I am working on a Python flask app, and the main method start() calls an external API (third_party_api_wrapper()). That external API has an associated webhook (webhook()) that receives the output of that external API call (note that the output that webhook() receives is actually different from the response returned in the third_party_wrapper())
The main method start() needs the result of webhook(). How do I make start() wait for webhook() to be executed? And how do wo pass the returned value of webhook() back to start()?
Here's is a minimal code snippet to capture the scenario.
#app.route('/webhook', methods=['POST'])
def webhook():
return "webhook method has executed"
# this method has a webhook that calls webhook() after this method has executed
def third_party_api_wrapper():
url = 'https://api.thirdparty.com'
response = requests.post(url)
return response
# this is the main entry point
#app.route('/start', methods=['POST'])
def start():
third_party_api_wrapper()
# The rest of this code depends on the output of webhook().
# How do we wait until webhook() is called, and how do we access the returned value?
The answer to this question really depends on how you plan on running your app in production. It's much simpler if we make the assumption that you only plan to have a single instance of your app running at once (as opposed to multiple behind a load balancer, for example), so I'll make that assumption first to give you a place to start, and comment on a more "production-ready" solution afterwards.
A big thing to keep in mind when writing a web application is that you have to understand how you want the outside world to interact with your app. Do you expect to have the /start endpoint called only once at the beginning of your app's lifetime, or is this a generic endpoint that may start any number of background processes that you want the caller of each to wait for? Or, do you want the behavior where any caller after the first one will wait for the same process to complete as the first one? I can't answer these questions for you, it depends on the use-case you're trying to implement. I'll give you a relatively simple solution that you should be able to modify to fulfill any of the ones I mentioned though.
This solution will use the Event class from the threading standard library module; I added some comments to clarify which parts you may have to change depending on the specifics of the API you're calling and stuff like that.
import threading
import uuid
from typing import Any
import requests
from flask import Flask, Response, request
# The base URL for your app, if you're running it locally this should be fine
# however external providers can't communicate with your `localhost` so you'll
# need to change this for your app to work end-to-end.
BASE_URL = "http://localhost:5000"
app = Flask(__name__)
class ThirdPartyProcessManager:
def __init__(self) -> None:
self.events = {}
self.values = {}
def wait_for_request(self, request_id: str) -> None:
event = threading.Event()
actual_event = self.events.setdefault(request_id, event)
if actual_event is not event:
raise ValueError(f"Request {request_id} already exists.")
event.wait()
return self.values.pop(request_id)
def finish_request(self, request_id: str, value: Any) -> None:
event = self.events.pop(request_id, None)
if event is None:
raise ValueError(f"Request {request_id} does not exist.")
self.values[request_id] = value
event.set()
MANAGER = ThirdPartyProcessManager()
# This is assuming that you can specify the callback URL per-request, otherwise
# you may have to get the request ID from the body of the request or something
#app.route('/webhook/<request_id>', methods=['POST'])
def webhook(request_id: str) -> Response:
MANAGER.finish_request(request_id, request.json)
return "webhook method has executed"
# Somehow in here you need to create or generate a unique identifier for this
# request--this may come from the third-party provider, or you can generate one
# yourself. There are three main paths I see here:
# - If you can specify the callback/webhook URL in each call, you can just pass them
# <base>/webhook/<request_id> and use that to identify which request is being
# responded to in the webhook.
# - If the provider gives you a request ID, you can return it from this function
# then retrieve it from the request body in the webhook route
# For now, I'll assume the first situation but you should be able to implement the second
# with minimal changes
def third_party_api_wrapper() -> str:
request_id = uuid.uuid4().hex
url = 'https://api.thirdparty.com'
# Just an example, I don't know how the third party API you're working with works
response = requests.post(
url,
json={"callback_url": f"{BASE_URL}/webhook/{request_id}"}
)
# NOTE: unrelated to the problem at hand, you should always check for errors
# in HTTP responses. This method is an easy way provided by requests to raise
# for non-success status codes.
response.raise_for_status()
return request_id
#app.route('/start', methods=['POST'])
def start() -> Response:
request_id = third_party_api_wrapper()
result = MANAGER.wait_for_request(request_id)
return result
If you want to run the example fully locally to test it, do the following:
Comment out lines 62-71, which actually make the external API call
Add a print statement after line 77, so that you can get the ID of the "in flight" request. E.g. print("Request ID", request_id)
In one terminal, run the app by pasting the above code into an app.py file and running flask run in that directory.
In another terminal, start the process via:
curl -XPOST http://localhost:5000/start
Copy the request ID that will be logged in the first terminal that's running the server.
In a third terminal, complete the process by calling the webhook:
curl -XPOST http://localhost:5000/webhook/<your_request_id> -H Content-Type:application/json -d '{"foo":"bar"}'
You should see {"foo":"bar"} as the response in the second terminal that made the /start request.
I hope that's enough to help you get started w/ whatever problem you're trying to solve.
There are a couple of design-y comments I have based on the information provided as well:
As I mentioned before, this will not work if you have more than one instance of the app running at once. This works by storing the state of in-flight requests in a global state inside your python process, so if you have more than one process, they won't all be working and modifying the same state. If you need to run more than one instance of your process, I would use a similar approach with some database backend to store the shared state (assuming your requests are pretty short-lived, Redis might be a good choice here, but once again it'll depend on exactly what you're trying to do).
Even if you do only have one instance of the app running, flask is capable of being run in a variety of different server contexts--for example, the server might be using threads (the default), greenlets via gevent or a similar library, or multiple processes, or maybe some other approach entirely in order to handle multiple requests concurrently. If you're using an approach that creates multiple processes, you should be able to use the utilities provided by the multiprocessing module to implement the same approach as I've given above.
This approach probably will work just fine for something where the difference in time between the API call and the webhook response is small (on the order of a couple of seconds at most I'd say), but you should be wary of using this approach for something where the difference in time can be quite large. If the connection between the client and your server fails, they'll have to make another request and run the long-running process that your third party is completing for you again. Some proxies and load balancers may also have time out behavior that could terminate the request after a certain amount of time even if nothing goes wrong in the connection between your server and the client making a request to it. An alternative approach would be for your /start endpoint to return quickly and give the client a request_id that they could poll for updates. As an example, AWS Athena's API is structured like this--there is a StartQueryExecution method, and separate GetQueryExecution and GetQueryResults methods that the client makes requests to check the status of a query and retrieve the results respectively (there are also other methods like StopQueryExecution and GetQueryRuntimeStatistics available as well). You can check out the documentation here.
I know that's a lot of info, but I hope it helps. Happy to update the answer w/ more specific info if you'll provide some more details about your use-case.
I am trying to setting up an acceptance test harness for a flask app and I am currently struggling to wait for the app to start before making calls.
Following construct works fine:
class SpinUpTests(unittest.TestCase):
def tearDown(self):
super().tearDown()
self.stubby_server.kill()
self.stubby_server.communicate()
def test_given_not_yet_running_when_created_without_config_then_started_on_default_port(self):
self.not_yet_running(5000)
self.stubby_server = subprocess.Popen(['python', '../../app/StubbyServer.py'], stdout=subprocess.PIPE)
time.sleep(1)#<--- I would like to get rid of this
self.then_started_on_port(5000)
I would like to wait on stdout for:
self.stubby_server = subprocess.Popen(['python', '../../app/StubbyServer.py'], stdout=subprocess.PIPE)
time.sleep(1)#<--- I would like to get rid of this
Running on http://127.0.0.1:[port]/ (Press CTRL+C to quit)
I tried
for line in self.stubby_server.stdout.readline()
but readline() never finishes, tho I already see the output in the test output window.
Any ideas how I can wait for the flask app to start without having to use an explicit sleep()?
Using the retry package, this will help overcome your problem. Ultimately, you set what you are looking to try again, what exception you want to retry on, and you can set specific timing parameters based on how you want to retry. It's pretty well documented.
Here is an example of how I solved this in one of the projects I was working on here
Here is the snippet of code that will help you, in case that link does not work:
#classmethod
def _start_app_locally(cls):
subprocess.Popen(["fake-ubersmith"])
retry_call(
requests.get,
fargs=["{}/status".format(cls.endpoint)],
exceptions=RequestException,
delay=1
)
As you can see I just tried to hit my endpoint with a get using requests (the fargs are the arguments passed to requests.get as you can see it calls back the method you pass to retry_call), and based on the RequestException I was expecting, I would retry with a 1 second delay.
Finally, "fake-ubersmith" is the command that will run your server, which is ultimately your similar command of: 'python', '../../app/StubbyServer.py'
The problem statement is as follows:
I am working with Abaqus, a program for analyzing mechanical problems. It is basically a standalone Python interpreter with its own objects etc. Within this program, I run a python script to set up my analysis (so this script can be modified). It also contains a method which has to be executed when an external signal is received. These signals come from the main script that I am running in my own Python engine.
For now, I have the following workflow:
The main script sets a boolean to True when the Abaqus script has to execute a specific function, and pickles this boolean into a file. The Abaqus script regularly checks this file to see whether the boolean has been set to true. If so, it does an analysis and pickles the output, so that the main script can read this output and act on it.
I am looking for a more efficient way to signal the other process to start the analysis, since there is a lot of unnecessary checking going on right know. Data exchange via pickle is not an issue for me, but a more efficient solution is certainly welcome.
Search results always give me solutions with subprocess or the like, which is for two processes started within the same interpreter. I have also looked at ZeroMQ since this is supposed to achieve things like this, but I think this is overkill and would like a solution in python. Both interpreters are running python 2.7 (although different versions)
Edit:
Like #MattP, I'll add this statement of my understanding:
Background
I believe that you are running a product called abaqus. The abaqus product includes a linked-in python interpreter that you can access somehow (possibly by running abaqus python foo.py on the command line).
You also have a separate python installation, on the same machine. You are developing code, possibly including numpy/scipy, to run on that python installation.
These two installations are different: they have different binary interpreters, different libraries, different install paths, etc. But they live on the same physical host.
Your objective is to enable the "plain python" programs, written by you, to communicate with one or more scripts running in the "Abaqus python" environment, so that those scripts can perform work inside the Abaqus system, and return results.
Solution
Here is a socket based solution. There are two parts, abqlistener.py and abqclient.py. This approach has the advantage that it uses a well-defined mechanism for "waiting for work." No polling of files, etc. And it is a "hard" API. You can connect to a listener process from a process on the same machine, running the same version of python, or from a different machine, or from a different version of python, or from ruby or C or perl or even COBOL. It allows you to put a real "air gap" into your system, so you can develop the two parts with minimal coupling.
The server part is abqlistener. The intent is that you would copy some of this code into your Abaqus script. The abq process would then become a server, listening for connections on a specific port number, and doing work in response. Sending back a reply, or not. Et cetera.
I am not sure if you need to do setup work for each job. If so, that would have to be part of the connection. This would just start ABQ, listen on a port (forever), and deal with requests. Any job-specific setup would have to be part of the work process. (Maybe send in a parameter string, or the name of a config file, or whatever.)
The client part is abqclient. This could be moved into a module, or just copy/pasted into your existing non-ABQ program code. Basically, you open a connection to the right host:port combination, and you're talking to the server. Send in some data, get some data back, etc.
This stuff is mostly scraped from example code on-line. So it should look real familiar if you start digging into anything.
Here's abqlistener.py:
# The below usage example is completely bogus. I don't have abaqus, so
# I'm just running python2.7 abqlistener.py [options]
usage = """
abacus python abqlistener.py [--host 127.0.0.1 | --host mypc.example.com ] \\
[ --port 2525 ]
Sets up a socket listener on the host interface specified (default: all
interfaces), on the given port number (default: 2525). When a connection
is made to the socket, begins processing data.
"""
import argparse
parser = argparse.ArgumentParser(description='Abacus listener',
add_help=True,
usage=usage)
parser.add_argument('-H', '--host', metavar='INTERFACE', default='',
help='Interface IP address or name, or (default: empty string)')
parser.add_argument('-P', '--port', metavar='PORTNUM', type=int, default=2525,
help='port number of listener (default: 2525)')
args = parser.parse_args()
import SocketServer
import json
class AbqRequestHandler(SocketServer.BaseRequestHandler):
"""Request handler for our socket server.
This class is instantiated whenever a new connection is made, and
must override `handle(self)` in order to handle communicating with
the client.
"""
def do_work(self, data):
"Do some work here. Call abaqus, whatever."
print "DO_WORK: Doing work with data!"
print data
return { 'desc': 'low-precision natural constants','pi': 3, 'e': 3 }
def handle(self):
# Allow the client to send a 1kb message (file path?)
self.data = self.request.recv(1024).strip()
print "SERVER: {} wrote:".format(self.client_address[0])
print self.data
result = self.do_work(self.data)
self.response = json.dumps(result)
print "SERVER: response to {}:".format(self.client_address[0])
print self.response
self.request.sendall(self.response)
if __name__ == '__main__':
print args
server = SocketServer.TCPServer((args.host, args.port), AbqRequestHandler)
print "Server starting. Press Ctrl+C to interrupt..."
server.serve_forever()
And here's abqclient.py:
usage = """
python2.7 abqclient.py [--host HOST] [--port PORT]
Connect to abqlistener on HOST:PORT, send a message, wait for reply.
"""
import argparse
parser = argparse.ArgumentParser(description='Abacus listener',
add_help=True,
usage=usage)
parser.add_argument('-H', '--host', metavar='INTERFACE', default='',
help='Interface IP address or name, or (default: empty string)')
parser.add_argument('-P', '--port', metavar='PORTNUM', type=int, default=2525,
help='port number of listener (default: 2525)')
args = parser.parse_args()
import json
import socket
message = "I get all the best code from stackoverflow!"
print "CLIENT: Creating socket..."
s = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
print "CLIENT: Connecting to {}:{}.".format(args.host, args.port)
s.connect((args.host, args.port))
print "CLIENT: Sending message:", message
s.send(message)
print "CLIENT: Waiting for reply..."
data = s.recv(1024)
print "CLIENT: Got response:"
print json.loads(data)
print "CLIENT: Closing socket..."
s.close()
And here's what they print when I run them together:
$ python2.7 abqlistener.py --port 3434 &
[2] 44088
$ Namespace(host='', port=3434)
Server starting. Press Ctrl+C to interrupt...
$ python2.7 abqclient.py --port 3434
CLIENT: Creating socket...
CLIENT: Connecting to :3434.
CLIENT: Sending message: I get all the best code from stackoverflow!
CLIENT: Waiting for reply...
SERVER: 127.0.0.1 wrote:
I get all the best code from stackoverflow!
DO_WORK: Doing work with data!
I get all the best code from stackoverflow!
SERVER: response to 127.0.0.1:
{"pi": 3, "e": 3, "desc": "low-precision natural constants"}
CLIENT: Got response:
{u'pi': 3, u'e': 3, u'desc': u'low-precision natural constants'}
CLIENT: Closing socket...
References:
argparse, SocketServer, json, socket are all "standard" Python libraries.
To be clear, my understanding is that you are running Abaqus/CAE via a Python script as an independent process (let's call it abq.py), which checks for, opens, and reads a trigger file to determine if it should run an analysis. The trigger file is created by a second Python process (let's call it main.py). Finally, main.py waits to read the output file created by abq.py. You want a more efficient way to signal abq.py to run an analysis, and you're open to different techniques to exchange data.
As you mentioned, subprocess or multiprocessing might be an option. However, I think a simpler solution is to combine your two scripts, and optionally use a callback function to monitor the solution and process your output. I'll assume there is no need to have abq.py constantly running as a separate process, and that all analyses can be started from main.py whenever it is appropriate.
Let main.py have access to the Abaqus Mdb. If it's already built, you open it with:
mdb = openMdb(FileName)
A trigger file is not needed if main.py starts all analyses. For example:
if SomeCondition:
j = mdb.Job(name=MyJobName, model=MyModelName)
j.submit()
j.waitForCompletion()
Once complete, main.py can read the output file and continue. This is straightforward if the data file was generated by the analysis itself (e.g. .dat or .odb files). OTH, if the output file is generated by some code in your current abq.py, then you can probably just include it in main.py instead.
If that doesn't provide enough control, instead of the waitForCompletion method you can add a callback function to the monitorManager object (which is automatically created when you import the abaqus module: from abaqus import *). This allows you to monitor and respond to various messages from the solver, such as COMPLETED, ITERATION, etc. The callback function is defined like:
def onMessage(jobName, messageType, data, userData):
if messageType == COMPLETED:
# do stuff
else:
# other stuff
Which is then added to the monitorManager and the job is called :
monitorManager.addMessageCallback(jobName=MyJobName,
messageType=ANY_MESSAGE_TYPE, callback=onMessage, userData=MyDataObj)
j = mdb.Job(name=MyJobName, model=MyModelName)
j.submit()
One of the benefits to this approach is that you can pass in a Python object as the userData argument. This could potentially be your output file, or some other data container. You could probably figure out how to process the output data within the callback function - for example, access the Odb and get the data, then do any manipulations as needed without needing the external file at all.
I agree with the answer, except for some minor syntax problems.
defining instance variables inside the handler is a no no. not to mention they are not being defined in any sort of init() method. Subclass TCPServer and define your instance variables in TCPServer.init(). Everything else will work the same.
I have created my micro web framework with flask which uses fabric to call the shell scripts which are in remote servers.
The shell script might take a longer time to get completed. I send the POST request from my browser and awaits for the results.
The fabric displays the real time contents on the flask run screen but flask returns the values to the browser after the completion of that remote script.
How can i make my flask to print that real time values on my browser screen ?
My flask piece:
#app.route("/abc/execute", methods=['POST'])
def execute_me():
value = request.json['value']
result = fabric_call(value)
result = formations(result)
return json.dumps(result)
My fabric piece:
def fabric_call(value):
with settings(host_string='my server', user='user',password='passwd',warn_only=True):
proc = run(my shell script)
return json.dumps(proc)
Update
I tried streamin` as well. But it didn't work. The output is displayed to my curl POST after script's complete execution. What am I missing ?
#app.route("/abc/execute", methods=['POST'])
def execute_me():
value = request.json['value']
def generate():
for row in formations(fabric_call(value)):
yield row + '\n'
return Response(generate(), mimetype="text/event-stream")
First of all, you need to make sure your data source (formations()) is actually a generator that yields data when available. Right now it very much looks like it runs the command and only returns a value once it has completely finished.
Also, in case you are using AJAX to call your endpoint remember that you cannot use e.g. jQuery's $.ajax(); you need to use XHR directly and poll for new data instead of using the onreadystatechange event since you want data once it's available and not only when the request finished.
I am playing around with a small project to get a better understanding of web technologies.
One requirement is that if multiple clients have access to my site, and one make a change all the others should be notified. From what I have gathered Server Sent events seems to do what I want.
However when I open my site in both Firefox and Chrome and try to send an event, only one of the browsers gets it. If I send an event again only one of the browsers gets the new event, usually the browser that did not get event number one.
Here is the relevant code snippets.
Client:
console.log("setting sse handlers")
viewEventSource = new EventSource("{{ url_for('viewEventRequest') }}");
viewEventSource.onmessage = handleViewEvent;
function handleViewEvent(event){
console.log("called handle view event")
console.log(event);
}
Server:
#app.route('/3-3-3/view-event')
def view_event_request():
return Response(handle_view_event(), mimetype='text/event-stream')
def handle_view_event():
while True:
for message in pubsub_view.listen():
if message['type'] == 'message':
data = 'retry: 1\n'
data += 'data: ' + message['data'] + '\n\n'
return data
#app.route('/3-3-3/test')
def test():
red.publish('view-event', "This is a test message")
return make_response("success", 200)
My question is, how do I get the event send to all connected clients and not just one?
Here are some gists that may help (I've been meaning to release something like 'flask-sse' based on 'django-sse):
https://gist.github.com/3680055
https://gist.github.com/3687523
also useful - https://github.com/jkbr/chat/blob/master/app.py
The first thing I notice about your code is that 'handle_view_event' is not a generator.
Though it is in a 'while' loop, the use of 'return' will always exit the function the first time we return data; a function can only return once. I think you want it to be 'yield' instead.
In any case, the above links should give you an example of a working setup.
As Anarov says, websockets and socket.io are also an option, but SSE should work anyway. I think socket.io supports using SSE if ws are not needed.