#Dapper definition code

If joins against the TVP are necessary, it is possible to add a clustered index on the column of interest, for example, SalesOrderId. For millions of rows, use Bulk Copy instead for better performance. TVPs are ideal when you have thousands of rows or less. Note if the query result is empty, this method will send back an empty list with a count of zero.Īs a side note, binding to a C# record instead of class requires at least a parameterless default constructor otherwise Dapper throws an exception. Specifying the return type via a generic parameter, i.e.,, binds the results in managed code. This method gets a list of query results that can be enumerated. T-SQL isn’t case sensitive, assuming the collation of the database is set this way, and will bind correctly even if there isn’t an exact case match. The one gotcha here is the property must match the SQL variable in the query.

Note param is a throwaway POCO that does not need to be strongly typed. If there are passthrough layers up in the call stack, it is acceptable to return a Task. A best practice is to go ahead and do async/await but do it as efficiently as possible. If context information is necessary at this level, one technique is sending this data via a method parameter to avoid synchronization.įailing to await the call in the repository bombs because the connection falls out of scope and gets closed before the task gets awaited. A good rule of thumb is if you are working in the DAL, put ConfigureAwait(false) in every call stack method. Unfortunately, C# does not do this automatically for the developer, so it must come from muscle memory. Therefore, it is a good idea to set configure await to false, so this does not wait on the main thread. It is best to nuke any synchronization with the main thread at the data access layer because this can affect scalability. In SQL, this typically means INSERT, UPDATE, or DELETE statements. The method returns an int with the number of rows affected by the query. Whenever you see the ExecuteAsync method, it is safe to assume this performs a mutation to the backend database. Fortunately, Visual Studio is not required unless you prefer to use this tool. It is also possible to point this to another SQL Server instance via the DataSource property. The connection string in the repo points to the MSLocalDB instance, which you can get from SQL Server Express.

#Dapper definition code

NET 6 SDK and a copy of SQL Server preloaded with the AdventureWorks database to run the code sample. NET make this relatively painless via async/await, albeit with caveats.

I opted to use only async methods because these are the ones anyone should be using in a production environment.

At each pause, I encourage you to play with the code and allow the information to sink in. This guide can be used as a reference so you can read one section at a time. I recommend general familiarity with LINQ and the List generic class in C#. The set of extension methods can feel overwhelming because there is a lot of functionality to cover. The focus here is to walk through the code API and follow best practices for building a DAL. To keep this relevant to any real application, there is quite a bit of code, which I won’t be able to show, so I recommend downloading the repo from GitHub. In this take, I will walk you through what Dapper has to offer and why it has become the tool of choice for many high-demand solutions.ĭapper is a lightweight shim around ADO.NET for data access via extension methods. Dapper is a micro-ORM built with simplicity, top-notch performance, and ease of use in mind. The Data Access Layer (DAL) is often the most critical part of any application.