I am working on a flask application that interacts with redis. This applciation is deployed on heroku, with a redis add on.
When I am doing some testing with the interaction, I am not able to get the key value pair that I just set. Instead, I always get None as a return type. Here is the example:
import Flask
import redis
app = Flask(__name__)
redis_url = os.getenv('REDISTOGO_URL', 'redis://localhost:6379')
redis = redis.from_url(redis_url)
#app.route('/test')
def test():
redis.set("test", "{test1: test}")
print redis.get("test") # print None here
return "what the freak"
if __name__ == "__main__":
app.run(host='0.0.0.0')
As shown above, the test route will print None, means the value is not set. I am confused. When I test the server on my local browser it works, and when I tried interacting with redis using heroku python shell it works too.
testing with python shell:
heroku run python
from server import redis
redis.set('test', 'i am here') # return True
redis.get('test') # return i am here
I am confused now. How should I properly interact with redis using Flask?
Redis-py by default constructs a ConnectionPool client, and this is probably what the from_url helper function is doing. While Redis itself is single threaded, the commands from the connection pool have no guaranteed order of execution. For a single client, construct a redis.StrictRedis client directly, or pass through the param connection_pool=none. This is preferable for simple commands, low in number, as there is less connection management overhead. You can alternatively use a pipeline in the context of a connection pool to serialise a batch operation.
https://redis-py.readthedocs.io/en/latest/#redis.ConnectionPool
https://redis-py.readthedocs.io/en/latest/#redis.Redis.pipeline
I did more experiments on this. It seems there is an issue related to the delay. the below modification will make it work:
#app.route('/test')
def test():
redis.set("test", "{test1: test}")
time.sleep(5) # add the delay needed to the let the set finish
print redis.get("test") # print "{test1: test}" here
return "now it works"
I read the documentation on redis, redis seems to be single threaded. So I am not sure why it will execute the get function call before the set function is done. Someone with more experience please post an explanation.
Related
I have done threading in my Flask Application. I have to log my data in a separate table in mysql which has to work asynchronously. So my main function collects all the data and before sending the flask response i am calling the thread. So that the Response is also sent on time and also my thread function runs in background. This method works fine when run in local flask server. But when i deploy this in uWSGI server i need to enable thread in uWSGI. After that when my thread function is called the data in the thread is lost and there no value in my variable.
My Mail flask Function
#app.route('/', methods=['POST'])
def mainfunction():
Dictionary['Name'] = 'MyName'
Dictionary['Age'] = 'MyAge'
Dictionary['Address'] = 'MyAddress'
t1 = threading.Thread(target=loadinDBUsingThread, args=(Dictionary,))
t1.start()
return json.dumps(Dictionary)
My Thread Function
def loadinDBUsingThread(Dictionary):
localVariable0 = Dictionary['Name']
localVariable1 = Dictionary['Age']
localVariable2 = Dictionary['Address']
#Insert these variables to the Database
I got the Keyerror Name is not found in the Dictionary. I don't know how my variables are getting lost. Please help me with this.
Context
I have a server called "server.py" that functions as a post-commit webhook from GitLab.
Within "server.py", there is a long-running process (~40 seconds)
SSCCE
#!/usr/bin/env python
import time
from flask import Flask, abort, jsonify
debug = True
app = Flask(__name__)
#app.route("/", methods=['POST'])
def compile_metadata():
# the long running process...
time.sleep(40)
# end the long running process
return jsonify({"success": True})
if __name__ == "__main__":
app.run(host='0.0.0.0', port=8082, debug=debug, threaded=True)
Problem Statement
GitLab's webhooks expect return codes to be returned quickly. Since my webhook returns after or around 40 seconds; GitLab sends a retry sending my long running process in a loop until GitLab tries too many times.
Question
Am I able to return a status code from Flask back to GitLab, but still run my long running process?
I've tried adding something like:
...
def compile_metadata():
abort(200)
# the long running process
time.sleep(40)
but abort() only supports failure codes.
I've also tried using #after_this_request:
#app.route("/", methods=['POST'])
def webhook():
#after_this_request
def compile_metadata(response):
# the long running process...
print("Starting long running process...")
time.sleep(40)
print("Process ended!")
# end the long running process
return jsonify({"success": True})
Normally, flask returns a status code only from python's return statement, but I obviously cannot use that before the long running process as it will escape from the function.
Note: I am not actually using time.sleep(40) in my code. That is there only for posterity, and for the SSCCE. It will return the same result
Have compile_metadata spawn a thread to handle the long running task, and then return the result code immediately (i.e., without waiting for the thread to complete). Make sure to include some limitation on the number of simultaneous threads that can be spawned.
For a slightly more robust and scalable solution, consider some sort message queue based solution like celery.
For the record, a simple solution might look like:
import time
import threading
from flask import Flask, abort, jsonify
debug = True
app = Flask(__name__)
def long_running_task():
print 'start'
time.sleep(40)
print 'finished'
#app.route("/", methods=['POST'])
def compile_metadata():
# the long running process...
t = threading.Thread(target=long_running_task)
t.start()
# end the long running process
return jsonify({"success": True})
if __name__ == "__main__":
app.run(host='0.0.0.0', port=8082, debug=debug, threaded=True)
I was able to achieve this by using multiprocessing.dummy.Pool. After using threading.Thread, it proved unhelpful as Flask would still wait for the thread to finish (even with t.daemon = True)
I achieved the result of returning a status code before the long-running task like such:
#!/usr/bin/env python
import time
from flask import Flask, jsonify, request
from multiprocessing.dummy import Pool
debug = True
app = Flask(__name__)
pool = Pool(10)
def compile_metadata(data):
print("Starting long running process...")
print(data['user']['email'])
time.sleep(5)
print("Process ended!")
#app.route('/', methods=['POST'])
def webhook():
data = request.json
pool.apply_async(compile_metadata, [data])
return jsonify({"success": True}), 202
if __name__ == "__main__":
app.run(host='0.0.0.0', port=8082, debug=debug, threaded=True)
When you want to return a response from the server quickly, and still do some time consuming work, generally you should use some sort of shared storage like Redis to quickly store all the stuff you need, then return your status code. So the request gets served very quickly.
And have a separate server routinely work that semantic job queue to do the time consuming work. And then remove the job from the queue once the work is done. Perhaps storing the final result in shared storage as well. This is the normal approach, and it scales very well. For example, if your job queue grows too fast for a single server to keep up with, you can add more servers to work that shared queue.
But even if you don't need scalability, it's a very simple design to understand, implement, and debug. If you ever get an unexpected spike in request load, it just means that your separate server will probably be chugging away all night long. And you have peace of mind that if your servers shut down, you won't lose any unfinished work because they're safe in the shared storage.
But if you have one server do everything, performing the long running tasks asynchronously in the background, I guess maybe just make sure that the background work is happening like this:
------------ Serving Responses
---- Background Work
And not like this:
---- ---- Serving Responses
---- Background Work
Otherwise it would be possible that if the server is performing some block of work in the background, it might be unresponsive to a new request, depending on how long that time consuming work takes (even under very little request load). But if the client times out and retries, I think you're still safe from performing double work. But you're not safe from losing unfinished jobs.
So I'm using Flask_Socket to try to implement a websocket on Flask. Using this I hope to notify all connected clients whenever a piece of data has changed. Here's a simplification of my routes/index.py. The issue that I have is that when a websocket connection is opened, it will stay in the notify_change loop until the socket is closed, and in the meantime, other routes like /users can't be accessed.
from flask_sockets import Sockets
sockets = Sockets(app)
#app.route('/users',methods=['GET'])
def users():
return json.dumps(get_users())
data = "Some value" # the piece of data to push
is_dirty = False # A flag which is set by the code that changes the data
#sockets.route("/notifyChange")
def notify_change(ws):
global is_dirty, data
while not ws.closed:
if is_dirty:
is_dirty = False
ws.send(data)
This seems a normal consequence of what is essentially a while True: however, I've been looking online for a way to get around this while still using flask_sockets and haven't had any luck. I'm running the server on GUnicorn
flask/bin/gunicorn -b '0.0.0.0:8000' -k flask_sockets.worker app:app
I tried adding threads by doing --threads 12 but no luck.
Note: I'm only serving up to 4 users at a time, so scaling is not a requirement, and the solution doesn't need to be ultra-optimized.
I have written a single user application that currently works with Flask internal web server. It does not seem to be very robust and it crashes with all sorts of socket errors as soon as a page takes a long time to load and the user navigates elsewhere while waiting. So I thought to replace it with Apache.
The problem is, my current code is a single program that first launches about ten threads to do stuff, for example set up ssh tunnels to remote servers and zmq connections to communicate with a database located there. Finally it enters run() loop to start the internal server.
I followed all sorts of instructions and managed to get Apache service the initial page. However, everything goes wrong as I now don't have any worker threads available, nor any globally initialised classes, and none of my global variables holding interfaces to communicate with these threads do not exist.
Obviously I am not a web developer.
How badly "wrong" my current code is? Is there any way to make that work with Apache with a reasonable amount of work? Can I have Apache just replace the run() part and have a running application, with which Apache communicates? My current app in a very simplified form (without data processing threads) is something like this:
comm=None
app = Flask(__name__)
class CommsHandler(object):
__init__(self):
*Init communication links to external servers and databases*
def request_data(self, request):
*Use initialised links to request something*
return result
#app.route("/", methods=["GET"]):
def mainpage():
return render_template("main.html")
#app.route("/foo", methods=["GET"]):
def foo():
a=comm.request_data("xyzzy")
return render_template("foo.html", data=a)
comm = CommsHandler()
app.run()
Or have I done this completely wrong? Now when I remove app.run and just import app class to wsgi script, I do get a response from the main page as it does not need reference to global variable comm.
/foo does not work, as "comm" is an uninitialised variable. And I can see why, of course. I just never thought this would need to be exported to Apache or any other web server.
So the question is, can I launch this application somehow in a rc script at boot, set up its communication links and everyhing, and have Apache/wsgi just call function of the running application instead of launching a new one?
Hannu
This is the simple app with flask run on internal server:
from flask import Flask
app = Flask(__name__)
#app.route("/")
def hello():
return "Hello World!"
if __name__ == "__main__":
app.run()
To run it on apache server Check out fastCGI doc :
from flup.server.fcgi import WSGIServer
from yourapplication import app
if __name__ == '__main__':
WSGIServer(app).run()
How can I manage my rabbit-mq connection in Pyramid app?
I would like to re-use a connection to the queue throughout the web application's lifetime. Currently I am opening/closing connection to the queue for every publish call.
But I can't find any "global" services definition in Pyramid. Any help appreciated.
Pyramid does not need a "global services definition" because you can trivially do that in plain Python:
db.py:
connection = None
def connect(url):
global connection
connection = FooBarBaz(url)
your startup file (__init__.py)
from db import connect
if __name__ == '__main__':
connect(DB_CONNSTRING)
elsewhere:
from db import connection
...
connection.do_stuff(foo, bar, baz)
Having a global (any global) is going to cause problems if you ever run your app in a multi-threaded environment, but is perfectly fine if you run multiple processes, so it's not a huge restriction. If you need to work with threads the recipe can be extended to use thread-local variables. Here's another example which also connects lazily, when the connection is needed the first time.
db.py:
import threading
connections = threading.local()
def get_connection():
if not hasattr(connections, 'this_thread_connection'):
connections.this_thread_connection = FooBarBaz(DB_STRING)
return connections.this_thread_connection
elsewhere:
from db import get_connection
get_connection().do_stuff(foo, bar, baz)
Another common problem with long-living connections is that the application won't auto-recover if, say, you restart RabbitMQ while your application is running. You'll need to somehow detect dead connections and reconnect.
It looks like you can attach objects to the request with add_request_method.
Here's a little example app using that method to make one and only one connection to a socket on startup, then make the connection available to each request:
from wsgiref.simple_server import make_server
from pyramid.config import Configurator
from pyramid.response import Response
def index(request):
return Response('I have a persistent connection: {} with id {}'.format(
repr(request.conn).replace("<", "<"),
id(request.conn),
))
def add_connection():
import socket
s = socket.socket()
s.connect(("google.com", 80))
print("I should run only once")
def inner(request):
return s
return inner
if __name__ == '__main__':
config = Configurator()
config.add_route('index', '/')
config.add_view(index, route_name='index')
config.add_request_method(add_connection(), 'conn', reify=True)
app = config.make_wsgi_app()
server = make_server('0.0.0.0', 8080, app)
server.serve_forever()
You'll need to be careful about threading / forking in this case though (each thread / process will need its own connection). Also, note that I am not very familiar with pyramid, there may be a better way to do this.