private Task<Listing<Source>> SourcesList() { Client c = new Client(userName, apiKey); Ordered<Source.Filterable, Source.Orderable, Source> result = (from s in c.ListSources() orderby s.Created descending select s); return result.InternalTask; }
/// <summary> /// Simple sample that runs through all steps to explicitly create a prediction /// from a csv file with the classic iris data. /// </summary> static async Task MainAsync() { // New BigML client using username and API key. Console.Write("user: "******"key: "); var ApiKey = Console.ReadLine(); var client = new Client(User, ApiKey); Ordered<Source.Filterable, Source.Orderable, Source> result = (from s in client.ListSources() orderby s.Created descending select s); var sources = await result; foreach(var src in sources) { Console.WriteLine(src.ToString()); } // New source from in-memory stream, with separate header. var source = await client.Create(iris, "Iris.csv", "sepal length, sepal width, petal length, petal width, species"); // No push, so we need to busy wait for the source to be processed. while ((source = await client.Get(source)).StatusMessage.StatusCode != Code.Finished) await Task.Delay(10); Console.WriteLine(source.StatusMessage.ToString()); // Default dataset from source var dataset = await client.Create(source); // No push, so we need to busy wait for the source to be processed. while ((dataset = await client.Get(dataset)).StatusMessage.StatusCode != Code.Finished) await Task.Delay(10); Console.WriteLine(dataset.StatusMessage.ToString()); // Default model from dataset var model = await client.Create(dataset); // No push, so we need to busy wait for the source to be processed. while ((model = await client.Get(model)).StatusMessage.StatusCode != Code.Finished) await Task.Delay(10); Console.WriteLine(model.StatusMessage.ToString()); // The model description is what we are really after var description = model.ModelDescription; Console.WriteLine(description.ToString()); // First convert it to a .NET expression tree var expression = description.Expression(); Console.WriteLine(expression.ToString()); // Then compile the expression tree into MSIL var predict = expression.Compile() as Func<double,double,double,double,string>; // And try the first flower of the example set. var result2 = predict(5.1, 3.5, 1.4, 0.2); Console.WriteLine("result = {0}, expected = {1}", result2, "setosa"); }
// add async attribute in the event handler private async void button1_Click(object sender, EventArgs e) { button1.Enabled = false; label1.Text = "Loading..."; Client c = new Client(userName, apiKey); Ordered<Source.Filterable, Source.Orderable, Source> result = (from s in c.ListSources() orderby s.Created descending select s); Listing<Source> sources = await result; //use await keyword int countSources = 0; foreach (Source src in sources) { countSources++; } label1.Text = countSources + " sources found"; button1.Enabled = true; }