Database.Persist.Types

Updating a database entity.

Persistent users use combinators to create these.

Query options.

Persistent users use these directly.

Filters which are available for select, updateWhere and deleteWhere. Each filter constructor specifies the field being filtered on, the type of comparison applied (equals, not equals, etc) and the argument for the comparison.

Persistent users use combinators to create these.

Note that it's important to be careful about the PersistFilter that you are using, if you use this directly. For example, using the In PersistFilter requires that you have an array- or list-shaped EntityField. It is possible to construct values using this that will create malformed runtime values.

Value to filter with. Highly dependant on the type of filter used.

By default, a backend will automatically generate the key Instead you can specify a Primary key made up of unique values.

Datatype that represents an entity, with both its Key and its Haskell record representation.

When using a SQL-based backend (such as SQLite or PostgreSQL), an Entity may take any number of columns depending on how many fields it has. In order to reconstruct your entity on the Haskell side, persistent needs all of your entity columns and in the right order. Note that you don't need to worry about this when using persistent's API since everything is handled correctly behind the scenes.

However, if you want to issue a raw SQL command that returns an Entity, then you have to be careful with the column order. While you could use SELECT Entity.* WHERE ... and that would work most of the time, there are times when the order of the columns on your database is different from the order that persistent expects (for example, if you add a new field in the middle of you entity definition and then use the migration code -- persistent will expect the column to be in the middle, but your DBMS will put it as the last column). So, instead of using a query like the one above, you may use rawSql (from the Database.Persist.Sql module) with its /entity selection placeholder/ (a double question mark ??). Using rawSql the query above must be written as SELECT ?? WHERE ... Then rawSql will replace ?? with the list of all columns that we need from your entity in the right order. If your query returns two entities (i.e. (Entity backend a, Entity backend b)), then you must you use SELECT ??, ?? WHERE ..., and so on.

Prior to persistent-2.11.0, we provided an instance of PersistField for the Natural type. This was in error, because Natural represents an infinite value, and databases don't have reasonable types for this.

The instance for Natural used the Int64 underlying type, which will cause underflow and overflow errors. This type has the exact same code in the instances, and will work seamlessly.

A more appropriate type for this is the Word series of types from Data.Word. These have a bounded size, are guaranteed to be non-negative, and are quite efficient for the database to store.

A FieldDef represents the inormation that persistent knows about a field of a datatype. This includes information used to parse the field out of the database and what the field corresponds to.

A raw value which can be stored in any backend and can be marshalled to and from a PersistField.

This pattern synonym used to be a data constructor on PersistValue, but was changed into a catch-all pattern synonym to allow backwards compatiblity with database types. See the documentation on PersistDbSpecific for more details.

This pattern synonym used to be a data constructor on PersistValue, but was changed into a catch-all pattern synonym to allow backwards compatiblity with database types. See the documentation on PersistDbSpecific for more details.

This pattern synonym used to be a data constructor for the PersistValue type. It was changed to be a pattern so that JSON-encoded database values could be parsed into their corresponding values. You should not use this, and instead prefer to pattern match on PersistLiteral_ directly.

If you use this, it will overlap a patern match on the 'PersistLiteral_, PersistLiteral, and PersistLiteralEscaped patterns. If you need to disambiguate between these constructors, pattern match on PersistLiteral_ directly.

An action that might happen on a deletion or update on a foreign key change.

A Checkmark should be used as a field type whenever a uniqueness constraint should guarantee that a certain kind of record may appear at most once, but other kinds of records may appear any number of times.

NOTE: You need to mark any Checkmark fields as nullable (see the following example).

For example, suppose there's a Location entity that represents where a user has lived:

Location
    user    UserId
    name    Text
    current Checkmark nullable

    UniqueLocation user current

The UniqueLocation constraint allows any number of Inactive Locations to be current. However, there may be at most one current Location per user (i.e., either zero or one per user).

This data type works because of the way that SQL treats NULLable fields within uniqueness constraints. The SQL standard says that NULL values should be considered different, so we represent Inactive as SQL NULL, thus allowing any number of Inactive records. On the other hand, we represent Active as TRUE, so the uniqueness constraint will disallow more than one Active record.

Note: There may be DBMSs that do not respect the SQL standard's treatment of NULL values on uniqueness constraints, please check if this data type works before relying on it.

The SQL BOOLEAN type is used because it's the smallest data type available. Note that we never use FALSE, just TRUE and NULL. Provides the same behavior Maybe () would if () was a valid PersistField.

An EmbedEntityDef is the same as an EntityDef But it is only used for fieldReference so it only has data needed for embedding

An EmbedFieldDef is the same as a FieldDef But it is only used for embeddedFields so it only has data needed for embedding

Attributes that may be attached to fields that can affect migrations and serialization in backend-specific ways.

While we endeavor to, we can't forsee all use cases for all backends, and so FieldAttr is extensible through its constructor FieldAttrOther.

This datatype describes how a foreign reference field cascades deletes or updates.

This type is used in both parsing the model definitions and performing migrations. A Nothing in either of the field values means that the user has not specified a CascadeAction. An unspecified CascadeAction is defaulted to Restrict when doing migrations.

A FieldType describes a field parsed from the QuasiQuoter and is used to determine the Haskell type in the generated code.

name Text parses into FTTypeCon Nothing Text

name T.Text parses into FTTypeCon (Just T Text)

name (Jsonb User) parses into:

FTApp (FTTypeCon Nothing Jsonb) (FTTypeCon Nothing User)

Used instead of FieldDef to generate a smaller amount of code

A type that determines how a backend should handle the literal.

There are 3 kinds of references 1) composite (to fields that exist in the record) 2) single field 3) embedded

A SQL data type. Naming attempts to reflect the underlying Haskell datatypes, eg SqlString instead of SqlVarchar. Different SQL databases may have different translations for these types.

Type for storing the Uniqueness constraint in the Schema. Assume you have the following schema with a uniqueness constraint:

Person
  name String
  age Int
  UniqueAge age

This will be represented as:

UniqueDef
    { uniqueHaskell = ConstraintNameHS (packPTH UniqueAge)
    , uniqueDBName = ConstraintNameDB (packPTH "unique_age")
    , uniqueFields = [(FieldNameHS (packPTH "age"), FieldNameDB (packPTH "age"))]
    , uniqueAttrs = []
    }

The reason why a field is nullable is very important. A field that is nullable because of a Maybe tag will have its type changed from A to Maybe A. OTOH, a field that is nullable because of a nullable tag will remain with the same type.

Returns a NonEmpty list of FieldDef that correspond with the key columns for an EntityDef.

A FieldCascade that does nothing.

Parse raw field attributes into structured form. Any unrecognized attributes will be preserved, identically as they are encountered, as FieldAttrOther values.