Database.Persist.Sqlite

Run the given action with a connection pool.

Like createSqlitePool, this should not be used with :memory:.

Run the given action with a connection pool.

Like createSqlitePool, this should not be used with :memory:.

Create a pool of SQLite connections.

Note that this should not be used with the :memory: connection string, as the pool will regularly remove connections, destroying your database. Instead, use withSqliteConn.

Create a pool of SQLite connections.

Note that this should not be used with the :memory: connection string, as the pool will regularly remove connections, destroying your database. Instead, use withSqliteConn.

Create a pool of SQLite connections.

A Statement is a representation of a database query that has been prepared and stored on the server side.

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 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.

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.

Convert list of PersistValues into textual representation of JSON object. This is a type-constrained synonym for toJsonText.

Convert map (list of tuples) into textual representation of JSON object. This is a type-constrained synonym for toJsonText.

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

A SqlBackend represents a handle or connection to a database. It contains functions and values that allow databases to have more optimized implementations, as well as references that benefit performance and sharing.

Instead of using the SqlBackend constructor directly, use the mkSqlBackend function.

A SqlBackend is *not* thread-safe. You should not assume that a SqlBackend can be shared among threads and run concurrent queries. This *will* result in problems. Instead, you should create a Pool SqlBackend, known as a ConnectionPool, and pass that around in multi-threaded applications.

To run actions in the persistent library, you should use the runSqlConn function. If you're using a multithreaded application, use the runSqlPool function.

Backends supporting conditional read operations.

A backwards-compatible alias for those that don't care about distinguishing between read and write queries. It signifies the assumption that, by default, a backend can write as well as read.

A backwards-compatible alias for those that don't care about distinguishing between read and write queries. It signifies the assumption that, by default, a backend can write as well as read.

A backwards-compatible alias for those that don't care about distinguishing between read and write queries. It signifies the assumption that, by default, a backend can write as well as read.

Represents a value containing all the configuration options for a specific backend. This abstraction makes it easier to write code that can easily swap backends.

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.

Updating a database entity.

Persistent users use combinators to create these.

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.

Persistent serialized Haskell records to the database. A Database Entity (A row in SQL, a document in MongoDB, etc) corresponds to a Key plus a Haskell record.

For every Haskell record type stored in the database there is a corresponding PersistEntity instance. An instance of PersistEntity contains meta-data for the record. PersistEntity also helps abstract over different record types. That way the same query interface can return a PersistEntity, with each query returning different types of Haskell records.

Some advanced type system capabilities are used to make this process type-safe. Persistent users usually don't need to understand the class associated data and functions.

An EntityField is parameterised by the Haskell record it belongs to and the additional type of that field.

As of persistent-2.11.0.0, it's possible to use the OverloadedLabels language extension to refer to EntityField values polymorphically. See the documentation on SymbolToField for more information.

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.

Persistent allows multiple different backends (databases).

A type class which is used to witness that a type is safe to insert into the database without providing a primary key.

The TemplateHaskell function mkPersist will generate instances of this class for any entity that it works on. If the entity has a default primary key, then it provides a regular instance. If the entity has a Primary natural key, then this works fine. But if the entity has an Id column with no default=, then this does a TypeError and forces the user to use insertKey.

This type class is used with the OverloadedLabels extension to provide a more convenient means of using the EntityField type. EntityField definitions are prefixed with the type name to avoid ambiguity, but this ambiguity can result in verbose code.

If you have a table User with a name Text field, then the corresponding EntityField is UserName. With this, we can write #name :: EntityField User Text.

What's more fun is that the type is more general: it's actually #name :: (SymbolToField "name" rec typ) => EntityField rec typ

Which means it is *polymorphic* over the actual record. This allows you to write code that can be generic over the tables, provided they have the right fields.

Unique keys besides the Key.

Predefined parseJSON. The input JSON looks like {"id": 1, "name": ...}.

The typical usage is:

instance FromJSON (Entity User) where
    parseJSON = entityIdFromJSON

Predefined toJSON. The resulting JSON looks like {"id": 1, "name": ...}.

The typical usage is:

instance ToJSON (Entity User) where
    toJSON = entityIdToJSON

Get list of values corresponding to given entity.

Convenience function for getting a free PersistField instance from a type with JSON instances. The JSON parser used will accept JSON values other that object and arrays. So, if your instance serializes the data to a JSON string, this will still work.

Example usage in combination with toPersistValueJSON:

instance PersistField MyData where
  fromPersistValue = fromPersistValueJSON
  toPersistValue = toPersistValueJSON

Predefined parseJSON. The input JSON looks like {"key": 1, "value": {"name": ...}}.

The typical usage is:

instance FromJSON (Entity User) where
    parseJSON = keyValueEntityFromJSON

Predefined toJSON. The resulting JSON looks like {"key": 1, "value": {"name": ...}}.

The typical usage is:

instance ToJSON (Entity User) where
    toJSON = keyValueEntityToJSON

Construct an Entity record by providing a value for each of the record's fields.

These constructions are equivalent:

entityMattConstructor, entityMattTabulate :: Entity User
entityMattConstructor =
    Entity
        { entityKey = toSqlKey 123
        , entityVal =
            User
                { userName = Matt
                , userAge = 33
                }
        }

entityMattTabulate =
    tabulateEntity $ \case
        UserId ->
            toSqlKey 123
        UserName ->
            Matt
        UserAge ->
            33

This is a specialization of tabulateEntityA, which allows you to construct an Entity by providing an Applicative action for each field instead of a regular function.

Convenience function for getting a free PersistField instance from a type with JSON instances.

Example usage in combination with fromPersistValueJSON:

instance PersistField MyData where
  fromPersistValue = fromPersistValueJSON
  toPersistValue = toPersistValueJSON

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.

This class teaches Persistent how to take a custom type and marshal it to and from a PersistValue, allowing it to be stored in a database.

Examples

Simple Newtype

You can use newtype to add more type safety/readability to a basis type like ByteString. In these cases, just derive PersistField and PersistFieldSql:

{-# LANGUAGE GeneralizedNewtypeDeriving #-}

newtype HashedPassword = HashedPassword ByteString
  deriving (Eq, Show, PersistField, PersistFieldSql)

Smart Constructor Newtype

In this example, we create a PersistField instance for a newtype following the "Smart Constructor" pattern.

{-# LANGUAGE GeneralizedNewtypeDeriving #-}
import qualified Data.Text as T
import qualified Data.Char as C

-- | An American Social Security Number
newtype SSN = SSN Text
 deriving (Eq, Show, PersistFieldSql)

mkSSN :: Text -> Either Text SSN
mkSSN t = if (T.length t == 9) && (T.all C.isDigit t)
 then Right $ SSN t
 else Left $ "Invalid SSN: " <> t

instance PersistField SSN where
  toPersistValue (SSN t) = PersistText t
  fromPersistValue (PersistText t) = mkSSN t
  -- Handle cases where the database does not give us PersistText
  fromPersistValue x = Left $ "File.hs: When trying to deserialize an SSN: expected PersistText, received: " <> T.pack (show x)

Tips:

• This file contain dozens of PersistField instances you can look at for examples.

• Typically custom PersistField instances will only accept a single PersistValue constructor in fromPersistValue.

• Internal PersistField instances accept a wide variety of PersistValues to accomodate e.g. storing booleans as integers, booleans or strings.

• If you're making a custom instance and using a SQL database, you'll also need PersistFieldSql to specify the type of the database column.

FIXME Add documentation to that.

Backends supporting conditional write operations

Get the Keys of all records matching the given criterion.

For an example, see selectList.

Call selectKeys but return the result as a list.

Returns a [Entity record] corresponding to the filters and options provided.

Filters are constructed using the operators defined in Database.Persist (and re-exported from Database.Persist.Sql). Let's look at some examples:

usersWithAgeOver40 :: SqlPersistT IO [Entity User]
usersWithAgeOver40 =
    selectList [UserAge >=. 40] []

If you provide multiple values in the list, the conditions are ANDed together.

usersWithAgeBetween30And50 :: SqlPersistT IO [Entity User]
usersWithAgeBetween30And50 =
     selectList
         [ UserAge >=. 30
         , UserAge <=. 50
         ]
         []

The second list contains the SelectOpt for a record. We can select the first ten records with LimitTo

firstTenUsers =
    selectList [] [LimitTo 10]

And we can select the second ten users with OffsetBy.

secondTenUsers =
    selectList [] [LimitTo 10, OffsetBy 10]

Warning that LIMIT/OFFSET is bad for pagination!

The type of record can usually be infered from the types of the provided filters and select options. In the previous two examples, though, you'll notice that the select options are polymorphic, applying to any record type. In order to help type inference in such situations, or simply as an enhancement to readability, you might find type application useful, illustrated below.

{-# LANGUAGE TypeApplications #-}
...

firstTenUsers =
    selectList User [] [LimitTo 10]

secondTenUsers =
    selectList User [] [LimitTo 10, OffsetBy 10]

With Asc and Desc, we can provide the field we want to sort on. We can provide multiple sort orders - later ones are used to sort records that are equal on the first field.

newestUsers =
    selectList [] [Desc UserCreatedAt, LimitTo 10]

oldestUsers =
    selectList [] [Asc UserCreatedAt, LimitTo 10]

Get all records matching the given criterion in the specified order. Returns also the identifiers.

WARNING: This function returns a ConduitM, which suggests that it streams the results. It does not stream results on most backends. If you need streaming, see persistent-pagination for a means of chunking results based on indexed ranges.

This class witnesses that two backend are compatible, and that you can convert from the sub backend into the sup backend. This is similar to the HasPersistBackend and IsPersistBackend classes, but where you don't want to fix the type associated with the PersistEntityBackend of a record.

Generally speaking, where you might have:

foo ::
  ( PersistEntity record
  , PersistEntityBackend record ~ BaseBackend backend
  , IsSqlBackend backend
  )

this can be replaced with:

foo ::
  ( PersistEntity record,
  , PersistEntityBackend record ~ backend
  , BackendCompatible SqlBackend backend
  )

This works for SqlReadBackend because of the instance BackendCompatible SqlBackend SqlReadBackend, without needing to go through the BaseBackend type family.

Likewise, functions that are currently hardcoded to use SqlBackend can be generalized:

-- before:
asdf :: ReaderT SqlBackend m ()
asdf = pure ()

-- after:
asdf' :: BackendCompatible SqlBackend backend => ReaderT backend m ()
asdf' = withCompatibleBackend asdf

Class which allows the plucking of a BaseBackend backend from some larger type. For example, instance HasPersistBackend (SqlReadBackend, Int) where type BaseBackend (SqlReadBackend, Int) = SqlBackend persistBackend = unSqlReadBackend . fst

Class which witnesses that backend is essentially the same as BaseBackend backend. That is, they're isomorphic and backend is just some wrapper over BaseBackend backend.

A convenient alias for common type signatures

ToBackendKey converts a PersistEntity Key into a BackendKey This can be used by each backend to convert between a Key and a plain Haskell type. For Sql, that is done with toSqlKey and fromSqlKey.

By default, a PersistEntity uses the default BackendKey for its Key and is an instance of ToBackendKey

A Key that instead uses a custom type will not be an instance of ToBackendKey.

Curry this to make a convenience function that loads an associated model.

foreign = belongsTo foreignId

Same as belongsTo, but uses getJust and therefore is similarly unsafe.

Like get, but returns the complete Entity.

Example usage

With schema-1 and dataset-1,

getSpjEntity :: MonadIO m => ReaderT SqlBackend m (Maybe (Entity User))
getSpjEntity = getEntity spjId

mSpjEnt <- getSpjEntity

The above query when applied on dataset-1, will get this entity:

+----+------+-----+
| id | name | age |
+----+------+-----+
|  1 | SPJ  |  40 |
+----+------+-----+

Same as get, but for a non-null (not Maybe) foreign key. Unsafe unless your database is enforcing that the foreign key is valid.

Example usage

With schema-1 and dataset-1,

getJustSpj :: MonadIO m => ReaderT SqlBackend m User
getJustSpj = getJust spjId

spj <- getJust spjId

The above query when applied on dataset-1, will get this record:

+----+------+-----+
| id | name | age |
+----+------+-----+
|  1 | SPJ  |  40 |
+----+------+-----+

getJustUnknown :: MonadIO m => ReaderT SqlBackend m User
getJustUnknown = getJust unknownId

mrx <- getJustUnknown

This just throws an error.

Same as getJust, but returns an Entity instead of just the record.

Example usage

With schema-1 and dataset-1,

getJustEntitySpj :: MonadIO m => ReaderT SqlBackend m (Entity User)
getJustEntitySpj = getJustEntity spjId

spjEnt <- getJustEntitySpj

The above query when applied on dataset-1, will get this entity:

+----+------+-----+
| id | name | age |
+----+------+-----+
|  1 | SPJ  |  40 |
+----+------+-----+

Like insert, but returns the complete Entity.

Example usage

With schema-1 and dataset-1,

insertHaskellEntity :: MonadIO m => ReaderT SqlBackend m (Entity User)
insertHaskellEntity = insertEntity $ User "Haskell" 81

haskellEnt <- insertHaskellEntity

The above query when applied on dataset-1, will produce this:

+----+---------+-----+
| id |  name   | age |
+----+---------+-----+
|  1 | SPJ     |  40 |
+----+---------+-----+
|  2 | Simon   |  41 |
+----+---------+-----+
|  3 | Haskell |  81 |
+----+---------+-----+

Like insertEntity but just returns the record instead of Entity.

Example usage

With schema-1 and dataset-1,

insertDaveRecord :: MonadIO m => ReaderT SqlBackend m User
insertDaveRecord = insertRecord $ User "Dave" 50

dave <- insertDaveRecord

The above query when applied on dataset-1, will produce this:

+-----+------+-----+
|id   |name  |age  |
+-----+------+-----+
|1    |SPJ   |40   |
+-----+------+-----+
|2    |Simon |41   |
+-----+------+-----+
|3    |Dave  |50   |
+-----+------+-----+

Run a query against a larger backend by plucking out BaseBackend backend

This is a helper for reusing existing queries when expanding the backend type.

Run a query against a compatible backend, by projecting the backend

This is a helper for using queries which run against a specific backend type that your backend is compatible with.

This class is used to ensure that functions requring at least one unique key are not called with records that have 0 unique keys. The quasiquoter automatically writes working instances for appropriate entities, and generates TypeError instances for records that have 0 unique keys.

This is an error message. It is used when an entity has multiple unique keys, and the function expects a single unique key.

This is an error message. It is used when writing instances of OnlyOneUniqueKey for an entity that has no unique keys.

This class is used to ensure that upsert is only called on records that have a single Unique key. The quasiquoter automatically generates working instances for appropriate records, and generates TypeError instances for records that have 0 or multiple unique keys.

Queries against Unique keys (other than the id Key).

Please read the general Persistent documentation to learn how to create Unique keys.

Using this with an Entity without a Unique key leads to undefined behavior. A few of these functions require a single Unique, so using an Entity with multiple Uniques is also undefined. In these cases persistent's goal is to throw an exception as soon as possible, but persistent is still transitioning to that.

SQL backends automatically create uniqueness constraints, but for MongoDB you must manually place a unique index on a field to have a uniqueness constraint.

Some functions in this module (insertUnique, insertBy, and replaceUnique) first query the unique indexes to check for conflicts. You could instead optimistically attempt to perform the operation (e.g. replace instead of replaceUnique). However,

• there is some fragility to trying to catch the correct exception and determing the column of failure;

• an exception will automatically abort the current SQL transaction.

Check whether there are any conflicts for unique keys with this entity and existing entities in the database.

Returns Nothing if the entity would be unique, and could thus safely be inserted. on a conflict returns the conflicting key

Example usage

We use schema-1 and dataset-1 here.

This would be Nothing:

mAlanConst <- checkUnique $ User "Alan" 70

While this would be Just because SPJ already exists:

mSpjConst <- checkUnique $ User "SPJ" 60

Check whether there are any conflicts for unique keys with this entity and existing entities in the database.

Returns Nothing if the entity would stay unique, and could thus safely be updated. on a conflict returns the conflicting key

This is similar to checkUnique, except it's useful for updating - when the particular entity already exists, it would normally conflict with itself. This variant ignores those conflicts

Example usage

We use schema-1 and dataset-1 here.

This would be Nothing:

mAlanConst <- checkUnique $ User "Alan" 70

While this would be Just because SPJ already exists:

mSpjConst <- checkUnique $ User "SPJ" 60

A modification of getBy, which takes the PersistEntity itself instead of a Unique record. Returns a record matching one of the unique keys. This function makes the most sense on entities with a single Unique constructor.

Example usage

With schema-1 and dataset-1,

getBySpjValue :: MonadIO m => ReaderT SqlBackend m (Maybe (Entity User)) getBySpjValue = getByValue $ User SPJ 999

mSpjEnt <- getBySpjValue

The above query when applied on dataset-1, will get this record:

+----+------+-----+
| id | name | age |
+----+------+-----+
|  1 | SPJ  |  40 |
+----+------+-----+

Insert a value, checking for conflicts with any unique constraints. If a duplicate exists in the database, it is returned as Left. Otherwise, the new 'Key is returned as Right.

Example usage

With schema-2 and dataset-1, we have following lines of code:

l1 <- insertBy $ User "SPJ" 20
l2 <- insertBy $ User "XXX" 41
l3 <- insertBy $ User "SPJ" 40
r1 <- insertBy $ User "XXX" 100

First three lines return Left because there're duplicates in given record's uniqueness constraints. While the last line returns a new key as Right.

Like insertEntity, but returns Nothing when the record couldn't be inserted because of a uniqueness constraint.

Example usage

We use schema-2 and dataset-1 here.

insertUniqueSpjEntity :: MonadIO m => ReaderT SqlBackend m (Maybe (Entity User))
insertUniqueSpjEntity = insertUniqueEntity $ User "SPJ" 50

mSpjEnt <- insertUniqueSpjEntity

The above query results Nothing as SPJ already exists.

insertUniqueAlexaEntity :: MonadIO m => ReaderT SqlBackend m (Maybe (Entity User))
insertUniqueAlexaEntity = insertUniqueEntity $ User "Alexa" 3

mAlexaEnt <- insertUniqueSpjEntity

Because there's no such unique keywords of the given record, the above query when applied on dataset-1, will produce this:

+----+-------+-----+
| id | name  | age |
+----+-------+-----+
|  1 | SPJ   |  40 |
+----+-------+-----+
|  2 | Simon |  41 |
+----+-------+-----+
|  3 | Alexa |   3 |
+----+-------+-----+

Given a proxy for a PersistEntity record, this returns the sole UniqueDef for that entity.

Return the single unique key for a record.

Example usage

We use shcema-1 and dataset-1 here.

onlySimonConst :: MonadIO m => ReaderT SqlBackend m (Unique User)
onlySimonConst = onlyUnique $ User "Simon" 999

mSimonConst <- onlySimonConst

mSimonConst would be Simon's uniqueness constraint. Note that onlyUnique doesn't work if there're more than two constraints. It will fail with a type error instead.

Attempt to replace the record of the given key with the given new record. First query the unique fields to make sure the replacement maintains uniqueness constraints.

Return Nothing if the replacement was made. If uniqueness is violated, return a Just with the Unique violation

Return the database name for the given entity.

Retrieve the list of FieldDef that makes up the fields of the entity.

This does not return the fields for an Id column or an implicit id. It will return the key columns if you used the Primary syntax for defining the primary key.

This does not return fields that are marked SafeToRemove or MigrationOnly - so it only returns fields that are represented in the Haskell type. If you need those fields, use getEntityFieldsDatabase.

This returns all of the FieldDef defined for the EntityDef, including those fields that are marked as MigrationOnly (and therefore only present in the database) or SafeToRemove (and a migration will drop the column if it exists in the database).

For all the fields that are present on the Haskell-type, see getEntityFields.

Retrieve the Haskell name of the given entity.

Retrieve the list of UniqueDef from an EntityDef. As of version 2.14, this will also include the primary key on the entity, if one is defined. If you do not want the primary key, see getEntityUniquesNoPrimaryKey.

Retrieve the list of UniqueDef from an EntityDef. This does not include a Primary key, if one is defined. A future version of persistent will include a Primary key among the Unique constructors for the Entity.

Perform a mapping function over all of the entity fields, as determined by getEntityFieldsDatabase.

Set an entityId to be the given FieldDef.

Add an attribute to the list of field attributes.

Check if the field is `Maybe a`

Check if the field definition is nullable

Modify the list of field attributes.

Replace the FieldDef FieldAttr with the new list.

A ConstraintNameDB represents the datastore-side name that persistent will use for a constraint.

An ConstraintNameHS represents the Haskell-side name that persistent will use for a constraint.

Convenience operations for working with '-NameDB' types.

An EntityNameDB represents the datastore-side name that persistent will use for an entity.

An EntityNameHS represents the Haskell-side name that persistent will use for an entity.

A FieldNameDB represents the datastore-side name that persistent will use for a field.

A FieldNameHS represents the Haskell-side name that persistent will use for a field.

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.

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.