A tactic for dealing with keys present in one map but not the other in merge.
A tactic of type SimpleWhenMissing k x z is an abstract representation
of a function of type k -> x -> Maybe z .
:: a typeCtrl KGHC 9.10.3 · lts/ghc-9.10.x · 248f8f0 · 2026-10-05
Modulecontainers-0.7Haskell2010
This module defines an API for writing functions that merge two maps. The key functions are merge and mergeA. Each of these can be used with several different "merge tactics".
The merge and mergeA functions are shared by the lazy and strict modules. Only the choice of merge tactics determines strictness. If you use mapMissing from Data.Map.Merge.Strict then the results will be forced before they are inserted. If you use mapMissing from this module then they will not.
The Category, Applicative, and Monad instances for WhenMissing tactics are included because they are valid. However, they are inefficient in many cases and should usually be avoided. The instances for WhenMatched tactics should not pose any major efficiency problems.
A tactic for dealing with keys present in one map but not the other in merge.
A tactic of type SimpleWhenMissing k x z is an abstract representation
of a function of type k -> x -> Maybe z .
A tactic for dealing with keys present in both maps in merge.
A tactic of type SimpleWhenMatched k x y z is an abstract representation
of a function of type k -> x -> y -> Maybe z .
merge :: Ord k=> SimpleWhenMissing k a cWhat to do with keys in m1 but not m2
-> SimpleWhenMissing k b cWhat to do with keys in m2 but not m1
-> SimpleWhenMatched k a b cWhat to do with keys in both m1 and m2
-> Map k aMap m1
-> Map k bMap m2
-> Map k cMerge two maps.
merge takes two WhenMissing tactics, a WhenMatched tactic and two maps. It uses the tactics to merge the maps. Its behavior is best understood via its fundamental tactics, mapMaybeMissing and zipWithMaybeMatched.
Consider
merge (mapMaybeMissing g1)
(mapMaybeMissing g2)
(zipWithMaybeMatched f)
m1 m2
Take, for example,
m1 = [(0, 'a'), (1, 'b'), (3, 'c'), (4, 'd')]
m2 = [(1, "one"), (2, "two"), (4, "three")]
merge will first "align" these maps by key:
m1 = [(0, 'a'), (1, 'b'), (3, 'c'), (4, 'd')]
m2 = [(1, "one"), (2, "two"), (4, "three")]
It will then pass the individual entries and pairs of entries
to g1, g2, or f as appropriate:
maybes = [g1 0 'a', f 1 'b' "one", g2 2 "two", g1 3 'c', f 4 'd' "three"]
This produces a Maybe for each key:
keys = 0 1 2 3 4
results = [Nothing, Just True, Just False, Nothing, Just True]
Finally, the Just results are collected into a map:
return value = [(1, True), (2, False), (4, True)]
The other tactics below are optimizations or simplifications of mapMaybeMissing for special cases. Most importantly,
dropMissing drops all the keys.
preserveMissing leaves all the entries alone.
When merge is given three arguments, it is inlined at the call site. To prevent excessive inlining, you should typically use merge to define your custom combining functions.
Examples:
unionWithKey f = merge preserveMissing preserveMissing (zipWithMatched f)intersectionWithKey f = merge dropMissing dropMissing (zipWithMatched f)differenceWith f = merge preserveMissing dropMissing (zipWithMatched f)symmetricDifference = merge preserveMissing preserveMissing (zipWithMaybeMatched $ \ _ _ _ -> Nothing)mapEachPiece f g h = merge (mapMissing f) (mapMissing g) (zipWithMatched h)WhenMatched tacticsWhen a key is found in both maps, apply a function to the key and values and maybe use the result in the merged map.
zipWithMaybeMatched :: (k -> x -> y -> Maybe z)
-> SimpleWhenMatched k x y z
When a key is found in both maps, apply a function to the key and values and use the result in the merged map.
zipWithMatched :: (k -> x -> y -> z)
-> SimpleWhenMatched k x y z
WhenMissing tacticsMap over the entries whose keys are missing from the other map, optionally removing some. This is the most powerful SimpleWhenMissing tactic, but others are usually more efficient.
mapMaybeMissing :: (k -> x -> Maybe y) -> SimpleWhenMissing k x y
mapMaybeMissing f = traverseMaybeMissing (\k x -> pure (f k x))but mapMaybeMissing uses fewer unnecessary Applicative operations.
Drop all the entries whose keys are missing from the other map.
dropMissing :: SimpleWhenMissing k x y
dropMissing = mapMaybeMissing (\_ _ -> Nothing)but dropMissing is much faster.
Preserve, unchanged, the entries whose keys are missing from the other map.
preserveMissing :: SimpleWhenMissing k x x
preserveMissing = Merge.Lazy.mapMaybeMissing (\_ x -> Just x)but preserveMissing is much faster.
Map over the entries whose keys are missing from the other map.
mapMissing :: (k -> x -> y) -> SimpleWhenMissing k x y
mapMissing f = mapMaybeMissing (\k x -> Just $ f k x)but mapMissing is somewhat faster.
Filter the entries whose keys are missing from the other map.
filterMissing :: (k -> x -> Bool) -> SimpleWhenMissing k x x
filterMissing f = Merge.Lazy.mapMaybeMissing $ \k x -> guard (f k x) *> Just xbut this should be a little faster.
(Applicative f, Monad f) => Category (WhenMissing f k)Defined in containers-0.7 · Data.Map.Internal(Applicative f, Monad f) => Monad (WhenMissing f k x)Defined in containers-0.7 · Data.Map.InternalEquivalent to ReaderT k (ReaderT x (MaybeT f)) .
(Applicative f, Monad f) => Functor (WhenMissing f k x)Defined in containers-0.7 · Data.Map.Internal(Applicative f, Monad f) => Applicative (WhenMissing f k x)Defined in containers-0.7 · Data.Map.InternalEquivalent to ReaderT k (ReaderT x (MaybeT f)) .
(Monad f, Applicative f) => Category (WhenMatched f k x)Defined in containers-0.7 · Data.Map.Internal(Monad f, Applicative f) => Monad (WhenMatched f k x y)Defined in containers-0.7 · Data.Map.InternalEquivalent to ReaderT k (ReaderT x (ReaderT y (MaybeT f)))
Functor f => Functor (WhenMatched f k x y)Defined in containers-0.7 · Data.Map.Internal(Monad f, Applicative f) => Applicative (WhenMatched f k x y)Defined in containers-0.7 · Data.Map.InternalEquivalent to ReaderT k (ReaderT x (ReaderT y (MaybeT f)))
mergeA :: (Applicative f, Ord k)=> WhenMissing f k a cWhat to do with keys in m1 but not m2
-> WhenMissing f k b cWhat to do with keys in m2 but not m1
-> WhenMatched f k a b cWhat to do with keys in both m1 and m2
-> Map k aMap m1
-> Map k bMap m2
-> f (Map k c)An applicative version of merge.
mergeA takes two WhenMissing tactics, a WhenMatched tactic and two maps. It uses the tactics to merge the maps. Its behavior is best understood via its fundamental tactics, traverseMaybeMissing and zipWithMaybeAMatched.
Consider
mergeA (traverseMaybeMissing g1)
(traverseMaybeMissing g2)
(zipWithMaybeAMatched f)
m1 m2
Take, for example,
m1 = [(0, 'a'), (1, 'b'), (3, 'c'), (4, 'd')]
m2 = [(1, "one"), (2, "two"), (4, "three")]
mergeA will first "align" these maps by key:
m1 = [(0, 'a'), (1, 'b'), (3, 'c'), (4, 'd')]
m2 = [(1, "one"), (2, "two"), (4, "three")]
It will then pass the individual entries and pairs of entries
to g1, g2, or f as appropriate:
actions = [g1 0 'a', f 1 'b' "one", g2 2 "two", g1 3 'c', f 4 'd' "three"]
Next, it will perform the actions in the actions list in order from
left to right.
keys = 0 1 2 3 4
results = [Nothing, Just True, Just False, Nothing, Just True]
Finally, the Just results are collected into a map:
return value = [(1, True), (2, False), (4, True)]
The other tactics below are optimizations or simplifications of traverseMaybeMissing for special cases. Most importantly,
dropMissing drops all the keys.
preserveMissing leaves all the entries alone.
mapMaybeMissing does not use the Applicative context.
When mergeA is given three arguments, it is inlined at the call site. To prevent excessive inlining, you should generally only use mergeA to define custom combining functions.
WhenMatched tacticsWhen a key is found in both maps, apply a function to the key and values, perform the resulting action, and maybe use the result in the merged map.
This is the fundamental WhenMatched tactic.
When a key is found in both maps, apply a function to the key and values to produce an action and use its result in the merged map.
WhenMissing tacticsTraverse over the entries whose keys are missing from the other map, optionally producing values to put in the result. This is the most powerful WhenMissing tactic, but others are usually more efficient.
Traverse over the entries whose keys are missing from the other map.
Filter the entries whose keys are missing from the other map using some Applicative action.
filterAMissing f = Merge.Lazy.traverseMaybeMissing $
\k x -> (\b -> guard b *> Just x) <$> f k xbut this should be a little faster.
Map covariantly over a WhenMissing f k x.
Map covariantly over a WhenMatched f k x y.
Map contravariantly over a WhenMissing f k _ x.
Map contravariantly over a WhenMatched f k _ y z.
Map contravariantly over a WhenMatched f k x _ z.
Along with zipWithMaybeAMatched, witnesses the isomorphism between
WhenMatched f k x y z and k -> x -> y -> f (Maybe z).
Along with traverseMaybeMissing, witnesses the isomorphism between
WhenMissing f k x y and k -> x -> f (Maybe y).