Record Types
Records are types for grouping values together. They generalise the dependent product type by providing named fields and (optional) further components.
Example: the Pair type constructor
Record types can be declared using the record
keyword
record Pair (A B : Set) : Set where
field
fst : A
snd : B
This defines a new type constructor Pair : Set → Set → Set
and two projection functions
Pair.fst : {A B : Set} → Pair A B → A
Pair.snd : {A B : Set} → Pair A B → B
Note that the parameters A
and B
are implicit arguments to the projection functions.
Elements of record types can be defined using a record expression
p23 : Pair Nat Nat
p23 = record { fst = 2; snd = 3 }
or using copatterns. Copatterns may be used prefix
p34 : Pair Nat Nat
Pair.fst p34 = 3
Pair.snd p34 = 4
suffix (in which case they are written prefixed with a dot)
p56 : Pair Nat Nat
p56 .Pair.fst = 5
p56 .Pair.snd = 6
or using an anonymous copattern-matching lambda (you may only use the suffix form of copatterns in this case)
p78 : Pair Nat Nat
p78 = λ where
.Pair.fst → 7
.Pair.snd → 8
If you use the constructor
keyword, you can also use the named constructor to define elements of the record type:
record Pair (A B : Set) : Set where
constructor _,_
field
fst : A
snd : B
p45 : Pair Nat Nat
p45 = 4 , 5
In this sense, record types behave much like single constructor datatypes (but see Eta-expansion below).
Declaring, constructing and decomposing records
Declaring record types
The general form of a record declaration is as follows:
record <recordname> <parameters> : Set <level> where
<directives>
constructor <constructorname>
field
<fieldname1> : <type1>
<fieldname2> : <type2>
-- ...
<declarations>
All the components are optional, and can be given in any order. In particular, fields can be given in more than one block, interspersed with other declarations. Each field is a component of the record. Types of later fields can depend on earlier fields.
The directives available are eta-equality
, no-eta-equality
, pattern
(see Eta-expansion), inductive
and co-inductive
(see Recursive records).
Constructing record values
Record values are constructed by giving a value for each record field:
record { <fieldname1> = <term1> ; <fieldname2> = <term2> ; ... }
where the types of the terms match the types of the fields. If a constructor <constructorname>
has been declared for the record, this can also be written
<constructorname> <term1> <term2> ...
For named definitions, this can also be expressed using copatterns:
<named-def> : <recordname> <parameters>
<recordname>.<fieldname1> <named-def> = <term1>
<recordname>.<fieldname2> <named-def> = <term2>
...
Records can also be constructed by updating other records.
Building records from modules
The record { <fields> }
syntax also accepts module names. Fields are defined using the corresponding definitions from the given module. For instance assuming this record type R and module M:
record R : Set where
field
x : X
y : Y
z : Z
module M where
x = ...
y = ...
r : R
r = record { M; z = ... }
This construction supports any combination of explicit field definitions and applied modules. If a field is both given explicitly and available in one of the modules, then the explicit one takes precedence. If a field is available in more than one module then this is ambiguous and therefore rejected. As a consequence the order of assignments does not matter.
The modules can be both applied to arguments and have import directives such as hiding, using, and renaming. Here is a contrived example building on the example above:
module M2 (a : A) where
w = ...
z = ...
r2 : A → R
r2 a = record { M hiding (y); M2 a renaming (w to y) }
Decomposing record values
With the field name, we can project the corresponding component out of a record value. It is also possible to pattern match against inductive records:
sum : Pair Nat Nat → Nat
sum (x , y) = x + y
Or, using a let binding record pattern:
sum' : Pair Nat Nat → Nat
sum' p = let (x , y) = p in x + y
Note
Naming the constructor is not required to enable pattern matching against record values. Record expressions can appear as patterns.
Record update
Assume that we have a record type and a corresponding value:
record MyRecord : Set where
field
a b c : Nat
old : MyRecord
old = record { a = 1; b = 2; c = 3 }
Then we can update (some of) the record value’s fields in the following way:
new : MyRecord
new = record old { a = 0; c = 5 }
Here new
normalises to record { a = 0; b = 2; c = 5 }
. Any expression yielding a value of type MyRecord
can be used instead of old
. Using that records can be built from module names, together with the fact that all records define a module, this can also be written as
new' : MyRecord
new' = record { MyRecord old; a = 0; c = 5}
Record updating is not allowed to change types: the resulting value must have the same type as the original one, including the record parameters. Thus, the type of a record update can be inferred if the type of the original record can be inferred.
The record update syntax is expanded before type checking. When the expression
record old { upd-fields }
is checked against a record type R
, it is expanded to
let r = old in record { new-fields }
where old
is required to have type R
and new-fields
is defined as follows: for each field x
in R
,
if
x = e
is contained inupd-fields
thenx = e
is included innew-fields
, and otherwiseif
x
is an explicit field thenx = R.x r
is included innew-fields
, andif
x
is an implicit or instance field, then it is omitted fromnew-fields
.
The reason for treating implicit and instance fields specially is to allow code like the following:
data Vec (A : Set) : Nat → Set where
[] : Vec A zero
_∷_ : ∀{n} → A → Vec A n → Vec A (suc n)
record R : Set where
field
{length} : Nat
vec : Vec Nat length
-- More fields ...
xs : R
xs = record { vec = 0 ∷ 1 ∷ 2 ∷ [] }
ys = record xs { vec = 0 ∷ [] }
Without the special treatment the last expression would need to include a new binding for length
(for instance length = _
).
Record modules
Along with a new type, a record declaration also defines a module with the same name, parameterised over an element of the record type containing the projection functions. This allows records to be “opened”, bringing the fields into scope. For instance
swap : {A B : Set} → Pair A B → Pair B A
swap p = snd , fst
where open Pair p
In the example, the record module Pair
has the shape
module Pair {A B : Set} (p : Pair A B) where
fst : A
snd : B
Note
This is not quite right: The projection functions take the parameters as erased arguments. However, the parameters are not erased in the module telescope if they were not erased to start with.
It’s possible to add arbitrary definitions to the record module, by defining them inside the record declaration
record Functor (F : Set → Set) : Set₁ where
field
fmap : ∀ {A B} → (A → B) → F A → F B
_<$_ : ∀ {A B} → A → F B → F A
x <$ fb = fmap (λ _ → x) fb
Note
In general new definitions need to appear after the field declarations, but simple non-recursive function definitions without pattern matching can be interleaved with the fields. The reason for this restriction is that the type of the record constructor needs to be expressible using let-expressions. In the example below D₁
can only contain declarations for which the generated type of mkR
is well-formed.
record R Γ : Setᵢ where
constructor mkR
field f₁ : A₁
D₁
field f₂ : A₂
mkR : ∀ {Γ} (f₁ : A₁) (let D₁) (f₂ : A₂) → R Γ
Eta-expansion
The eta (η) rule for a record type
record R : Set where
field
a : A
b : B
c : C
states that every x : R
is definitionally equal to record { a = R.a x ; b = R.b x ; c = R.c x }
. By default, all (inductive) record types enjoy η-equality if the positivity checker has confirmed it is safe to have it. The keywords eta-equality
/no-eta-equality
enable/disable η rules for the record type being declared.
Recursive records
Recursive records need to be declared as either inductive or coinductive.
record Tree (A : Set) : Set where
inductive
constructor tree
field
elem : A
subtrees : List (Tree A)
record Stream (A : Set) : Set where
coinductive
constructor _::_
field
head : A
tail : Stream A
Inductive records have eta-equality
on by default, while no-eta-equality
is the default for coinductive records. In fact, the eta-equality
and coinductive
directives are not allowed together, since this can easily make Agda loop. This can be overridden at your own risk by using the pragma ETA
instead.
It is possible to pattern match on inductive records, but not on coinductive ones.
However, inductive records without η-equality do not support both matching on the record constructor and construction of record elements by copattern matching. It has been discovered that the combination of both leads to loss of subject reduction, i.e., reduction does not preserve typing. For records without η, matching on the record constructor is off by default and construction by copattern matching is on. If you want the converse, you can add the record directive pattern
:
record HereditaryList : Set where
inductive
no-eta-equality
pattern
field sublists : List HereditaryList
pred : HereditaryList → List HereditaryList
pred record{ sublists = ts } = ts
If both eta-equality
and pattern
are given for a record types, Agda will alert the user of a redundant pattern
directive. However, if η is inferred but not declared explicitly, Agda will just ignore a redundant pattern
directive; this is because the default can be changed globally by option --no-eta-equality.
Constructors of records supporting co-pattern matching may be marked with an {-# INLINE #-}
pragma to assist the termination checker.
Instance fields
Instance fields, that is record fields marked with {{ }}
can be used to model “superclass” dependencies. For example:
record Eq (A : Set) : Set where
field
_==_ : A → A → Bool
open Eq {{...}}
record Ord (A : Set) : Set where
field
_<_ : A → A → Bool
{{eqA}} : Eq A
open Ord {{...}} hiding (eqA)
Now anytime you have a function taking an Ord A
argument the Eq A
instance is also available by virtue of η-expansion. So this works as you would expect:
_≤_ : {A : Set} {{OrdA : Ord A}} → A → A → Bool
x ≤ y = (x == y) || (x < y)
There is a problem however if you have multiple record arguments with conflicting instance fields. For instance, suppose we also have a Num
record with an Eq
field
record Num (A : Set) : Set where
field
fromNat : Nat → A
{{eqA}} : Eq A
open Num {{...}} hiding (eqA)
_≤3 : {A : Set} {{OrdA : Ord A}} {{NumA : Num A}} → A → Bool
x ≤3 = (x == fromNat 3) || (x < fromNat 3)
Here the Eq A
argument to _==_
is not resolved since there are two conflicting candidates: Ord.eqA OrdA
and Num.eqA NumA
. To solve this problem you can declare instance fields as overlappable using the overlap
keyword:
record Ord (A : Set) : Set where
field
_<_ : A → A → Bool
overlap {{eqA}} : Eq A
open Ord {{...}} hiding (eqA)
record Num (A : Set) : Set where
field
fromNat : Nat → A
overlap {{eqA}} : Eq A
open Num {{...}} hiding (eqA)
_≤3 : {A : Set} {{OrdA : Ord A}} {{NumA : Num A}} → A → Bool
x ≤3 = (x == fromNat 3) || (x < fromNat 3)
Whenever there are multiple valid candidates for an instance goal, if all candidates are overlappable, the goal is solved by the left-most candidate. In the example above that means that the Eq A
goal is solved by the instance from the Ord
argument.
Clauses for instance fields can be omitted when defining values of record types. For instance we can define Nat
instances for Eq
, Ord
and Num
as follows, leaving out cases for the eqA
fields:
instance
EqNat : Eq Nat
_==_ {{EqNat}} = Agda.Builtin.Nat._==_
OrdNat : Ord Nat
_<_ {{OrdNat}} = Agda.Builtin.Nat._<_
NumNat : Num Nat
fromNat {{NumNat}} n = n