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https://github.com/zaid-ajaj/fable.sqlclient
Fable Node client for Microsoft SQL Server, built around a node-mssql binding
https://github.com/zaid-ajaj/fable.sqlclient
database fable microsoft-sql-server node-mssql sqlclient
Last synced: about 1 month ago
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Fable Node client for Microsoft SQL Server, built around a node-mssql binding
- Host: GitHub
- URL: https://github.com/zaid-ajaj/fable.sqlclient
- Owner: Zaid-Ajaj
- License: mit
- Created: 2018-04-01T18:13:57.000Z (over 6 years ago)
- Default Branch: master
- Last Pushed: 2023-01-01T20:09:18.000Z (almost 2 years ago)
- Last Synced: 2024-10-12T07:22:37.038Z (about 1 month ago)
- Topics: database, fable, microsoft-sql-server, node-mssql, sqlclient
- Language: F#
- Size: 456 KB
- Stars: 13
- Watchers: 3
- Forks: 2
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# Fable.SqlClient [![Nuget](https://img.shields.io/nuget/v/Fable.SqlClient.svg?colorB=green)](https://www.nuget.org/packages/Fable.SqlClient) [![Build status](https://ci.appveyor.com/api/projects/status/n7665851i24yh2d7?svg=true)](https://ci.appveyor.com/project/Zaid-Ajaj/fable-sqlclient)
[Fable](https://github.com/fable-compiler/Fable) binding for [node-mssql](https://github.com/tediousjs/node-mssql), Microsoft SQL Server client library with an idiomatic and type-safe F# API to be used from Fable Node applications.
### Installation
Install the Fable binding from Nuget
```bash
# using nuget
dotnet add package Fable.SqlClient# or with paket
paket add Fable.SqlClient --project /path/to/project.fsproj
```
Install the actual node-mssql from Npm
```
npm install --save node-mssql
```
# Getting started
First of all, configure the connection using `SqlConfig`:
```fs
open Fable.SqlClientlet connectionConfig =
[ SqlConfig.User "admin"
SqlConfig.Password "str0ngPa$$word"
SqlConfig.Host "localhost"
SqlConfig.Database "AdventuresWorks"
SqlConfog.Port 1433 ]
```# `Sql.readRows` querying a tabular result set
```fs
open Fable.SqlClient
open Fable.SqlClient.OptionWorkflowtype User = { Id: int; Name: string }
let getUsers() : Async> =
async {
let! usersResult =
connectionConfig
|> Sql.connect
|> Sql.query "SELECT id, name from [dbo].[Users]"
|> Sql.readRows (fun row ->
option {
let! id = Sql.readInt "id" row
let! name = Sql.readString "name" row
return { Id = id; Name = name; }
})match usersResult with
| Ok users -> return Some users
| Error sqlError -> return None
}
```
Here `Sql.readRows` takes a transformer function that maps every row into an `Option<'t>`. Because we are using the `option` workflow, the mapping is done safely and if either `id` or `name` is null, then the row is skipped.If you want to handle the null values manually, then simply use `let` instead of `let!` in combination with `defaultArg`. For example, if you want to use an empty string as a default for the `name` column, then you simply write the following:
```fs
async {
let! usersResult =
connectionConfig
|> Sql.connect
|> Sql.query "SELECT id, name from [dbo].[Users]"
|> Sql.readRows (fun row ->
option {
let! id = Sql.readInt "id" row
// notice: no ! in the let binding
let name = Sql.readString "name" row
let nameOrEmpty = defaultArg name ""
return { Id = id; Name = nameOrEmpty; }
})match usersResult with
| Ok users -> return Some users
| Error sqlError -> return None
}
```
# `Sql.readRows` from a parameterized query
Queries can be parameterized with named parameters to avoid SQL injections:
```fs
open Fable.SqlClient
open Fable.SqlClient.OptionWorkflowlet userByUsername (username: string) : Async =
async {
let! results =
connectionConfig
|> Sql.connect
|> Sql.query "SELECT TOP 1 id, name from [dbo].[Users] where name = @name"
|> Sql.parameters [ SqlParam.From ("@name", username) ]
|> Sql.readRows (fun row ->
option {
let! id = Sql.readInt "id" row
let! name = Sql.readString "name" row
return { Id = id; Name = name }
})match results with
| Ok (user :: _) -> return Some user
| _ -> return None
}
```
# `Sql.readScalar` querying a scalar value
```fs
open Fable.SqlClientlet pingDatabase() : Async =
async {
let! serverTime =
connectionConfig
|> Sql.connect
|> Sql.query "SELECT GETDATE()"
|> Sql.readScalarmatch serverTime with
| Ok (SqlValue.Date time) -> return Some time
| _ -> return None
}
```
# `Sql.storedProcedure`
executing a stored procedure with parameters
```fs
let userExists (name: string) : Async =
async {
let! exists =
connectionConfig
|> Sql.connect
|> Sql.storedProcedure "user_exists"
|> Sql.parameters [ SqlParam.From("@name", name) ]
|> Sql.readScalarmatch exists with
| Ok (SqlValue.Bool value) -> return value
| _ -> return false
}
```
# `Sql.readAffectedRows`
Returns the number of rows affected. For example when you execute a `DELETE`, `INSERT` or `UPDATE` statements, the rows affected will the ones that were deleted, inserted or updated. If you read the rows affected by a `SELECT` statements, the row count is returned.
```fs
/// delete events older than 2 months
let deleteOldEvents() : Async> =
async {
let! eventsDeleted =
connectionConfig
|> Sql.connect
|> Sql.query "DELETE FROM [dbo].[Events] WHERE DateAdded < @TwoMonthsAgo"
|> Sql.parameters [ SqlParam.From("@TwoMonthsAgo", DateTime.Now.AddMonths(-2)) ]
|> Sql.readAffectedRowsmatch eventsDeleted with
| Ok count -> return Ok count
| Error error ->
// Extract info from the SqlError
let (errType, errMsg, errStack) = error.Info()
return Error errMsg
}
```
# `Sql.readJson`
Since Microsoft SQL Server supports JSON natively, you can query the database and have it return the result set as a single JSON string. `Sql.readJson` is a utility function that extracts the JSON from the scalar value. You can then parse the resulting serialized JSON using your favorite Json library:
```fs
async {
let! json =
connectionConfig
|> Sql.connect
|> Sql.query "SELECT id, name FROM (VALUES(42, N'Fable')) as TableName(id, name) FOR JSON PATH"
|> Sql.readJson
match json with
| Ok serialized =
let values = Json.parseAs<{| id: int; name: string |} array> serialized
let value = values.[0]
printfn "Id = %d and Name = %s" value.id value.name
| Error error ->
printfn "Something went wrong..."
}
```
# API definitions
```fs
val Sql.readRows : ((string * SqlValue) list -> Option<'t>) -> (props: ISqlProps) -> Async>val Sql.readAffectedRows (props: ISqlProps) -> Async>
val Sql.readJson (props: ISqlProps) -> Async>
val Sql.readScalar (props: ISqlProps) -> Async>
```
where the important types are defined as follows. The types within `SqlValue` are those that you can read from Sql Server.
```fs
type SqlValue =
| TinyInt of uint8
| SmallInt of int16
| Int of int
| Bool of bool
| Date of DateTime
| UniqueIdentifier of Guid
| BigInt of int64
| Decimal of decimal
| String of string
| Number of float
| Binary of byte[]
| Null
type SqlError =
| ConnectionError of message: string * stack: string
| TransactionError of message: string * stack: string
| RequestError of message: string * stack: string
| ApplicationError of message: string * stack: string
| GenericError of errorType: string * message: string * stack: string
```
the type `ISqlProps` is just a helper type that accumulate the configuration for a query using a fluent syntax
# Development and Testing
The test project is in the `test` directory and includes *integration* tests. To run these tests on your local machine, you will need to setup a couple of environment variables:
- `SQLCLIENT_DATABASE`: the name of the database to run the tests against. The tests don't require a specific database, you can just use `master`.
- `SQLCLIENT_SERVER`: the IP address of the hosting machine, if you have a local MSSQL server, then `local/{instance}` will do
- `SQLCLIENT_USER`: the username to log in with
- `SQLCLIENT_PASSWORD`: the password of the userAfter you have set up these variables, you can run the commands:
```bash
npm install
npm test
```
This will compile the test the project and runs tests using `Mocha`.# Known issues
Reading `DateTimeOffset` directly is not supported. It has to be converted to `nvarchar` first and parsed from `SqlValue.String value`. However, a `DateTimeOffset` value can still be used as a parameter value directly. The following test demonstrates what's supported:
```fs
testCaseAsync "DateTimeOffset round trip works" <| fun () ->
async {
let input = DateTimeOffset.UtcNow
let! value =
defaultConfig
|> Sql.connect
// convert the value to nvarchar
|> Sql.query "SELECT CONVERT(nvarchar(100), @DateTimeOffset) as [Value]"
|> Sql.parameters [ SqlParam.From("@DateTimeOffset", input) ]
|> Sql.readScalarmatch value with
// parse the value here
| Ok (SqlValue.String serialized) ->
let deserialized = DateTimeOffset.Parse serialized
areEqual input deserialized
| otherwise -> return! failwithf "Unexpected results:\n%s" (Json.stringify otherwise)
}
```