Every so often someone bemoans the space leaks that can arise due to Haskell’s laziness. A frequently touted remedy is to make data stricter by turning on BangPatterns
, by defining data structures with explicitly strict fields, or by creating implicitly strict fields with the StrictData
extension. Each of these approaches leaves something to be desired. In this article I’ll explain how the approaches work, what they leave to be desired, and a suggest a reasonably general alternative. The alternative seems lightweight enough for Haskell programmers to adopt when they define strict data structures.
Consider the function pairFoldBad
:
pairFoldBad :: (Integer, Integer)
= foldl' f (0, 0) [1..million]
pairFoldBad where f (count, theSum) x = (count + 1, theSum + x)
Strict foldl'
was the correct thing to use here, rather than lazy foldl
, so why is the function bad? Because each pair component (count
and theSum
) is not necessarily an evaluated Integer
, merely a thunk which can be evaluated to an Integer
. Each time f
processes a list element x
the thunk count
has a + 1
operation added on top of it and the thunk theSum
has a + x
operation added on top of it. After foldl'
has finished, the return value of pairFoldBad
will be a pair of two thunks, each one million elements deep! In other words, it has a space leak.
A typical solution is to use bang patterns to make sure count
and theSum
are evaluated on the way in to f
, as in pairFoldBangs
.
pairFoldBangs :: (Integer, Integer)
= foldl' f (0, 0) [1..million]
pairFoldBangs where f (!count, !theSum) x = (count + 1, theSum + x)
Each time around the loop f
returns two thunks of depth 1. The subsequent call to f
takes them as arguments. The bang patterns (i.e. the !
symbols) evaluate each of the thunks to evaluated Integer
s. The overall return value of the foldl'
is a pair of depth 1 thunks.
This does the job. It’s a little bit weird that f
produces thunks of depth 1 because that means the foldl'
produces thunks of depth 1 and we really want evaluated Integer
s. They are evaluated immediately to Integers
as soon as we use them and there’s no space leak but it feels like we’re doing something not exactly right.
An alternative that produces a pair of evaluated Integer
s is pairFoldBangsAwkward
. It ensures that the pair components are evaluated on the way out (i.e. when the pair is created) not on the way in (i.e. when the pair is inspected).
pairFoldBangsAwkward :: (Integer, Integer)
= foldl' f (0, 0) [1..million]
pairFoldBangsAwkward where f (count, theSum) x = let !count' = count + 1
!theSum' = theSum + x
in (count', theSum')
This form is rather unwieldy though. No less unwieldy is use of the strict function application operator $!
:
...
where f (count, theSum) x = ((,) $! count + 1) $! theSum + x
The major drawback of using BangPatterns
to solve this problem is that we have to remember to do so! The type system does not guide us to write our program correctly. The program is type correct even if we omit all the bang patterns.
To get some help from the type system we can switch out Haskell’s standard pair type for one we define ourselves, with strict fields:
data StrictPair a b = StrictPair !a !b
Then when we write pairFoldStrictPair
as below there is no space leak.
pairFoldStrictPair :: StrictPair Integer Integer
= foldl' f (StrictPair 0 0) [1..million]
pairFoldStrictPair where f (StrictPair count theSum) x = StrictPair (count + 1) (theSum + x)
Why is there no space leak? This code looks exactly the same as the original problematic code pairFoldBad
, except we are using the StrictPair
type we defined ourselves instead of Haskell’s built-in pair. Why is it different? It is different because whenever a value is constructed using a constructor with a strict field (i.e. a field with a !
in front of it in the data
declaration, such as the fields of StrictPair
above) the compiler inserts code to evaluate that field. In the case of pairFoldStrictPair
the code that is generated is the same as if we had written the desugared form pairFoldStrictPair_Desugared
below.
pairFoldStrictPair_Desugared :: StrictPair Integer Integer
= foldl' f (StrictPair 0 0) [1..million]
pairFoldStrictPair_Desugared where f (StrictPair count theSum) x = let !count' = count + 1
!theSum' = theSum + x
in StrictPair count' theSum'
This is helpful: we now cannot avoid being strict. If we use the StrictPair
type then we can’t forget to evaluate the components.
The major drawback of defining strict data types to replace the more familiar lazy ones is that they really are completely different types with completely different associated libraries (if any). We can’t use the standard fst
and snd
functions on StrictPair
, for example (although libraries do exist that provide this functionality). It is necessary to explicitly convert back and forth between (,)
and StrictPair
.
A further problem with strict data fields is that users often think that they provide more benefit than the reality. For example, from the above we know not to write maybeFoldBad
:
maybeFoldBad :: (Integer, Maybe Integer)
= foldl' f (0, Nothing) [1..million]
maybeFoldBad where f (i, Nothing) x = (i + 1, Just x)
Just j) x = (i + 2, Just (j + x)) f (i,
Perhaps we should try writing it with a StrictPair
instead:
maybeFoldStillBad :: StrictPair Integer (Maybe Integer)
= foldl' f (StrictPair 0 Nothing) [1..million]
maybeFoldStillBad where f (StrictPair i Nothing) x = StrictPair (i + 1) (Just x)
StrictPair i (Just j)) x = StrictPair (i + 2) (Just (j + x)) f (
This is still no good! The problem is that although the Maybe Integer
in the second component of the StrictPair
is strictly evaluated that only means that evaluating the constructor of the StrictPair
evaluates the constructor of the Maybe
. The payload of the Just
is not evaluated so we build up a layer of thunk each time around the loop.
It is common in the Haskell world to see strict data field definitions like
data MyData = MyData { field1 :: !String
field2 :: ![Double]
, field3 :: !(Maybe Bool)
, }
Those strict fields probably don’t do what the author hoped! They are almost entirely pointless. The bang annotations on the String
and list mean that those fields are only evaluated one cons cell deep. The tail of the data structure is left unevaluated, as is the first element. Similarly the Maybe Bool
is only evaluated to a Nothing
or Just
. If it’s the latter then its payload is unevaluated.
Having noted this caveat we can find a way of addressing the problem in our case. maybeFoldBangs
is just too painful to write by hand, and besides, we might leave out a bang accidentally. Instead we can repeat the strict data type creation process and define StrictMaybe
(indeed this has already been done for us) and write maybeFoldStrictMaybe
, a function without space leaks.
maybeFoldBangs :: (Integer, Maybe Integer)
= foldl' f (0, Nothing) [1..million]
maybeFoldBangs where f (!i, Nothing) x = (i + 1, Just x)
!i, Just !j) x = (i + 2, Just (j + x))
f (
data StrictMaybe a = StrictNothing | StrictJust !a
maybeFoldStrictMaybe :: StrictPair Integer (StrictMaybe Integer)
= foldl' f (StrictPair 0 StrictNothing) [1..million]
maybeFoldStrictMaybe where f (StrictPair i StrictNothing) x = StrictPair (i + 1) (StrictJust x)
StrictPair i (StrictJust j)) x = StrictPair (i + 2) (StrictJust (j + x)) f (
This works fine, but we’re going down a path where we will have to deal with two universes of data types: one lazy universe and one strict universe.
Can we do better than two distinct universes? Yes, I think we can! Let’s define a newtype
Strict
with which we will represent the invariant: “when it is evaluated all its immediate children are evaluated too”. By way of convenience we can define a typeclass Strictly
to allow us to create Strict
values and a pattern synonym Strict
to allow us to extract values from the newtype
(we should be careful with the actual constructor because it should be used only in ways which preserve the invariant).
-- Any value of `Strict` should satisfy the invariant that when it is
-- evaluated then all its immediate children are evaluated too.
--
-- The constructor is "unsafe" in the sense that if you don't ensure
-- the invariant holds when you use it then you will violate the
-- expectations of the consumer.
newtype Strict a = MkStrictUnsafe a
pattern Strict a <- MkStrictUnsafe a
class Strictly a where
strict :: a -> Strict a
instance Strictly (a, b) where
-- This is a safe use of MkStrictUnsafe because it satisfies the
-- invariant! We know a and b are evaluated at the point we
-- construct the pair.
!a, !b) = MkStrictUnsafe (a, b) strict (
Now let’s see an example of using our “Strict
pair” to write a pair fold. In pairFoldStrict
the Strict
type guides us to write correct, space leak free, code, which was the benefit of StrictPair
. On the other hand we don’t have the downside of StrictPair
: there is no new data type. We can interoperate freely with the existing ecosystem!
pairFoldStrict :: Strict (Integer, Integer)
= foldl' f (strict (0, 0)) [1..million]
pairFoldStrict where f (Strict (count, theSum)) x = strict (count + 1, theSum + x)
We can also freely compose Strict
types. After defining a standard Strictly
instance for Maybe
the fold with Maybe
can be written, space leak free, as maybeFoldStrict
.
instance Strictly (Maybe a) where
= \case
strict -- This is a safe use of MkStrictUnsafe because it satisfies
-- the invariant. Nothing has no children. Just has one child
-- which we know is evaluated when we construct the Strict Maybe.
Nothing -> MkStrictUnsafe Nothing
Just !x -> MkStrictUnsafe (Just x)
maybeFoldStrict :: Strict (Integer, Strict (Maybe Integer))
= foldl' f (strict (0, strict Nothing)) [1..million]
maybeFoldStrict where f (Strict (i, Strict Nothing)) x = strict (i + 1, strict (Just x))
Strict (i, Strict (Just j))) x = strict (i + 2, strict (Just (j + x))) f (
Strict
buy us in practice?Strict
could buy us the ability to conveniently define strict nested data types without requiring a parallel universe of strict types. We now know that writing
data MyData = MyData
field1 :: !(Either Int Bool)
{ field2 :: !(Maybe Double, Data.Map.Strict.Map Int Float) ,
doesn’t make a data type as strict as we probably hoped. Instead of the parallel universe version
data MyData = MyData
field1 :: !(StrictEither Int Bool)
{ field2 :: !(StrictPair (StrictMaybe Double)
,Data.Map.Strict.Map Int Float)) (
we can use Strict
with the existing universe of data types
data MyData = MyData
field1 :: !(Strict (Either Int Bool))
{ field2 :: !(Strict (Strict (Maybe Double),
,Data.Map.Strict.Map Int Float))
If strict
is inlined then the compiler ought to be able to determine whether constructor arguments have already been evaluated and thus avoid redundantly evaluating them again.
New 2020-11-04
Although inlining strict
allows us to avoid redundant evaluations when constructing I don’t think the simple form above avoids redundant evaluation when destructing. For example, if we write
case strictMaybe of
Strict (Just x) -> let !x' = x in f x'
...
then we would like the compiler to be able to elide the evaluation of x
, as below, because, given our implementation, x
has already been evaluated.
case strictMaybe of
Strict (Just x) -> f x
...
To achieve efficient destruction we need to use a more complicated, and somewhat hairy, setup. The class becomes
class Strictly a where
data Strict a
strict :: a -> Strict a
matchStrict :: Strict a -> a
unstrict :: Strict a -> a
and the Maybe a
instance becomes
instance Strictly (Maybe a) where
newtype Strict (Maybe a) = StrictMaybe (Data.Strict.Maybe a)
= unsafeCoerce $ case x of
strict x Nothing -> x
Just !_ -> x
StrictMaybe x) = case x of
matchStrict (Data.Strict.Just j -> Just j
Data.Strict.Nothing -> Nothing
= unsafeCoerce
unstrict
pattern Strict :: Strictly a => a -> Strict a
pattern Strict x <- (matchStrict->x)
Note that Strict (Maybe a)
is now a separate data type to Maybe a
, but representationally equivalent, so we can unsafeCoerce
between them at zero run time cost. How do we use this class and its methods?
To create a Strict (Maybe a)
we use strict :: Maybe a -> Strict (Maybe a)
. The contents (if any) of the Maybe a
are evaluated but nothing new is allocated. If strict
is inlined and the compiler knows that the contents are already evaluated, then the strict
call should compile to a no-op!
To use a Strict (Maybe a)
we do one of two things:
If we simply want to unwrap the Maybe a
and pass it to another function then we can use unstrict
, which is a no-op!
If we want to match on the contents of the Maybe a
then we use the Strict
pattern, for example:
case sm of
Strict (Just a) -> ...
Strict Nothing -> ...
The Strict
pattern is implemented in terms of the function matchStrict
. If matchStrict
is inlined then a case-of-case transformation will eliminate the allocation and make matchStrict
a no-op!
The new setup is hairy because it requires us to be very careful with unsafePerformIO
. However, I believe it gives us a convenient API to strict data types at zero additional run time cost.
Strict
buy us?I don’t see how Strict
could help much with large lazy data structures such as lists (including String
s). The only way that I can see to use Strict
with standard lists whilst satisfying its invariant would be to walk the whole list, which is prohibitively inefficient. Instead I recommend not using large lazy data structures anywhere one desires strictness. Instead use strict data structures such as strict Text
, ByteString
, Map
, Vector
or Array
(I’m not sure of the strictness characteristics of Seq
and I haven’t validated the strictness guarantees of Vector
or Array
. That will have to be another article.)
Defining strict fields that contain lazy types is almost completely pointless:
data MyData = MyData { field1 :: !String
field2 :: ![Double]
, field3 :: !(Maybe Bool)
, }
As an alternative, it is an open question whether Strict
, as defined in this article, can prove general enough to achieve widespread use or whether the solution is a parallel universe of strict data types.
Have you seen or used anything like Strict
before? If so please contact me.