in3_out2

object in3_out2 extends core with Molecule_Factory2 with Molecule_In_1_Factory2 with Molecule_In_2_Factory2 with Molecule_In_3_Factory2 with Composite_Factory2 with Composite_In_1_Factory2 with Composite_In_2_Factory2 with Composite_In_3_Factory2

Source: api.scala

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in3_out2
Composite_In_3_Factory2
Composite_In_2_Factory2
Composite_In_1_Factory2
Composite_Factory2
Molecule_In_3_Factory2
Molecule_In_2_Factory2
Molecule_In_1_Factory2
Molecule_Factory2
core
GenericVAET
GenericEAVT
GenericAVET
GenericAEVT
GenericLog
GenericSchema
TxMethods
EntityOps
LogicImplicits
AggregateKeywords
AttrExpressions
Datomic
AnyRef
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Type Members

type ?? = expression.AttrExpressions.?
Definition Classes
AttrExpressions
trait avg extends AnyRef
Average of attribute values.
Average of attribute values.

Apply avg keyword to attribute to return average of attribute values of entities matching the molecule.
```
Match.score.insert(1, 2, 4)
Match.score(avg).get.head === 2.3333333333333335 // (1 + 2 + 4) / 3
```
returns
Double
Definition Classes
AggregateKeywords

trait count extends AnyRef

Count of attribute values.

Count of attribute values.

Apply count keyword to attribute to return count of attribute values of entities matching the molecule.

Person.firstName.lastName.age insert List(
  ("Ben", "Hayday", 42),
  ("Liz", "Taylor", 34),
  ("Liz", "Swifty", 34),
  ("Liz", "Mooray", 25)
)
Person.firstName.age(count).get === List(
  ("Ben", 1),
  ("Liz", 3) // 34, 34, 25
)

returns: Int

Definition Classes: AggregateKeywords

trait countDistinct extends AnyRef
Count of distinct attribute values.
Count of distinct attribute values.

Apply countDistinct keyword to attribute to return count of distinct attribute values of entities matching the molecule.
```
Person.firstName.lastName.age insert List(
  ("Ben", "Hayday", 42),
  ("Liz", "Taylor", 34),
  ("Liz", "Swifty", 34),
  ("Liz", "Mooray", 25)
)
Person.firstName.age(countDistinct).get === List(
  ("Ben", 1),
  ("Liz", 2) // 34, 25
)
```
returns
Int
Definition Classes
AggregateKeywords

trait distinct extends AnyRef

Distinct attribute values.

Distinct attribute values.

Apply distinct keyword to attribute to return Vector of distinct attribute values of entities matching the molecule.

Person.firstName.lastName.age insert List(
  ("Ben", "Hayday", 42),
  ("Liz", "Taylor", 34),
  ("Liz", "Swifty", 34),
  ("Liz", "Mooray", 25)
)
Person.firstName.age(distinct) insert List(
  ("Ben", 42),
  ("Liz", Vector(34, 25)) // only single 34 returned
)

returns: List[attribute-type]

Definition Classes: AggregateKeywords

trait max extends AnyRef
Maximum attribute value(s).
Maximum attribute value(s).

Apply max keyword to attribute to return the maximum attribute value of entities matching the molecule.
```
Person.age.insert(25, 34, 37, 42, 70)
Person.age(max).get.head === 70
```
Apply max(n) to return Vector of the n biggest values.
```
Person.age(max(3)).get.head === Vector(37, 42, 70)
```
Definition Classes
AggregateKeywords
Note
max/max(n) supports all value types (via comparators).
max(n) Can at most return the number of values that match.
trait maxs extends AnyRef
Definition Classes
AggregateKeywords
trait median extends AnyRef
Median of attribute values.
Median of attribute values.

Apply median keyword to attribute to return median of attribute values of entities matching the molecule.
```
Match.score.insert(1, 2, 4)
Match.score(median).get.head === 2
```
OBS: When it comes to an even number of values, Datomic has a special implementation of median that is different from the one described on the Wiki entry on the median function.

Datomic calculates the median of even number of values as the average of the two middle numbers rounded down to nearest whole number
```
Match.score.insert(1, 2, 3, 4)
Match.score(median).get.head === 2 // (2 + 3) / 2 = 2.5 rounded down to 2
```
With decimal numbers this can go wrong:
```
Match.score.insert(1.0, 2.5, 2.5, 3.0)
Match.score(median).get.head === 2 // (2.5 + 2.5) / 2 = 2.5 rounded down to 2 (This is wrong and bug report has been filed)
```
returns
Value of Attribute type
Definition Classes
AggregateKeywords
trait min extends AnyRef
Minimum attribute value(s).
Minimum attribute value(s).

Apply min keyword to attribute to return the minimum attribute value of entities matching the molecule.
```
Person.age.insert(25, 34, 37, 42, 70)
Person.age(min).get.head === 25
```
Apply min(n) to return Vector of the n smallest values.
```
Person.age(min(3)).get.head === Vector(25, 34, 37)
```
Definition Classes
AggregateKeywords
Note
min/min(n) supports all value types (via comparators).
min(n) Can at most return the number of values that match.
trait mins extends AnyRef
Definition Classes
AggregateKeywords
trait rand extends AnyRef
Random attribute value(s).
Random attribute value(s).

Apply random keyword to attribute to return a single random attribute of entities matching the molecule.
```
Person.age.insert(25, 34, 37, 42, 70)
Person.age(random).get.head === 34 // or other..
```
Apply random(n) to return Vector of n random values. Observe though that duplicate random values can re-occur.
```
Person.age(random(3)).get.head === Vector(42, 25, 42) // or other..
```
To get distinct values only, use the sample(n) keyword instead.
Definition Classes
AggregateKeywords
trait rands extends AnyRef
Definition Classes
AggregateKeywords
trait sample extends AnyRef
Sample attribute value(s).
Sample attribute value(s).

Apply sample keyword to attribute to return a single sample (random) attribute value of entities matching the molecule.
```
Person.age.insert(25, 34, 37, 42, 70)
Person.age(sample).get.head === 42 // or other..
```
Apply sample(n) to return Vector of up to n distinct sample values.
```
Person.age(sample(3)).get.head === Vector(70, 25, 37) // or other..
```
If values don't need to be distinct, random(n) can be used also.
Definition Classes
AggregateKeywords
Note
Can at most return the number of values that match.
trait samples extends AnyRef
Definition Classes
AggregateKeywords
trait stddev extends AnyRef
Variance of attribute values.
Variance of attribute values.

Apply stddev keyword to attribute to return variance of attribute values of entities matching the molecule.
```
Match.score.insert(1, 2, 4)
Match.score(stddev).get.head === 1.247219128924647
```
returns
Double
Definition Classes
AggregateKeywords
trait sum extends AnyRef
Sum of attribute values.
Sum of attribute values.

Apply sum keyword to attribute to return sum of attribute values of entities matching the molecule.
```
Match.score.insert(1, 2, 4)
Match.score(sum).get.head === 7
```
returns
Value of Attribute type
Definition Classes
AggregateKeywords
trait variance extends AnyRef
Variance of attribute values.
Variance of attribute values.

Apply variance keyword to attribute to return variance of attribute values of entities matching the molecule.
```
Match.score.insert(1, 2, 4)
Match.score(variance).get.head === 1.5555555555555556
```
returns
Double
Definition Classes
AggregateKeywords
trait ? extends AnyRef
Turn molecule into input molecule awaiting input.
Turn molecule into input molecule awaiting input.

Apply input marker ? to attribute to turn molecule into an 'input molecule'.

At runtime the input molecule expects input for the attribute in place of the ? marker.
```
// Input molecule created at compile time.
val ageOfPersons = m(Person.name_(?).age) // awaiting name of type String

// At runtime, "Ben" is applied as input replacing the `?` placeholder and we can get the age.
ageOfPersons("Ben").get === List(42)
```
Definition Classes
AttrExpressions
Note
Data can only be retrieved from input molecules once they have been resolved with input.
Input molecule queries are cached and optimized by Datomic.
trait AttrExpr[Ns, T] extends AnyRef
Expression methods common for all attributes.
Expression methods common for all attributes.
Definition Classes
AttrExpressions
trait FulltextExpr[Ns, In] extends AnyRef
Expression methods of String attributes with fulltext search.
Expression methods of String attributes with fulltext search.
Definition Classes
AttrExpressions
trait ManyAttrExpr[Ns, Add, OldNew, Rem] extends AnyRef
Value update methods for card-many attributes.
Value update methods for card-many attributes.
Definition Classes
AttrExpressions
trait ManyExpr[Ns, In, T] extends ValueAttrExpr[Ns, In, T] with ManyAttrExpr[Ns, T, (T, T), T]
Expression methods of card-many attributes.
Expression methods of card-many attributes.
Definition Classes
AttrExpressions
trait MapAttrExpr[Ns, In, T] extends ValueAttrExpr[Ns, In, T] with ManyAttrExpr[Ns, (String, T), (String, T), String]
Expression methods of map attributes.
Expression methods of map attributes.
Definition Classes
AttrExpressions
trait OneExpr[Ns, In, T] extends ValueAttrExpr[Ns, In, T]
Expression methods of card-one attributes.
Expression methods of card-one attributes.
Definition Classes
AttrExpressions
trait OptionalExpr[Ns, T] extends AnyRef
Expression methods of optional attributes.
Expression methods of optional attributes.
Definition Classes
AttrExpressions
trait ValueAttrExpr[Ns, In, T] extends AttrExpr[Ns, T]
Expression methods of value attributes.
Expression methods of value attributes.
Definition Classes
AttrExpressions

trait unify extends AnyRef

Unify attribute value in self-join.

Unify attribute value in self-join.

Apply unify marker to attribute to unify its value with previous values of the same attribute in the molecule in a self-join.

m(Person.age.name.Beverages * Beverage.name.rating) insert List(
    (23, "Joe", List(("Coffee", 3), ("Cola", 2), ("Pepsi", 3))),
    (25, "Ben", List(("Coffee", 2), ("Tea", 3))),
    (23, "Liz", List(("Coffee", 1), ("Tea", 3), ("Pepsi", 1))))

// What beverages do pairs of 23- AND 25-year-olds like in common?
// Drink name is unified - Joe and Ben both drink coffee, etc..
Person.age_(23).name.Beverages.name._Ns.Self
      .age_(25).name.Beverages.name_(unify).get.sorted === List(
  ("Joe", "Coffee", "Ben"),
  ("Liz", "Coffee", "Ben"),
  ("Liz", "Tea", "Ben")
)

Definition Classes: AttrExpressions

Value Members

final def !=(arg0: Any): Boolean
Definition Classes
AnyRef → Any
final def ##: Int
Definition Classes
AnyRef → Any
final def ==(arg0: Any): Boolean
Definition Classes
AnyRef → Any
final def asInstanceOf[T0]: T0
Definition Classes
Any
implicit final def bigDec2Model(v: BigDecimal): TermValue[BigDecimal]
Definition Classes
LogicImplicits
implicit final def bigDecSet2Model(set: Set[BigDecimal]): TermValue[Set[BigDecimal]]
Definition Classes
LogicImplicits
implicit final def bigInt2Model(v: BigInt): TermValue[BigInt]
Definition Classes
LogicImplicits
implicit final def bigIntSet2Model(set: Set[BigInt]): TermValue[Set[BigInt]]
Definition Classes
LogicImplicits
implicit final def boolean2Model(v: Boolean): TermValue[Boolean]
Definition Classes
LogicImplicits
implicit final def booleanSet2Model(set: Set[Boolean]): TermValue[Set[Boolean]]
Definition Classes
LogicImplicits
def clone(): AnyRef
Attributes
protected[lang]
Definition Classes
AnyRef
Annotations
@throws(classOf[java.lang.CloneNotSupportedException]) @native()
implicit final def date2Model(v: Date): TermValue[Date]
Definition Classes
LogicImplicits
implicit final def dateSet2Model(set: Set[Date]): TermValue[Set[Date]]
Definition Classes
LogicImplicits

def debugRetract(eids: Iterable[Long], txMetaDataMolecules: MoleculeBase*)(implicit conn: Conn): Unit

Debug retracting multiple entities with optional transaction meta data.

Debug retracting multiple entities with optional transaction meta data.

Without affecting the database, a multiple entity retract action can be debugged by adding a 'D' (for 'Debug') to the retract method.

Here we debug a possible retraction of two comment entities with transaction meta data asserting that the retraction was done by Ben Goodman:

debugRetract(Seq(commentEid1, commentEid2), MetaData.user("Ben Goodman"))

This will print debugging info about the retraction to output (without affecting the database):

## 1 ## molecule.Datomic.debugRetract
===================================================================================================================
1      Model(
  1      TxMetaData(
    1      Atom(metaData,user,String,1,Eq(List(Ben Goodman)),None,List(),List())))
------------------------------------------------
2      List(
  1      :db/add     'tx                             :MetaData/user     Values(Eq(List(Ben Goodman)),None)   Card(1))
------------------------------------------------
3      List(
  1      List(
    1      :db.fn/retractEntity   17592186045445
    2      :db.fn/retractEntity   17592186045446
    3      :db/add   #db/id[:db.part/tx -1000097]    :MetaData/user     b                                    Card(1)))
===================================================================================================================

eids: Iterable of entity ids of type Long
txMetaDataMolecules: Zero or more transaction meta data molecules
conn: Implicit Conn value in scope
returns: Unit (prints to output)

Definition Classes: EntityOps

macro def debugTransact(txFnCall: Seq[Seq[Statement]], txMolecules: MoleculeBase*): Unit

Debug tx function invocation

Print transaction statements to output of a tx function invocation without affecting the live database.

// Print debug info for tx function invocation
debugTransact(transfer(fromAccount, toAccount, 20))

// Prints produced tx statements to output:
/*
## 1 ## TxReport
========================================================================
1          ArrayBuffer(
  1          List(
    1          :db/add       17592186045445       :Account/balance    80        Card(1))
  2          List(
    1          :db/add       17592186045447       :Account/balance    720       Card(1)))
------------------------------------------------
2          List(
  1    1     added: true ,   t: 13194139534345,   e: 13194139534345,   a: 50,   v: Thu Nov 22 16:23:09 CET 2018

  2    2     added: true ,   t: 13194139534345,   e: 17592186045445,   a: 64,   v: 80
       3     added: false,  -t: 13194139534345,  -e: 17592186045445,  -a: 64,  -v: 100

  3    4     added: true ,   t: 13194139534345,   e: 17592186045447,   a: 64,   v: 720
       5     added: false,  -t: 13194139534345,  -e: 17592186045447,  -a: 64,  -v: 700)
========================================================================
*/

txFnCall: Tx function invocation
txMolecules: Optional tx meta data molecules

Definition Classes: TxMethods

def debugTransact(stmtss: Seq[Seq[Statement]]*)(implicit conn: Conn): Unit

Debug bundled transaction statements

Add transaction statements from one or more molecule actions to debugTransact to see the bundled transaction statements.

debugTransact(
  // retract
  e1.getRetractTx,
  // save
  Ns.int(4).getSaveTx,
  // insert
  Ns.int.getInsertTx(List(5, 6)),
  // update
  Ns(e2).int(20).getUpdateTx
)

// Prints transaction data to output:
/*
  ## 1 ## TxReport
  ========================================================================
  1          ArrayBuffer(
    1          List(
      1          :db.fn/retractEntity   17592186045445)
    2          List(
      1          :db/add       #db/id[:db.part/user -1000247]     :Ns/int          4           Card(1))
    3          List(
      1          :db/add       #db/id[:db.part/user -1000252]     :Ns/int          5           Card(1))
    4          List(
      1          :db/add       #db/id[:db.part/user -1000253]     :Ns/int          6           Card(1))
    5          List(
      1          :db/add       17592186045446                     :Ns/int          20          Card(1)))
  ------------------------------------------------
  2          List(
    1    1     added: true ,   t: 13194139534345,   e: 13194139534345,   a: 50,   v: Wed Nov 14 23:38:15 CET 2018

    2    2     added: false,  -t: 13194139534345,  -e: 17592186045445,  -a: 64,  -v: 1

    3    3     added: true ,   t: 13194139534345,   e: 17592186045450,   a: 64,   v: 4

    4    4     added: true ,   t: 13194139534345,   e: 17592186045451,   a: 64,   v: 5

    5    5     added: true ,   t: 13194139534345,   e: 17592186045452,   a: 64,   v: 6

    6    6     added: true ,   t: 13194139534345,   e: 17592186045446,   a: 64,   v: 20
         7     added: false,  -t: 13194139534345,  -e: 17592186045446,  -a: 64,  -v: 2)
  ========================================================================
*/

stmtss: Statement's from multiple molecule operations
conn: Implicit Conn value in scope

Definition Classes: TxMethods

implicit final def double2Model(v: Double): TermValue[Double]
Definition Classes
LogicImplicits
implicit final def doubleSet2Model(set: Set[Double]): TermValue[Set[Double]]
Definition Classes
LogicImplicits
final def eq(arg0: AnyRef): Boolean
Definition Classes
AnyRef
def equals(arg0: AnyRef): Boolean
Definition Classes
AnyRef → Any
def finalize(): Unit
Attributes
protected[lang]
Definition Classes
AnyRef
Annotations
@throws(classOf[java.lang.Throwable])
implicit final def float2Model(v: Float): TermValue[Float]
Definition Classes
LogicImplicits
implicit final def floatSet2Model(set: Set[Float]): TermValue[Set[Float]]
Definition Classes
LogicImplicits
final def getClass(): Class[_ <: AnyRef]
Definition Classes
AnyRef → Any
Annotations
@native()
def hashCode(): Int
Definition Classes
AnyRef → Any
Annotations
@native()
implicit final def int2Model(v: Int): TermValue[Int]
Definition Classes
LogicImplicits
implicit final def intSet2Model(set: Set[Int]): TermValue[Set[Int]]
Definition Classes
LogicImplicits
final def isInstanceOf[T0]: Boolean
Definition Classes
Any
implicit final def long2Entity(id: Long)(implicit conn: Conn): Entity
Long -> Entity api implicit.
Long -> Entity api implicit.

Convenience implicit to allow calling Entity methods directly on entity Long value.
```
// Get entity id of Ben
val benId = Person.e.name_("Ben").get.head

// Retract Ben entity directly on his entity id
benId.retract
```
id
Entity id of type Long
conn
Implicit Conn value in scope
Definition Classes
EntityOps
implicit final def long2Model(v: Long): TermValue[Long]
Definition Classes
LogicImplicits
implicit final def longSet2Model(set: Set[Long]): TermValue[Set[Long]]
Definition Classes
LogicImplicits
macro def m[I1, I2, I3, T1, T2](dsl: Composite_In_3_02[I1, I2, I3, T1, T2]): InputMolecule_3_02[I1, I2, I3, T1, T2]
Macro creation of composite input molecule awaiting 3 inputs from user-defined DSL with 2 output groups (arity 2).
Macro creation of composite input molecule awaiting 3 inputs from user-defined DSL with 2 output groups (arity 2).

The builder pattern is used to add one or more attributes to an initial namespace like Person from the example below. Further non-related attributes can be tied together with the + method to form "composite molecules" that is basically just attributes sharing the same entity id.

Applying the ? marker to attributes changes the semantics of the composite molecule to become a "composite input molecule" that awaits input at runtime for the attributes marked with ?.

Once the composite input molecule models the desired data structure and has been resolved with input we can call various actions on it, like get that retrieves matching data from the database.
```
// Apply `?` to `age`, `score` and `flags` attributes to create composite input molecule
val personsAgeScoreFlags = m(Person.name.age_(?) + Tag.score_(?).flags_(?))

// At runtime, `age`, `score` and `flags` values are applied to get the Person's name
personsAgeScoreFlags(42, 7, 3).get.head === "Ben"
```
Composite molecules of arity 2 has two sub-molecules with output attribute(s). If a sub-molecule has multiple output attributes, a tuple is returned, otherwise just the single value. The two groups of either a single type or tuple are then tied together in an outer composite tuple:
```
Composite input molecule               Composite type (2 output groups)

A.a1.a2_(?) + B.b1(?).b2_(?)     =>    (a1, b1)
A.a1.a2_(?) + B.b1(?).b2(?)      =>    (a1, (b1, b2))
A.a1.a2(?)  + B.b1(?).b2_(?)     =>    ((a1, a2), b1)
A.a1.a2(?)  + B.b1(?).b2(?)      =>    ((a1, a2), (b1, b2)) etc...

We could even have additional non-output sub-molecules:
A.a1.a2(?) + B.b1(?).b2 + C.c1_(?)     =>    ((a1, a2), (b1, b2)) etc...
```
Translating into the example:
```
m(Person.name.age_(?) + Tag.score(?).flags_(?))(42, 7, 3).get.head === ("Ben", 7)
m(Person.name.age_(?) + Tag.score(?).flags(?) )(42, 7, 3).get.head === ("Ben", (7, 3))
m(Person.name.age(?)  + Tag.score(?).flags_(?))(42, 7, 3).get.head === (("Ben", 42), 7)
m(Person.name.age(?)  + Tag.score(?).flags(?) )(42, 7, 3).get.head === (("Ben", 42), (7, 3))

m(Person.name.age(?) +
  Tag.score(?).flags +
  Cat.name_(?))(42, 7, "pitcher").get.head === (("Ben", 42), (7, 3))
```
I1
Type of input attribute 1 (age: Int)
I2
Type of input attribute 2 (score: Int)
I3
Type of input attribute 3 (flags: Int)
T1
Type of output group 1
T2
Type of output group 2
dsl
User-defined DSL structure modelling the composite input molecule awaiting 3 inputs
returns
Composite input molecule awaiting 3 inputs
Definition Classes
Composite_In_3_Factory2
macro def m[I1, I2, I3, T1](dsl: Composite_In_3_01[I1, I2, I3, T1]): InputMolecule_3_01[I1, I2, I3, T1]
Macro creation of composite input molecule awaiting 3 inputs from user-defined DSL with 1 output group (arity 1).
Macro creation of composite input molecule awaiting 3 inputs from user-defined DSL with 1 output group (arity 1).

The builder pattern is used to add one or more attributes to an initial namespace like Person from the example below. Further non-related attributes can be tied together with the + method to form "composite molecules" that is basically just attributes sharing the same entity id.

Applying the ? marker to attributes changes the semantics of the composite molecule to become a "composite input molecule" that awaits input at runtime for the attributes marked with ?.

Once the composite input molecule models the desired data structure and has been resolved with input we can call various actions on it, like get that retrieves matching data from the database.
```
// Apply `?` to `age`, `score` and `flags` attributes to create composite input molecule
val personsAgeScoreFlags = m(Person.name.age_(?) + Tag.score_(?).flags_(?))

// At runtime, `age`, `score` and `flags` values are applied to get the Person's name
personsAgeScoreFlags(42, 7, 3).get.head === "Ben"
```
Composite input molecules of arity 1 has only one sub-molecule with output attribute(s). If the sub-molecule has multiple output attributes, a tuple is returned, otherwise just the single value:
```
Composite input molecule                  Composite type (1 output group)

A.a1(?)       + B.b1_(?).b2_(?)     =>    a1
A.a1.a2(?)    + B.b1_(?).b2_(?)     =>    (a1, a2)
A.a1.a2.a3(?) + B.b1_(?).b2_(?)     =>    (a1, a2, a3)

A.a1_(?).a2_(?) + B.b1(?)           =>    b1
A.a1_(?).a2_(?) + B.b1.b2(?)        =>    (b1, b2)
A.a1_(?).a2_(?) + B.b1.b2.b3(?)     =>    (b1, b2, b3)

We could even have multiple tacit sub-molecules with multiple tacit attributes
A.a1_(?).a2_ + B.b1_(?) + C.c1.c2_(?).c3     =>    (c1, c3)
```
So, given 2 output attributes, a tuple is returned:
```
m(Person.name.age(?) + Tag.score_(?).flags_(?))(42, 7, 3).get.head === ("Ben", 42)
//  A   . a1 . a2(?) +  B .   b1_(?).   b2_(?)                      => (  a1 , a2)
```
I1
Type of input attribute 1 (age: Int)
I2
Type of input attribute 2 (score: Int)
I3
Type of input attribute 3 (flags: Int)
T1
Type of output group
dsl
User-defined DSL structure modelling the composite input molecule awaiting 2 inputs
returns
Composite input molecule awaiting 3 inputs
Definition Classes
Composite_In_3_Factory2
macro def m[I1, I2, T1, T2](dsl: Composite_In_2_02[I1, I2, T1, T2]): InputMolecule_2_02[I1, I2, T1, T2]
Macro creation of composite input molecule awaiting 2 inputs from user-defined DSL with 2 output groups (arity 2).
Macro creation of composite input molecule awaiting 2 inputs from user-defined DSL with 2 output groups (arity 2).

The builder pattern is used to add one or more attributes to an initial namespace like Person from the example below. Further non-related attributes can be tied together with the + method to form "composite molecules" that is basically just attributes sharing the same entity id.

Applying the ? marker to attributes changes the semantics of the composite molecule to become a "composite input molecule" that awaits input at runtime for the attributes marked with ?.

Once the composite input molecule models the desired data structure and has been resolved with input we can call various actions on it, like get that retrieves matching data from the database.
```
// Apply `?` to `age` and `score` attributes to create composite input molecule
val personsAgeScore = m(Person.name.age_(?) + Tag.score(?))

// At runtime, `age` and `score` values are applied to get the Person's name
personsAgeScore(42, 7).get.head === ("Ben", 7)
```
Composite input molecules of arity 2 has two sub-molecules with output attribute(s). If a sub-molecule has multiple output attributes, a tuple is returned, otherwise just the single value. The two groups of either a single type or tuple are then tied together in an outer composite tuple:
```
Composite input molecule          Composite type (2 output groups)

A.a1(?)    + B.b1(?)        =>    (a1, b1)
A.a1(?)    + B.b1(?).b2     =>    (a1, (b1, b2))
A.a1.a2(?) + B.b1(?)        =>    ((a1, a2), b1)
A.a1.a2(?) + B.b1(?).b2     =>    ((a1, a2), (b1, b2)) etc...

We could even have additional non-output sub-molecules:
A.a1.a2 + B.b1(?).b2 + C.c1_(?)     =>    ((a1, a2), (b1, b2)) etc...
```
Translating into the example:
```
m(Person.name(?)     + Tag.score(?)      )("Ben", 7).get.head === ("Ben", 7)
m(Person.name(?)     + Tag.score(?).flags)("Ben", 7).get.head === ("Ben", (7, 3))
m(Person.name.age(?) + Tag.score(?)      )(42, 7)   .get.head === (("Ben", 42), 7)
m(Person.name.age(?) + Tag.score(?).flags)(42, 7)   .get.head === (("Ben", 42), (7, 3))

m(Person.name.age +
  Tag.score(?).flags +
  Cat.name_(?))(7, "pitcher").get.head === (("Ben", 42), (7, 3))
```
I1
Type of input attribute 1 (name: String or age: Int)
I2
Type of input attribute 2 (score: Int)
T1
Type of output group 1
T2
Type of output group 2
dsl
User-defined DSL structure modelling the composite input molecule awaiting 2 inputs
returns
Composite input molecule awaiting 2 inputs
Definition Classes
Composite_In_2_Factory2
macro def m[I1, I2, T1](dsl: Composite_In_2_01[I1, I2, T1]): InputMolecule_2_01[I1, I2, T1]
Macro creation of composite input molecule awaiting 2 inputs from user-defined DSL with 1 output group (arity 1).
Macro creation of composite input molecule awaiting 2 inputs from user-defined DSL with 1 output group (arity 1).

The builder pattern is used to add one or more attributes to an initial namespace like Person from the example below. Further non-related attributes can be tied together with the + method to form "composite molecules" that is basically just attributes sharing the same entity id.

Applying the ? marker to attributes changes the semantics of the composite molecule to become a "composite input molecule" that awaits input at runtime for the attributes marked with ?.

Once the composite input molecule models the desired data structure and has been resolved with input we can call various actions on it, like get that retrieves matching data from the database.
```
// Apply `?` to `age` and `score` attributes to create composite input molecule
val personsAgeScore = m(Person.name.age_(?) + Tag.score_(?))

// At runtime, `age` and `score` values are applied to get the Person's name
personsAgeScore(42, 7).get.head === "Ben"
```
Composite input molecules of arity 1 has only one sub-molecule with output attribute(s). If the sub-molecule has multiple output attributes, a tuple is returned, otherwise just the single value:
```
Composite input molecule            Composite type (1 output group)

A.a1(?)       + B.b1_(?)      =>    a1
A.a1.a2(?)    + B.b1_(?)      =>    (a1, a2)
A.a1.a2.a3(?) + B.b1_(?)      =>    (a1, a2, a3)

A.a1_(?) + B.b1(?)            =>    b1
A.a1_(?) + B.b1.b2(?)         =>    (b1, b2)
A.a1_(?) + B.b1.b2.b3(?)      =>    (b1, b2, b3)

We could even have multiple tacit sub-molecules with multiple tacit attributes
A.a1_(?).a2_ + B.b1_(?) + C.c1.c2_.c3     =>    (c1, c3)
```
So, given 2 output attributes, a tuple is returned:
```
m(Person.name.age(?) + Tag.score_(?))(42, 7).get.head === ("Ben", 42)
//  A   . a1 . a2(?) +  B .   b1_(?)                   => (  a1 , a2)
```
I1
Type of input attribute 1 (age: Int)
I2
Type of input attribute 2 (score: Int)
T1
Type of output group
dsl
User-defined DSL structure modelling the composite input molecule awaiting 2 inputs
returns
Composite input molecule awaiting 2 inputs
Definition Classes
Composite_In_2_Factory2
macro def m[I1, T1, T2](dsl: Composite_In_1_02[I1, T1, T2]): InputMolecule_1_02[I1, T1, T2]
Macro creation of composite input molecule awaiting 1 input from user-defined DSL with 2 output groups (arity 2).
Macro creation of composite input molecule awaiting 1 input from user-defined DSL with 2 output groups (arity 2).

The builder pattern is used to add one or more attributes to an initial namespace like Person from the example below. Further non-related attributes can be tied together with the + method to form "composite molecules" that is basically just attributes sharing the same entity id.

Applying the ? marker to an attribute changes the semantics of the composite molecule to become a "composite input molecule" that awaits input at runtime for the attribute marked with ?.

Once the composite input molecule models the desired data structure and has been resolved with input we can call various actions on it, like get that retrieves matching data from the database.
```
// Apply `?` to `score` attribute to create composite input molecule
val personsWithScore = m(Person.name + Tag.score(?))

// At runtime, a `score` value is applied to get the Person's name
personsWithScore(7).get.head === ("Ben", 7)
```
Composite input molecules of arity 2 has two sub-molecules with output attribute(s). If a sub-molecule has multiple output attributes, a tuple is returned, otherwise just the single value. The two groups of either a single type or tuple are then tied together in an outer composite tuple:
```
Composite input molecule          Composite type (2 output groups)

A.a1    + B.b1(?)           =>    (a1, b1)
A.a1    + B.b1(?).b2        =>    (a1, (b1, b2))
A.a1.a2 + B.b1(?)           =>    ((a1, a2), b1)
A.a1.a2 + B.b1(?).b2        =>    ((a1, a2), (b1, b2)) etc...

We could even have additional non-output sub-molecules:
A.a1.a2 + B.b1.b2 + C.c1_(?)     =>    ((a1, a2), (b1, b2)) etc...
```
Translating into the example:
```
m(Person.name     + Tag.score(?)      )(7).get.head === ("Ben", 7)
m(Person.name     + Tag.score(?).flags)(7).get.head === ("Ben", (7, 3))
m(Person.name.age + Tag.score(?)      )(7).get.head === (("Ben", 42), 7)
m(Person.name.age + Tag.score(?).flags)(7).get.head === (("Ben", 42), (7, 3))

m(Person.name.age +
  Tag.score.flags +
  Cat.name_(?))("pitcher").get.head === (("Ben", 42), (7, 3))
```
I1
Type of input attribute 1 (score: Int)
T1
Type of output group 1
T2
Type of output group 2
dsl
User-defined DSL structure modelling the composite input molecule awaiting 1 input
returns
Composite input molecule awaiting 1 input
Definition Classes
Composite_In_1_Factory2
macro def m[I1, T1](dsl: Composite_In_1_01[I1, T1]): InputMolecule_1_01[I1, T1]
Macro creation of composite input molecule awaiting 1 input from user-defined DSL with 1 output group (arity 1).
Macro creation of composite input molecule awaiting 1 input from user-defined DSL with 1 output group (arity 1).

The builder pattern is used to add one or more attributes to an initial namespace like Person from the example below. Further non-related attributes can be tied together with the + method to form "composite molecules" that is basically just attributes sharing the same entity id.

Applying the ? marker to an attribute changes the semantics of the composite molecule to become a "composite input molecule" that awaits input at runtime for the attribute marked with ?.

Once the composite input molecule models the desired data structure and has been resolved with input we can call various actions on it, like get that retrieves matching data from the database.
```
// Apply `?` to `score` attribute to create composite input molecule
val personsWithScore = m(Person.name + Tag.score_(?))

// At runtime, a `score` value is applied to get the Person's name
personsWithScore(7).get.head === "Ben"
```
Composite input molecules of arity 1 has only one sub-molecule with output attribute(s). If the sub-molecule has multiple output attributes, a tuple is returned, otherwise just the single value:
```
Composite input molecule         Composite type (1 output group)

A.a1       + B.b1_(?)      =>    a1
A.a1.a2    + B.b1_(?)      =>    (a1, a2)
A.a1.a2.a3 + B.b1_(?)      =>    (a1, a2, a3)

A.a1_(?) + B.b1            =>    b1
A.a1_(?) + B.b1.b2         =>    (b1, b2)
A.a1_(?) + B.b1.b2.b3      =>    (b1, b2, b3)

We could even have multiple tacit sub-molecules with multiple tacit attributes
A.a1_(?).a2_ + B.b1_ + C.c1.c2_.c3     =>    (c1, c3)
```
So, given two output attributes, a tuple is returned:
```
m(Person.name.age + Tag.score_(?))(7).get.head === ("Ben", 42)
//  A   . a1 . a2 +  B .   b1_(?)               => (  a1 , a2)
```
I1
Type of input attribute 1 (score: Int)
T1
Type of output group
dsl
User-defined DSL structure modelling the composite input molecule awaiting 1 input
returns
Composite input molecule awaiting 1 input
Definition Classes
Composite_In_1_Factory2
implicit final macro def m[T1, T2](dsl: Composite02[T1, T2]): Molecule02[T1, T2]
Macro creation of composite molecule from user-defined DSL structure with 2 output groups.
Macro creation of composite molecule from user-defined DSL structure with 2 output groups.

The builder pattern is used to add one or more attributes to an initial namespace like Person from the example below. Further non-related attributes can be tied together with the + method to form "composite molecules" that is basically just attributes sharing the same entity id.

Once the composite molecule models the desired data structure we can call various actions on it, like get that retrieves matching data from the database.
```
// Explicitly calling `m` to create composite molecule with 2 output attributes
m(Person.name + Tag.score).get.head === ("Ben", 7)

// Alternatively we can create the composite molecule implicitly
Person.name.+(Tag.score).get.head === ("Ben", 7)
```
Composite molecules of arity 2 has two sub-molecules with output attribute(s). If a sub-molecule has multiple output attributes, a tuple is returned, otherwise just the single value. The two groups of either a single type or tuple are then tied together in an outer composite tuple:
```
Composite molecule          Composite type (2 output groups)

A.a1    + B.b1        =>    (a1, b1)
A.a1    + B.b1.b2     =>    (a1, (b1, b2))
A.a1.a2 + B.b1        =>    ((a1, a2), b1)
A.a1.a2 + B.b1.b2     =>    ((a1, a2), (b1, b2)) etc...

We could even have additional non-output sub-molecules:
A.a1.a2 + B.b1.b2 + C.c1_     =>    ((a1, a2), (b1, b2)) etc...
```
Translating into the example:
```
m(Person.name + Tag.score.flags).get.head                         === ("Ben", (7, 3))
m(Person.name.age + Tag.score).get.head                           === (("Ben", 42), 7)
m(Person.name.age + Tag.score.flags).get.head                     === (("Ben", 42), (7, 3))

m(Person.name.age +
  Tag.score.flags +
  Cat.name_("pitcher")).get.head === (("Ben", 42), (7, 3))
```
T1
Type of output group 1
T2
Type of output group 2
dsl
User-defined DSL structure modelling the composite molecule
returns
Composite molecule
Definition Classes
Composite_Factory2
implicit final macro def m[T1](dsl: Composite01[T1]): Molecule01[T1]
Macro creation of composite molecule from user-defined DSL structure with 1 output group.
Macro creation of composite molecule from user-defined DSL structure with 1 output group.

The builder pattern is used to add one or more attributes to an initial namespace like Person from the example below. Further non-related attributes can be tied together with the + method to form "composite molecules" that is basically just attributes sharing the same entity id.

Once the composite molecule models the desired data structure we can call various actions on it, like get that retrieves matching data from the database.
```
// Explicitly calling `m` to create composite molecule
// with 1 output attribute (`name`) and 1 tacit attribute (`score`).
m(Person.name + Tag.score_).get.head === "Ben"

// Alternatively we can create the composite molecule implicitly
Person.name.+(Tag.score_).get.head === "Ben"
```
Composite molecules of arity 1 has only one sub-molecule with output attribute(s). If the sub-molecule has multiple output attributes, a tuple is returned, otherwise just the single value:
```
Composite molecule           Composite type (1 output group)

A.a1       + B.b1_     =>    a1
A.a1.a2    + B.b1_     =>    (a1, a2)
A.a1.a2.a3 + B.b1_     =>    (a1, a2, a3) etc...

A.a1_ + B.b1           =>    b1
A.a1_ + B.b1.b2        =>    (b1, b2)
A.a1_ + B.b1.b2.b3)    =>    (b1, b2, b3) etc...

We could even have multiple tacit sub-molecules with multiple tacit attributes
A.a1_.a2_ + B.b1_ + C.c1.c2_.c3     =>    (c1, c3) etc...
```
So, given two output attributes, a tuple is returned:
```
m(Person.name.age + Tag.score_).get.head === ("Ben", 42)
//  A   . a1 . a2 +  B .  b1              => (  a1 , a2)
```
T1
Type of output group 1
dsl
User-defined DSL structure modelling the composite molecule
returns
Composite molecule
Definition Classes
Composite_Factory2
macro def m[I1, I2, I3, A, B](dsl: IN3_02[I1, I2, I3, A, B]): InputMolecule_3_02[I1, I2, I3, A, B]
Macro creation of input molecule awaiting 3 inputs from user-defined DSL structure with 2 output attributes (arity 2).
Macro creation of input molecule awaiting 3 inputs from user-defined DSL structure with 2 output attributes (arity 2).

Molecules are build by adding one or more attributes to an initial namespace like Person from the example below.

Applying the ? marker to attributes changes the semantics of a molecule to become an "input molecule" that awaits input at runtime for the attributes marked with ?.

Once the input molecule has been resolved with input, we can call various actions on it, like get that retrieves matching data from the database.
```
// Apply `?` to `age`, `score` and `flags` attributes to create input molecule.
// Input attributes can be tacit or mandatory
val personAgeScoreFlag = m(Person.name.age_(?).score(?).flags_(?))

// At runtime `age`, `score` and `flags` values are applied to get the Person's name and score.
// Since `score` was mandatory (without underscore), its value is also returned.
personAgeScoreFlag(42, 7, 3).get.head === ("Ben", 7)
```
I1
Type of input attribute 1 (age: Int)
I2
Type of input attribute 2 (score: Int)
I3
Type of input attribute 3 (flags: Int)
A
Type of output attribute 1 (name: String)
B
Type of output attribute 2 (score: Int)
dsl
User-defined DSL structure modelling the input molecule
returns
Input molecule ready to be resolved
Definition Classes
Molecule_In_3_Factory2
macro def m[I1, I2, I3, A](dsl: IN3_01[I1, I2, I3, A]): InputMolecule_3_01[I1, I2, I3, A]
Macro creation of input molecule awaiting 3 inputs from user-defined DSL structure with 1 output attribute (arity 1).
Macro creation of input molecule awaiting 3 inputs from user-defined DSL structure with 1 output attribute (arity 1).

Molecules are build by adding one or more attributes to an initial namespace like Person from the example below.

Applying the ? marker to attributes changes the semantics of a molecule to become an "input molecule" that awaits input at runtime for the attributes marked with ?.

Once the input molecule has been resolved with input, we can call various actions on it, like get that retrieves matching data from the database.
```
// Apply `?` to `age`, `score` and `flags` attributes to create input molecule.
val personAgeScoreFlag = m(Person.name.age_(?).score_(?).flags_(?))

// At runtime `age`, `score` and `flags` values are applied to get the Person's name.
personAgeScoreFlag(42, 7, 3).get.head === "Ben"
```
For arity-many molecules, data structures are returned as tuples. But for arity-1 molecules (like the example having only 1 output attribute, name) there's no need for a tuple, so values type-safely matching the attribute are returned directly in the list.
I1
Type of input attribute 1 (age: Int)
I2
Type of input attribute 2 (score: Int)
I3
Type of input attribute 3 (flags: Int)
A
Type of output attribute 1 (name: String)
dsl
User-defined DSL structure modelling the input molecule
returns
Input molecule ready to be resolved
Definition Classes
Molecule_In_3_Factory2
macro def m[I1, I2, A, B](dsl: IN2_02[I1, I2, A, B]): InputMolecule_2_02[I1, I2, A, B]
Macro creation of input molecule awaiting 2 inputs from user-defined DSL structure with 2 output attributes (arity 2).
Macro creation of input molecule awaiting 2 inputs from user-defined DSL structure with 2 output attributes (arity 2).

Molecules are build by adding one or more attributes to an initial namespace like Person from the example below.

Applying the ? marker to attributes changes the semantics of a molecule to become an "input molecule" that awaits input at runtime for the attributes marked with ?.

Once the input molecule has been resolved with input, we can call various actions on it, like get that retrieves matching data from the database.
```
// Apply `?` to `age` and `score` attributes to create input molecule.
// Input attributes can be tacit or mandatory
val personAgeScore = m(Person.name.age_(?).score(?))

// At runtime `age` and `score` values are applied to get the Person's name and score.
// Since `score` was mandatory (without underscore), its value is also returned.
personAgeScore(42, 7).get.head === ("Ben", 7)
```
I1
Type of input attribute 1 (age: Int)
I2
Type of input attribute 2 (score: Int)
A
Type of output attribute 1 (name: String)
B
Type of output attribute 2 (score: Int)
dsl
User-defined DSL structure modelling the input molecule
returns
Input molecule ready to be resolved
Definition Classes
Molecule_In_2_Factory2
macro def m[I1, I2, A](dsl: IN2_01[I1, I2, A]): InputMolecule_2_01[I1, I2, A]
Macro creation of input molecule awaiting 2 inputs from user-defined DSL structure with 1 output attribute (arity 1).
Macro creation of input molecule awaiting 2 inputs from user-defined DSL structure with 1 output attribute (arity 1).

Molecules are build by adding one or more attributes to an initial namespace like Person from the example below.

Applying the ? marker to attributes changes the semantics of a molecule to become an "input molecule" that awaits input at runtime for the attributes marked with ?.

Once the input molecule has been resolved with input, we can call various actions on it, like get that retrieves matching data from the database.
```
// Apply `?` to `age` and `score` attributes to create input molecule.
val personAgeScore = m(Person.name.age_(?).score_(?))

// At runtime `age` and `score` values are applied to get the Person's name.
personAgeScore(42, 7).get.head === "Ben"
```
For arity-many molecules, data structures are returned as tuples. But for arity-1 molecules (like the example having only 1 output attribute, name) there's no need for a tuple, so values type-safely matching the attribute are returned directly in the list.
I1
Type of input attribute 1 (age: Int)
I2
Type of input attribute 2 (score: Int)
A
Type of output attribute 1 (name: String)
dsl
User-defined DSL structure modelling the input molecule
returns
Input molecule ready to be resolved
Definition Classes
Molecule_In_2_Factory2
macro def m[I1, A, B](dsl: IN1_02[I1, A, B]): InputMolecule_1_02[I1, A, B]
Macro creation of input molecule awaiting 1 input from user-defined DSL structure with 2 output attributes (arity 2).
Macro creation of input molecule awaiting 1 input from user-defined DSL structure with 2 output attributes (arity 2).

Molecules are build by adding one or more attributes to an initial namespace like Person from the example below.

Applying the ? marker to an attribute changes the semantics of a molecule to become an "input molecule" that awaits input at runtime for the attribute marked with ?.

Once the input molecule has been resolved with input, we can call various actions on it, like get that retrieves matching data from the database.
```
// Apply `?` to `age` attribute to create input molecule
val personOfAge = m(Person.name.age_(?).score)

// At runtime, an `age` value is applied to get the Person's name and score
personOfAge(42).get.head === ("Ben", 7)
```
I1
Type of input attribute 1 (age: Int)
A
Type of output attribute 1 (name: String)
B
Type of output attribute 2 (score: Int)
dsl
User-defined DSL structure modelling the input molecule
returns
Input molecule ready to be resolved
Definition Classes
Molecule_In_1_Factory2
macro def m[I1, A](dsl: IN1_01[I1, A]): InputMolecule_1_01[I1, A]
Macro creation of input molecule awaiting 1 input from user-defined DSL structure with 1 output attribute (arity 1).
Macro creation of input molecule awaiting 1 input from user-defined DSL structure with 1 output attribute (arity 1).

Molecules are build by adding one or more attributes to an initial namespace like Person from the example below.

Applying the ? marker to an attribute changes the semantics of a molecule to become an "input molecule" that awaits input at runtime for the attribute marked with ?.

Once the input molecule has been resolved with input, we can call various actions on it, like get that retrieves matching data from the database.
```
// Apply `?` to `age` attribute to create input molecule
val personOfAge = m(Person.name.age_(?))

// At runtime, an `age` value is applied to get the Person's name
personOfAge(42).get.head === "Ben"
```
For arity-many molecules, data structures are returned as tuples. But for arity-1 molecules (like the example having only 1 output attribute, name) there's no need for a tuple, so values type-safely matching the attribute are returned directly in the list.
I1
Type of input attribute 1 (age: Int)
A
Type of output attribute 1 (name: String)
dsl
User-defined DSL structure modelling the input molecule
returns
Input molecule ready to be resolved
Definition Classes
Molecule_In_1_Factory2
implicit final macro def m[A, B](dsl: NS02[A, B]): Molecule02[A, B]
Macro creation of molecule from user-defined DSL structure with 2 output attributes.
Macro creation of molecule from user-defined DSL structure with 2 output attributes.

Molecules can be created explicitly or implicitly by building a DSL structure using boilerplate code generated from the schema definition file.

The builder pattern is used to add one or more attributes to an initial namespace like Person from the example below. Once the molecule models the desired data structure we can call various actions on it, like get that retrieves matching data from the database.

Data structures are returned as tuples of values type-safely matching the molecule attribute types
```
// Explicitly calling `m` to create Person molecule with 2 attributes
m(Person.name.age).get.head === ("Ben", 42)

// Molecule implicitly created so we can call `get`
Person.name.age.get.head === ("Ben", 42)
```
A
Type of output attribute 1 (name: String)
B
Type of output attribute 2 (age: Int)
dsl
User-defined DSL structure modelling the molecule
returns
Molecule of arity-2 typed to two attributes (Molecule02[A, B])
Definition Classes
Molecule_Factory2
implicit final macro def m[A](dsl: NS01[A]): Molecule01[A]
Macro creation of molecule from user-defined DSL structure with 1 output attribute.
Macro creation of molecule from user-defined DSL structure with 1 output attribute.

Molecules can be created explicitly or implicitly by building a DSL structure using boilerplate code generated from the schema definition file.

The builder pattern is used to add one or more attributes to an initial namespace like Person from the example below. Once the molecule models the desired data structure we can call various actions on it, like get that retrieves matching data from the database.
```
// Explicitly calling `m` to create Person molecule with 1 output attribute
m(Person.name).get === List("Ben")

// Molecule implicitly created so we can call `get`
Person.name.get.head === "Ben"
```
For arity-many molecules, data structures are returned as tuples. But for arity-1 molecules (like the example having only 1 output attribute, name) there's no need for a tuple, so values type-safely matching the attribute are returned directly in the list.
A
Type of output attribute 1 (name: String)
dsl
User-defined DSL structure modelling the molecule
returns
Molecule of arity-1 typed to first attribute (Molecule01[A])
Definition Classes
Molecule_Factory2
final def ne(arg0: AnyRef): Boolean
Definition Classes
AnyRef
final def notify(): Unit
Definition Classes
AnyRef
Annotations
@native()
final def notifyAll(): Unit
Definition Classes
AnyRef
Annotations
@native()
def recreateDbFrom(schema: SchemaTransaction, identifier: String = "", protocol: String = "mem"): Conn
Deletes existing database (!) and creates a new empty db with schema from Schema Transaction file.
Deletes existing database (!) and creates a new empty db with schema from Schema Transaction file.

A typical development cycle in the initial stages of creating the db schema:
1. Edit schema definition file
2. sbt compile to update boilerplate code in generated jars
3. Obtain a fresh connection to new empty db with updated schema:
  implicit val conn = recreateDbFrom(YourDomainSchema)
schema
Auto-generated YourDomainSchema Transaction object
(in package yourdomain.schema of generated source jar)
identifier
Optional String identifier to name database (default empty string creates a randomUUID)
protocol
Datomic protocol. Defaults to "mem" for in-memory database.
returns
Conn
Definition Classes
Datomic
def recreateDbFromRaw(schemaData: List[_], identifier: String = "", protocol: String = "mem"): Conn
Deletes existing database (!) and creates a new empty db with schema from schema data structure.
Deletes existing database (!) and creates a new empty db with schema from schema data structure.

Schema data structure is a java List of Map's of key/value pairs defining the schema.

Can be an EDN file like the mbrainz example.
schemaData
java.util.List of java.util.Maps of key/values defining a Datomic schema
identifier
Optional String identifier to name database (default empty string creates a randomUUID)
protocol
Datomic protocol. Defaults to "mem" for in-memory database.
returns
Conn
Definition Classes
Datomic
See also
https://docs.datomic.com/on-prem/data-structure-literals.html
def retract(eids: Iterable[Long], txMetaDataMolecules: MoleculeBase*)(implicit conn: Conn): TxReport
Retract multiple entities with optional transaction meta data.
Retract multiple entities with optional transaction meta data.

0 or more transaction meta data molecules can be asserted together with a retraction of entities.

Here we retract two comment entities with transaction meta data asserting that the retraction was done by Ben Goodman:
```
retract(Seq(commentEid1, commentEid2), MetaData.user("Ben Goodman"))
```
We can then later see what comments Ben Goodman retracted (op_(false)):
```
Comment.e.text.op_(false).Tx(MetaData.user_("Ben Goodman")).getHistory === List(
  (commentEid1, "I like this"),
  (commentEid2, "I hate this")
)
```
eids
Iterable of entity ids of type Long
txMetaDataMolecules
Zero or more transaction meta data molecules
conn
Implicit Conn value in scope
returns
TxReport with result of retract
Definition Classes
EntityOps
See also
Manual | Test
def retractAsync(eids: Iterable[Long], txMetaDataMolecules: MoleculeBase*)(implicit conn: Conn, ec: ExecutionContext): Future[TxReport]
Asynchronously retract multiple entities with optional transaction meta data.
Asynchronously retract multiple entities with optional transaction meta data.

0 or more transaction meta data molecules can be asserted together with a retraction of entities.

Here we asynchronously retract two comment entities with transaction meta data asserting that the retraction was done by Ben Goodman:
```
retractAsync(Seq(commentEid1, commentEid2), MetaData.user("Ben Goodman"))
```
We can then later see what comments Ben Goodman retracted (op_(false)):
```
Comment.e.text.op_(false).Tx(MetaData.user_("Ben Goodman")).getHistory === List(
  (commentEid1, "I like this"),
  (commentEid2, "I hate this")
)
```
eids
Iterable of entity ids of type Long
txMetaDataMolecules
Zero or more transaction meta data molecules
conn
Implicit Conn value in scope
returns
TxReport with result of retract
Definition Classes
EntityOps
See also
Manual | Test
implicit final def string2Model(v: String): TermValue[String]
Definition Classes
LogicImplicits
implicit final def stringSet2Model(set: Set[String]): TermValue[Set[String]]
Definition Classes
LogicImplicits
final def synchronized[T0](arg0: => T0): T0
Definition Classes
AnyRef
def toString(): String
Definition Classes
AnyRef → Any
macro def transact(txFnCall: Seq[Seq[Statement]], txMolecules: MoleculeBase*): TxReport
Transact tx function invocation

Macro that takes a tx function invocation itself as its argument.
Transact tx function invocation

Macro that takes a tx function invocation itself as its argument. The tx function is analyzed by the macro and the necessary transaction preparations done at compile time.

At runtime, the returned statements from the tx function is transacted as one atomic transaction.
```
val txReport = transact(transfer(fromAccount, toAccount, 20))
```
Transaction meta data molecules can be added
```
// Add tx meta data that John did the transfer and that it is a scheduled transfer
transact(
  transfer(fromAccount, toAccount, 20),
  Person.name("John"),
  UseCase.name("Scheduled transfer"))

// Query multiple Tx meta data molecules
Account(fromAccount).balance
  .Tx(Person.name_("John"))
  .Tx(UseCase.name_("Scheduled transfer")).get.head === 80
Account(toAccount).balance
  .Tx(Person.name_("John"))
  .Tx(UseCase.name_("Scheduled transfer")).get.head === 720
```
txFnCall
Tx function invocation
txMolecules
Optional tx meta data molecules
returns
TxReport with result of transaction
Definition Classes
TxMethods
def transact(stmtss: Seq[Seq[Statement]]*)(implicit conn: Conn): TxReport
Transact bundled transaction statements

Supply transaction statements of one or more molecule actions to perform a single atomic transaction.
Transact bundled transaction statements

Supply transaction statements of one or more molecule actions to perform a single atomic transaction.
```
transact(
  // retract entity
  e1.getRetractTx,
  // save new entity
  Ns.int(4).getSaveTx,
  // insert multiple new entities
  Ns.int.getInsertTx(List(5, 6)),
  // update entity
  Ns(e2).int(20).getUpdateTx
)
```
stmtss
Statement's from multiple molecule operations
conn
Implicit Conn value in scope
returns
TxReport with result of transaction
Definition Classes
TxMethods
macro def transactAsync(txFnCall: Seq[Seq[Statement]], txMolecules: MoleculeBase*): TxReport
Asynchronously transact tx function invocation

Macro that takes a tx function invocation itself as its argument.
Asynchronously transact tx function invocation

Macro that takes a tx function invocation itself as its argument. The tx function is analyzed by the macro and the necessary transaction preparations done at compile time.

At runtime, the returned statements from the tx function is asynchronously transacted as one atomic transaction using Datomic's asynchronous API.
```
Await.result(
  transactAsync(transfer(fromAccount, toAccount, 20)) map { txReport =>
    Account(fromAccount).balance.get.head === 80 // (could be asynchronous too)
    Account(toAccount).balance.get.head === 720
  },
  2.seconds
)
```
Additional transaction meta data can be added
```
Await.result(
  transactAsync(
    transfer(fromAccount, toAccount, 20),
    Person.name("John"),
    UseCase.name("Scheduled transfer")) map { txReport =>
      Account(fromAccount).balance
      .Tx(Person.name_("John"))
      .Tx(UseCase.name_("Scheduled transfer"))
      .get.head === 80 // (could be asynchronous too)
  },
  2.seconds
)
```
txFnCall
Tx function invocation
txMolecules
Optional tx meta data molecules
returns
Future with TxReport with result of transaction
Definition Classes
TxMethods
def transactAsync(stmtss: Seq[Seq[Statement]]*)(implicit conn: Conn, ec: ExecutionContext): Future[TxReport]
Asynchronously transact bundled transaction statements
Asynchronously transact bundled transaction statements
Supply transaction statements of one or more molecule actions to asynchronously transact a single atomic transaction.
```
Await.result(
  transactAsync(
    e1.getRetractTx,
    Ns.int(4).getSaveTx,
    Ns.int.getInsertTx(List(5, 6)),
    Ns(e2).int(20).getUpdateTx
  ) map { bundleTx =>
    Ns.int.getAsync map { queryResult =>
      queryResult === List(3, 4, 5, 6, 20)
    }
  },
  2.seconds
)
```
stmtss
Statement's from multiple molecule operations
conn
Implicit Conn value in scope
returns
Future with TxReport with result of transaction
Definition Classes
TxMethods
def transactSchema(schema: SchemaTransaction, identifier: String, protocol: String = "mem"): Conn
Transact schema from auto-generated schema transaction data.
Transact schema from auto-generated schema transaction data.
schema
sbt-plugin auto-generated Transaction file path.to.schema.YourDomainSchema
Definition Classes
Datomic
implicit final def tuple2Model[A, B](tpl: (A, B)): TermValue[(A, B)]
Definition Classes
LogicImplicits
implicit final def uri2Model(v: URI): TermValue[URI]
Definition Classes
LogicImplicits
implicit final def uriSet2Model(set: Set[URI]): TermValue[Set[URI]]
Definition Classes
LogicImplicits
implicit final def uuid2Model(v: UUID): TermValue[UUID]
Definition Classes
LogicImplicits
implicit final def uuidSet2Model(set: Set[UUID]): TermValue[Set[UUID]]
Definition Classes
LogicImplicits
final def wait(): Unit
Definition Classes
AnyRef
Annotations
@throws(classOf[java.lang.InterruptedException])
final def wait(arg0: Long, arg1: Int): Unit
Definition Classes
AnyRef
Annotations
@throws(classOf[java.lang.InterruptedException])
final def wait(arg0: Long): Unit
Definition Classes
AnyRef
Annotations
@throws(classOf[java.lang.InterruptedException]) @native()
object ? extends expression.AttrExpressions.?
Definition Classes
core
object avg extends core.avg
Definition Classes
core
object count extends core.count
Definition Classes
core
object countDistinct extends core.countDistinct
Definition Classes
core
object distinct extends core.distinct
Definition Classes
core
object max extends core.max
Definition Classes
core
object median extends core.median
Definition Classes
core
object min extends core.min
Definition Classes
core
object rand extends core.rand
Definition Classes
core
object sample extends core.sample
Definition Classes
core
object stddev extends core.stddev
Definition Classes
core
object sum extends core.sum
Definition Classes
core
object unify extends core.unify
Definition Classes
core
object variance extends core.variance
Definition Classes
core
object Log extends Log_0 with FirstNS
Log object to start Log molecule.
Log object to start Log molecule.
Definition Classes
GenericLog
object AEVT extends AEVT_0 with FirstNS
AEVT Index object to start AEVT Index molecule.
AEVT Index object to start AEVT Index molecule.
Definition Classes
GenericAEVT
object AVET extends AVET_0 with FirstNS
AVET Index object to start AVET Index molecule.
AVET Index object to start AVET Index molecule.
Definition Classes
GenericAVET
object EAVT extends EAVT_0 with FirstNS
EAVT Index object to instantiate EAVT Index molecule.
EAVT Index object to instantiate EAVT Index molecule.
Definition Classes
GenericEAVT
object VAET extends VAET_0 with FirstNS
VAET Index object to start VAET reverse Index molecule.
VAET Index object to start VAET reverse Index molecule.
Definition Classes
GenericVAET
object Schema extends Schema_0 with FirstNS
Schema object to start Schema molecule.
Schema object to start Schema molecule.
Definition Classes
GenericSchema

Inherited from Composite_In_3_Factory2

Inherited from Composite_In_2_Factory2

Inherited from Composite_In_1_Factory2

Inherited from Composite_Factory2

Inherited from Molecule_In_3_Factory2

Inherited from Molecule_In_2_Factory2

Inherited from Molecule_In_1_Factory2

Inherited from Molecule_Factory2

Inherited from core

Inherited from GenericVAET

Inherited from GenericEAVT

Inherited from GenericAVET

Inherited from GenericAEVT

Inherited from GenericLog

Inherited from GenericSchema

Inherited from TxMethods

Inherited from EntityOps

Inherited from LogicImplicits

Inherited from AggregateKeywords

Inherited from AttrExpressions

Inherited from Datomic

Inherited from AnyRef

Inherited from Any

Database operations

Entity operations

Bundled transactions

Multiple molecule operations in one atomic transaction.

Transaction functions

Atomic transaction logic with access to tx database value.

Attribute markers

Markers applied to attributes that change the semantics of the attribute/molecule.

Expression implicits

Turns basic types into TermValue's that can be used in Expression

Aggregate keywords

Keywords applied to attributes that return aggregated value(s).

Number aggregation keywords

Keywords applied to number attributes that return aggregated value(s).

api		Molecule API.
ast		Internal Molecule ASTs.
boilerplate		Internal interfaces for auto-generated DSL boilerplate code.
composition		Builder methods to compose molecules.
exceptions		Exceptions thrown by Molecule.
expression		Attribute expressions and operations.
facade		Molecule facades to Datomic.
factory		Implicit macro methods `m` to instantiate molecules from custom DSL molecule constructs.
input		Input molecules awaiting input.
macros		Internal macros generating molecule code from custom DSL molecule constructs.
generic		Interfaces to generic information about datoms and Datomic database.
ops		Internal operational helpers for transforming DSL to molecule.
schema		Schema definition DSL.
transform		Internal transformers from DSL to Model/Query/Transaction.
util		Internal Java database functions for Datomic.

Packages

Sub-packages

in3_out2