private static void CreateAdminUser(UserManager <ApplicationUser> userManager)
{
var roleManager = new RoleManager <IdentityRole>(new RoleStore <IdentityRole>(new PartsUnlimitedContext()));
if (!roleManager.RoleExists(AdminConstants.Role))
{
roleManager.Create(new IdentityRole(AdminConstants.Role));
}
var username = ConfigurationHelpers.GetString("Authentication.Administrator.UserName");
var password = ConfigurationHelpers.GetString("Authentication.Administrator.Password");
var user = userManager.FindByName(username);
if (user == null)
{
user = new ApplicationUser {
UserName = username, Email = username
};
var result = userManager.Create(user, password);
if (!result.Succeeded)
{
throw new Exception(string.Format("Failed to create admin user: {0}", string.Join(",", result.Errors)));
}
user = userManager.FindByName(username);
userManager.AddToRole(user.Id, AdminConstants.Role);
userManager.AddClaim(user.Id, new Claim(AdminConstants.ManageStore.Name, AdminConstants.ManageStore.Allowed));
}
}
public ConfigurationLoginProviderCredentials(string providerName)
{
Key = ConfigurationHelpers.GetString(string.Format("Authentication.{0}.Key", providerName));
Secret = ConfigurationHelpers.GetString(string.Format("Authentication.{0}.Secret", providerName));
Use = !string.IsNullOrWhiteSpace(Key) && !string.IsNullOrWhiteSpace(Secret);
}
public async Task <IEnumerable <string> > GetRecommendationsAsync(string productId)
{
string modelName = ConfigurationHelpers.GetString("MachineLearning.ModelName");
//The Azure ML service takes in a recommendation model name (trained ahead of time) and a product id
string uri = string.Format("https://api.datamarket.azure.com/data.ashx/amla/mba/v1/Score?Id=%27{0}%27&Item=%27{1}%27", modelName, productId);
try
{
//The Azure ML service returns a set of numbers, which indicate the recommended product id
var response = await client.GetStringAsync(uri);
AzureMLFrequentlyBoughtTogetherServiceResponse deserializedResponse = JsonConvert.DeserializeObject <AzureMLFrequentlyBoughtTogetherServiceResponse>(response);
//When there is no recommendation, The Azure ML service returns a JSON object that does not contain ItemSet
var recommendation = deserializedResponse.ItemSet;
if (recommendation == null)
{
return(Enumerable.Empty <string>());
}
else
{
return(recommendation);
}
}
catch (HttpRequestException e)
{
telemetry.TrackException(e);
return(Enumerable.Empty <string>());
}
}
/// <summary>
/// Starts a SignalR client which listens for change notifications from the LOB app.
/// Whenever match data is changed update notifications are automatically pushed to clients of this website.
/// </summary>
private static void StartGameDataListener()
{
Task.Run(() => {
try
{
Trace.TraceInformation("Connecting to Game Data notifications");
var serverUrl = ConfigurationHelpers.GetString("Contoso.Lob.Endpoint");
_lobHubConnection = new HubConnection(serverUrl);
_updatesDisposer = _lobHubConnection.CreateHubProxy("UpdatesHub")
.On <int>("NotifyGameDataUpdated", SendGameUpdateNotifications);
_lobHubConnection.Start().Wait();
Trace.TraceInformation("Connected");
}
catch (Exception ex)
{
Trace.TraceError("Error in game data poller: {0}", ex);
}
});
}