SQLiteORM for Swift

SQLiteORM-Swift is an ORM library for SQLite3 built with Swift 5

Advantages

No raw string queries
Intuitive syntax
Comfortable interface - one call per single query
CRUD support
Aggregate functions support
Does not depend on Codable protocol
The only dependency - SQLite3
In memory database support - provide :memory: or empty filename
Transactions support
Migrations functionality
LIMIT support

SQLiteORM library allows to create easy data model mappings to your database schema. It is built to manage (CRUD) objects with a primary key and without it. It also allows you to specify table names and column names explicitly no matter how your classes actually named. And it does not depend on Codable protocol. Take a look at example:

import SQLiteORM

struct User : Initializable {
    var id = 0
    var firstName = ""
    var lastName = ""
    var birthDate = ""
    var imageUrl: String?
    var typeId = 0
}

struct UserType : Initializable {
    var id = 0
    var name = ""
}

So we have database with predefined schema like

CREATE TABLE users (
    id INTEGER PRIMARY KEY NOT NULL, 
    first_name TEXT NOT NULL, 
    last_name TEXT NOT NULL, 
    birth_date INTEGER NOT NULL, 
    image_url TEXT, 
    type_id INTEGER NOT NULL)
    
CREATE TABLE user_types (
    id INTEGER PRIMARY KEY NOT NULL, 
    name TEXT NOT NULL)

Now we tell SQLiteORM library about our schema and provide database filename. We create storage helper object that has CRUD interface. Also we create every table and every column. All code is intuitive and minimalistic.

let path = getDocumentsDirectory() + "/db.sqlite"
do {
    let storage = try Storage(filename: path,
                              tables:
                                Table<User>(name: "users",
                                            columns:
                                               Column(name: "id", keyPath: \User.id, constraints: primaryKey(), notNull()),
                                               Column(name: "first_name", keyPath: \User.firstName, constraints: notNull()),
                                               Column(name: "last_name", keyPath: \User.lastName, constraints: notNull()),
                                               Column(name: "birth_date", keyPath: \User.birthDate, constraints: notNull()),
                                               Column(name: "image_url", keyPath: \User.imageUrl),
                                               Column(name: "type_id", keyPath: \User.typeId, constraints: notNull())),
                                Table<UserType>(name: "user_types",
                                                columns:
                                                    Column(name: "id", keyPath: \UserType.id, constraints: primaryKey(), notNull()),
                                                    Column(name: "name", keyPath: \UserType.name, constraints: notNull())))
}catch{
    print("error happened \(error)")
}

Too easy isn't it? To create a column you have to pass two arguments at least: its name in the table and your mapped class keypath. You can also add extra arguments to tell your storage about column's constraints like primaryKey(), notNull(), unique().

CRUD

Let's create and insert new User into our database. First we need to create a User object with any id and call insert function. It will return id of just created user or throw exception if something goes wrong. If you want to insert a user with id you specified then you need to use replace function instead of insert.

var user = User(id: 0, firstName: "John", lastName: "Doe", birthDate: 664416000, imageUrl: "url_to_heaven", typeId: 3)
let insertedId = try storage.insert(object: user)
print("insertedId = \(insertedId)")
user.id = Int(insertedId)

let secondUser = User(id: 2, firstName: "Alice", lastName: "Inwonder", birthDate: 831168000, imageUrl: nil, typeId: 2)
try storage.replace(object: secondUser) //  insert with 'id' 2

Next let's get our user by id.

if let user1: User = try storage.get(id: 1) {
    print("user = \(user1.firstName) \(user1.lastName)")
} else {
    print("user with id 1 does not exist")
}

We can also update our user. Storage updates row by id provided in user object and sets all other non primary_key fields to values stored in the passed user object. So you can just assign fields to user object you want and call update:

user.firstName = "Nicholas"
user.imageUrl = "https://cdn1.iconfinder.com/data/icons/man-icon-set/100/man_icon-21-512.png"
try storage.update(object: user)

And delete. To delete you have to pass a whole object.

try storage.delete(object: user)

Also we can extract all objects into Array:

let allUsers: [User] = try storage.getAll()
print("allUsers (\(allUsers.count):")
for user in allUsers {
    print(user)
}

Aggregate functions

//  SELECT AVG(id) FROM users
let averageId = try storage.avg(\User.id)

//  SELECT AVG(birth_date) FROM users
let averageBirthDate = try storage.avg(\User.birthDate)

//  SELECT COUNT(*) FROM users
let usersCount = try storage.count(all: User.self)

//  SELECT COUNT(id) FROM users
let countId = try storage.count(\User.id)

//  SELECT COUNT(image_url) FROM users
let countImageUrl = try storage.count(\User.imageUrl)

//  SELECT GROUP_CONCAT(id) FROM users
let concatedUserId = try storage.groupConcat(\User.id)

//  SELECT GROUP_CONCAT(id, '---') FROM users
let concatedUserIdWithDashes = try storage.groupConcat(\User.id, separator: "---")

//  SELECT MAX(id) FROM users
if let maxId = try storage.max(\User.id) {
    print("maxId = \(maxId)")
} else {
    print("maxId is nil")
}

//  SELECT MIN(id) FROM users
if let minId = try storage.min(\User.id) {
    print("minId = \(minId)")
} else {
    print("maxId is nil")
}

//  SELECT SUM(id) FROM users
if let sumId = try storage.sum(\User.id) {
    print("sumId = \(sumId)")
} else {
    print("sumId is nil")
}

//  SELECT TOTAL(id) FROM users
let totalId = try storage.total(\User.id)

Where conditions

You also can select objects with custom where conditions with ==, !=, >, >=, <, <=.

For example: let's select users with id lesser than 10:

//  SELECT * FROM users WHERE id < 10
let idLesserThan10: [User] = try storage.getAll(where_(\User.id < 10))
print("idLesserThan10 count = \(idLesserThan10.count)")
for user in idLesserThan10 {
    print("\(user)")
}

Or select all users who's first name is not equal "John":

//  SELECT * FROM users WHERE first_name != 'John'
let notJohn: [User] = try storage.getAll(where_(\User.firstName != "John"))
print("notJohn count = \(notJohn.count)")
for user in idLesserThan10 {
    print("\(user)")
}

Migrations functionality

There are no explicit up and down functions that are used to be used in migrations. Instead SQLiteORM offers syncSchema function that takes responsibility of comparing actual db file schema with one you specified in Storage init call and if something is not equal it alters or drops/creates schema.

try storage.syncSchema(preserve: true)

Please beware that syncSchema doesn't guarantee that data will be saved. It tries to save it only. Below you can see rules list that syncSchema follows during call:

if there are excess tables exist in db they are ignored (not dropped)
every table from storage is compared with it's db analog and
- if table doesn't exist it is created
- if table exists its colums are being compared with table_info from db and
  - if there are columns in db that do not exist in storage (excess) table will be dropped and recreated if preserve is false, and table will be copied into temporary table without excess columns, source table will be dropped, copied table will be renamed to source table (sqlite remove column technique) if preserve is true. Beware that setting it to true may take time for copying table rows.
  - if there are columns in storage that do not exist in db they will be added using 'ALTER TABLE ... ADD COLUMN ...' command and table data will not be dropped but if any of added columns is null but has not default value table will be dropped and recreated
  - if there is any column existing in both db and storage but differs by any of properties (pk, notnull) table will be dropped and recreated (dflt_value isn't checked cause there can be ambiguity in default values, please beware).

The best practice is to call this function right after storage creation.

Notes

To work well your data model class must inherit from Initializable which required only init() with no arguments existance and must not have const fields mapped to database cause they are assigned during queries. Otherwise code won't compile.