Today, I had to restart my browser due to some issue with an extension. What I found when I restarted it, was that my browser (Chromium) automatically updated to a new version that doesn't allow synchronous AJAX-requests anymore. Quote:
Synchronous XMLHttpRequest on the main thread is deprecated because of
its detrimental effects to the end user's experience. For more help,
check http://xhr.spec.whatwg.org/.
I need synchronous AJAX-requests for my node.js applications to work though, as they store and load data from disk through a server utilizing fopen. I found this to be a very simplistic and effective way of doing things, very handy in the creation of little hobby projects and editors... Is there a way to re-enable synchronous XMLHttpRequests in Chrome/Chromium?
This answer has been edited.
Short answer:
They don't want sync on the main thread.
The solution is simple for new browsers that support threads/web workers:
var foo = new Worker("scriptWithSyncRequests.js")
Neither DOM nor global vairables aren't going to be visible within a worker but encapsulation of multiple synchronous requests is going to be really easy.
Alternative solution is to switch to async but to use browser localStorage along with JSON.stringify as a medium. You might be able to mock localStorage if you allowed to do some IO.
http://caniuse.com/#search=localstorage
Just for fun, there are alternative hacks if we want to restrict our self using only sync:
It is tempting to use setTimeout because one might think it is a good way to encapsulate synchronous requests together. Sadly, there is a gotcha. Async in javascript doesn't mean it gets to run in its own thread. Async is likely postponing the call, waiting for others to finish. Lucky for us there is light at the end of the tunnel because it is likely you can use xhttp.timeout along with xhttp.ontimeout to recover. See Timeout XMLHttpRequest
This means we can implement tiny version of a schedular that handles failed request and allocates time to try again or report error.
// The basic idea.
function runSchedular(s)
{
setTimeout(function() {
if (s.ptr < callQueue.length) {
// Handles rescheduling if needed by pushing the que.
// Remember to set time for xhttp.timeout.
// Use xhttp.ontimeout to set default return value for failure.
// The pushed function might do something like: (in pesudo)
// if !d1
// d1 = get(http...?query);
// if !d2
// d2 = get(http...?query);
// if (!d1) {pushQue tryAgainLater}
// if (!d2) {pushQue tryAgainLater}
// if (d1 && d2) {pushQue handleData}
s = s.callQueue[s.ptr++](s);
} else {
// Clear the que when there is nothing more to do.
s.ptr = 0;
s.callQueue = [];
// You could implement an idle counter and increase this value to free
// CPU time.
s.t = 200;
}
runSchedular(s);
}, s.t);
}
Doesn't "deprecated" mean that it's available, but won't be forever. (I read elsewhere that it won't be going away for a number of years.) If so, and this is for hobby projects, then perhaps you could use async: false for now as a quick way to get the job done?
Related
I want to be able to call an HTTP endpoint (that I own) from an Azure Function at the end of the Azure Function request.
I do not need to know the result of the request
If there is a problem in the HTTP endpoint that is called I will log it there
I do not want to hold up the return to the client calling the initial Azure Function
Offloading the call of the secondary WebApi onto a background job queue is considered overkill for this requirement
Do I simply call HttpClient.PutAsync without an await?
I realise that the dependencies I have used up until the point that the call is made may well not be available when the call returns. Is there a safe way to check if they are?
My answer may cause some controversy but, you can always start a background task and execute it that way.
For anyone reading this answer, this is far from recommended. The OP has been very clear that they don't care about exceptions or understanding what sort of result the request is returning ...
Task.Run(async () =>
{
using (var httpClient = new HttpClient())
{
await httpClient.PutAsync(...);
}
});
If you want to ensure that the call has fired, it may be worth waiting for a second or two after the call is made to ensure it's actually on it's way.
await Task.Delay(1000);
If you're worried about dependencies in the call, be sure to construct your payload (i.e. serialise it, etc.) external to the Task.Run, basically, minimise any work the background task does.
I'm trying to synchronize my POSTs to an endpoint in Angular. I did see some examples of doing a synchronized GET but had trouble understanding the examples well enough to apply them to POSTs.
The POSTs are pretty simple, at least from my perspective as the front-end developer. I send an object with an parent group ID and a sub group ID to a /parentgroups endpoint. On the backend, however, async calls cause the data to get overwritten.
Apologies for lack of an example, but I am pretty far from having one that's close to working how I need. My code is still async and a loop over calls to $http.post().
You actually cannot do real synchronous (as in blocking) http calls in Angular, it forces you do use async. If you can't do it with callbacks then you have a problem with your architecture that the entire team should focus on solving ASAP. If your current architecture requires the frontend to do blocking calls then your architecture is quite simply broken and needs to be fixed.
Anyway, while I recommend against it you could always register your request in a list, and then in each callback you pop the next request from the list and run it. That way you can just keep pushing requests into the list without knowing how many there will be. Something like this (untested, but the general principle should work):
var requestList = [];
requestList.push(function() {
$http.post('/someUrl', {})
.success(function(data, status, headers, config) {
// Remove the next request from list and call it
requestList.shift()();
});
});
requestList.push(function() {
$http.post('/someOtherUrl', {})
.success(function(data, status, headers, config) {
// Remove the next request from list and call it
requestList.shift()();
});
});
// Start the first request
requestList.shift()();
This is fairly clean, but still a bit of a hack. It would probably work fine but I would be taking a good long look at why the API forces you to do something like this.
I need to design a rate limiter service for throttling requests.
For every incoming request a method will check if the requests per second has exceeded its limit or not. If it has exceeded then it will return the amount of time it needs to wait for being handled.
Looking for a simple solution which just uses system tick count and rps(request per second). Should not use queue or complex rate limiting algorithms and data structures.
Edit: I will be implementing this in c++. Also, note I don't want to use any data structures to store the request currently getting executed.
API would be like:
if (!RateLimiter.Limit())
{
do work
RateLimiter.Done();
}
else
reject request
The most common algorithm used for this is token bucket. There is no need to invent a new thing, just search for an implementation on your technology/language.
If your app is high avalaible / load balanced you might want to keep the bucket information on some sort of persistent storage. Redis is a good candidate for this.
I wrote Limitd is a different approach, is a daemon for limits. The application ask the daemon using a limitd client if the traffic is conformant. The limit is configured on the limitd server and the app is agnostic to the algorithm.
since you give no hint of language or platform I'll just give out some pseudo code..
things you are gonna need
a list of current executing requests
a wait to get notified where a requests is finished
and the code can be as simple as
var ListOfCurrentRequests; //A list of the start time of current requests
var MaxAmoutOfRequests;// just a limit
var AverageExecutionTime;//if the execution time is non deterministic the best we can do is have a average
//for each request ether execute or return the PROBABLE amount to wait
function OnNewRequest(Identifier)
{
if(count(ListOfCurrentRequests) < MaxAmoutOfRequests)//if we have room
{
Struct Tracker
Tracker.Request = Identifier;
Tracker.StartTime = Now; // save the start time
AddToList(Tracker) //add to list
}
else
{
return CalculateWaitTime()//return the PROBABLE time it will take for a 'slot' to be available
}
}
//when request as ended release a 'slot' and update the average execution time
function OnRequestEnd(Identifier)
{
Tracker = RemoveFromList(Identifier);
UpdateAverageExecutionTime(Now - Tracker.StartTime);
}
function CalculateWaitTime()
{
//the one that started first is PROBABLY the first to finish
Tracker = GetTheOneThatIsRunnigTheLongest(ListOfCurrentRequests);
//assume the it will finish in avg time
ProbableTimeToFinish = AverageExecutionTime - Tracker.StartTime;
return ProbableTimeToFinish
}
but keep in mind that there are several problems with this
assumes that by returning the wait time the client will issue a new request after the time as passed. since the time is a estimation, you can not use it to delay execution, or you can still overflow the system
since you are not keeping a queue and delaying the request, a client can be waiting for more time that what he needs.
and for last, since you do not what to keep a queue, to prioritize and delay the requests, this mean that you can have a live lock, where you tell a client to return later, but when he returns someone already took its spot, and he has to return again.
so the ideal solution should be a actual execution queue, but since you don't want one.. I guess this is the next best thing.
according to your comments you just what a simple (not very precise) requests per second flag. in that case the code can be something like this
var CurrentRequestCount;
var MaxAmoutOfRequests;
var CurrentTimestampWithPrecisionToSeconds
function CanRun()
{
if(Now.AsSeconds > CurrentTimestampWithPrecisionToSeconds)//second as passed reset counter
CurrentRequestCount=0;
if(CurrentRequestCount>=MaxAmoutOfRequests)
return false;
CurrentRequestCount++
return true;
}
doesn't seem like a very reliable method to control whatever.. but.. I believe it's what you asked..
I m developping a Winjs/HTML windows Store application .
I have to do some tests every period of time so let's me explain my need.
when i navigate to my specific page , I have to test (without a specific time in advance=loop)
So when my condition is verified it Will render a Flyout(Popup) and then exit from the Promise. (Set time out need a specific time but i need to verify periodically )
I read the msdn but i can't fullfill this goal .
If someone has an idea how to do it , i will be thankful.
Every help will be appreciated.
setInterval can be used.
var timerId = setInternal(function ()
{
// do you work.
}, 2000); // timer event every 2s
// invoke this when timer needs to be stopped or you move out of the page; that is unload() method
clearInternal(timerId);
Instead of polling at specific intervals, you should check if you can't adapt your code to use events or databinding instead.
In WinJS you can use databinding to bind input values to a view model and then check in its setter functions if your condition has been fulfilled.
Generally speaking, setInterval et al should be avoided for anything that's not really time-related domain logic (clocks, countdowns, timeouts or such). Of course there are situations when there's no other way (like polling remote services), so this may not apply to your situation at hand.
I am displaying information from a data model on a user interface. My current approach to doing so is by means of delegation as follows:
#protocol DataModelDelegate <NSObject>
- (void)updateUIFromDataModel;
#end
I am implementing the delegate method in my controller class as follows, using GCD to push the UI updating to the main thread:
- (void)updateUIFromDataModel {
dispatch_async(dispatch_get_main_queue(), ^{
// Code to update various UI controllers
// ...
// ...
});
}
What I am concerned about is that in some situations, this method can be called very frequently (~1000 times per second, each updating multiple UI objects), which to me feels very much like I am 'spamming' the main thread with commands.
Is this too much to be sending to the main thread? If so does anyone have any ideas on what would be the best way of approaching this?
I have looked into dispatch_apply, but that appears to be more useful when coalescing data, which is not what I am after - I really just want to skip updates if they are too frequent so only a sane amount of updates are sent to the main thread!
I was considering taking a different approach and implementing a timer instead to constantly poll the data, say every 10 ms, however since the data updating tends to be sporadic I feel that it would be wasteful to do so.
Combining both approaches, another option I have considered would be to wait for an update message and respond by setting the timer to poll the data at a set interval, and then disabling the timer if the data appears to have stopped changing. But would this be over-complicating the issue, and would the sane approach be to simply have a constant timer running?
edit: Added an answer below showing the adaptations using a dispatch source
One option is to use a Dispatch Source with type DISPATCH_SOURCE_TYPE_DATA_OR which lets you post events repeatedly and have libdispatch combine them together for you. When you have something to post, you use dispatch_source_merge_data to let it know there's something new to do. Multiple calls to dispatch_source_merge_data will be coalesced together if the target queue (in your case, the main queue) is busy.
I have been experimenting with dispatch sources and got it working as expected now - Here is how I have adapted my class implementation in case it is of use to anyone who comes across this question:
#implementation AppController {
#private
dispatch_source_t _gcdUpdateUI;
}
- (void)awakeFromNib {
// Added the following code to set up the dispatch source event handler:
_gcdUpdateUI = dispatch_source_create(DISPATCH_SOURCE_TYPE_DATA_ADD, 0, 0,
dispatch_get_main_queue());
dispatch_source_set_event_handler(_gcdUpdateUI, ^{
// For each UI element I want to update, pull data from model object:
// For testing purposes - print out a notification:
printf("Data Received. Messages Passed: %ld\n",
dispatch_source_get_data(_gcdUpdateUI));
});
dispatch_resume(_gcdUpdateUI);
}
And now in the delegate method I have removed the call to dispatch_async, and replaced it with the following:
- (void)updateUIFromDataModel {
dispatch_source_merge_data(_gcdUpdateUI, 1);
}
This is working absolutely fine for me. Now Even during the most intense data updating the UI stays perfectly responsive.
Although the printf() output was a very crude way of checking if the coalescing is working, a quick scrolling back up the console output showed me that the majority of the messages print outs had a value 1 (easily 98% of them), however there were the intermittent jumps to around 10-20, reaching a peak value of just over 100 coalesced messages around a time when the model was sending the most update messages.
Thanks again for the help!
If the app beach-balls under heavy load, then you've blocked the main thread for too long and you need to implement a coalescing strategy for UI updates. If the app remains responsive to clicks, and doesn't beach-ball, then you're fine.