DTO's and why you should be using them

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If you've worked in any form of modern (decent sized) application, you know that the de facto standard is to use a layered design where people usually define operations into layers corresponding to certain functionality, for example a Data Access Layer, that is nothing else but an implementation of your repository using nHibernate, Entity Framework, etc. While that is a very good idea for most scenarios, a bit of a problem comes around with it, and is the fact that you need to pass around lots of calls between layers, and sometimes is not just calling a DLL inside your solution, sometimes, it's calling a service hosted somewhere over the network.

The problem

If your app calls services and receives data from them (obviously?) then you might encounter in your service something like this:
public Person AddPerson(string name, string lastName, string email)
Now, let's first look at the parameters and why this is probably not a very good definition. 

In this method, you have 3 arguments, name, lastName and email; what happens if somebody needs a telephone number? Well, we just add another argument! Dead easy! Yeah, no. Suppose we make it more interesting saying we have Workers and Customers, both inheriting from person, we would then have something like this:
public Person AddWorker(string name, string lastName, string email)
public Person AddCustomer(string name, string lastName, string email)
If you need to add that telephone number now and go for that extra param, you have to add code in two locations, so you need to touch more code, and what happens if we touch more code? Simple, we put more bugs.


The Good

Now, what happens if you have this?
public Worker AddWorker(Worker worker)
public Customer AddCustomer(Customer customer)

DTO stands for Data Transfer Object, and that is precisely what these classes do, we use them to transfer data on our services. For one, code is much simpler to read now! But there is another thing, if Worker and Customer inherit from Person as they should considering they are both a Person, then we can safely add that email to the person without having to change the signature of the service, yes, our service will now have an extra argument but we don't have to change our service signature on the code, just the DTO it receives. 

Now, more on the common use for DTO's, just as Martin Fowler states a DTO is

An object that carries data between processes in order to reduce the number of method calls.

Now, it's fairly obvious that using DTOs for input arguments is good, but what happens for output arguments? Well, similar story really, with a small twist, considering that many people today use ORMs for accessing the database, it's very likely that you already have a Worker, Customer and person class, because they are part of your domain model, or they are created by Linq To Sql (not a huge fan, but many people still use it), so, should you be using those entities to return on your services? Not a very good idea and I have some reasons for it.

One very simple reason is that the objects generated by these frameworks usually are not serialization friendly, because they are on top of proxy classes which are a pain to serialize for something that outputs JSON or XML. Another potential problem is when your entity doesn't quite fit the response you want to give, what happens if your service has something like this?
public Salary CalculateWorkerSalary(Worker worker)
You could have a very simple method just returning a double, but let's think of a more convoluted solution to illustrate the point, imagine salary being like this:
public class Salary
{
     public double FinalSalary {get;}
     public double TaxDeducted {get;}
     public double Overtime {get;}
}
So, this is our class, and Overtime means it's coupled to a user because not everybody does the same amount of overtime. So, what happens now if we also need the Tax code for that salary? Or the overtime rate for the calculation? That is assuming these are not stored on the salary table. More importantly, what happens if we don't want whoever is calling the API to see the Overtime the Worker is doing? Well, the entity is not fit for purpose and we need a DTO where we can put all of these, simple as that.


The Bad

However, DTOs are not all glory, there is a problem with them and it's the fact they bloat your application, especially if you have a large application with many entities. If that's the case, it's up to you to decide when a DTO is worth it and when it's not, like many things on software design, there is no rule of thumb and it's very easy to get it wrong. But for most of things where you pass complex data, you should be using DTOs.


The Ugly

There is another problem with DTOs, and it's the fact you end up having a lot of code like this:
var query = _workerRepository.GetAll();
var workers = query.Select(ConvertWorkerDTO).ToList();
return workers;
Where ConvertWorkerDTO is just a method looking pretty much like this:
public WorkerDTO ConvertWorkerDTO(Worker worker)
{
    return new WorkerDTO() {
        Name = worker.Name,
        LastName = worker.LastName,
        Email = worker.Email
    };
}
Wouldn't be cool if you could do something without a mapping method, like this:
var query = _workerRepository.GetAll();
var workers = query.Select(x => Worker.BuildFromEntity<Worker, WorkerDTO>(x))
                   .ToList();
return workers;
Happily, there is a simple way to achieve a result like this one, and it's combining two very powerful tools, inheritance and reflection. Just have a BaseDTO class that all of your DTOs inherit from and make a method like that one, that manages the conversion by performing a mapping property to property. A fairly simple, yet fully working, version could be this:
public static TDTO BuildFromEntity<TEntity, TDTO>(TEntity entity)
{
    var dto = Activator.CreateInstance<TDTO>();
    var dtoProperties = typeof (TDTO).GetProperties();
    var entityProperties = typeof (TEntity).GetProperties();

    foreach (var property in dtoProperties)
    {
        if (!property.CanWrite)
            continue;

        var entityProp =
            entityProperties.FirstOrDefault(x => x.Name == property.Name && x.PropertyType == property.PropertyType);

        if (entityProp == null)
            continue;

        if (!property.PropertyType.IsAssignableFrom(entityProp.PropertyType))
            continue;

        var propertyValue = entityProp.GetValue(entity, new object[] {});
        property.SetValue(dto, propertyValue, new object[]{});
    }

    return dto;
}

And Finally...


The bottom line is like everything, you can over engineer your way into adding far too many DTOs into your system, but ignoring them is not a very good solution either, and adding one or two to a project with more than 15 entities just to feel you're using them, it's just as good as using one interface to say you make decoupled systems.

What's your view on this? Do you agree? Disagree? Share what you think on the comments!

EDIT: As a side note, it's work checking this article that talks a lot about the subject.

Empower your lambdas!

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If you’ve used generic repositories, you will encounter one particular problem, matching items using dynamic property names isn't easy. However, using generic repositories has always been a must for me, as it saves me having to write a lot of boilerplate code for saving, updating and so forth. Not long ago, I had a problem, I was fetching entities from a web service and writing them to the database and given that these entities had relationships, I couldn’t retrieve the same entity and save it twice, so I had a problem.
Whenever my code fetched the properties from the service, it had to realize if this entity had been loaded previously and instead of saving it twice, just modified the last updated time and any actual properties that may had changed. To begin with, I had a simple code on a base web service consumer class like this.
var client = ServiceUtils.CreateClient();
var request = ServiceUtils.CreateRequest(requestUrl);
var resp = client.ExecuteAsGet(request, "GET");
var allItems = JsonConvert.DeserializeObject<List<T>>(resp.Content);
This was all very nice and so far, I had a very generic approach (using DeserializeObject<T>). However, I had to check if the item had been previously fetched and one item’s own identity could be determined by one or more properties and my internal Id was meaningless on this context to determine if an object existed previously or not. So, I had to come up with another approach. I created a basic attribute and called it IdentityProperty, whenever a property would define identity of an object externally, I would annotate it with it, so I ended up with entities like this:
public class Person: Entity
{
    [IdentityProperty]
    public string PassportNumber { get; set; } 
    
    [IdentityProperty] 
    public string SocialSecurityNumber { get; set; }

    public string Name {get; set}
}
This would mark all properties that defined identity on the context of web services. So far, so good, my entities now know what defines them on the domain, now I need my generic service consumer to find them on the database so I don’t get duplicates. Now, considering that all my entities fetched from a web service have a Cached and a Timeout property, ideally, I would have something like this:
foreach (var item in allItems)
{
    var calculatedLambda = CalculateLambdaMatchingEntity(item);
    var match = repository.FindBy(calculatedLambda);

    if (match == null) {
        item.LastCached = DateTime.Now;
        item.Timeout = cacheControl;
    }
    else {
        var timeout = match.Cached.AddSeconds(match.Timeout);
        if (DateTime.Now > timeout){
            //Update Entity using reflection
            item.LastCached = DateTime.Now;
    }
}

Well, actually, this is what I have, but the good stuff is on the CalculateLambda method. The idea behind that method is to calculate a lambda to be passed to the FindBy method using the only the properties that contains the IdentityProperty attribute. So, my method looks like this:
private Expression<Func<T, bool>> CalculateLambdaMatchingEntity<T>(T entityToMatch)
{
 var properties = typeof (T).GetProperties();
 var expresionParameter = Expression.Parameter(typeof (T));
 Expression resultingFilter = null;

 foreach (var propertyInfo in properties) {
  var hasIdentityAttribute = propertyInfo.GetCustomAttributes(typeof (IdentityPropertyAttribute), false).Any();

  if (!hasIdentityAttribute)
   continue;

  var propertyCall = Expression.Property(expresionParameter, propertyInfo);

  var currentValue = propertyInfo.GetValue(entityToMatch, new object[] {});
  var comparisonExpression = Expression.Constant(currentValue);

  var component = Expression.Equal(propertyCall, comparisonExpression);

  var finalExpression = Expression.Lambda(component, expresionParameter);

  if (resultingFilter == null)
   resultingFilter = finalExpression;
  else
   resultingFilter = Expression.And(resultingFilter, finalExpression);
 }

    return (Expression<Func<T, bool>>)resultingFilter;
}
Fancy code apart, what this does is just iterate trough the properties of the object and construct a lambda matching the object received as sample, so for our sample class Person, if our service retrieves a person with passport "SAMPLE" and social security number "ANOTHER", the generated lambda would be the equivalent of issuing a query like

repository.FindBy(person => person.Passport == "SAMPLE" && person.SocialSecurityNumber == "ANOTHER")

Performance you say?

If you've read the about section on my blog, you'll know that I work for a company that cares about performance, so once I did this, I knew the next step was bechmarking the process. It doesn't really matter the fact that it was for a personal project, I had to know that the performance made it a viable idea. So, I ended up doing a set of basic tests benchmarking the total time that the update foreach would take and I came up with these results:
Scenario Matching data Ticks Faster?
Lambda calculation Yes 5570318 Yes
No Lambda calculation Yes 7870450
Lambda calculation No 1780102 No
No Lambda calculation No 1660095
These are actually quite simple to explain, when no data is available, the overhead of calculating a lambda, makes it loose the edge because no items match on the query, however, when there are items matching the power of lambdas shows up, because the compiler doesn't have to build the expression tree from an expression, but instead, it will receive a previously built tree, so it's faster to execute. So, back into the initial title, empower your lambdas!
If you have any other point of view on these ideas, feel free to leave a comment even if you are going to prove me wrong with it because I've always said that nobody knows everything, so I might be very mistaken here. On the other hand, if this helps, then my job is complete here.

Common method for saving and updating on Entity Framework

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This problem has been bugging me for some time now. One of the things that I miss the most from NHibernate when I'm working with EF is the SaveOrUpdate methods. Once you lose that, you realize just how much you loved it in the first place. So, I set out to make my EF repositories to use one of those. My initial approach was rather simple and really close to what you can find here or here, so I basically came out with this:

public T SaveOrUpdate(T item)
{
 if (item == null)
  return default(T);

 var entry = _internalDataContext.Entry(item);

 if (entry.State == EntityState.Detached)
  if (item.Id != null)
   TypeDbSet.Attach(item);
  else 
   TypeDbSet.Add(item);
 
 _internalDataContext.SaveChanges();
 return item;
}
This is a neat idea and it works for most of the cases, with one tiny issue. I was working with an external API and I was caching the objects received on my calls and since these objects had their own keys, I was using those keys on my DB. So, I had a Customer class, but the Id property was set when I was about to insert and since our method uses the convention that if it has an Id, it was already saved, then the repo would just attach it to the change tracker but the object was never saved! Boo! Well, no panic, my repo also has a method called GetOne which receives an Id and returns that object, so I added that into the soup and got this:
public T SaveOrUpdate(T item)
{
 if (item == null)
  return default(T);

 var entry = _internalDataContext.Entry(item);

 if (entry.State == EntityState.Detached)
 {
  if (item.Id != null)
  {
   var exists = GetOne(item.Id) != null;

   if (exists)
    TypeDbSet.Attach(item);
   else
    TypeDbSet.Add(item);
  }
  else 
   TypeDbSet.Add(item);
 }
 
 _internalDataContext.SaveChanges();

 return item;
}
Now, if you think about it, how would you update an object?

  • Check if the object already exists on the DB
  • If it's there.. update it!
  • If it's not there.. insert it!

As you can see, Check involves GetOne. Now, if you are thinking that you don't want an extra DB call, there is always a solution...

public T SaveOrUpdate(T item, bool enforceInsert = false)
{
 if (item == null)
  return default(T);

 var entry = _internalDataContext.Entry(item);

 if (entry.State == EntityState.Detached)
 {
  if (item.Id != null)
  {
   var exists = enforceInsert || GetOne(item.Id) != null;

   if (exists)
    TypeDbSet.Attach(item);
   else
    TypeDbSet.Add(item);
  }
  else 
   TypeDbSet.Add(item);
 }
 
 _internalDataContext.SaveChanges();

 return item;
}

Granted, is not fancy, but gets the job done and doesn't requires many changes. If you pass the enforceInsert flag, means you are certain that the object you're saving requires an insert, so it will have an Id, but you know is not there. Just what I was doing!

Do you have any other way of doing this? Do you think this is wrong? Feel free to comment and let me know!

Consuming web services and notifying your app about it on Objective C

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Since almost the beginning of my exploits as an iOS developer I've been working on several apps consuming web services and one big problem has been notifying different areas of my app that certain event has been updated. My first genius idea was to create my own home brew of notifications using the observer pattern. It wasn't all that bad, but then a while later I realized that I was reinventing the wheel, so I resorted to the one and only NSNotificationCenter.

Enter NSNotificationCenter


According to Apple on the docs for the notification center, this is the definition:

An NSNotificationCenter object (or simply, notification center) provides a mechanism for broadcasting information within a program. An NSNotificationCenter object is essentially a notification dispatch table.

So, this was my observer! How does it work you say? Let's get to it! But before, let's get into context. What I have is a class called ServiceBase which is the base class (duh!) for all classes consuming services. The interface definition for the class looks a bit like this...

 @interface ServiceBase : NSObject<ASIHTTPRequestDelegate>
  - (void) performWebServiceRequest: (NSString*) serviceUrl;
  - (void) triggerNotificationWithName: (NSString*) notificationName andArgument: (NSObject*) notificationArgument;
  - (NSString*) getServiceBaseUrl;
 @end
 

The class has been simplified and the actual class has a few other things that depend more on how I work, but you get the point. However, given the idea of this post, I'm going to concentrate more on the notification side of the class. However, we do need to get some sort of example here going on and to get that done, let's take a look on the performWebServiceRequest method.

- (void) performWebServiceRequest: (NSString*) serviceUrl
{
    if (!self.queue) {
        self.queue = [[NSOperationQueue alloc] init];
    }
    
    NSURL *url = [NSURL URLWithString: serviceUrl];
    ASIHTTPRequest *request = [ASIHTTPRequest requestWithURL:url];
    [request addRequestHeader:@"accept" value:@"text/json"];
 
 [requestion setCompletionBlock: ^{
  //this will keep the self object reference alive until the request is done
  [self requestFinished: request];
 }];
 
    [self.queue addOperation: request];
}
 

Now, we have this simplified method that creates a request, sets the requestFinished method as the completion block and queues up the request. Now, I said I would focus on the notifications, but one thing to consider here:

 [requestion setCompletionBlock: ^{
  //this will keep the self object reference alive until the request is done
  [self requestFinished: request];
 }];
 

Keep in mind, that this sentence will preserve the reference to self until the request is finished, so it's not autoreleased by ARC, however, the way I use services on my app, each service works as a singleton (or quite close to that) and keeping the reference is not a problem because you are not creating one new instance of each service class every time you make a request. This also solves an issue with ASIHttpRequest loosing the reference to the delegate before the service is complete, however, that's a story for another day. Now, moving on the the end of the request...

- (void)requestFinished:(ASIHTTPRequest *)request
{
    JSONDecoder* decoder = [[JSONDecoder alloc] init];
    NSData * data = [request responseData];
    NSArray* dictionary = [decoder objectWithData: data];

    for (NSDictionary* element in dictionary) {
  [self triggerNotificationWithName: @"ItemLoaded" andArgument: element];
    }
}
 

When the request is finished, it will only convert the data received, notice that this is a simple scenario, and make a notification that an Item has been loaded using the [triggerNotificationWithName: andArgument] method. Now, into the actual notification method...

- (void) triggerNotificationWithName: (NSString*) notificationName andArgument: (NSObject*) notificationArgument
{
    NSNotificationCenter * notificationCenter = [NSNotificationCenter defaultCenter];
   
 if ( notificationArgument == nil )
 {
  [notificationCenter postNotificationName: notificationName  object: nil];
 }
 else
 {
  NSMutableDictionary * arguments = [[NSMutableDictionary alloc] init];
  [arguments setValue: notificationArgument forKey: @"Value"];
  [notificationCenter postNotificationName: notificationName  object:self userInfo: arguments];
 }
}
 

Now, we only need to subscribe to a notification and retrieve the value which is very simple, take this example inside a UIViewController:

- (void) viewDidLoad
{
 NSNotificationCenter * notificationCenter = [NSNotificationCenter defaultCenter];
 [notificationCenter addObserver: self selector: @selector(authenticationFinished:) name:@"AuthenticationCompleted" object: nil];
}

- (void) itemLoadedNotificationReceived: (NSNotification*) notification
{
 NSDictionary* itemLoaded = [notification.userInfo valueForKey: @"Value"];
    // Do something with the item you just loaded
}
 


In the itemLoadedNotificationReceived method the app will receive a notification when each item is loaded. This may not be the best example, because when you're loading several items, they normally go into a cache to be loaded from a UITableView afterwards, but this idea should get you going.

Do you use a different approach? Do you normally use it like this? Well, if you have anything at all to say, feel free to leave it in the comments!