Discover vapor/sql-kit Open Source project by Vapor (@vapor)

Build SQL queries in Swift. Extensible, protocol-based design that supports DQL, DML, and DDL.

Using SQLKit

Use standard SwiftPM syntax to include SQLKit as a dependency in your Package.swift file.

.package(url: "https://github.com/vapor/sql-kit.git", from: "3.0.0")

SQLKit 3.x requires SwiftNIO 2.x or later. Previous major versions are no longer supported.

Supported Platforms

SQLKit supports the following platforms:

Ubuntu 20.04+
macOS 10.15+
iOS 13+
tvOS 13+ and watchOS 7+ (experimental)

SQLKit is an API for building and serializing SQL queries in Swift. SQLKit attempts to abstract away SQL dialect inconsistencies where possible allowing you to write queries that can run on multiple database flavors. Where abstraction is not possible, SQLKit provides powerful APIs for custom or dynamic behavior.

Supported Databases

These database packages are drivers for SQLKit:

vapor/postgres-kit: PostgreSQL
vapor/mysql-kit: MySQL and MariaDB
vapor/sqlite-kit: SQLite

Configuration

SQLKit does not deal with creating or managing database connections itself. This package is focused entirely around building and serializing SQL queries. To connect to your SQL database, refer to your specific database package's documentation. Once you are connected to your database and have an instance of SQLDatabase, you are ready to continue.

Database

Instances of SQLDatabase are capable of serializing and executing SQLExpression.

let db: any SQLDatabase = ...
db.execute(sql: any SQLExpression, onRow: (any SQLRow) -> ())

SQLExpression is a protocol that represents a SQL query string and optional bind values. It can represent an entire SQL query or just a fragment.

SQLKit provides SQLExpressions for common queries like SELECT, UPDATE, INSERT, DELETE, CREATE TABLE, and many more.

var select = SQLSelect()
select.columns = [...]
select.tables = [...]
select.predicate = ...

SQLDatabase can be used to create fluent query builders for most of these query types.

struct Planet: Codable { var id: Int, name: String }

let db: some SQLDatabase = ...
try await db.create(table: "planets")
    .column("id", type: .int, .primaryKey(autoIncrement: true), .notNull)
    .column("name", type: .string, .notNull)
    .run()
try await db.insert(into: "planets")
    .columns("id", "name")
    .values(SQLLiteral.default, SQLBind("Earth"))
    .values(SQLLiteral.default, SQLBind("Mars"))
    .run()
let planets = try await db.select()
    .columns("id", "name")
    .from("planets")
    .all(decoding: Planet.self)
print(planets) // [Planet(id: 1, name: "Earth"), Planet(id: 2, name: "Mars")]

You can execute a query builder by calling run().

Rows

For query builders that support returning results (e.g. any builder conforming to the SQLQueryFetcher protocol), there are additional methods for handling the database output:

all(): Returns an array of rows.
first(): Returns an optional row.
run(_:): Accepts a closure that handles rows as they are returned.

Each of these methods returns SQLRow, which has methods for access column values.

let row: any SQLRow
let name = try row.decode(column: "name", as: String.self)
print(name) // String

Codable

SQLRow also supports decoding Codable models directly from a row.

struct Planet: Codable {
    var name: String
}

let planet = try row.decode(model: Planet.self)

Query builders that support returning results have convenience methods for automatically decoding models.

let planets: [Planet] = try await db.select()
    ...
    .all(decoding: Planet.self)

Select

The SQLDatabase.select() method creates a SELECT query builder:

let planets: [any SQLRow] = try await db.select()
    .columns("id", "name")
    .from("planets")
    .where("name", .equal, "Earth")
    .all()

This code generates the following SQL when used with the PostgresKit driver:

SELECT "id", "name" FROM "planets" WHERE "name" = $1 -- bindings: ["Earth"]

Notice that Encodable values are automatically bound as parameters instead of being serialized directly to the query.

The select builder includes the following methods (typically with several variations):

columns() (specify a list of columns and/or expressions to return)
from() (specify a table to select from)
join() (specify additional tables and how to relate them to others)
where() and orWhere() (specify conditions that narrow down the possible results)
limit() and offset() (specify a limited and/or offsetted range of results to return)
orderBy() (specify how to sort results before returning them)
groupBy() (specify columns and/or expressions for aggregating results)
having() and orHaving() (specify secondary conditions to apply to the results after aggregation)
distinct() (specify coalescing of duplicate results)
for() and lockingClause() (specify locking behavior for rows that appear in results)

Conditional expressions provided to where() or having() are joined with AND. Corresponding orWhere() and orHaving() methods join conditions with OR instead.

builder.where("name", .equal, "Earth").orWhere("name", .equal, "Mars")

This code generates the following SQL when used with the MySQL driver:

WHERE `name` = ? OR `name` = ? -- bindings: ["Earth", "Mars"]

where(), orWhere(), having(), and orHaving() also support creating grouped clauses:

builder.where("name", .notEqual, SQLLiteral.null).where {
    $0.where("name", .equal, SQLBind("Milky Way"))
      .orWhere("name", .equal, SQLBind("Andromeda"))
}

This code generates the following SQL when used with the SQLite driver:

WHERE "name" <> NULL AND ("name" = ?1 OR "name" = ?2) -- bindings: ["Milky Way", "Andromeda"]

Insert

The insert(into:) method creates an INSERT query builder:

try await db.insert(into: "galaxies")
    .columns("id", "name")
    .values(SQLLiteral.default, SQLBind("Milky Way"))
    .values(SQLLiteral.default, SQLBind("Andromeda"))
    .run()

This code generates the following SQL when used with the PostgreSQL driver:

INSERT INTO "galaxies" ("id", "name") VALUES (DEFAULT, $1), (DEFAULT, $2) -- bindings: ["Milky Way", "Andromeda"]

The insert builder also has a method for encoding a Codable type as a set of values:

struct Galaxy: Codable {
    var name: String
}

try builder.model(Galaxy(name: "Milky Way"))

This code generates the same SQL as would builder.columns("name").values("Milky Way").

Update

The update(_:) method creates an UPDATE query builder:

try await db.update("planets")
    .set("name", to: "Jupiter")
    .where("name", .equal, "Jupiter")
    .run()

This code generates the following SQL when used with the MySQL driver:

UPDATE `planets` SET `name` = ? WHERE `name` = ? -- bindings: ["Jupiter", "Jupiter"]

The update builder supports the same where() and orWhere() methods as the select builder, via the SQLPredicateBuilder protocol.

Delete

The delete(from:) method creates a DELETE query builder:

try await db.delete(from: "planets")
    .where("name", .equal, "Jupiter")
    .run()

This code generates the following SQL when used with the SQLite driver:

DELETE FROM "planets" WHERE "name" = ?1 -- bindings: ["Jupiter"]

The delete builder is also an SQLPredicateBuilder.

Raw

The raw(_:) method allows passing custom SQL query strings, with support for parameterized bindings and correctly-quoted identifiers:

let planets = try await db.raw("SELECT \(SQLLiteral.all) FROM \(ident: table) WHERE \(ident: name) = \(bind: "planet")")
    .all()

This code generates the following SQL when used with the PostgreSQL driver:

SELECT * FROM "planets" WHERE "name" = $1 -- bindings: ["planet"]

The \(bind:) interpolation should be used for any user input to avoid SQL injection. The \(ident:) interpolation is used to safely specify identifiers such as table and column names.

⚠️ Important!⚠️

Always prefer a structured query (i.e. one for which a builder or expression type exists) over raw queries. Consider writing your own SQLExpressions, and even your own SQLQueryBuilders, rather than using raw queries, and don't hesitate to open an issue to ask for additional feature support.

vapor/sql-kit

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