Currently we have implemented a repository pattern at work. All our repositories sit behind their own interfaces and are mapped via Ninject. Our project is quite large and there are a couple quirks with this pattern I'm trying to solve.
First, there are some controllers where we need upwards of 10 to 15 repositories all in the same controller. The constructor gets rather ugly when asking for so many repositories. The second quirk reveals itself after you call methods on multiple repositories. After doing work with multiple repositories we need to call the SaveChanges method, but which repository should we call it on? Every repository has one. All repositories have the same instance of the Entity Framework data context injected so picking any random repository to call save on will work. It just seems so messy.
I looked up the "Unit Of Work" pattern and came up with a solution that I think solves both problems, but I'm not 100% confident in this solution. I created a class called DataBucket
.
// Slimmed down for readability
public class DataBucket
{
private DataContext _dataContext;
public IReportsRepository ReportRepository { get; set; }
public IEmployeeRepository EmployeeRepository { get; set; }
public IDashboardRepository DashboardRepository { get; set; }
public DataBucket(DataContext dataContext,
IReportsRepository reportsRepository,
IEmployeeRepository employeeRepository,
IDashboardRepository dashboardRepository)
{
_dataContext = dataContext;
this.ReportRepository = reportsRepository;
this.EmployeeRepository = employeeRepository;
this.DashboardRepository = dashboardRepository;
}
public void SaveChanges()
{
_dataContext.SaveChanges();
}
}
This appears to solve both issues. There is now only one SaveChanges
method on the data bucket itself and you only inject one object, the data bucket. You then access all the repositories as properties. The data bucket would be a little messy looking since it would be accepting ALL (easily 50 or more) of our repositories in its constructor.
The process of adding a new repository would now include: creating the interface, creating the repository, mapping the interface and repository in Ninject, and adding a property to the data bucket and populating it.
I did think of an alternative to this that would eliminate a step from above.
public class DataBucket
{
private DataContext _dataContext;
public IReportsRepository ReportRepository { get; set; }
public IEmployeeRepository EmployeeRepository { get; set; }
public IDashboardRepository DashboardRepository { get; set; }
public DataBucket(DataContext dataContext)
{
_dataContext = dataContext;
this.ReportRepository = new ReportsRepository(dataContext);
this.EmployeeRepository = new EmployeeRepository(dataContext);
this.DashboardRepository = new DashboardRepository(dataContext);
}
public void SaveChanges()
{
_dataContext.SaveChanges();
}
}
This one pretty much eliminates all the repository mappings in Ninject because they are all instantiated in the data bucket. So now the steps to adding a new repository include: Create interface, create repository, add property to data bucket and instantiate.
Can you see any flaws with this model? On the surface it seems much more convenient to consume our repositories in this way. Is this a problem that has been addressed before? If so, what is the most common and/or most efficient approach to this issue?
The Repository pattern. Repositories are classes or components that encapsulate the logic required to access data sources. They centralize common data access functionality, providing better maintainability and decoupling the infrastructure or technology used to access databases from the domain model layer.
In essence, the Repository design pattern facilitates de-coupling of the business logic and the data access layers in your application with the former not having to have any knowledge on how data persistence would actually take place.
The Repository pattern is used to decouple the business logic and the data access layers in your application. The data access layer typically contains storage specific code and methods to operate on the data to and from the data storage.
First, there are some controllers where we need upwards of 10 to 15 repositories all in the same controller.
Say hello to Abstract factory pattern. Instead of registering all repositories in Ninject and injecting them to controllers register just single implementation of the factory which will be able to provide any repository you need - you can even create them lazily only if the controller really needs them. Than inject the factory to controller.
Yes it also has some disadvantages - you are giving controller permission to get any repository. Is it problem for you? You can always create multiple factories for some sub systems if you need or simply expose multiple factory interfaces on single implementation. It still doesn't cover all cases but it is better than passing 15 parameters to constructor. Btw. are you sure those controllers should not be split?
Note: This is not Service provider anti-pattern.
After doing work with multiple repositories we need to call the SaveChanges method, but which repository should we call it on?
Say hello to Unit of Work pattern. Unit of Work is logical transaction in your application. It persists all changes from logical transaction together. Repository should not be responsible for persisting changes - the unit of work should be. Somebody mentioned that DbContext
is implementation of Repository pattern. It is not. It is implementation of Unit of Work pattern and DbSet
is implementation of Repository pattern.
What you need is central class holding the instance of the context. The context will be also passed to repositories because they need it to retrieve data but only the central class (unit of work) will offer saving changes. It can also handle database transaction if you for example need to change isolation level.
Where should be unit of work handled? That depends where your logical operation is orchestrated. If the operation is orchestrated directly in controller's actions you need to have unit of work in the action as well and call SaveChanges
once all modifications are done.
If you don't care about separation of concerns too much you can even combine unit of work and factory into single class. That brings us to your DataBucket
.
I think you are absolutely right to use the Unit of Work pattern in this case. Not only does this prevent you from needing a SaveChanges
method on every repository, it provides you a nice way to handle transactions from within code rather than in your database itself. I included a Rollback
method with my UOW so that if there was an exception I could undo any of the changes the operation had already made on my DataContext
.
One thing you could do to prevent weird dependency issues would be to group related repositories on their own Unit of Work, rather than having one big DataBucket that holds every Repository you have (if that was your intent). Each UOW would only need to be accessible at the same level as the repositories it contained, and other repositories should probably not depend on other UOWs themselves (your repositories shouldn't need to use other repositories).
If wanted to be an even bigger purist of the pattern, you could also structure your UOWs to represent just that, a single Unit of Work. You define them to represent a specific operation in your domain, and provide it with the repositories required to complete that operation. Individual repositories could exist on more than one UOW, if it made sense to be used by more than one operation in your domain.
For example, a PlaceCustomerOrderUnitOfWork
may need a CustomerRepository
, OrderRepository
, BillingRepository
, and a ShippingRepository
An CreateCustomerUnitOfWork
may need just a CustomerRepository
. Either way, you can easily pass that dependency around to its consumers, more fine grained interfaces for your UOW can help target your testing and reduce the effort to create a mock.
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