Ipykernel Comm] Javascript (Display)
However, the pattern is different when I'm want to fetch the status of the frontend to wait for the meshes to finish loading:
Main thread (Status request) --> Server (Status request) --> Main thread (Waiting for reply)
| |
<--------------------------------Javascript (Processing) <--
This time, the server sends a request to the frontend, which in return does not send the reply directly back to the server, but to the main thread, that will forward the reply to the server, and finally to the main thread.
There is a clear issue: the main thread is supposed to jointly forward the reply of the frontend and receive the reply from the server, which is impossible. The ideal solution would be to enable the server to communicate directly with the frontend but I don't know how to do that, since I cannot use get_ipython().kernel.comm_manager.register_target on the server side. I tried to instantiate an ipython kernel client on the server side using jupyter_client.BlockingKernelClient, but I didn't manged to use it to communicate nor to register targets.
OK so I found a solution for now but it is not great. Indeed of just waiting for a reply and keep busy the main loop, I added a timeout and interleave it with do_one_iteration of the kernel to force to handle to messages:
while True:
try:
rep = zmq_socket.recv(flags=zmq.NOBLOCK).decode("utf-8")
except zmq.error.ZMQError:
kernel.do_one_iteration()
It works but unfortunately it is not really portable and it messes up with the Jupyter evaluation stack (all queued evaluations will be processed here instead of in order)...
Alternatively, there is another way that is more appealing:
import zmq
import asyncio
import nest_asyncio
nest_asyncio.apply()
zmq_socket.send(b"ready")
async def enforce_receive():
await kernel.process_one(True)
return zmq_socket.recv().decode("utf-8")
loop = asyncio.get_event_loop()
rep = loop.run_until_complete(enforce_receive())
but in this case you need to know in advance that you expect the kernel to receive exactly one message, and relying on nest_asyncio is not ideal either.
Here is a link to an issue on this topic of Github, along with an example notebook.
UPDATE
I finally manage to solve completely my issue, without shortcomings. The trick is to analyze every incoming messages. The irrelevant messages are put back in the queue in order, while the comm-related ones are processed on-the-spot:
class CommProcessor:
"""
#brief Re-implementation of ipykernel.kernelbase.do_one_iteration
to only handle comm messages on the spot, and put back in
the stack the other ones.
#details Calling 'do_one_iteration' messes up with kernel
'msg_queue'. Some messages will be processed too soon,
which is likely to corrupt the kernel state. This method
only processes comm messages to avoid such side effects.
"""
def __init__(self):
self.__kernel = get_ipython().kernel
self.qsize_old = 0
def __call__(self, unsafe=False):
"""
#brief Check once if there is pending comm related event in
the shell stream message priority queue.
#param[in] unsafe Whether or not to assume check if the number
of pending message has changed is enough. It
makes the evaluation much faster but flawed.
"""
# Flush every IN messages on shell_stream only
# Note that it is a faster implementation of ZMQStream.flush
# to only handle incoming messages. It reduces the computation
# time from about 10us to 20ns.
# https://github.com/zeromq/pyzmq/blob/e424f83ceb0856204c96b1abac93a1cfe205df4a/zmq/eventloop/zmqstream.py#L313
shell_stream = self.__kernel.shell_streams[0]
shell_stream.poller.register(shell_stream.socket, zmq.POLLIN)
events = shell_stream.poller.poll(0)
while events:
_, event = events[0]
if event:
shell_stream._handle_recv()
shell_stream.poller.register(
shell_stream.socket, zmq.POLLIN)
events = shell_stream.poller.poll(0)
qsize = self.__kernel.msg_queue.qsize()
if unsafe and qsize == self.qsize_old:
# The number of queued messages in the queue has not changed
# since it last time it has been checked. Assuming those
# messages are the same has before and returning earlier.
return
# One must go through all the messages to keep them in order
for _ in range(qsize):
priority, t, dispatch, args = \
self.__kernel.msg_queue.get_nowait()
if priority <= SHELL_PRIORITY:
_, msg = self.__kernel.session.feed_identities(
args[-1], copy=False)
msg = self.__kernel.session.deserialize(
msg, content=False, copy=False)
else:
# Do not spend time analyzing already rejected message
msg = None
if msg is None or not 'comm_' in msg['header']['msg_type']:
# The message is not related to comm, so putting it back in
# the queue after lowering its priority so that it is send
# at the "end of the queue", ie just at the right place:
# after the next unchecked messages, after the other
# messages already put back in the queue, but before the
# next one to go the same way. Note that every shell
# messages have SHELL_PRIORITY by default.
self.__kernel.msg_queue.put_nowait(
(SHELL_PRIORITY + 1, t, dispatch, args))
else:
# Comm message. Processing it right now.
comm_handler = getattr(
self.__kernel.comm_manager, msg['header']['msg_type'])
msg['content'] = self.__kernel.session.unpack(msg['content'])
comm_handler(None, None, msg)
self.qsize_old = self.__kernel.msg_queue.qsize()
process_kernel_comm = CommProcessor()
Related
So I have written API for a device. The unit tests are going to run on CI automatically, therefore I will not test the connection with the device, purpose of these unit tests are to just test that my API generate appropriate requests and appropriately react to responses.
Before I had the following:
import serial
import threading
from src.device import Device # that is my API
class TestDevice:
#pytest.fixture(scope='class')
def device(self):
dev = Device()
dev.connect(port='/dev/ttyUSB0')
dev.connect() constantly sends command through serial port to establish handshake it will stay inside the function until response is received or timeout happens
So in order to simulate device, I have opened virtual serial port using socat:
socat -d -d pty,raw,echo=0 pty,raw,echo=0
My idea is to write into one virtual port and read from another. For that I would launch another threading and read from the message that has been sent, and upon thread receiving handshake request, I would sent a reply like this:
class TestDevice:
#pytest.fixture(scope='class')
def device(self):
reader_thread = threading.Thread(target=self.reader)
reader_thread.start()
dev = Device()
dev.connect('/dev/pts/3')
def reader(self):
EXPECTED_HANDSHAKE = b"hello"
HANDSHAKE_REPLY = b"hi"
timeout_handshake_ms = 1000
reader_port = serial.Serial(port='/dev/pts/4', baudrate=115200)
start_time_ns = time.time_ns()
timeout_time_ns = start_time_ns + (timeout_handshake_ms * 1e6)
while time.time_ns() < timeout_time_ns:
response = reader_port.read(1024)
# if dev.connect() sent an appropriate handshake request
# this port would receive it and then
if response == EXPECTED_HANDSHAKE:
reader_port.write(HANDSHAKE_REPLY)
And once the reply is received, dev.connect() will exit successfully and device will be considered successful. All of the code that I have posted works. As you can see, my approach is that I first start reading in a different thread, then I send a command, and in the reader thread I read the response and send appropriate response if applicable. The connection part was an easy one. However, I have 30 commands to test, all of them have different inputs, multiple arguments and etc. Reader's response also varies depending on the Request generated by API. Therefore, I will be needing to send same command with different arguments and I will need to reply to command in many different ways. What is the best way to organize my code, so I can test everything as possible as efficiently as possible. Do I need a thread for every command I am testing? Is there an efficient way to do all of this I have set out to?
I'm building an apllication which is intended to do a bulk-job processing data within another software. To control the other software automatically I'm using pyautoit, and everything works fine, except for application errors, caused from the external software, which occur from time to time.
To handle those cases, I built a watchdog:
It starts the script with the bulk job within a subprocess
process = subprocess.Popen(['python', job_script, src_path], stdout=subprocess.PIPE,
stderr=subprocess.PIPE, shell=True)
It listens to the system event using winevt.EventLog module
EventLog.Subscribe('System', 'Event/System[Level<=2]', handle_event)
In case of an error occurs, it shuts down everything and re-starts the script again.
Ok, if an system error event occurs, this event should get handled in a way, that the supprocess gets notified. This notification should then lead to the following action within the subprocess:
Within the subprocess there's an object controlling everything and continuously collecting
generated data. In order to not having to start the whole job from the beginnig, after re-starting the script, this object has to be dumped using pickle (which isn't the problem here!)
Listening to the system event from inside the subprocess didn't work. It results in a continuous loop, when calling subprocess.Popen().
So, my question is how I can either subscribe for system events from inside a childproces, or communicate between the parent and childprocess - means, sending a message like "hey, an errorocurred", listening within the subprocess and then creating the dump?
I'm really sorry not being allowed to post any code in this case. But I hope (and actually think), that my description should be understandable. My question is just about what module to use to accomplish this in the best way?
Would be really happy, if somebody could point me into the right direction...
Br,
Mic
I believe the best answer may lie here: https://docs.python.org/3/library/subprocess.html#subprocess.Popen.stdin
These attributes should allow for proper communication between the different processes fairly easily, and without any other dependancies.
Note that Popen.communicate() may suit better if other processes may cause issues.
EDIT to add example scripts:
main.py
from subprocess import *
import sys
def check_output(p):
out = p.stdout.readline()
return out
def send_data(p, data):
p.stdin.write(bytes(f'{data}\r\n', 'utf8')) # auto newline
p.stdin.flush()
def initiate(p):
#p.stdin.write(bytes('init\r\n', 'utf8')) # function to send first communication
#p.stdin.flush()
send_data(p, 'init')
return check_output(p)
def test(p, data):
send_data(p, data)
return check_output(p)
def main()
exe_name = 'Doc2.py'
p = Popen([sys.executable, exe_name], stdout=PIPE, stderr=STDOUT, stdin=PIPE)
print(initiate(p))
print(test(p, 'test'))
print(test(p, 'test2')) # testing responses
print(test(p, 'test3'))
if __name__ == '__main__':
main()
Doc2.py
import sys, time, random
def recv_data():
return sys.stdin.readline()
def send_data(data):
print(data)
while 1:
d = recv_data()
#print(f'd: {d}')
if d.strip() == 'test':
send_data('return')
elif d.strip() == 'init':
send_data('Acknowledge')
else:
send_data('Failed')
This is the best method I could come up with for cross-process communication. Also make sure all requests and responses don't contain newlines, or the code will break.
I am using CherryPy to speak to an authentication server. The script runs fine if all the inputted information is fine. But if they make an mistake typing their ID the internal HTTP error screen fires ok, but the server keeps running and nothing else in the script will run until the CherryPy engine is closed so I have to manually kill the script. Is there some code I can put in the index along the lines of
if timer >10 and connections == 0:
close cherrypy (< I have a method for this already)
Im mostly a data mangler, so not used to web servers. Googling shows lost of hits for closing CherryPy when there are too many connections but not when there have been no connections for a specified (short) time. I realise the point of a web server is usually to hang around waiting for connections, so this may be an odd case. All the same, any help welcome.
Interesting use case, you can use the CherryPy plugins infrastrcuture to do something like that, take a look at this ActivityMonitor plugin implementation, it shutdowns the server if is not handling anything and haven't seen any request in a specified amount of time (in this case 10 seconds).
Maybe you have to adjust the logic on how to shut it down or do anything else in the _verify method.
If you want to read a bit more about the publish/subscribe architecture take a look at the CherryPy Docs.
import time
import threading
import cherrypy
from cherrypy.process.plugins import Monitor
class ActivityMonitor(Monitor):
def __init__(self, bus, wait_time, monitor_time=None):
"""
bus: cherrypy.engine
wait_time: Seconds since last request that we consider to be active.
monitor_time: Seconds that we'll wait before verifying the activity.
If is not defined, wait half the `wait_time`.
"""
if monitor_time is None:
# if monitor time is not defined, then verify half
# the wait time since the last request
monitor_time = wait_time / 2
super().__init__(
bus, self._verify, monitor_time, self.__class__.__name__
)
# use a lock to make sure the thread that triggers the before_request
# and after_request does not collide with the monitor method (_verify)
self._active_request_lock = threading.Lock()
self._active_requests = 0
self._wait_time = wait_time
self._last_request_ts = time.time()
def _verify(self):
# verify that we don't have any active requests and
# shutdown the server in case we haven't seen any activity
# since self._last_request_ts + self._wait_time
with self._active_request_lock:
if (not self._active_requests and
self._last_request_ts + self._wait_time < time.time()):
self.bus.exit() # shutdown the engine
def before_request(self):
with self._active_request_lock:
self._active_requests += 1
def after_request(self):
with self._active_request_lock:
self._active_requests -= 1
# update the last time a request was served
self._last_request_ts = time.time()
class Root:
#cherrypy.expose
def index(self):
return "Hello user: current time {:.0f}".format(time.time())
def main():
# here is how to use the plugin:
ActivityMonitor(cherrypy.engine, wait_time=10, monitor_time=5).subscribe()
cherrypy.quickstart(Root())
if __name__ == '__main__':
main()
I'm trying to connect Python with Supercollider through OSC, but it's not working.
I'm using Python3 and the library osc4py3.
The original idea was to send a text word by word, but upon trying I realized the connection was not working.
Here's the SC code:
(
OSCdef.new(\texto,{
|msg, time, addr, port|
[msg, time, addr,port].postIn;
},
'/texto/supercollider',
n
)
)
OSCFunc.trace(true);
o = OSCFunc(\texto);
And here's the Python code:
osc_startup()
osc_udp_client("127.0.0.1", 57120, "supercollider")
## here goes a function called leerpalabras to separate words in rows.
with open("partitura.txt", "r") as f:
for palabra in leerpalabras(f):
msg = oscbuildparse.OSCMessage("/texto/supercollider", ",s", palabra)
osc_send(msg, "supercollider")
sleep(2)
osc_terminate()
I've also tried with this, to see if maybe there was something wrong with my for loop (with the startup, and terminate of course):
msg = oscbuildparse.OSCMessage("/texto/supercollider", ",s", "holis")
osc_send(msg, "supercollider")
I run the trace method on SC, nothing appears on the post window when I run the Python script on terminal, but no error appears on neither one of them, so I'm a bit lost on what I can test to make sure is getting somewhere.
It doesn't print on the SC post window, it just says OSCdef(texto, /texto/supercollider, nil, nil, nil).
When I run the SuperCollider piece of your example, and then run:
n = NetAddr("127.0.0.1", 57120);
n.sendMsg('/texto/supercollider', 1, 2, 3);
... I see the message printed immediately (note that you used postIn instead of postln, if you don't fix that you'll get an error instead of a printed message).
Like you, I don't see anything when I send via the Python library - my suspicion is that there's something wrong on the Python side? There's a hint in this response that you have to call osc_process() after sends, but that still doesn't work for me
You can try three things:
Run OSCFunc.trace in SuperCollider and watch for messages (this will print ALL incoming OSC messages), to see if your OSCdef is somehow not receiving messages.
Try a network analyzer like Packet Peeper (http://packetpeeper.org/) to watch network traffic on your local loopback network lo0. When I do this, I can clearly see messages sent by SuperCollider, but I don't see any of the messages I send from Python, even when I send in a loop and call osc_process().
If you can't find any sign of Python sending OSC packets, try a different Python library - there are many others available.
(I'm osc4py3 author)
osc4py3 store messages to send within internal lists and returns immediately. These lists are processed during osc_process() calls or directly by background threads (upon selected theading model).
So, if you have selected as_eventloop threading model, you need to call osc_process() some times, like:
…
with open("partitura.txt", "r") as f:
for palabra in leerpalabras(f):
msg = oscbuildparse.OSCMessage("/texto/supercollider", ",s", palabra)
osc_send(msg, "supercollider")
for missme in range(4):
osc_process()
sleep(0.5)
…
See doc: https://osc4py3.readthedocs.io/en/latest/userdoc.html#threading-model
using python 3, I'm trying to send a file from a server to a client as soon as the client connects to the server, problem is that the client do only continue from recv when I close it (when the connection is closed)
I'm running the client in blender game engine, the client is running until it gets to recv, then it just stops, until i exit the game engine, then I can see that the console is receiving the bytes expected.
from other threads I have read that this might be bco the recv never gets an end, that's why I added "\n\r" to the end of my bytearray that the server is sending. but still, the client just stops at recv until I exit the application.
in the code below I'm only sending the first 6 bytes, these are to tell the client the size of the file. after this i intend to send data of the file on the same connection.
what am I doing wrong here?
client:
import socket
import threading
def TcpConnection():
TCPsocket = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
TCPsocket.setsockopt(socket.IPPROTO_TCP, socket.TCP_NODELAY, 1)
server_address = ('localhost', 1338)
TCPsocket.connect(server_address)
print("TCP Socket open!, starting thread!")
ServerResponse = threading.Thread(target=TcpReciveMessageThread,args=(TCPsocket,))
ServerResponse.daemon = True
ServerResponse.start()
def TcpReciveMessageThread(Sock):
print("Tcp thread running!")
size = Sock.recv(6)#Sock.MSG_WAITALL
print("Recived data", size)
Sock.close()
Server:
import threading
import socket
import os
def StartTcpSocket():
server_socket = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
server_socket.bind(('localhost', 1338))
server_socket.listen(10)
while 1:
connection, client_address = server_socket.accept()
Response = threading.Thread(target=StartTcpClientThread,args=(connection,))
Response.daemon = True # thread dies when main thread (only non-daemon thread) exits.
Response.start()
def StartTcpClientThread(socket):
print("Sending data")
length = 42
l1 = ToByts(length)
socket.send(l1)
#loop that sends the file goes here
print("Data sent")
#socket.close()
def ToByts(Size):
byt_res = (Size).to_bytes(4,byteorder='big')
result = bytearray()
for r in byt_res:
result.append(r)
t = bytearray("\r\n","utf-8")
for b in t:
result.append(b)
return result
MessageListener = threading.Thread(target=StartTcpSocket)
MessageListener.daemon = True # thread dies when main thread (only non-daemon thread) exits.
MessageListener.start()
while 1:
pass
if the problem is that the client don't find a end of the stream, then how can solve this without closing the connection, as I intend to send the file on the same connection.
Update #1:
to clarify, the print in the client that say "recived" is printed first when I exit the ge (the client is closing). The loop that sends the file and recives it where left out of the question as they are not the problem. the problem still occurs without them, client freeze at recv until it is closed.
Update #2:
here are a image of what my consoles are printing when i run the server and client:
as you can see it is never printing the "Recived" print
when i exit the blender game engine, I get this output:
now, when the engine and the server script is exited/closed/finished i get the data printed. so recv is probably pausing the thread until the socket is closed, why are it doing this? and how can i get my data (and the print) before the socket is closing? This also happens if I set
ServerResponse.daemon = False
here are a .blend (on mediafire) of the client, the server running on python 3 (pypy). I'm using blender 2.78a
Update #3:
I tested and verified that the problem is the same on windows 10 and linux mint. I also made a Video showing the problem:
In the video you can see how I only receive data from the server when i exit blender ge. After some research I besinning to suspect that the problem is related to python threading not playing well with the bge.
https://www.youtube.com/watch?v=T5l9YGIoDYA
I have observed a similar phenomenon. It appears that the Python instance doesn't receive any execution cycles from Blender Game Engine (BGE) unless a controller gets invoked.
A simple solution is:
Add another Always sensor that is fired on every logic tick.
Add another Python controller that does nothing, a no-op.
Hook the sensor to the controller.
I applied this to your .blend as shown in the following screen capture.
I tested it by running your server and it seems to work OK.
Cheers, Jim