I have a web application which acts as an interface to an offsite server which runs a very long task. The user enters information and hits submit and then chrome waits for the response, and loads a new webpage when it receives it. However depending on the network, input of the user, the task can take a pretty long time and occasionally chrome loads a "no data received page" before the data is returned (though the task is still running).
Is there a way to put either a temporary page while my task is thinking or simply force chrome to continue waiting? Thanks in advance
While you could change your timeout on the server or other tricks to try to keep the page "alive", keep in mind that there might be other parts of the connection that you have no control over that could timeout the request (such as the timeout value of the browser, or any proxy between the browser and server, etc). Also, you might need to constantly up your timeout value if the task takes longer to complete (becomes more advanced, or just slower because more people use it).
In the end, this sort of problem is typically solved by a change in your architecture.
Use a Separate Process for Long-Running Tasks
Rather than submitting the request and running the task in the handling view, the view starts the running of the task in a separate process, then immediately returns a response. This response can bring the user to a "Please wait, we're processing" page. That page can use one of the many push technologies out there to determine when the task was completed (long-polling, web-sockets, server-sent events, an AJAX request every N seconds, or the dead-simplest: have the page reload every 5 seconds).
Have your Web Request "Kick Off" the Separate Process
Anyway, as I said, the view handling the request doesn't do the long action: it just kicks off a background process to do the task for it. You can create this background process dispatch yourself (check out this Flask snippet for possible ideas), or use a library like Celery or (RQ).
Once the task is complete, you need some way of notifying the user. This will be dependent on what sort of notification method you picked above. For a simple "ajax request every N seconds", you need to create a view that handles the AJAX request that checks if the task is complete. A typical way to do this is to have the long-running task, as a last step, make some update to a database. The requests for checking the status can then check this part of the database for updates.
Advantages and Disadvantages
Using this method (rather than trying to fit the long-running task into a request) has a few benefits:
1.) Handling long-running web requests is a tricky business due to the fact that there are multiple points that could time out (besides the browser and server). With this method, all your web requests are very short and much less likely to timeout.
2.) Flask (and other frameworks like it) is designed to only support a certain number of threads that can respond to web queries. Assume it has 8 threads: if four of them are handling the long requests, that only leaves four requests to actually handle more typical requests (like a user getting their profile page). Half of your web server could be tied up doing something that is not serving web content! At worse, you could have all eight threads running a long process, meaning your site is completely unable to respond to web requests until one of them finishes.
The main drawback: there is a little more set up work in getting a task queue up and running, and it does make your entire system slightly more complex. However, I would highly recommend this strategy for long-running tasks that run on the web.
I believe this is due to your web server (apache in most cases) which has a timeout to small. Try to increase this number
For apache, have a look at the timeout option
EDIT: I don't think you can do set this time out in Chrome (see this topic on google forums even though it's really old)
In firefox, on the about:config page, type timeout and you'll have some options you can set. I have no idea about Internet Explorer.
Let's assume:
This is not a server issue, so we don't have to go fiddle with Apache, nginx, etc. timeout settings.
The delay is minutes, not hours or days, just to make the scenario manageable.
You control the web page on which the user hits submit, and from which user interaction is managed.
If those obtain, I'd suggest not using a standard HTML form submission, but rather have the submit button kick off a JavaScript function to oversee processing. It would put up a "please be patient...this could take a little while" style message, then use jQuery.ajax, say, to call the long-time-taking server with a long timeout value. jQuery timeouts are measured in milliseconds, so 60000 = 60 seconds. If it's longer than that, increase your specified timeout accordingly. I have seen reports that not all clients will allow super-extra-long timeouts (e.g. Safari on iOS apparently has a 60-second limitation). But in general, this will give you a platform from which to manage the interactions (with your user, with the slow server) rather than being at the mercy of simple web form submission.
There are a few edge cases here to consider. The web server timeouts may indeed need to be adjusted upward (Apache defaults to 300 seconds aka 5 minutes, and nginx less, IIRC). Your client timeouts (on iOS, say) may have maximums too low for the delays you're seeing. Etc. Those cases would require either adjusting at the server, or adopting a different interaction strategy. But an AJAX-managed interaction is where I would start.
Related
I deployed a Django app on Heroku. I have a function (inside views) in my app that take some time (3m-5m) before it returns.
The problem is that function doesn't return when the app is deployed to Heroku. On my PC it works fine.
Heroku is not giving me useful feedback. There is no 'timeout' or anything in the logs.
Three to five minutes is way too long for a request to take. Heroku will kill such requests:
Best practice is to get the response time of your web application to be under 500ms, this will free up the application for more requests and deliver a high quality user experience to your visitors. Occasionally a web request may hang or take an excessive amount of time to process by your application. When this happens the router will terminate the request if it takes longer than 30 seconds to complete.
I'm not sure why you aren't seeing timeouts in the logs, but if you truly need that much time to compute something you'll need to do it asynchronously.
There are lots of ways to do that, e.g. you could queue the work and then respond immediately with a "loading" state, then poll the back-end and update the view when the result is ready.
Start by reading Worker Dynos, Background Jobs and Queueing and then decide how you wish to proceed. We can't tell you the "right" way of doing this; it's something you need to decide about your application.
This isn't specifically related to programming, more-so infrastructure, but of all the exchange sites StackOverflow seems to be most knowledgeable in departments of RESTful APIs.
I have a single endpoint configured for handling events that could take in up to 1k events within a 3 minute window. I am noticing a lot of events "missed", but I'm not sure that I'm willing to blame over-utilization right away without fully understanding.
The listening endpoint is /users/events?user=2345345 where 2345345 is the user id. From here we perform necessary actions on that particular user, but what if during this the next user, 2895467 performs an action which results in a new event being sent to /users/events?user=2895467 before the first could be processed. What happens?
I intend to alleviate the concern by using celery to signal tasks which would greatly reduce this, but is it fair to assume that events could be missed while this single endpoint remains synchronous?
Real-life behavior depends on approach used for "deployment".
For example if you are using uwsgi with single unthreaded worker behind nginx, then requests will be processed "sequentially": if second request arrives before first is processed, then second will be "queued" (added to backlog).
How long it can be queued and how many requests may be in queue
depends on the configuration of nginx (listen backlog), configuration of uwsgi (concurrency, listen backlog) and even on configuration
of OS kernel (search for net.core.somaxconn,
net.core.netdev_max_backlog). When queue becomes "full" then new
"concurrent" connections will be dropped instead of being added to queue.
I've got a simple pyramid app up and running, most of the views are a fairly thin wrapper around an sqlite database, with forms thrown in to edit/add some information.
A couple of times a month a new chunk of data will need to be added to this system (by csv import). The data is saved in an SQL table (the whole process right till commit takes about 4 seconds).
Every time a new chunk of data is uploaded, this triggers a recalculation of other tables in the database. The recalculation process takes a fairly long time (about 21-50 seconds for a month's worth of data).
Currently I just let the browser/client sit there waiting for the process to finish, but I do foresee the calculation process taking more and more time as the system gets more usage. From a UI perspective, this obviously looks like a hung process.
What can I do to indicate to the user that:-
That the long wait is normal/expected?
How MUCH longer they should have to wait (progress bar etc.)?
Note: I'm not asking about long-polling or websockets here, as this isn't really an interactive application and based on my basic knowledge websockets/async are overkill for my purposes.
I guess a follow-on question at this point, am I doing the wrong thing running processes in my view functions? Hardly seem to see that being done in examples/tutorials around the web. Am I supposed to be using celery or similar in this situation?
You're right, doing long calculations in a view function is generally frowned upon - I mean, if it's a typical website with random visitors who are able to hung a webserver thread for a minute then it's a recipe for a DoS vulnerability. But in some situations (internal website, few users, only admin has access to the "upload csv" form) you may get away with it. In fact, I used to have maintenance scripts which ran for hours :)
The trick here is to avoid browser timeouts - at the moment your client sends the data to the server and just sits there waiting for any reply, without any idea whether their request is being processed or not. Generally, at about 60 seconds the browser (or proxy, or frontend webserver) may become impatient and close the connection. Your server process will then get an error trying writing anything to the already closed connection and crash/raise an error.
To prevent this from happening the server needs to write something to the connection periodically, so the client sees that the server is alive and won't close the connection.
"Normal" Pyramid templates are buffered - i.e. the output is not sent to the client until the whole template to generated. Because of that you need to directly use response.app_iter / response.body_file and output some data there periodically.
As an example, you can duplicate the Todo List Application in One File example from Pyramid Cookbook and replace the new_view function with the following code (which itself has been borrowed from this question):
#view_config(route_name='new', request_method='GET', renderer='new.mako')
def new_view(request):
return {}
#view_config(route_name='new', request_method='POST')
def iter_test(request):
import time
if request.POST.get('name'):
request.db.execute(
'insert into tasks (name, closed) values (?, ?)',
[request.POST['name'], 0])
request.db.commit()
def test_iter():
i = 0
while True:
i += 1
if i == 5:
yield str('<p>Done! Click here to see the results</p>')
raise StopIteration
yield str('<p>working %s...</p>' % i)
print time.time()
time.sleep(1)
return Response(app_iter=test_iter())
(of cource, this solution is not too fancy UI-wise, but you said you didn't want to mess with websockets and celery)
So is the long running process triggered by browser action? I.e., the user is uploading the CSV that gets processed and then the view is doing the processing right there? For short-ish running browser processes I've used a loading indicator via jQuery or javascript, basically popping a modal animated spinner or something while a process runs, then when it completes hiding the spinner.
But if you're getting into longer and longer processes I think you should really look at some sort of background processing that will offload it from the UI. It doesn't have to be a message based worker, but even something like the end user uploads the file and a "to be processed" entry gets set in a database. Then you could have a pyramid script scheduled periodically in the background polling the status table and running anything it finds. You can move your file processing that is in the view to a separate method, and that can be called from the command line script. Then when the processing is finished it can update the status table indicating it is finished and that feedback could be presented back to the user somewhere, and not blocking their UI the whole time.
I have a simple Django project.
Each time a user hits the homepage,some operations are performed based on which,view is generated. Now the problem is that when a user hits the homepage ,sometimes the operations take a long time based on network connectivity. If in the meantime, a new user hits the homepage,he has to wait for the request from the previous user to get serviced before the page gets rendered.
I found Celery is used for task scheduling and queuing . But I wonder if Celery is what i need.I need each user to have his request be processed independently and not queued.
My project is a single app project and will receive a maximum of 100 users a time.
Thanks.
If the long process needs to be done in order to serve the request and generate the proper response then you cannot use Celery.
The debug web-server that is shipped with Django is a multi-threaded-single-process server, but is really very limited and should not be used in production.
If you use gunicorn or other wsgi servers you can run your application in multiple processes but you will hit the limit quickly if you're doing heavy processing.
The solution would be in my opinion is to either change the way you're processing stuff, either prepare ahead or serve the request and do the processing in the background, you can show the user a Please wait... message, here you can use Celery to do the processing.
The other solution would be to use event-based web-server like Twisted or cyclone or others
Using Django (hosted by Webfaction), I have the following code
import time
def my_function(request):
time.sleep(10)
return HttpResponse("Done")
This is executed via Django when I go to my url, www.mysite.com
I enter the url twice, immediately after each other. The way I see it, both of these should finish after 10 seconds. However, the second call waits for the first one and finishes after 20 seconds.
If, however, I enter some dummy GET parameter, www.mysite.com?dummy=1 and www.mysite.com?dummy=2 then they both finish after 10 seconds. So it is possible for both of them to run simultaneously.
It's as though the scope of sleep() is somehow global?? Maybe entering a parameter makes them run as different processes instead of the same???
It is hosted by Webfaction. httpd.conf has:
KeepAlive Off
Listen 30961
MaxSpareThreads 3
MinSpareThreads 1
ServerLimit 1
SetEnvIf X-Forwarded-SSL on HTTPS=1
ThreadsPerChild 5
I do need to be able to use sleep() and trust that it isn't stopping everything. So, what's up and how to fix it?
Edit: Webfaction runs this using Apache.
As Gjordis pointed out, sleep will pause the current thread. I have looked at Webfaction and it looks like their are using WSGI for running the serving instance of Django. This means, every time a request comes in, Apache will look at how many worker processes (that are processes that each run a instance of Django) are currently running. If there are none/to view it will spawn additonally workers and hand the requests to them.
Here is what I think is happening in you situation:
first GET request for resource A comes in. Apache uses a running worker (or starts a new one)
the worker sleeps 10 seconds
during this, a new request for resource A comes in. Apache sees it is requesting the same resource and sends it to the same worker as for request A. I guess the assumption here is that a worker that recently processes a request for a specific resource it is more likely that the worker has some information cached/preprocessed/whatever so it can handle this request faster
this results in a 20 second block since there is only one worker that waits 2 times 10 seconds
This behavior makes complete sense 99% of the time so it's logical to do this by default.
However, if you change the requested resource for the second request (by adding GET parameter) Apache will assume that this is a different resource and will start another worker (since the first one is already "busy" (Apache can not know that you are not doing any hard work). Since there are now two worker, both waiting 10 seconds the total time goes down to 10 seconds.
Additionally I assume that something is **wrong** with your design. There are almost no cases which I can think of where it would be sensible to not respond to a HTTP request as fast as you can. After all, you want to serve as many requests as possible in the shortest amount of time, so sleeping 10 seconds is the most counterproductive thing you can do. I would recommend the you create a new question and state what you actual goal is that you are trying to achieve. I'm pretty sure there is a more sensible solution to this!
Assuming you run your Django-server just with run() , by default this makes a single threaded server. If you use sleep on a single threaded process, the whole application freezes for that sleep time.
It may simply be that your browser is queuing the second request to be performed only after the first one completes. If you are opening your URLs in the same browser, try using the two different ones (e.g. Firefox and Chrome), or try performing requests from the command line using wget or curl instead.