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Within Stackage Nightly 2025-10-08 (ghc-9.12.2)

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  1. offsetBytes :: Int -> StringBuffer -> StringBuffer

    ghc GHC.Data.StringBuffer

    Return a StringBuffer with the first n bytes removed. Warning: If there aren't enough characters, the returned StringBuffer will be invalid and any use of it may lead to undefined behavior. The result shares the same buffer as the original.

  2. fromSet :: (Key -> a) -> Word64Set -> Word64Map a

    ghc GHC.Data.Word64Map.Internal

    Build a map from a set of keys and a function which for each key computes its value.

    fromSet (\k -> replicate k 'a') (Data.Word64Set.fromList [3, 5]) == fromList [(5,"aaaaa"), (3,"aaa")]
    fromSet undefined Data.Word64Set.empty == empty
    

  3. keysSet :: Word64Map a -> Word64Set

    ghc GHC.Data.Word64Map.Internal

    The set of all keys of the map.

    keysSet (fromList [(5,"a"), (3,"b")]) == Data.Word64Set.fromList [3,5]
    keysSet empty == Data.Word64Set.empty
    

  4. fromSet :: (Key -> a) -> Word64Set -> Word64Map a

    ghc GHC.Data.Word64Map.Lazy

    Build a map from a set of keys and a function which for each key computes its value.

    fromSet (\k -> replicate k 'a') (Data.Word64Set.fromList [3, 5]) == fromList [(5,"aaaaa"), (3,"aaa")]
    fromSet undefined Data.Word64Set.empty == empty
    

  5. keysSet :: Word64Map a -> Word64Set

    ghc GHC.Data.Word64Map.Lazy

    The set of all keys of the map.

    keysSet (fromList [(5,"a"), (3,"b")]) == Data.Word64Set.fromList [3,5]
    keysSet empty == Data.Word64Set.empty
    

  6. fromSet :: (Key -> a) -> Word64Set -> Word64Map a

    ghc GHC.Data.Word64Map.Strict

    Build a map from a set of keys and a function which for each key computes its value.

    fromSet (\k -> replicate k 'a') (Data.Word64Set.fromList [3, 5]) == fromList [(5,"aaaaa"), (3,"aaa")]
    fromSet undefined Data.Word64Set.empty == empty
    

  7. keysSet :: Word64Map a -> Word64Set

    ghc GHC.Data.Word64Map.Strict

    The set of all keys of the map.

    keysSet (fromList [(5,"a"), (3,"b")]) == Data.Word64Set.fromList [3,5]
    keysSet empty == Data.Word64Set.empty
    

  8. fromSet :: (Key -> a) -> Word64Set -> Word64Map a

    ghc GHC.Data.Word64Map.Strict.Internal

    Build a map from a set of keys and a function which for each key computes its value.

    fromSet (\k -> replicate k 'a') (Data.Word64Set.fromList [3, 5]) == fromList [(5,"aaaaa"), (3,"aaa")]
    fromSet undefined Data.Word64Set.empty == empty
    

  9. keysSet :: Word64Map a -> Word64Set

    ghc GHC.Data.Word64Map.Strict.Internal

    The set of all keys of the map.

    keysSet (fromList [(5,"a"), (3,"b")]) == Data.Word64Set.fromList [3,5]
    keysSet empty == Data.Word64Set.empty
    

  10. module GHC.Data.Word64Set

    Finite Int Sets

    The Word64Set type represents a set of elements of type Int. For a walkthrough of the most commonly used functions see their sets introduction. These modules are intended to be imported qualified, to avoid name clashes with Prelude functions, e.g.
    import Data.Word64Set (Word64Set)
    import qualified Data.Word64Set as Word64Set
    

    Performance information

    Many operations have a worst-case complexity of <math>. This means that the operation can become linear in the number of elements with a maximum of <math> -- the number of bits in an Int (32 or 64).

    Implementation

    The implementation is based on big-endian patricia trees. This data structure performs especially well on binary operations like union and intersection. However, my benchmarks show that it is also (much) faster on insertions and deletions when compared to a generic size-balanced set implementation (see Data.Set).
    • Chris Okasaki and Andy Gill, "Fast Mergeable Integer Maps", Workshop on ML, September 1998, pages 77-86, http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.37.5452
    • D.R. Morrison, "PATRICIA -- Practical Algorithm To Retrieve Information Coded In Alphanumeric", Journal of the ACM, 15(4), October 1968, pages 514-534.
    Additionally, this implementation places bitmaps in the leaves of the tree. Their size is the natural size of a machine word (32 or 64 bits) and greatly reduces the memory footprint and execution times for dense sets, e.g. sets where it is likely that many values lie close to each other. The asymptotics are not affected by this optimization.

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