Models

In DBFlow we dont have any restrictions on what your table class is. We do, however if you use Java, we recommend you subclass BaseModel on your highest-order base-class, which provides a default implementation for you.

When using regular models:

FlowManager.getModelAdapter(MyTable.class).save(myTableObject);

When using BaseModel, it is much cleaner:

myTableObject.save();

if you use Kotlin, you can add the kotlin extensions to your project use them as extension methods:

myTableObject.save()

Columns

By default, DBFlow lazily looks for columns. This means that they all must contain either @PrimaryKey, @Column, or @ForeignKey to be used in tables.

If you wish to make it simpler and include all fields in a class, set @Table(allFields = true). However this still requires you to specify at least one @PrimaryKey field. You can then explicitly ignore fields via the @ColumnIgnore annotation.

Columns can be public, package-private, or private. private fields must come with public java-bean-style getters and setters.

Here is an example of a "nice" private field:

@Table(database = AppDatabase.class)
public class Dog {

  @PrimaryKey
  private String name;

  public void setName(String name) {
    this.name = name;
  }

  public String getName() {
    return name;
  }

}

@Table(database = AppDatabase.class)
public class Dog(@Primary var name: String? = null)

Columns have a wide-range of supported types in the Model classes: Supported Types:

1. all java primitives including char,byte, short, and boolean.
2. All java boxed primitive classes
3. String, Date, java.sql.Date, Calendar, Blob, Boolean
4. Custom data types via a TypeConverter
5. Model as fields, but only as @PrimaryKey and/or @ForeignKey
6. @ColumnMap objects that flatten an object into the current table. Just like a @ForeignKey, but without requiring a separate table. (4.1.0+). Avoid nesting more than one object, as the column count could get out of control.

Unsupported Types:

1. List<T> : List columns are not supported and not generally proper for a relational database. However, you can get away with a non-generic List column via a TypeConverter. But again, avoid this if you can.
2. Anything that is generically typed (even with an associated TypeConverter). If you need to include the field, subclass the generic object and provide a TypeConverter.

Inherited Columns

Since we don't require extension on BaseModel directly, tables can extend non-model classes and inherit their fields directly (given proper accessibility) via the @InheritedColumn annotation (or @InheritedPrimaryKey for primary keys):

@Table(database = AppDatabase.class,
        inheritedColumns = {@InheritedColumn(column = @Column, fieldName = "name"),
                @InheritedColumn(column = @Column, fieldName = "number")},
        inheritedPrimaryKeys = {@InheritedPrimaryKey(column = @Column,
                primaryKey = @PrimaryKey,
                fieldName = "inherited_primary_key")})
public class InheritorModel extends InheritedModel implements Model {

Primary Keys

DBFlow supports multiple primary keys, right out of the box. Simply create a table with multiple @PrimaryKey:

@Table(database = AppDatabase.class)
public class Dog extends BaseModel {

  @PrimaryKey
  String name;

  @PrimaryKey
  String breed;

}

@Table(database = AppDatabase::class)
class Dog(@PrimaryKey var name: String? = null,
          @PrimaryKey var breed: String? = null)

If we want an auto-incrementing key, you specify @PrimaryKey(autoincrement = true), but only one of these kind can exist in a table and you cannot mix with regular primary keys.

Unique Columns

DBFlow has support for SQLite UNIQUE constraint (here for documentation)[http://www.tutorialspoint.com/sqlite/sqlite_constraints.htm].

Add @Unique annotation to your existing @Column and DBFlow adds it as a constraint when the database table is first created. This means that once it is created you should not change or modify this.

We can also support multiple unique clauses in order to ensure any combination of fields are unique. For example:

To generate this in the creation query:

UNIQUE('name', 'number') ON CONFLICT FAIL, UNIQUE('name', 'address') ON CONFLICT ROLLBACK

We declare the annotations as such:

@Table(database = AppDatabase.class,
  uniqueColumnGroups = {@UniqueGroup(groupNumber = 1, uniqueConflict = ConflictAction.FAIL),
                        @UniqueGroup(groupNumber = 2, uniqueConflict = ConflictAction.ROLLBACK))
public class UniqueModel {

  @PrimaryKey
  @Unique(unique = false, uniqueGroups = {1,2})
  String name;

  @Column
  @Unique(unique = false, uniqueGroups = 1)
  String number;

  @Column
  @Unique(unique = false, uniqueGroups = 2)
  String address;

}

The groupNumber within each defined uniqueColumnGroups with an associated @Unique column. We need to specify unique=false for any column used in a group so we expect the column to be part of a group. If true as well, the column will also alone be unique.

Default Values

DBFlow supports default values in a slighty different way that SQLite does. Since we do not know exactly the intention of missing data when saving a Model, since we group all fields, defaultValue specifies a value that we replace when saving to the database when the value of the field is null.

This feature only works on Boxed primitive and the DataClass equivalent of objects (such as from TypeConverter), such as String, Integer, Long, Double, etc. Note: If the DataClass is a Blob, unfortunately this will not work. For Boolean classes, use "1" for true, "0" for false.

@Column(defaultValue = "55")
Integer count;

@Column(defaultValue = "\"this is\"")
String test;

@Column(defaultValue = "1000L")
Date date;

@Column(defaultValue = "1")
Boolean aBoolean;

DBFlow inserts it's literal value into the ModelAdapter for the table so any String must be escaped.