Dapper/Readme.md

Dapper - a simple object mapper for .Net

Release Notes

Located at https://github.com/DapperLib/Dapper/releases

Packages

Package	NuGet Stable	NuGet Pre-release	Downloads
Dapper
Dapper.EntityFramework
Dapper.EntityFramework.StrongName
Dapper.Rainbow
Dapper.SqlBuilder
Dapper.StrongName

Package Purposes:

• Dapper
  • The core library
• Dapper.EntityFramework
  • Extension handlers for EntityFramework
• Dapper.EntityFramework.StrongName
  • Extension handlers for EntityFramework
• Dapper.Rainbow
  • Micro-ORM implemented on Dapper, provides CRUD helpers (readme)
• Dapper.SqlBuilder
  • Component for building SQL queries dynamically and composably

Sponsors

Dapper was originally developed for and by Stack Overflow, but is F/OSS. Sponsorship is welcome and invited - see the sponsor link at the top of the page. A huge thanks to everyone (individuals or organisations) who have sponsored Dapper, but a massive thanks in particular to:

• Dapper Plus is a major sponsor and is proud to contribute to the development of Dapper (read more)
• AWS who sponsored Dapper from Oct 2023 via the .NET on AWS Open Source Software Fund

Features

Dapper is a NuGet library that you can add in to your project that will enhance your ADO.NET connections via extension methods on your DbConnection instance. This provides a simple and efficient API for invoking SQL, with support for both synchronous and asynchronous data access, and allows both buffered and non-buffered queries.

It provides multiple helpers, but the key APIs are:

// insert/update/delete etc
var count  = connection.Execute(sql [, args]);

// multi-row query
IEnumerable<T> rows = connection.Query<T>(sql [, args]);

// single-row query ({Single|First}[OrDefault])
T row = connection.QuerySingle<T>(sql [, args]);

where args can be (among other things):

• a simple POCO (including anonyomous types) for named parameters
• a Dictionary<string,object>
• a DynamicParameters instance

Execute a query and map it to a list of typed objects

public class Dog
{
    public int? Age { get; set; }
    public Guid Id { get; set; }
    public string Name { get; set; }
    public float? Weight { get; set; }

    public int IgnoredProperty { get { return 1; } }
}

var guid = Guid.NewGuid();
var dog = connection.Query<Dog>("select Age = @Age, Id = @Id", new { Age = (int?)null, Id = guid });

Assert.Equal(1,dog.Count());
Assert.Null(dog.First().Age);
Assert.Equal(guid, dog.First().Id);

Execute a query and map it to a list of dynamic objects

This method will execute SQL and return a dynamic list.

Example usage:

var rows = connection.Query("select 1 A, 2 B union all select 3, 4").AsList();

Assert.Equal(1, (int)rows[0].A);
Assert.Equal(2, (int)rows[0].B);
Assert.Equal(3, (int)rows[1].A);
Assert.Equal(4, (int)rows[1].B);

Execute a Command that returns no results

Example usage:

var count = connection.Execute(@"
  set nocount on
  create table #t(i int)
  set nocount off
  insert #t
  select @a a union all select @b
  set nocount on
  drop table #t", new {a=1, b=2 });
Assert.Equal(2, count);

Execute a Command multiple times

The same signature also allows you to conveniently and efficiently execute a command multiple times (for example to bulk-load data)

Example usage:

var count = connection.Execute(@"insert MyTable(colA, colB) values (@a, @b)",
    new[] { new { a=1, b=1 }, new { a=2, b=2 }, new { a=3, b=3 } }
  );
Assert.Equal(3, count); // 3 rows inserted: "1,1", "2,2" and "3,3"

Another example usage when you already have an existing collection:

var foos = new List<Foo>
{
    { new Foo { A = 1, B = 1 } }
    { new Foo { A = 2, B = 2 } }
    { new Foo { A = 3, B = 3 } }
};

var count = connection.Execute(@"insert MyTable(colA, colB) values (@a, @b)", foos);
Assert.Equal(foos.Count, count);

This works for any parameter that implements IEnumerable<T> for some T.

Performance

A key feature of Dapper is performance. The following metrics show how long it takes to execute a SELECT statement against a DB (in various config, each labeled) and map the data returned to objects.

The benchmarks can be found in Dapper.Tests.Performance (contributions welcome!) and can be run via:

dotnet run --project .\benchmarks\Dapper.Tests.Performance\ -c Release -f net8.0 -- -f * --join

Output from the latest run is:

BenchmarkDotNet v0.13.7, Windows 10 (10.0.19045.3693/22H2/2022Update)
Intel Core i7-3630QM CPU 2.40GHz (Ivy Bridge), 1 CPU, 8 logical and 4 physical cores
.NET SDK 8.0.100
  [Host]   : .NET 8.0.0 (8.0.23.53103), X64 RyuJIT AVX
  ShortRun : .NET 8.0.0 (8.0.23.53103), X64 RyuJIT AVX

ORM	Method	Return	Mean	StdDev	Error	Gen0	Gen1	Gen2	Allocated
Dapper cache impact	ExecuteParameters_Cache	Void	96.75 us	0.668 us	1.010 us	0.6250	-	-	2184 B
Dapper cache impact	QueryFirstParameters_Cache	Void	96.86 us	0.493 us	0.746 us	0.8750	-	-	2824 B
Hand Coded	SqlCommand	Post	119.70 us	0.706 us	1.067 us	1.3750	1.0000	0.1250	7584 B
Hand Coded	DataTable	dynamic	126.64 us	1.239 us	1.873 us	3.0000	-	-	9576 B
SqlMarshal	SqlCommand	Post	132.36 us	1.008 us	1.523 us	2.0000	1.0000	0.2500	11529 B
Dapper	QueryFirstOrDefault	Post	133.73 us	1.301 us	2.186 us	1.7500	1.5000	-	11608 B
Mighty	Query	dynamic	133.92 us	1.075 us	1.806 us	2.0000	1.7500	-	12710 B
LINQ to DB	Query	Post	134.24 us	1.068 us	1.614 us	1.7500	1.2500	-	10904 B
RepoDB	ExecuteQuery	Post	135.83 us	1.839 us	3.091 us	1.7500	1.5000	-	11649 B
Dapper	'Query (buffered)'	Post	136.14 us	1.755 us	2.653 us	2.0000	1.5000	-	11888 B
Mighty	Query	Post	137.96 us	1.485 us	2.244 us	2.2500	1.2500	-	12201 B
Dapper	QueryFirstOrDefault	dynamic	139.04 us	1.507 us	2.279 us	3.5000	-	-	11648 B
Mighty	SingleFromQuery	dynamic	139.74 us	2.521 us	3.811 us	2.0000	1.7500	-	12710 B
Dapper	'Query (buffered)'	dynamic	140.13 us	1.382 us	2.090 us	2.0000	1.5000	-	11968 B
ServiceStack	SingleById	Post	140.76 us	1.147 us	2.192 us	2.5000	1.2500	0.2500	15248 B
Dapper	'Contrib Get'	Post	141.09 us	1.394 us	2.108 us	2.0000	1.5000	-	12440 B
Mighty	SingleFromQuery	Post	141.17 us	1.941 us	2.935 us	1.7500	1.5000	-	12201 B
Massive	'Query (dynamic)'	dynamic	142.01 us	4.957 us	7.494 us	2.0000	1.5000	-	12342 B
LINQ to DB	'First (Compiled)'	Post	144.59 us	1.295 us	1.958 us	1.7500	1.5000	-	12128 B
RepoDB	QueryField	Post	148.31 us	1.742 us	2.633 us	2.0000	1.5000	0.5000	13938 B
Norm	'Read<> (tuples)'	ValueTuple`8	148.58 us	2.172 us	3.283 us	2.0000	1.7500	-	12745 B
Norm	'Read<()> (named tuples)'	ValueTuple`8	150.60 us	0.658 us	1.106 us	2.2500	2.0000	1.2500	14562 B
RepoDB	Query	Post	152.34 us	2.164 us	3.271 us	2.2500	1.5000	0.2500	14106 B
RepoDB	QueryDynamic	Post	154.15 us	4.108 us	6.210 us	2.2500	1.7500	0.5000	13930 B
RepoDB	QueryWhere	Post	155.90 us	1.953 us	3.282 us	2.5000	0.5000	-	14858 B
Dapper cache impact	ExecuteNoParameters_NoCache	Void	162.35 us	1.584 us	2.394 us	-	-	-	760 B
Dapper cache impact	ExecuteNoParameters_Cache	Void	162.42 us	2.740 us	4.142 us	-	-	-	760 B
Dapper cache impact	QueryFirstNoParameters_Cache	Void	164.35 us	1.206 us	1.824 us	0.2500	-	-	1520 B
DevExpress.XPO	FindObject	Post	165.87 us	1.012 us	1.934 us	8.5000	-	-	28099 B
Dapper cache impact	QueryFirstNoParameters_NoCache	Void	173.87 us	1.178 us	1.781 us	0.5000	-	-	1576 B
LINQ to DB	First	Post	175.21 us	2.292 us	3.851 us	2.0000	0.5000	-	14041 B
EF 6	SqlQuery	Post	175.36 us	2.259 us	3.415 us	4.0000	0.7500	-	24209 B
Norm	'Read<> (class)'	Post	186.37 us	1.305 us	2.496 us	3.0000	0.5000	-	17579 B
DevExpress.XPO	GetObjectByKey	Post	186.78 us	3.407 us	5.151 us	4.5000	1.0000	-	30114 B
Dapper	'Query (unbuffered)'	dynamic	194.62 us	1.335 us	2.019 us	1.7500	1.5000	-	12048 B
Dapper	'Query (unbuffered)'	Post	195.01 us	0.888 us	1.343 us	2.0000	1.5000	-	12008 B
DevExpress.XPO	Query	Post	199.46 us	5.500 us	9.243 us	10.0000	-	-	32083 B
Belgrade	FirstOrDefault	Task`1	228.70 us	2.181 us	3.665 us	4.5000	0.5000	-	20555 B
EF Core	'First (Compiled)'	Post	265.45 us	17.745 us	26.828 us	2.0000	-	-	7521 B
NHibernate	Get	Post	276.02 us	8.029 us	12.139 us	6.5000	1.0000	-	29885 B
NHibernate	HQL	Post	277.74 us	13.032 us	19.703 us	8.0000	1.0000	-	31886 B
NHibernate	Criteria	Post	300.22 us	14.908 us	28.504 us	13.0000	1.0000	-	57562 B
EF 6	First	Post	310.55 us	27.254 us	45.799 us	13.0000	-	-	43309 B
EF Core	First	Post	317.12 us	1.354 us	2.046 us	3.5000	-	-	11306 B
EF Core	SqlQuery	Post	322.34 us	23.990 us	40.314 us	5.0000	-	-	18195 B
NHibernate	SQL	Post	325.54 us	3.937 us	7.527 us	22.0000	1.0000	-	80007 B
EF 6	'First (No Tracking)'	Post	331.14 us	27.760 us	46.649 us	12.0000	1.0000	-	50237 B
EF Core	'First (No Tracking)'	Post	337.82 us	27.814 us	46.740 us	3.0000	1.0000	-	17986 B
NHibernate	LINQ	Post	604.74 us	5.549 us	10.610 us	10.0000	-	-	46061 B
Dapper cache impact	ExecuteParameters_NoCache	Void	623.42 us	3.978 us	6.684 us	3.0000	2.0000	-	10001 B
Dapper cache impact	QueryFirstParameters_NoCache	Void	630.77 us	3.027 us	4.576 us	3.0000	2.0000	-	10640 B

Feel free to submit patches that include other ORMs - when running benchmarks, be sure to compile in Release and not attach a debugger (Ctrl+F5).

Alternatively, you might prefer Frans Bouma's RawDataAccessBencher test suite or OrmBenchmark.

Parameterized queries

Parameters are usually passed in as anonymous classes. This allows you to name your parameters easily and gives you the ability to simply cut-and-paste SQL snippets and run them in your db platform's Query analyzer.

new {A = 1, B = "b"} // A will be mapped to the param @A, B to the param @B

Parameters can also be built up dynamically using the DynamicParameters class. This allows for building a dynamic SQL statement while still using parameters for safety and performance.

    var sqlPredicates = new List<string>();
    var queryParams = new DynamicParameters();
    if (boolExpression)
    {
        sqlPredicates.Add("column1 = @param1");
        queryParams.Add("param1", dynamicValue1, System.Data.DbType.Guid);
    } else {
        sqlPredicates.Add("column2 = @param2");
        queryParams.Add("param2", dynamicValue2, System.Data.DbType.String);
    }

DynamicParameters also supports copying multiple parameters from existing objects of different types.

    var queryParams = new DynamicParameters(objectOfType1);
    queryParams.AddDynamicParams(objectOfType2);

When an object that implements the IDynamicParameters interface passed into Execute or Query functions, parameter values will be extracted via this interface. Obviously, the most likely object class to use for this purpose would be the built-in DynamicParameters class.

List Support

Dapper allows you to pass in IEnumerable<int> and will automatically parameterize your query.

For example:

connection.Query<int>("select * from (select 1 as Id union all select 2 union all select 3) as X where Id in @Ids", new { Ids = new int[] { 1, 2, 3 } });

Will be translated to:

select * from (select 1 as Id union all select 2 union all select 3) as X where Id in (@Ids1, @Ids2, @Ids3)" // @Ids1 = 1 , @Ids2 = 2 , @Ids2 = 3

Literal replacements

Dapper supports literal replacements for bool and numeric types.

connection.Query("select * from User where UserTypeId = {=Admin}", new { UserTypeId.Admin });

The literal replacement is not sent as a parameter; this allows better plans and filtered index usage but should usually be used sparingly and after testing. This feature is particularly useful when the value being injected is actually a fixed value (for example, a fixed "category id", "status code" or "region" that is specific to the query). For live data where you are considering literals, you might also want to consider and test provider-specific query hints like OPTIMIZE FOR UNKNOWN with regular parameters.

Buffered vs Unbuffered readers

Dapper's default behavior is to execute your SQL and buffer the entire reader on return. This is ideal in most cases as it minimizes shared locks in the db and cuts down on db network time.

However when executing huge queries you may need to minimize memory footprint and only load objects as needed. To do so pass, buffered: false into the Query method.

Multi Mapping

Dapper allows you to map a single row to multiple objects. This is a key feature if you want to avoid extraneous querying and eager load associations.

Example:

Consider 2 classes: Post and User

class Post
{
    public int Id { get; set; }
    public string Title { get; set; }
    public string Content { get; set; }
    public User Owner { get; set; }
}

class User
{
    public int Id { get; set; }
    public string Name { get; set; }
}

Now let us say that we want to map a query that joins both the posts and the users table. Until now if we needed to combine the result of 2 queries, we'd need a new object to express it but it makes more sense in this case to put the User object inside the Post object.

This is the use case for multi mapping. You tell dapper that the query returns a Post and a User object and then give it a function describing what you want to do with each of the rows containing both a Post and a User object. In our case, we want to take the user object and put it inside the post object. So we write the function:

(post, user) => { post.Owner = user; return post; }

The 3 type arguments to the Query method specify what objects dapper should use to deserialize the row and what is going to be returned. We're going to interpret both rows as a combination of Post and User and we're returning back a Post object. Hence the type declaration becomes

<Post, User, Post>

Everything put together, looks like this:

var sql =
@"select * from #Posts p
left join #Users u on u.Id = p.OwnerId
Order by p.Id";

var data = connection.Query<Post, User, Post>(sql, (post, user) => { post.Owner = user; return post;});
var post = data.First();

Assert.Equal("Sams Post1", post.Content);
Assert.Equal(1, post.Id);
Assert.Equal("Sam", post.Owner.Name);
Assert.Equal(99, post.Owner.Id);

Dapper is able to split the returned row by making an assumption that your Id columns are named Id or id. If your primary key is different or you would like to split the row at a point other than Id, use the optional splitOn parameter.

Multiple Results

Dapper allows you to process multiple result grids in a single query.

Example:

var sql =
@"
select * from Customers where CustomerId = @id
select * from Orders where CustomerId = @id
select * from Returns where CustomerId = @id";

using (var multi = connection.QueryMultiple(sql, new {id=selectedId}))
{
   var customer = multi.Read<Customer>().Single();
   var orders = multi.Read<Order>().ToList();
   var returns = multi.Read<Return>().ToList();
   ...
}

Stored Procedures

Dapper fully supports stored procs:

var user = cnn.Query<User>("spGetUser", new {Id = 1},
        commandType: CommandType.StoredProcedure).SingleOrDefault();

If you want something more fancy, you can do:

var p = new DynamicParameters();
p.Add("@a", 11);
p.Add("@b", dbType: DbType.Int32, direction: ParameterDirection.Output);
p.Add("@c", dbType: DbType.Int32, direction: ParameterDirection.ReturnValue);

cnn.Execute("spMagicProc", p, commandType: CommandType.StoredProcedure);

int b = p.Get<int>("@b");
int c = p.Get<int>("@c");

Ansi Strings and varchar

Dapper supports varchar params, if you are executing a where clause on a varchar column using a param be sure to pass it in this way:

Query<Thing>("select * from Thing where Name = @Name", new {Name = new DbString { Value = "abcde", IsFixedLength = true, Length = 10, IsAnsi = true }});

On SQL Server it is crucial to use the unicode when querying unicode and ANSI when querying non unicode.

Type Switching Per Row

Usually you'll want to treat all rows from a given table as the same data type. However, there are some circumstances where it's useful to be able to parse different rows as different data types. This is where IDataReader.GetRowParser comes in handy.

Imagine you have a database table named "Shapes" with the columns: Id, Type, and Data, and you want to parse its rows into Circle, Square, or Triangle objects based on the value of the Type column.

var shapes = new List<IShape>();
using (var reader = connection.ExecuteReader("select * from Shapes"))
{
    // Generate a row parser for each type you expect.
    // The generic type <IShape> is what the parser will return.
    // The argument (typeof(*)) is the concrete type to parse.
    var circleParser = reader.GetRowParser<IShape>(typeof(Circle));
    var squareParser = reader.GetRowParser<IShape>(typeof(Square));
    var triangleParser = reader.GetRowParser<IShape>(typeof(Triangle));

    var typeColumnIndex = reader.GetOrdinal("Type");

    while (reader.Read())
    {
        IShape shape;
        var type = (ShapeType)reader.GetInt32(typeColumnIndex);
        switch (type)
        {
            case ShapeType.Circle:
            	shape = circleParser(reader);
            	break;
            case ShapeType.Square:
            	shape = squareParser(reader);
            	break;
            case ShapeType.Triangle:
            	shape = triangleParser(reader);
            	break;
            default:
            	throw new NotImplementedException();
        }

      	shapes.Add(shape);
    }
}

User Defined Variables in MySQL/MariaDB

In order to use Non-parameter SQL variables with MySql Connector, you have to add the following option to your connection string:

Allow User Variables=True

Make sure you don't provide Dapper with a property to map.

Limitations and caveats

Dapper caches information about every query it runs, this allows it to materialize objects quickly and process parameters quickly. The current implementation caches this information in a ConcurrentDictionary object. Statements that are only used once are routinely flushed from this cache. Still, if you are generating SQL strings on the fly without using parameters it is possible you may hit memory issues.

Dapper's simplicity means that many features that ORMs ship with are stripped out. It worries about the 95% scenario, and gives you the tools you need most of the time. It doesn't attempt to solve every problem.

Will Dapper work with my DB provider?

Dapper has no DB specific implementation details, it works across all .NET ADO providers including SQLite, SQL CE, Firebird, Oracle, MariaDB, MySQL, PostgreSQL and SQL Server.

Do you have a comprehensive list of examples?

Dapper has a comprehensive test suite in the test project.

Who is using this?

Dapper is in production use at Stack Overflow.