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It was just pointed out to me in a comment by Jimi<\/strong>, that DownloadFileAsync<\/a> is an event driven call and not awaitable. Though, there is a WebClient.DownloadFileTaskAsync<\/a> version, which would be the appropriate one to use in this example, it is an awaitable call and returns a Downloads the specified resource to a local file as an asynchronous I know I could run multiple threads or even parallel but what’s the Yes you can make it parallel and be in control of the resources you use.<\/p>\n I’m not too worried about speed as long as it isn’t as slow as right You should be able to achieve this and configure this fairly well.<\/p>\n OK, so there are many ways to do this. Here are some things to think about:<\/p>\n Some immediate solutions:<\/p>\n Please note<\/strong>: there are many other approaches.<\/p>\n So In this case, downloading a file is clearly I\/O<\/em>, there is a Here is a very basic example of how you might achieve this:<\/p>\n Given<\/strong><\/p>\n Dataflow example<\/strong><\/p>\n Summary<\/strong><\/p>\n This approach gives you Asynchrony<\/em>, it also gives you Disclaimer<\/strong>, DataFlow may not be where you want to be, however I just thought I’d give you some more information<\/p>\n Disclaimer 2<\/strong>, Also the above code has not been tested, I would seriously consider researching this technology first and doing your on due diligence thoroughly.<\/p>\n Loosely related demo here<\/strong><\/a><\/p>\n<\/p><\/div>\nTask<\/code><\/p>\n\n
\noperation using a task object.<\/p>\n<\/blockquote>\nOriginal answer<\/h1>\n
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\nbest way<\/p>\n<\/blockquote>\n\n
\nnow, but I don’t want to overpower the device’s resources such as CPU
\ntrying to speed it up<\/p>\n<\/blockquote>\n
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async<\/code> \/ await<\/code> pattern so you’re not wasting system resources on IO completion ports or smashing your CPU<\/li>\n<\/ul>\n\n
WaitAll<\/code><\/a> in an asnyc<\/code> \/ await<\/code> pattern, this is a great approach however it’s a little bit trickier to limit concurrent tasks.<\/li>\nParallel.ForEach<\/code><\/a> and Parallel.For<\/code><\/a>, this has a nice approach to limit concurrent workloads, but its just not suited to IO bound tasks<\/li>\nParallel.ForEach<\/code> uses the thread pool. Moreover, IO bound<\/em> operations will block those threads waiting for a device to respond and tie up resources. A general rule of thumb here is<\/p>\n\n
Parallel.ForEach<\/code> is appropriate;<\/li>\nDownloadFileAsync<\/code> version, and 1000 files to download, so you are best to use async<\/code>\/await<\/code> pattern and some type of limit on concurrent tasks<\/p>\n
\npublic class WorkLoad\n{\n public string Url {get;set;}\n public string FileName {get;set;}\n\n}\n<\/code><\/pre>\npublic async Task DoWorkLoads(List<WorkLoad> workloads)\n{\n var options = new ExecutionDataflowBlockOptions\n {\n \/\/ add pepper and salt to taste\n MaxDegreeOfParallelism = 50\n };\n\n \/\/ create an action block\n var block = new ActionBlock<WorkLoad>(MyMethodAsync, options);\n\n \/\/ Queue them up\n foreach (var workLoad in workloads)\n block.Post(workLoad );\n\n \/\/ wait for them to finish\n block.Complete();\n await block.Completion;\n\n}\n\n...\n\n\/\/ Notice we are using the async \/ await pattern\npublic async Task MyMethodAsync(WorkLoad workLoad)\n{\n \n try\n {\n Console.WriteLine(\"Downloading: \" + workLoad.Url);\n await client.DownloadFileAsync(workLoad.Url, workLoad.FileName);\n }\n catch (Exception)\n {\n \/\/ probably best to add some error checking some how\n }\n}\n<\/code><\/pre>\nMaxDegreeOfParallelism<\/code>, it doesn’t waste resources, and lets IO<\/em> be IO<\/em><\/p>\n
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