Posts Tagged ‘CodeFluent Entities’

Team Work with CodeFluent Entities

Working on your own and working along a whole developers team are obviously not the same. As a team, you will experience issues that you would never encounter working alone.

In order to help you work in a harmless way with CodeFluent Entities in that context, we wrote a new paper about every little things you can configure while you are:

  • Designing your model collaboratively
  • Generating your own database
  • Handling work station custom connection strings
  • Using source control

You can get this paper here.

Happy Configurating,

The R&D Team.

CodeFluent Entities and Fetch Performance Benchmark

Two month ago, we heard about a benchmark that fetch performance of .NET Data Access Tools and ORMs. This benchmark has been introduced by Frans Bouma in this following blog post.

We started by creating a simple implementation with CodeFluent Entities and then analyze the result. Thanks to the flexibility of our product, it seems natural for us to provide an optimized but generic implementation. This means that the code is still generated.

CodeFluent Entities provides dynamics modeling features like “Aspects” to implement application-wide behaviors. This is what we call dynamic modeling. In a nutshell, in CodeFluent Entities, dynamic modeling is materialized as aspects and it allows developers to inject extra-behaviors in models.

That’s what gave us the idea of developing a new Aspect called “FasterReader” to reduce the number of data type conversion.
We explained our approach in a blog Post named “Fetch performance of CodeFluent Entities compared to others“.
This Aspect is generic (not “benchmark dedicated”) and can be used in any kind of model.

Once the article is published, we sent a Pull Request on the RawDataAccessBencher GitHub repository to submit the CodeFluent Entities implementation:


The initial commit is available here and includes the CodeFluent Entities Model with the SoftFluent.FasterReader.xml aspect.

We also modified the README.MD file with the following changes:

CodeFluent Entities is a Model-First code generator. CodeFluent Entities will access database using automatically generated stored procedures. For more information about CodeFluent Entities and this benchmark:

Of course, this readme includes a link to our blog post that explains the approach.

Then, Frans Bouma asked us to make some understandable changes before merging the code:

  • remove links to CodeFluent Entities website
  • remove a large file with all the procs
  • remove useless files in various folders regarding TFS, scc, resx, .user, etc.
  • remove the CodeFluent Entities Model

For your information about the last statement: we have chosen to add this project to let users generate again the code and to be completely transparent.

Of course, feedbacks has been considered a few days later:


At the end of April, the CodeFluent Entities implementation was finally merged:

But… the 5th of May, Frans Bouma removed our code:


With the following reason:

The CodeFluent code was removed as it kept the connection open during
individual fetches which therefore turned out to be faster than everyone
else. This was hard to find, and therefore a form of cheating.

By default, CodeFluent Entities opens one connection per thread but we attempted to explain that we can change this behavior. His reaction was the following:


You will find below the result with the custom configuration:

ADO.NET’s Connection Pooling keeps all connections open so that doesn’t change a lot of things so we don’t change this setting:


We understand the way out products connects to a database out-of-the-box is not ok for Mr Bouma, but we don’t really understand why he went so mad about this, treating us cheaters. Again, this is how it works out-the-box. Why should we investigate why our product – based on stored procedures – is faster than others? Mr Bouma could have discussed with us – like he did in the beginning of the whole process – and we could have changed this default behavior happily to comply with his rules. We were not trying to make a fool of him or to hide crucial information from him, just compete with other products. It’s a sad way of doing thing, and in the end, this behavior does not change anything to the numbers.

Moreover, if you want to check or test our implementation (the Model is included), please visit the following GitHub repository.

The R&D Team.

ASP.NET Identity v2 and CodeFluent Entities

April 30, 2014 Leave a comment

Update (2014/06/23) – please check out this related post :

A few weeks ago, we wrote about ASP.NET Identity v1 and CodeFluent Entities. The ASP.NET Identity system is designed to replace the previous ASP.NET Membership and Simple Membership systems. It includes profile support, OAuth integration, works with OWIN and is included with the ASP.NET templates shipped with Visual Studio 2013.

ASP.NET Identity 2.0 was released last month so today we’ll see how to use it with CodeFluent Entities.

What’s new?

One of the drawbacks of the first release was that the primary key must be of type “string”. This new version allows to use any type as primary key. To do so, interfaces now have a second generic parameter, “TKey”, to specify the type of the primary key (int, Guid, etc.).
They also introduce new interfaces:

  • IUserLockoutStore<User, TKey>: allow to lock-out an account after a determined failed connection attempts
  • IUserEmailStore<User, TKey>: allow to store an email address and to confirm it (by sending an email for example)
  • IUserPhoneNumberStore<User, TKey>: allow to store a phone number and to confirm it (by sending a SMS for example)
  • IUserTwoFactorStore<User, TKey>: enable two-factor authentification (for example login/password and a token sent by email or SMS)

The implementation


Here’s the CodeFluent Entities Model to support those interfaces:


You’ll note that our model contains:

  • Implementation rules. We don’t even have to add partial class, everything is in the model
  • validation rules (EmailValidation) to ensure email address is valid
  • Unique contraints (UserName, Email, Role Name)

As for ASP.NET Identity v1, each method is only one or two lines of code:

public class UserStore :
    IUserStore<User, Guid>,
    IUserPasswordStore<User, Guid>,
    IUserSecurityStampStore<User, Guid>,
    IUserRoleStore<User, Guid>,
    IUserLoginStore<User, Guid>,
    IUserClaimStore<User, Guid>
    public Task<User> FindAsync(UserLoginInfo login)
        return Task.FromResult(User.LoadByProviderKey(login.ProviderKey));

    public Task ResetAccessFailedCountAsync(User user)
        user.AccessFailedCount = 0;
        return Task.FromResult(0);

    public Task<int> GetAccessFailedCountAsync(User user)
        return Task.FromResult(user.AccessFailedCount);

    // and so on

The full implementation is available on our GitHub repository.

The R&D team.

Views, Auto-Lightweight and the Modeler

April 22, 2014 Leave a comment

In a previous post we saw how to create views and lightweight entities by using XML. Nowadays most of you are using the graphical modeler, so let’s see how to create views.

First, let’s create a simple model:


We can create a view that contains the supplier name and the country name. Select the supplier entity and click the “Add view” button from the ribbon:

ribbon - add view

You should see the following window:

Add view 1

Enter a valid name and select properties to include in the view. Only properties from the selected entity are shown. So to add the country name, we have to click the “Add” button and enter the binding expression “Country.Name” (auto completion prevents mistakes).

Add view 2

The « Auto infer lightweight entity » checkbox allows to generate an entity that contains selected properties. As the name suggests it’s a light entity: it’s not persistent, it has no CRUD methods (e.g. load, save, delete) nor extra properties by default, and it does not implement any interfaces other than the ICodeFluentLightEntity by default.

Now we can create a method that will load data from this view:

load from view

The generated code contains the SQL view :

CREATE VIEW [dbo].[vSupplierSupplierLight]
SELECT [Supplier].[Supplier_Name], [Country].[Country_Name] AS 'CountryName'
FROM [Supplier]
INNER JOIN [Country]
ON ([Supplier].[Supplier_Country_Id] = [Country].[Country_Id])

And the inferred lightweight entity:



Happy View-ing!

The R&D team

Fetch performance of CodeFluent Entities compared to others

March 27, 2014 Leave a comment

CodeFluent Entities has a great way to extend or modify generated code. This can be done through Custom Producers, Sub-Producers or Aspects. In fact, it can happen that you will meet very special requirements during your project, the kind of requirements that will involve some customizations to all of your code. Of course you don’t want to do this job manually by modifying each property or method in your project. Instead you can change the generated code to fit your expectations by using aspect. For a first introduction to aspect development in CodeFluent Entities please visit our blog.

In our situation, after reading Frans Bouma’s blog on benchmark of several ORMs of the .Net platform (Entity Framework, NHibernate, LLBLGen Pro, Linq To Sql and more), we wanted to integrate CodeFluent Entities to the benchmarks he made.

Integrating CodeFluent Entities to the benchmark project

First we downloaded the project from its GitHub repository.

After opening the RawBencher solution we created a CodeFluent Entities Model project:

CodeFluent Entities Project

Also we created a class library project to hold the code generated by CodeFluent Entities:

Class Library Project

Then we added one Business Object Model Producer and one SQL Server Producer to this project:

Solution Explorer

Here is the configuration for each producer:

Business Object Model

Business Object Model

Microsoft SQL Server

Microsoft SQL Server

Then we imported the AdventureWorks database to our CodeFluent Entities model:


Then select the Microsoft SQL Server importer:

SQL Server Importer

Finally, set the connection string as pictured below:

SQL Server importer configuration

Once the import from database was done we built the model project to generate C# code and database stored procedures. After this, for the final step we added a bencher class to call CodeFluent Entities generated code. We basically reproduced the same schema as the existing ones for other ORMs already set up in this benchmarking project.

We are now ready to start the benchmarking!

Running the benchmark and analyzing results

We ran the project in release mode and we got the following results:

Non-change tracking fetches, set fetches (10 runs), no caching:

  1. Handcoded materializer using DbDataReader: 214,63ms
  2. PetaPoco Fast v4.0.3: 285,50ms
  3. Dapper: 306,25ms
  4. Linq to SQL v4: 318,50ms
  5. PetaPoco v4.0.3: 355,00ms
  6. Entity Framework v6: 362,13ms
  7. CodeFluent Entities 551,00ms
  8. ServiceStack OrmList v4.0.9.0: 555,75ms
  9. LLBLGen Pro v4.1.0.0, typed view: 585,00ms
  10. Oak.DynamicDb using dynamic Dto class: 902,50ms

Non-change tracking individual fetches (100 elements, 10 runs), no caching:

  1. CodeFluent Entities: 0,18ms
  2. DataTable, using DbDataAdapter: 0,37ms
  3. Oak.DynamicDb using dynamic Dto class: 0,40ms
  4. LLBLGen Pro v4.1.0.0: 0,44ms
  5. Telerik DataAccess/OpenAccess Fluent v4.0.3: 0,50ms
  6. Telerik DataAccess/OpenAccess Domain v4.0.3: 0,50ms
  7. NHibernate v3.3.1.4000: 0,68ms
  8. Entity Framework v6: 1,85ms
  9. Linq to Sql v4: 2,89ms

We focused only on non-change Tracking mode because it is the one that matches CodeFluent Entities features.

We can see that CodeFluent Entities is ranked at the first place for single fetch operations. Also we can see that it is ranked 7th for the multiple fetch operations.

Of course each ORM offers different features and because of that some of them can have a more naïve approach than others which will check data type conversion for instance or check cache during the fetch. This will lead to a speed difference in execution time.

For example if you compare a SQL hand coded query against any ORM among the ones available in .NET, hand coded query will be for sure faster. In our case we can explain why CodeFluent Entities generated code is taking more time in the multiple set fetch operation. Basically the code generated is doing some additional operations that we can get rid of in this particular scenario:

For instance in this LoadAll method we do not need to check if an element is already contained in the inner list so we should remove the check:


Another example is the ReadReacord method, in this case we do not need to test if the reader is null or not, neither the options and since the type are secure and primitive types we do not need to use the CodeFluent Persistence GetReader methods a simple reader.GetIn32 or reader.GetDate can be used depending on the type:


After making these changes we can run the benchmark again to see what changed!

Running the benchmark with the adapted code

Here are the new result after code adaptation:

Non-change tracking fetches, set fetches (10 runs), no caching:

  1. Handcoded materializer using DbDataReader: 214,63ms
  2. CodeFluent Entities 273,25ms
  3. PetaPoco Fast v4.0.3: 285,50ms
  4. Dapper: 306,25ms
  5. Linq to SQL v4: 318,50ms
  6. PetaPoco v4.0.3: 355,00ms
  7. Entity Framework v6: 362,13ms
  8. ServiceStack OrmList v4.0.9.0: 555,75ms
  9. LLBLGen Pro v4.1.0.0, typed view: 585,00ms
  10. Oak.DynamicDb using dynamic Dto class: 902,50ms

After these changes CodeFluent Entities is now ranked at the 2nd place just after the hand coded query!

I will now show you how to make these custom changes more generic to apply them to the entire project for instance.

Understanding CodeFluent Entities Aspects

In CodeFluent Entities, the code generation process is model-first and continuous: from your declarative model, a meta-model will be inferred which code generators will then translate into code.

AspectAspects introduce a new notion allowing you to plug into this process. Using aspects you’ll be able to work on this in-memory representation of the model, before anything is produced and dynamically add/remove/modify elements in your model: this is what we call dynamic modeling. In a nutshell, in CodeFluent Entities, dynamic modeling is materialized as aspects and it allows developers to inject extra-behaviors in models.

You can easily see what the inferred model contains by selecting the option “View Inferred Model” on your project:

View Inferred Model

Then you can get details about any method or property of your code, for instance in our case the LoadAll method of the SalesOrderHeader entity:

Inferred Model

This inferred model will be used by the Business Object Model Producer we configured before to generate our code.

When you build your project, the enabled producers are instantiated to work on your model. With CodeFluent Entities you can interact at moment of the code production. For example you can change on the fly the behavior of your CodeDom producer (aka Business Object Model Producer) by accessing its instance:

CodeDomProducer codeDomProducer = Project.Producers.GetProducerInstance<CodeDomProducer>();

codeDomProducer.CodeDomProduction += (sender, e) =>
    //write your code here ...

And then you can manipulate this codeDomProducer object to change the body of your methods or do any other change to the generated code. In our case this will be very helpful to change the body of the LoadAll and ReadRecord methods.

Making code adaptation using aspects

In fact the changes we made can be reproduced automatically among the code by using a custom aspect that will interact with the Business Object Model Producer on the fly.

You can download the FastReader.xml file that contains the aspect we developed to make our customizations generic.

To remind you here is what the LoadAll method looked like before using the aspect:

LoadAll Before

Here is the new version of the same function:

LoadAll After

Another example is the ReadRecord method; here is what it was like before using the aspect:

Read Record Before

After enabling the aspect the method is replaced by a new one with the name FastReadRecord:

Read Record After

CodeFluent Entities offers many ways to customize the code generation and aspects is only one way among the others. In fact code customization can also be done by using sub-producers or patch-producers. Each technic has its pros and cons and in our case aspects was the best way to reach our goal. If you want to read more about sub-producers or patch producers please visit our blog here and here.

I hope this article helped you to figure out the flexibility of CodeFluent Entities.

Feel free to download and use the FastReader.xml aspect if you need.
Moreover, the full source code is available on our GitHub Profile.

Happy Adapting!

The R&D team.

Define your own CodeFluent Entities Keyboard shortcuts

March 24, 2014 1 comment

Some of you ask us if we can create your own keyboard shortcuts with CodeFluent Entities. Yes, of course. You can assign a shortcut to add an entity or a property into your CodeFluent Entities surface thanks to Visual Studio Keyboard Commands. While we do not set default keyboard shortcuts, you can define your own:

  • Open the Visual Studio Options dialog (Tools / Options / Environment / Keyboard)
  • Select the desired command (search command containing CodeFluent)
  • Define the keyboard shortcut


Below is a list of the most common CodeFluent commands:

  • Add Entity: OtherContextMenus.CodeFluentSurface.Add.Entity
  • Add Property: OtherContextMenus.CodeFluentSurface.Add.Property
  • Add Rule: OtherContextMenus.CodeFluentSurface.Add.Rule
  • Add Instance: OtherContextMenus.CodeFluentSurface.Add.Instance
  • Model Search: OtherContextMenus.CodeFluentSurface.ModelSearch (my favorite!)
  • Arrange Surface: OtherContextMenus.CodeFluentSurface.Arrange.Surface

Happy shortcutting, The R&D Team

Multi-database deployment with PowerShell and the Pivot Script Runner – Part 2

March 6, 2014 Leave a comment

In Part 1 of this article, we looked at using the PowerShell strengths to automate the process of updating several databases through the PivotRunner tool.

Now, we want to go further and create a PowerShell command, better known as a Cmdlet.

Build the Cmdlet

A Cmdlet can be built directly in a Powershell script, or through the .NET Framework. We need to inherit from System.Management.Automation.Cmdlet and define its naming attributes therefor.

By agreement, the name of a Cmdlet consists of a verb, followed by a dash and a name (e.g: Get-ChildItem andAdd-PSSnapIn):

using System.Management.Automation;

namespace CodeFluentEntitiesCmdlet
    [Cmdlet(VerbsData.Update, "CFEDatabase", SupportsShouldProcess = true, 
            ConfirmImpact = ConfirmImpact.High)]
    public class UpdateCFEDatabase : Cmdlet

Here, the Cmdlet’s name will be Update-CFEDatabase.

Use the following PowerShell command: Copy ([PSObject].Assembly.Location) C:\MyDllPath to find the System.Management.Automation library

SupportsShouldProcess and ConfirmImpact attributes allow the Cmdlet to use the PowerShell Requesting Confirmation feature.

The Cmdlet abstract class includes a fairly advanced command parameters engine to define and manage parameters:

[Parameter(Mandatory = true)]
public string ConnectionString { get; set; }

[Parameter(Mandatory = true)]
public string PivotFilePath { get; set; }

The Mandatory term is used to warn the command parameters engine of whether or not a parameter is required.

Cmdlet also exposes some methods which can be overriden. These pipeline methods allow the cmdlet to perform pre-processing operations, input processing operations, and post-processing operations.

Here, we’ll just override the ProcessRecord method:

protected override void ProcessRecord()
  // Process logic code

Then, we need to use the PivotRunner which is located in the CodeFluent.Runtime.Database assembly.

The tool takes the connection string and the pivot script producer output file as parameters:

using CodeFluent.Runtime;
using CodeFluent.Runtime.Database.Management.SqlServer;

private void UpdateDatabase()
        PivotRunner runner = new PivotRunner(PivotFilePath);

        runner.ConnectionString = ConnectionString;

        if (!runner.Database.Exists)
            WriteObject("Error: The ConnectionString parameter does not lead to an existing database!");
    catch (Exception e)
        WriteObject("An exception has been thrown during the update process: " + e.Message);

Do not forget to reference CodeFluent.Runtime.dll and CodeFluent.Runtime.Database.dll!

Moreover, we can recover the PivotRunner output (internal logs) by providing an IServiceHost implementation:

public class CmdletLogger : IServiceHost
    private Cmdlet _cmdLet;

    public CmdletLogger(Cmdlet cmdlet)
        _cmdLet = cmdlet;

    public void Log(object value)

runner.Logger = new CmdletLogger(this);

Powershell integration

The Cmdlet is now finished! :)

Now we’ll see how to call it from Powershell! Here, we have several options, but we shall see the PSSnapIn one.

The “Writing a Windows PowerShell Snap-in” article shows that a PSSnapIn is mostly a descriptive object which inherits from System.Configuration.Install.Installer and is used to register all the cmdlets and providers in an assembly.

So, let’s implement our Powershell snap-in:

using System.ComponentModel;
using System.Management.Automation;

namespace CodeFluentEntitiesCmdlet
    public class CodeFluentEntitiesCmdletSnapin01 : PSSnapIn
        public CodeFluentEntitiesCmdletSnapin01()
            : base() { }

        public override string Name
            get { return ((object)this).GetType().Name; }

        public override string Vendor
            get { return "SoftFluent"; }

        public override string VendorResource
            get { return string.Format("{0},{1}", Name, Vendor); }

        public override string Description
            get { return "This is a PowerShell snap-in that includes the Update-CFEDatabase cmdlet."; }

        public override string DescriptionResource
            get { return string.Format("{0},{1}", Name, Description); }

Then, we build our solution which contains our Cmdlet and the PSSnapIn and finally register the built library thinks to the InstallUtil.exe (located in the installation folder of the .NET Framework):

Administrator rights are required.

Administrator rights are required.

By using the “Get-PSSnapIn –Registered” Powershell command, we can observe that our PSSnapIn is well registered. This component can now be used into your Powershell environment:


The “Add-PSSnapIn” command enables us to use our Cmdlet into the current session of Powershell.

As result, we can update our previously built Powershell script:

param([string[]]$Hosts, [string]$PivotFilePath, [switch]$Confirm = $true)

Add-PSSnapin CodeFluentEntitiesCmdletSnapin01

if ($Hosts -eq $null -or [string]::IsNullOrWhiteSpace($PivotFilePath))
    Write-Error "Syntax: .\UpdateDatabase.ps1 -Hosts Host1[, Host2, ...] -PivotFilePath PivotFilePath"

[System.Reflection.Assembly]::LoadWithPartialName('Microsoft.SqlServer.SMO') | out-null

Write-Host "-========- Script started -========-"

$Hosts | foreach {
    $srv = new-object ('Microsoft.SqlServer.Management.Smo.Server') $_

    $online_databases = $srv.Databases | where { $_.Status -eq 1 -and $_.Name.StartsWith("PivotTest_") }
    if ($online_databases.Count -eq 0)
        Write-Error "No database found"

    Write-Host "Database list:"
    $online_databases | foreach { Write-Host $_.Name }

    [string]$baseConnectionString = "$($srv.ConnectionContext.ConnectionString);database="
    $online_databases | foreach {
        Update-CFDatabase -ConnectionString "$($baseConnectionString)$($_.Name)" -PivotFilePath $PivotFilePath -Confirm:$Confirm

Write-Host "-========-  Script ended  -========-"

We can now simply deploy all changes we’ve recently made on our databases thanks to the Cmdlet and PivotRunner components.

The source code is available for download.

Happy PowerShelling !

The R&D team


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