How do I communicate with a game ("Quake II"), and retrieve/extract data from it?
I have this old game (ActionQuake II) which is an mod for Quake2.
Whenever an action has been executed within the game, it writes every transaction in a commando-prompt - just as Counter-strike. (I'm not sure, if this might be the solution...)
I suppose these transactions can be retrieved from the .EXE-files.
Is there a way to retrieve, and treat or even search in .EXE-files (in real-time)?
I know its possible, because in some IRC-channels are bots, which write every transaction on the channel. Many homepages are doing it aswell - giving the user a server-list, with details like: Score, Deaths, Players etc. (http://www.gametracker.com), but how are they doing it?
I want to use this data for statistics and progress-overview.
Any help?
If there's some kind of server, you can try sniffing the network packets with software like Wireshark.
Related
I am making a bot on Dialogflow with a Fulfillment. Considering the given strict 5-second window in DialogFlow, I am getting [empty response] as a response.
I want to overcome this issue, but my web service requires more than 9 seconds for the execution.
I am considering to redesigning the conversation flow in such a way that we will start streaming audio till the Response is processed.
Example:
User Question: xx xxx xxx xxxx xxxxx?
Response: a). We'll play fixed audio to keep the user engaged for few seconds till it finds a response text in the back end; b).
Receive answers from the web service and save them in the session to
display further.
How can I achieve this and how can I handle the Timeout issue?
You're on the right track, but there are a number of other things to consider.
First, however, keep in mind that anything that is trying to "avoid" the 5 second timeout already indicates some issues with the design. Waiting 10 seconds for a reply is a pretty long time with something as interactive as voice! Even 5 seconds, which is the timeout, is a long time. (And there is no way to change this timeout.)
So the first thing you may want to do is consider if there is a better/faster way to do what you want.
If not, the rough approach would be something like this:
Get the request from the user.
Track a unique identifier, either tied to the user or tied to the session. You'll be using this as a key into some kind of database or data store.
Start the API call as part of an asynchronous request or in another thread.
Reply immediately that you're working on it in a way that the user will send another request. (See below for this issue.) You'll want to make sure that the ID is maintained as part of this session - so you'll need to save it as part of the Session data.
At this point - you're basically doing two things in parallel.
When the API call completes, it needs to save the result in the datastore against the identifier. (It can't save it in the session itself - that response was already sent back to the Assistant.)
You're also waiting for a reply from the user. When it comes in:
Check to see if you have a response saved for this session yet.
If not, then go back to step 4. (You may want to track how many times you get here and give up at some point.)
If you do have the result, reply to the user with the information.
There is an issue with how you reply in step 4, since you want to do something that will guarantee you another request from the person expecting an answer. There are a few possible approaches:
The most straightforward way would be to send back a Media response to play a few seconds of "hold music". This has the advantage that, when the music stops, it will send an event to Dialogflow which you can capture as an Intent and then continue with step 5.
But there are some problems:
Not all versions of the Assistant support the Media response. You will need to check to confirm the feature is supported before you use it and, if not, use another approach (see below).
The media player that is presented on some Assistants allow the user to stop playback, or will not correctly send an event when the audio stops in some situations. So you may never get another request in this session.
Another approach involves some more advanced conversation design tricks, so may not always be suitable for your conversation. Your response can say that you're looking up the results but then ask the user a question - possibly one that is related to other information that you will need. With their reply, you can collect this information (if you need it) and then see if you have a result yet.
In some conversations - this works really well. For example, if you're looking up flights to somewhere, while you're looking that up you might ask them if they will need a hotel or rental car, which you might ask about anyway.
Other conversations, however, don't easily have such questions. In these cases, you may need to ask something that isn't relevant while you stall for time.
I am building my first web-based node.js application - an online game - as a hobby/project to try and teach myself how it all works.
I'm using socket.io to send real-time updates (who's in the lobby, points scored etc) to users, but I'm not sure whether the way I'm managing the sockets, and the information being sent through them, in the best way.
Whenever the game is updated, I'm sending an object to each user which updates everything at once, and a lot of the time, the information being updated is actually staying the same. For example, if a user scores a point, an update is sent to everyone's browser to update the leaderboard, but that same socket.on function is re-sending information such as usernames, which stay the same throughout the game:
exampleObject = {
"usernames" : [username1, username2], // only gets updated in the browser once, but is sent every time
"points": {
"username1": 1, // Different value with every update
"username2": 3
}
}
(The real object is quite a bit bigger than this)
Would it be more sensible to have a different socket.on function for every individual piece of information which needs updating, so I can then call them individually as and when required, or is there any sense in updating everything through one function? Any thoughts/advice would be greatly appreciated.
If you are regularly sending a piece of information over and over, then it makes sense to design a specific message that only contains that specific information so you aren't regularly sending information that does not need to be sent. You can have as many different messages as you want and you should use that to design efficient messages, particularly for the most common messages.
Would it be more sensible to have a different socket.on function for every individual piece of information which needs updating, so I can then call them individually as and when required
Yes. Design efficient messages specifically for things you regularly send.
or is there any sense in updating everything through one function?
Only if you need to change lots of stuff at once. It's wasteful to include data in a frequent message that never changes and doesn't need to be sent.
It's perfectly fine to have different messages you send for different purposes and then the client has different listeners for those specific messages. At the same time, if you regularly send three pieces of data together, you probably wouldn't make a separate message for each piece of data - you'd put those three together such that your message structure aligns with your usage.
And, you can also have different messages for different purposes even if some data is in both messages.
One more note here. The title of your question "How should I manage the number of sockets in a node.js application?" seems to ask about managing the number of sockets. But, the rest of your question isn't about that at all. The rest of your question is about having different messages on the same socket. You don't need a new socket in order to define and use a different message. You can have thousands of different messages that you use all on the same socket connection. That's the whole architecture of socket.io. You send a message name and some data that goes with it. You can use a limitless number of separate message names all on the same connection.
Question is related to CQRS - I have user that wants to order something from web and is presented with GUI showing his balance = 100$ and stock = 1 item. Let's say we have 2 services here AccountService and StockService with separate concerns. In order to generate GUI for client third service AggregatorService listens to domain events from AccountService and StockService, projects a view and creates GUI for clients.
When user decides to order this item, he clicks a button and Command for order is sent to AccountService. Here we load AccountAggregate in order to decrease balance for the price of the item that needs to be ordered. But before I can do this, I have to check if the item is still available (or somehow to reserve it). Only thing that comes up to my mind is:
Read current stock of the item from read model of StockService, but what can happen is that other services read model is updated just a second after I read it (e.g. somebody bought the item, so actual stock is =0. but read model still has =1).
Before decreasing a balance call some method on StockService to reserve the item for some time. If order is not successful (e.g. no enough funds on balance, I would have to un-reserve it somehow). This needs to be some sync-REST call and it is probably slower than some async solution (if any).
Are there any best practices for this kind of use-case?
You have 2 options, depending on whether you embrace eventual consistency or not.
Using immediate consistency I would have an OrderService that receives the order request and it makes async calls to AccountService.ReservePayment() and StockService.ReserveStock(). If either of those fail you call AccountService.UndoReservePayment() and StockService.UndoReserveStock(). If both succeed you call AccountService.CompleteReservePayment() and StockService.CompleteReserveStock(). Make sure each reservation should have a timestamp on it so a daemon process can occasionally run and Undo any reserves that are older than an hour or so.
This approach makes the user wait until both those services complete. If either the StockService or the AccountService are slow, the user experience is slow. I suggest a better way to do this is the eventual consistency approach which gives the user a very fast experience at the expense of receiving failure messages after the fact.
With eventual consistency you assume they have enough credit and you have enough inventory, and in response to their order request you immediately send back a success message. The user is happy and they go along to buy more stuff.
The OrderCreated event is then handled asynchronously to reserve stock and credit as described above. However, since there is no time pressure to reply to the waiting user you don’t have to scale up to handle as high a throughput. If the credit check and stock check take a minute or two, the user doesn’t care because he’s off doing other things.
The price you pay here is that the user may get a success message at the time of order submission, then a few minutes later get an email saying the sale didn’t go through after all because there’s no stock. This is what many large retailers do, including Amazon, Target, Walmart, etc. Eventual consistency can go a long way towards easing the load and cost of the back end.
Imagine Agar.io. Unlike a chat app, the list of users (or players) and other environment objects will be constantly changing, for each player, as players move around the map. That is because each client can't receive updates about every object, because the map is too large and the lag would be too much. So which of the following methods of updating clients, with Socket.IO, would be more efficient:
Send an environment array containing data, which replaces the local arrays on each client.
Send individual messages when objects appear/disappear in a players field of view, and tinker with the local arrays object by object.
If there is a better way than the above two, please outline it.
This is a multi-vector tradeoff decision so without some measuring and probably experimentation, we can't really tell you what situation is optimal. But, we can direct your thinking which you can hopefully use to finish the analysis.
First off, to scale and reduce lag, you want to:
Send fewer messages to each client.
Send smaller payloads with each message as long as it doesn't make item #1 worse (e.g. as long as it doesn't cause you to send more messages).
Have fewer times on the server where you are doing calculations and then sending messages.
To send fewer messages to each client you want to:
Reduce the scope of the map that the client gets sent updates about to only things that are closely in view (it sounds like you're already doing some of that).
Combine as much information as you can in each message that you are going to send to a client - make sure that you're never sending more than one message to a given client for a particular update.
To send smaller messages to each client you want to:
Reduce the size of the data you send to each client. This means that if some data has not changed since that last time you communicated with this client, then don't resend that data. This would suggest that your second option (client updates its own local array) is a better way to do it because you only have to send deltas to the client and it remembers previous state.
Carefully analyze the format of the data you're sending to the client and reduce its size wherever possible. Straight JSON is often not the most efficient way to send data if you're trying to optimize transmission size.
How can we implement a Facebook like status message system in mongodb (using mongoose), where whenever any given user posts his status it gets broadcasted on all his friends timeline.
It doesn't have to be real-time, there will be a refresh button to get the latest statuses.
here is what I have come up with:
Plan A:
status(collection)
id, user_id(reference), status_msg
Benefit: faster write speed
Plan B:
status(collection)
id, user_id(reference), status_msg, friends_list[sub-document]
Benefit: faster read speed
With plan A, I'll have to loop through all the friends a user has in his friends list and then fetch all the status.
I'll have to do this every time (page refresh/ new login) for every single friend.
With Plan B, I'll only have to fetch the statuses which has the current user in the friends_list.
I would like to know your opinion and suggestion on this ?
Is there any better way of approaching this problem ?
I would also like to know how I can use rabbitMQ here to increase the efficiency and lower the unnecessary db i/o .
Assuming that each user will likely have several friends, and these friends refresh their timeline several times a day, you can assume that reading will happen much more frequently than writing. That means from a pure performance standpoint you would optimize for read-access, not for write-access, and store the receivers with the message.
However, keep the semantics in mind. What if the friend-list of the author changes after they posted a status message?
Do you want the message to disappear from the timelines of any ex-friends?
Do you want the message to appear in the timeline of any new friends they make?
When the answers to these questions are yes, you should rather determine the receivers on read than on write.
There is also a third option which might be worth considering: Do not handle messages by sender, handle them by receiver. When someone posts a message, create an individual copy of the message for each of their friends and save them as separate documents. You can then get all messages for a user by querying your messages collection for messages where they are the receiver. The friend/unfriend operation would then need to check for any messages which need to be added/removed. The major drawback of this approach would be that users with a very high number of friends would create a very high write-load when posting something.