Dapper - a simple object mapper for .Net

Features

Dapper is a single file you can drop in to your project that will extend your IDbConnection interface.

It provides 3 helpers:

Execute a query and map the results to a strongly typed List

Note: all extension methods assume the connection is already open, they will fail if the connection is closed.

publicstaticIEnumerable<T>Query<T>(thisIDbConnectioncnn,stringsql,objectparam=null,SqlTransactiontransaction=null,boolbuffered=true)

Example usage:

publicclassDog{publicint?Age{get;set;}publicGuidId{get;set;}publicstringName{get;set;}publicfloat?Weight{get;set;}publicintIgnoredProperty{get{return1;}}}varguid=Guid.NewGuid();vardog=connection.Query<Dog>("select Age = @Age, Id = @Id",new{Age=(int?)null,Id=guid});dog.Count().IsEqualTo(1);dog.First().Age.IsNull();dog.First().Id.IsEqualTo(guid);

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

publicstaticIEnumerable<dynamic>Query(thisIDbConnectioncnn,stringsql,objectparam=null,SqlTransactiontransaction=null,boolbuffered=true)

This method will execute SQL and return a dynamic list.

Example usage:

varrows=connection.Query("select 1 A, 2 B union all select 3, 4");((int)rows[0].A).IsEqualTo(1);((int)rows[0].B).IsEqualTo(2);((int)rows[1].A).IsEqualTo(3);((int)rows[1].B).IsEqualTo(4);

Execute a Command that returns no results

publicstaticintExecute(thisIDbConnectioncnn,stringsql,objectparam=null,SqlTransactiontransaction=null)

Example usage:

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}).IsEqualTo(2);

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:

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}}).IsEqualTo(3);// 3 rows inserted: "1,1", "2,2" and "3,3"

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

Performance

A key feature of Dapper is performance. The following metrics show how long it takes to execute 500 SELECT statements against a DB and map the data returned to objects.

The performance tests are broken in to 3 lists:

• POCO serialization for frameworks that support pulling static typed objects from the DB. Using raw SQL.
• Dynamic serialization for frameworks that support returning dynamic lists of objects.
• Typical framework usage. Often typical framework usage differs from the optimal usage performance wise. Often it will not involve writing SQL.

Performance of SELECT mapping over 500 iterations - POCO serialization

Method	Duration	Remarks
Hand coded (using a SqlDataReader)	47ms	Can be faster
Dapper ExecuteMapperQuery	49ms
ServiceStack.OrmLite (QueryById)	50ms
PetaPoco	52ms
BLToolkit	80ms
SubSonic CodingHorror	107ms
NHibernate SQL	104ms
Linq 2 SQL ExecuteQuery	181ms
Entity framework ExecuteStoreQuery	631ms

Performance of SELECT mapping over 500 iterations - dynamic serialization

Method	Duration	Remarks
Dapper ExecuteMapperQuery (dynamic)	48ms
Massive	52ms
Simple.Data	95ms

Performance of SELECT mapping over 500 iterations - typical usage

Method	Duration	Remarks
Linq 2 SQL CompiledQuery	81ms	Not super typical involves complex code
NHibernate HQL	118ms
Linq 2 SQL	559ms
Entity framework	859ms
SubSonic ActiveRecord.SingleOrDefault	3619ms

Performance benchmarks are available here

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)

Parameterized queries

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

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

List Support

Dapper allow you to pass in IEnumerable 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=newint[]{1,2,3});

Will be translated to:

select*from(select1asId union allselect2union all select3)as X where Id in(@Ids1,@Ids2,@Ids3)" // @Ids1 = 1 , @Ids2 = 2 , @Ids2 = 3

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:

varsql=@"select * from #Posts p left join #Users u on u.Id = p.OwnerId Order by p.Id";vardata=connection.Query<Post,User,Post>(sql,(post,user)=>{post.Owner=user;returnpost;});varpost=data.First();post.Content.IsEqualTo("Sams Post1");post.Id.IsEqualTo(1);post.Owner.Name.IsEqualTo("Sam");post.Owner.Id.IsEqualTo(99);

important note Dapper assumes your Id columns are named "Id" or "id", if your primary key is different or you would like to split the wide row at point other than "Id", use the optional 'splitOn' parameter.

Multiple Results

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

Example:

varsql=@"select * from Customers where CustomerId = @idselect * from Orders where CustomerId = @idselect * from Returns where CustomerId = @id";using(varmulti=connection.QueryMultiple(sql,new{id=selectedId})){varcustomer=multi.Read<Customer>().Single();varorders=multi.Read<Order>().ToList();varreturns=multi.Read<Return>().ToList();
...}

Stored Procedures

Dapper supports fully stored procs:

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

If you want something more fancy, you can do:

varp=newDynamicParameters();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);intb=p.Get<int>("@b");intc=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=newDbString{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.

Limitations and caveats

Dapper caches information about every query it runs, this allow it to materialize objects quickly and process parameters quickly. The current implementation caches this information in a ConcurrentDictionary object. The objects it stores are never flushed. If you are generating SQL strings on the fly without using parameters it is possible you will hit memory issues. We may convert the dictionaries to an LRU Cache.

Dapper's simplicity means that many feature that ORMs ship with are stripped out, there is no identity map, there are no helpers for update / select and so on.

Dapper does not manage your connection's lifecycle, it assumes the connection it gets is open AND has no existing datareaders enumerating (unless MARS is enabled)

Will dapper work with my db provider?

Dapper has no DB specific implementation details, it works across all .net ado providers including sqlite, sqlce, firebird, oracle, MySQL 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, helpdesk

(if you would like to be listed here let me know)