Web-based game in Python + Django and client browser polling - python

I am creating a text-based game that implements a basic model in which multiple (10+) players interact with data and one moderator watches them and sets certain environmental statistics that affect gameplay.
Recently I have begun to familiarize myself with Django. It seems to me that it would be an excellent tool for creating a game quickly, particularly because the nature of my game depends largely on sets of data (which lends itself quite well to a database).
I am wondering how to "push" changes made by the game moderator to the players (for example, the moderator can decide to display an image to all players). The game is turn-based, not real-time, but certain messages need to be pushed out in roughly real-time.
My thoughts: I could have each player's browser poll a status periodically (say, every 30 seconds) to see if there is a message from a moderator. But this forces a lag and means different players might receive it at different times. And reducing this interval to <10 seems like a bad idea for the server.
Is there a better way to inform clients of changes? Would you suggest something other than using a web framework like Django?
Thanks!

In addition to long polling mentioned by Matti, the HTTP server can also stream the data by basically using one really long response and never finishing the response (but continuing to push more data to the client). The client can continue to respond to data as it comes in. As you've concluded polling is probably a bad solution for any decently sized project.
Before you can get started, you're going to want to have a fairly sound understanding of HTTP and Django. This type of technology is a little more bleeding edge and can be complex at times.
There's an interesting project which is probably worth checking out: evserver. It's an HTTP server that supports asynchronous WSGI and will allow you do develop COMET-ish apps with Django. (Disclaimer: I haven't actually used evserver, but it's on my list of "cool stuff to try")

You could use long polling.
Also, if you're creating a multiplayer game, it might be much easier and more efficient to use a server that's designed for long polling and multi-user interaction instead of using a standard HTTP server and framework.

Related

Can a server process data without client request?

I recently got into Flask web programming and built a shopping website fro scratch as an engineering school project, however I got lost when it came to product ranking etc.
I had this idea for a dating website as an exercise but as I see it the server will have to run its own calculations to rank different possible couples in terms of compatibility, which is really the interesting part of the project.
I don't really see these ranking calculations only being processed upon request as thay may take some time, but maybe I am highly underestimating SQL processing speed. I believe the data processing and calculations need to be run continuously on the server. If this is in fact continuous server data processing, how would I go about doing that?
I hope the question makes sense, my English tends to be a bit dodgy as I don't live in an English-speaking country.
Regards
If you need background tasks without client requests, you can go for Celery (https://docs.celeryproject.org/en/stable/userguide/periodic-tasks.html). You can assign works to this server and it will run in background without intervening Django server.

Fastest, simplest way to handle long-running upstream requests for Django

I'm using Django with Uwsgi. We have 8 processes running, and I have no real indication that our code is particularly thread safe, as it was never designed with threads in mind.
Recently, we added the ability to get live rates from vendors of a service through their various APIs and display them at once for the user. The problem is these requests are old web services technologies, and due to their response times, the time needed before the all rates from vendors are acquired (or it gives up), can be up to 10 seconds.
This presents a problem. We have a pretty decent amount of traffic on our site, and the customers need to look at these rates pretty often. With only 8 processes, it's quite easy to see how the server can get tied up waiting on these upstream requests. Especially when other optimizations need to be made to make the site baseline faster anyway (we're working on that).
We made a separate library (which should be mostly threadsafe, and if not, should be converted to it easily enough) for the rates requesting, and we can separate out its configuration. So I was thinking of making a separate service with its own threads, perhaps in Twisted, and having the browser contact that service for JSON instead of having it run in the main Django server.
Is this solution a good one? Can you think of a better or simpler way to do it? Should I use something other than Twisted, and if so, why?
If you want to use your code in-process with Django, you can simply call out to your Twisted by using Crochet, which can automatically manage the creation, running, and shutdown of the reactor within whatever WSGI implementation you choose (presuming that it behaves like a regular Python process, at least).
Obviously it might be less complex to just run within the Twisted WSGI container :-).
It might also be worth looking at TReq to issue your service client requests; your new "thread safe" library will still have the disadvantage of tying up an entire thread for each blocking client, which is a non-trivial amount of memory and additional concurrency overhead, whereas with Twisted you will only need to worry about a couple of objects.

Writing a Python data analysis server for a Java interface

I want to write data analysis plugins for a Java interface. This interface is potentially run on different computers. The interface will send commands and the Python program can return large data. The interface is distributed by a Java Webstart system. Both access the main data from a MySQL server.
What are the different ways and advantages to implement the communication? Of course, I've done some research on the internet. While there are many suggestions I still don't know what the differences are and how to decide for one. (I have no knowledge about them)
I've found a suggestion to use sockets, which seems fine. Is it simple to write a server that dedicates a Python analysis process for each connection (temporary data might be kept after one communication request for that particular client)?
I was thinking to learn how to use sockets and pass YAML strings.
Maybe my main question is: What is the relation to and advantage of systems like RabbitMQ, ZeroMQ, CORBA, SOAP, XMLRPC?
There were also suggestions to use pipes or shared memory. But that wouldn't fit to my requirements?
Does any of the methods have advantages for debugging or other pecularities?
I hope someone can help me understand the technology and help me decide on a solution, as it is hard to judge from technical descriptions.
(I do not consider solutions like Jython, JEPP, ...)
Offering an opinion on the merits you described, it sounds like you are dealing with potentially large data/queries that may take a lot of time to fetch and serialize, in which case you definitely want to go with something that can handle concurrent connections without stacking up threads. Thereby, in the Python domain, I can't recommend any networking library other than Twisted.
http://twistedmatrix.com/documents/current/core/examples/
Whether you decide to use vanilla HTTP or your own protocol, twisted is pretty much the one stop shop for concurrent networking. Sure, the name gets thrown around alot, and the documentation is Atlantean, but if you take the time to learn it there is very little in the networking domain you cannot accomplish. You can extend the base protocols and factories to make one server that can handle your data in a reactor-based event loop and respond to deferred request when ready.
The serialization format really depends on the nature of the data. Will there be any binary in what is output as a response? Complex types? That rules out JSON if so, though that is becoming the most common serialization format. YAML sometimes seems to enjoy a position of privilege among the python community - I haven't used it extensively as most of the kind of work I've done with serials was data to be rendered in a frontend with javascript.
Message queues are really the most important tool in the toolbox when you need to defer background tasks without hanging response. They are commonly employed in web apps where the HTTP request should not hang until whatever complex processing needs to take place completes, so the UI can render early and count on an implicit "promise" the processing will take place. They have two important traits: they rely on eventual consistency, in that the process can finish long after the response in the protocol is sent, and they also have fail-safe and try-again directives should a task fail. They are where you turn in the "do this really hard task as soon as you can and I trust you to get it done" problem domain.
If we are not talking about potentially HUGE response bodies, and relatively simple data types within the serialized output, there is nothing wrong with rolling a simple HTTP deferred server in Twisted.

Non-Message Queue / Simple Long-Polling in Python (and Flask)

I am looking for a simple (i.e., not one that requires me to setup a separate server to handle a messaging queue) way to do long-polling for a small web-interface that runs calculations and produces a graph. This is what my web-interface needs to do:
User requests a graph/data in a web-interface
Server runs some calculations.
While the server is running calculations, a small container is updated (likely via AJAX/jQuery) with the calculation progress (similar to what you'd do in a consol with print (i.e. print 'calculating density function...'))
Calculation finishes and graph is shown to user.
As the calculation is all done server-side, I'm not really sure how to easily set this up. Obviously I'll want to setup a REST API to handle the polling, which would be easy in Flask. However, I'm not sure how to retrieve the actual updates. An obvious, albeit complicated for this purpose, solution would be to setup a messaging queue and do some long polling. However, I'm not sure sure this is the right approach for something this simple.
Here are my questions:
Is there a way to do this using the file system? Performance isn't a huge issue. Can AJAX/jQuery find messages from a file? Save the progress to some .json file?
What about pickling? (I don't really know much about pickling, but maybe I could pickle a message dict and it could be read by an API that is handling the polling).
Is polling even the right approach? Is there a better or more common pattern to handle this?
I have a feeling I'm overcomplicating things as I know this kind of thing is common on the web. Quite often I see stuff happening and a little "loading.gif" image is running while some calculation is going on (for example, in Google Analytics).
Thanks for your help!
I've built several apps like this using just Flask and jQuery. Based on that experience, I'd say your plan is good.
Do not use the filesystem. You will run into JavaScript security issues/protections. In the unlikely event you find reasonable workarounds, you still wouldn't have anything portable or scalable. Instead, use a small local web serving framework, like Flask.
Do not pickle. Use JSON. It's the language of web apps and REST interfaces. jQuery and those nice jQuery-based plugins for drawing charts, graphs and such will expect JSON. It's easy to use, human-readable, and for small-scale apps, there's no reason to go any place else.
Long-polling is fine for what you want to accomplish. Pure HTTP-based apps have some limitations. And WebSockets and similar socket-ish layers like Socket.IO "are the future." But finding good, simple examples of the server-side implementation has, in my experience, been difficult. I've looked hard. There are plenty of examples that want you to set up Node.js, REDIS, and other pieces of middleware. But why should we have to set up two or three separate middleware servers? It's ludicrous. So long-polling on a simple, pure-Python web framework like Flask is the way to go IMO.
The code is a little more than a snippet, so rather than including it here, I've put a simplified example into a Mercurial repository on bitbucket that you can freely review, copy, or clone. There are three parts:
serve.py a Python/Flask based server
templates/index.html 98% HTML, 2% template file the Flask-based server will render as HTML
static/lpoll.js a jQuery-based client
Long-polling was a reasonable work-around before simple, natural support for Web Sockets came to most browsers, and before it was easily integrated alongside Flask apps. But here in mid-2013, Web Socket support has come a long way.
Here is an example, similar to the one above, but integrating Flask and Web Sockets. It runs atop server components from gevent and gevent-websocket.
Note this example is not intended to be a Web Socket masterpiece. It retains a lot of the lpoll structure, to make them more easily comparable. But it immediately improves responsiveness, server overhead, and interactivity of the Web app.
Update for Python 3.7+
5 years since the original answer, WebSocket has become easier to implement. As of Python 3.7, asynchronous operations have matured into mainstream usefulness. Python web apps are the perfect use case. They can now use async just as JavaScript and Node.js have, leaving behind some of the quirks and complexities of "concurrency on the side." In particular, check out Quart. It retains Flask's API and compatibility with a number of Flask extensions, but is async-enabled. A key side-effect is that WebSocket connections can be gracefully handled side-by-side with HTTP connections. E.g.:
from quart import Quart, websocket
app = Quart(__name__)
#app.route('/')
async def hello():
return 'hello'
#app.websocket('/ws')
async def ws():
while True:
await websocket.send('hello')
app.run()
Quart is just one of the many great reasons to upgrade to Python 3.7.

How to create a polling script in Python?

I was trying to create a polling script in python that starts when another python script starts and then keeps supplying data back to this script.
I can obviously write an infinite loop but is that the right way to go about it? I might loose control over how the functions work and how many times a function should be called in an hour.
Edit:
What I am trying to accomplish is to poll the REST API of twitter and get new mentions and people who follow me. I obviously can't keep polling because I will run out of API requests per hour. Thus, the issue. This poller, will send the new mention and follower id/user to the main script that would be listening to any such update.
I highly suggest looking into Twisted, one of the most popular async frameworks using the reactor pattern.
The "infinite loop" you are looking for is really an application pattern that Twisted implements to respond to events asynchronously, and it almost never makes sense to roll your own.
Twisted is largely used for networking requirements, but the it has a LoopingCall interface to set up the kind of functionality you require. Using the core Twisted deferred as your request model allows you to set up a long-polling server that can perform the kind of conditional network test you need. It can intially be a little intimidating, but once you understand the core components (Factories, Reactors, Protocols etc) that you need to inherit it becomes much easier to visualize your problem.
This also might be a good tutorial to start looking at the basics of the "push" model:
http://carloscarrasco.com/simple-http-pubsub-server-with-twisted.html

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