SQL Type Provider and Continuous Integration with FAKE

When we refactor code how can we be confident that we don't break anything?

3 of the most important things that allow us to refactor fearlessly are:

Side effect free - or pure - expressions
Statically typed expressions
Tests

In this article we will solely focus on the aspect of side effects and strictly speaking on how to identify them. Being able to identify side effects in our programs clearly is the precondition for eliminating them.

Why avoid side effects?

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Have you ever wanted to try out PureScript but were lacking a good way to get started?

If you

Have some prior functional programming knowledge - maybe you know Haskell,Elm,F#,or Scala,etc.
Want to solve a small task with PureScript
And want to get started quickly

This post is for you!

In this post we will walk through setting up and implementing a small exemplary PureScript application from scratch.

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In this article I would like to present a minimal implementation of a music data type and everything that is needed to turn that into audible sound from an Elm application.

We will see how to transcribe an existing composition - an excerpt from Chick Corea's Children's Songs No. 6 - and listen to the result right here,embedded in this article.

From a music data type to performance

My colleague Jonas recently pointed out the presentation Making Algorithmic Music by Donya Quick to me. Donya Quick shows how she uses the Haskell library Euterpea to produce algorithmic music.

It got me really excited about the idea of porting this to Elm and to be able to use this in web applications.

In the following we will see the core data types and algorithms from Euterpea ported to Elm. To focus on the core concepts the implementation is stripped down to the minimum that is required to transcribe and perform an existing polyphonic piece of music (for a single instrument).

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This post is about how to implement well structured,and purely functional command line applications in Scala using PureApp.

PureApp originated in an experiment while refactoring out some glue code of an interactive command line application. At the same time it was inspired by the Elm Architecture Pattern,and scalaz's SafeApp,as well as scalm.

To show the really cool things we can do with PureApp,we will implement a self-contained example application from scratch.

This application translates texts from and into different languages. And it provides basic user interactions via the command line.

The complete source code is compiled with tut. Every output (displayed as code comments) is generated by tut.
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In this post we will see how applicatives can be used for validation in Scala. It is an elegant approach. Especially when compared to an object-oriented way.

Usually when we have operations that can fail,we have them return types like Option or Try. We sequence operations and once there is an error the computation is short circuited and the result is a None or a Failure.

Applicatives allow us to compose independent operations and evaluate each one. Even if an intermediate evaluation fails. This allows us to collect error messages instead of returning only the first error that occurred.

A classic example where this is useful is the validation of user input. We would like to return a list of all invalid inputs rather than aborting the evaluation after the first error.

Scala Cats provides a type that does exactly that. So let's dive into some code and see how it works.

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After some initial struggles,the chapter Functional Parsers from the great book Programming in Haskell by Graham Hutton,where a basic parser library is built from scratch,significantly helped me to finally understand the core ideas of parser combinators and how to apply them to other programming languages other than Haskell as well.

While I recently revisited the material and started to port the examples to Scala I wasn't able to define a proper monad instance for the type Parser[A].

The type Parser[A] alias was defined like this:

type Parser[A] = String =>Option[(A,String)] // defined type alias Parser

To test the monad laws with discipline I had to provide an instance of Eq[Parser[A]]. Because Parser[A] is a function,equality could only be approximated by showing degrees of function equivalence,which is not a trivial task.

Also the implementation of tailRecM was challenging. (I couldn't figure it out.)

Using existing abstractions

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Most config libraries use a stringly typed approach.

Some handle runtime failures due to invalid configuration schemas by leveraging data types like Option or Result to represent missing values or errors. This allows us to handle these failures by either providing default values or by providing decent error messages.

This is a good strategy that we should definitely stick to.

However,the problem with default values is that we might not even notice if the configuration is broken. This could potentially fail in production. In any case an error e.g. due to a misspelled config property will be observable at runtime at the earliest.

Wouldn't it be a great user experience (for us developers) if the compiler told us if the configuration schema is invalid? Even better,imagine we could access the configuration data in a strongly typed way like any other data structure,and with autocompletion.

Moreover,what if we didn't have to write any glue code,not even when the configuration schema changes?

This can be done with the costs of an initial setup that won't take more than probably around 5 minutes.

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In this post I will look at a practical example where the combined application (through monad transformers) of the state monad and the either monad can be very useful.

I won't go into much theory,but instead demonstrate the problem and then slowly build it up to resolve it.

You don't have to be completely familiar with all the concepts as the examples will be easy to follow. Here is a very brief overview:

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If your API overflows with Boolean parameters,this is usually a bad smell.

Consider the following function call for example:

toContactInfoList(csv,true,true)

When looking at this snippet of code it is not very clear what kind of effect the two Boolean parameters will have exactly. In fact,we would probably be without a clue.

We have to inspect the documentation or at least the parameter names of the function declaration to get a better idea. But still,this doesn't solve all of our problems.

The more Boolean parameters there are,the easier it will be for the caller to mix them up. We have to be very careful.

Moreover,functions with Boolean parameters must have conditional logic like if or case statements inside. With a growing number of conditional statements,the number of possible execution paths will grow exponentially. It will become more difficult to reason about the implementation code.

Can we do better?

Sure we can. Lambdas and combinators come to the rescue and I'm going to show this with a simple example,a refactoring of the function from above.

This post is based on a great article by John A De Goes,Destroy All Ifs — A Perspective from Functional Programming.

I'm going to take John's ideas that he backed up with PureScript examples and present how the same thing can be elegantly achieved in Scala.

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I'm currently working on an sbt plugin that generates Scala case classes at compile time to model JSON API responses for easy deserialization especially with the Scala play-json library.

The plugin makes it possible to access JSON documents in a statically typed way including auto-completion. It takes a sample JSON document as input (either from a file or a URL) and generates Scala types that can be used to read data with the same structure.

Let's look at a basic example,an app that prints the current Bitcoin price to the console.

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If you want to access a relational database from an F# (or C#) application, SQL F# type providers are commonly used. SQL type providers will provide all the types, properties and methods needed to access and interact with the tables of a SQL database, without having to write any extra boilerplate code. Everything is type checked and if the actual database schema gets out of synch with the database related code, compilation will fail. This is very valuable because it gives you high confidence in the application's data access code.

So at compile time the database has to be up to date and accessible. But how does this work in a continuous integration environment? Off course an option is to have the connection string of the type provider point to a development database on the network. Another solution would be to manually create or update a database on the build server before the build. But I don't really like this because I think the build server should be independent and self-sufficient. A solution to this scenario, that worked for me, is to deploy the database during the build process using Visual Studio database projects and FAKE - F# Make.

There might be other and maybe better solutions that I haven't come up with. I'd be curious to find out. Actually this might be one. The approach that I used, however, works out nicely, so I will give a quick walkthrough on how to set things up.

Prerequisites

SQL Server Express or SQL Server and SQL Server Data Tools for Visual Studio should be installed locally and on the build server.

Creating the Visual Studio Database Project

These are the steps to create and configure a very basic database project in Visual Studio.

Project and schema

In Visual Studio Create a blank Solution TestSolution.
Add a database project and name it TestDb.
To TestDb add a new table named Table1 and replace the Table1.sql file contents with:

CREATE TABLE [dbo].[Table1]
(
    [Id] INT NOT NULL PRIMARY KEY,
    [Name] NVARCHAR(MAX) NOT NULL
)

Configuring the project

In the properties of the project check the "Create Script (.sql file)" check box under project settings.
As the target platform you might have to select "SQL Server 2012" depending on your SQL Server version.

Creating an F# project for the data access

Here are the steps to create an F# library for data access using the SqlDataConnection type provider.

First add a new F# library project to the solution and add references to FSharp.Data.TypeProviders, as well as System.Data, and System.Data.Linq as also described here.

Then add a new file to the project, named DataAcces.fs, with this content:

namespace Data

module DataAccess =

    open System
    open System.Data
    open System.Data.Linq
    open Microsoft.FSharp.Data.TypeProviders
    open Microsoft.FSharp.Linq

    [<Literal>]
    let ConnectionString = "Data Source=(localdb)\V11.0;Initial Catalog=TestDb;Integrated Security=SSPI;"
    type private DbSchema = SqlDataConnection<ConnectionString>

    let private db (connectionString:string) = DbSchema.GetDataContext(connectionString)

    let getNameById connectionstring id =
        let db = db ConnectionString
        let opt = db.Table1 |> Seq.tryFind (fun x -> x.Id = id)
        opt |> Option.map (fun x -> x.Name)

The solution won't compile at this point because the external source of the type provider (the database) doesn't exist yet.

Building the project with FAKE

Now we are going to configure the build process using FAKE - F# Make.

Enable the "Enable NuGet Package Restore" option on the solution.
In the solution's root directory add a new file named build.bat.
Add the following content to build.bat:

@echo off
cls
".nuget\NuGet.exe" "Install" "FAKE" "-OutputDirectory" "packages" "-ExcludeVersion"
"packages\FAKE\tools\Fake.exe" build.fsx
exit /b %errorlevel%

Next add a new Item of type "F# script File" to the solution named build.fsx, and add the following code to build.fsx:

// include Fake lib
#r @"packages/FAKE/tools/FakeLib.dll"
open Fake

// Default target
Target "Default" (fun _ ->
    trace "Hello World from FAKE"
)

// start build
RunTargetOrDefault "Default"

Run build.bat from the Windows Command Prompt or from PowerShell. The build script will not do much so far but it should successfully terminate.

Adding a target to build the database project

Change the content of the build.fsx to this:

// include Fake lib
#r @"packages/FAKE/tools/FakeLib.dll"
open Fake

RestorePackages()

// Properties
let buildDir = "./build/"

// SQL database project references
let sqlDbProjRef = 
  !! "./**/*.sqlproj"

// Targets
Target "Clean" (fun _ ->
    CleanDirs [buildDir]
)

Target "BuildSqlProj" (fun _ ->
    sqlDbProjRef
      |> MSBuildRelease buildDir "Build"
      |> Log "Database-Build-Output: "
)

// Dependencies
"Clean"
  ==> "BuildSqlProj"

// start build
RunTargetOrDefault "BuildSqlProj"

Run build.bat.

Now the database project should be build and a create script TestDb_Create.sql should be generated inside the build directory.

Adding a target to run the create script

FAKE does support SQL Server related tasks with the Fake.SQL.dll. But unfortunately the create script that is generated by the database project will contain SQLCMD commands. And when running the scripts with FAKE it seems that they can't be run in SQLCMD Mode.

One way to run the script is to use the Fake process Helper to start SQLCMD.EXE.

To do this we first have to add a reference to System and System.IO in the build.fsx file.

Then we will define some properties:

// SQL Properties
let server = "\"(localdb)\\v11.0\""
let scriptPath = buildDir </> "TestDb_Create.sql"
let sqlcmdOutputPath = buildDir </> "TestDb_Create.out"

Now we define a function that will start SQLCMD.EXE with the needed parameters and a target that calls this function. To pipe the output back into FAKE, the output file contents will be read and logged with log (File.ReadAllText(output)).

let runSqlcmd server input output = 
    let result = ExecProcess (fun info -> 
        info.FileName <- "SQLCMD.EXE"
        info.Arguments <- "-S " + server + " -i " + input + " -o " + output) (TimeSpan.FromMinutes 5.0)

    if result <> 0 then failwithf "SQLCMD.EXE returned with a non-zero exit code"

    log (File.ReadAllText(output))

Target "RunCreateScript" (fun _ ->
    runSqlcmd server scriptPath sqlcmdOutputPath
)

Next we have to updated the build target dependencies:

// Dependencies
"Clean"
  ==> "BuildSqlProj"
  ==> "RunCreateScript"

// start build
RunTargetOrDefault "RunCreateScript"

If build.bat is executed the Database should be created now.

Building the application

Add a property appReferences to specify the file sets of the application:

let appReferences  = 
    !! "./**/*.fsproj"

Add a target which compiles the application:

Target "BuildApp" (fun _ ->
    appReferences
      |> MSBuildRelease buildDir "Build"
      |> Log "Build-Output: "
)

Update the dependencies:

// Dependencies
"Clean"
  ==> "BuildSqlProj"
  ==> "RunCreateScript"
  ==> "BuildApp"

// start build
RunTargetOrDefault "BuildApp"

Now the application should be successfully built.

Testing the application

To test the application we will simply insert a data set into the database using e.g. SQL Management Studio or Visual Studio:

INSERT INTO Table1 VALUES (1, 'hello world')

Now we can test the DataAccess.dll with a script like this:

#r @"../../build/DataAccess.dll"

open Data.DataAccess

let getNameById = getNameById @"Data Source=(localdb)\V11.0;Initial Catalog=TestDb;Integrated Security=SSPI;"

let name = getNameById 1

The output should be:

Some "hello world"

Source code

The code from this post can be found here on GitHub.

Leif Battermann

Functional Programming Fu

Identify Side Effects And Refactor Fearlessly

Why avoid side effects?

PureScript Case Study And Guide For Newcomers

Elm And The Algorithm Of Music

From a music data type to performance

Interactive Command Line Applications In Scala –Well Structured And Purely Functional

How To Use Applicatives For Validation In Scala And Save Much Work

Parsers in Scala built upon existing abstractions

Using existing abstractions

Strongly Typed Configuration Access With Code Generation

Error and state handling with monad transformers in Scala

Use lambdas and combinators to improve your API

Modelling API Responses With sbt-json –Print Current Bitcoin Price

Leif Battermann

Functional Programming Fu

SQL Type Providers and Continuous Integration with FAKE

Prerequisites

Creating the Visual Studio Database Project

Project and schema

Configuring the project

Creating an F# project for the data access

Building the project with FAKE

Adding a target to build the database project

Adding a target to run the create script

Building the application

Testing the application

Source code