使用AlamoFire框架后,我注意到完成处理程序在主线程上运行。我想知道下面的代码是否是在完成处理程序中创建Core Data导入任务的好习惯:
Alamofire.request(.GET, "http://myWebSite.com", parameters: parameters) .responseJSON(options: .MutableContainers) { (_, _, JSON, error) -> Void in dispatch_async(dispatch_get_global_queue(DISPATCH_QUEUE_PRIORITY_HIGH, 0), { () -> Void in if let err = error{ println("Error:\(error)") return; } if let jsonArray = JSON as? [NSArray]{ let importer = CDImporter(incomingArray: jsonArray entity: "Artist", map: artistEntityMap); } }); }
这是一个非常好的问题。您的方法是完全有效的。但是,Alamofire实际上可以帮助您进一步简化此流程。
在示例代码中,您将在以下调度队列之间跳转:
如您所见,您到处都是。让我们看看利用Alamofire内部强大功能的另一种方法。
Alamofire在其自身的低级处理中内置了一种最佳方法。response如果您选择使用该方法,则最终由所有自定义响应序列化程序调用的单个方法将支持自定义调度队列。
response
尽管GCD在调度队列之间跳转非常出色,但您要避免跳转到繁忙的队列(例如主线程)。通过消除异步处理过程中跳回主线程的方式,您可以大大加快处理速度。以下示例演示了如何直接使用Alamofire逻辑来执行此操作。
let queue = dispatch_queue_create("com.cnoon.manager-response-queue", DISPATCH_QUEUE_CONCURRENT) let request = Alamofire.request(.GET, "http://httpbin.org/get", parameters: ["foo": "bar"]) request.response( queue: queue, serializer: Request.JSONResponseSerializer(options: .AllowFragments), completionHandler: { _, _, JSON, _ in // You are now running on the concurrent `queue` you created earlier. println("Parsing JSON on thread: \(NSThread.currentThread()) is main thread: \(NSThread.isMainThread())") // Validate your JSON response and convert into model objects if necessary println(JSON) // To update anything on the main thread, just jump back on like so. dispatch_async(dispatch_get_main_queue()) { println("Am I back on the main thread: \(NSThread.isMainThread())") } } )
let queue = dispatch_queue_create("com.cnoon.manager-response-queue", DISPATCH_QUEUE_CONCURRENT) let request = Alamofire.request(.GET, "http://httpbin.org/get", parameters: ["foo": "bar"]) request.response( queue: queue, responseSerializer: Request.JSONResponseSerializer(options: .AllowFragments), completionHandler: { response in // You are now running on the concurrent `queue` you created earlier. print("Parsing JSON on thread: \(NSThread.currentThread()) is main thread: \(NSThread.isMainThread())") // Validate your JSON response and convert into model objects if necessary print(response.result.value) // To update anything on the main thread, just jump back on like so. dispatch_async(dispatch_get_main_queue()) { print("Am I back on the main thread: \(NSThread.isMainThread())") } } )
let queue = DispatchQueue(label: "com.cnoon.response-queue", qos: .utility, attributes: [.concurrent]) Alamofire.request("http://httpbin.org/get", parameters: ["foo": "bar"]) .response( queue: queue, responseSerializer: DataRequest.jsonResponseSerializer(), completionHandler: { response in // You are now running on the concurrent `queue` you created earlier. print("Parsing JSON on thread: \(Thread.current) is main thread: \(Thread.isMainThread)") // Validate your JSON response and convert into model objects if necessary print(response.result.value) // To update anything on the main thread, just jump back on like so. DispatchQueue.main.async { print("Am I back on the main thread: \(Thread.isMainThread)") } } )
这是此方法涉及的不同调度队列的细分。
通过消除返回主调度队列的第一跳,您消除了潜在的瓶颈,并使整个请求和处理成为异步。太棒了!
话虽如此,我对强调Alamofire真正工作原理的内在知识有多么重要。您永远不知道什么时候可以找到真正可以帮助您改进自己的代码的东西。