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module Data.Type.Witness.Specific.List.
Sum No documentation available.
Sum :: [DealStats] -> DealStatsHastructure Types No documentation available.
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Magic sum operations using Generics These classes need not be instantiated manually, as GHC can automatically prove valid instances via Generics. Only the Generic class needs to be derived (see examples).
module Grisette.Lib.Data.Functor.
Sum No documentation available.
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pseudo-boolean Data.PseudoBoolean Sum of WeightedTerm
data
Sum (f :: Type -> Type -> Type) (g :: Type -> Type -> Type) scope termrzk Free.Scoped No documentation available.
module Generic.Data.Function.Contra.
Sum No documentation available.
module Generic.Data.Function.FoldMap.
Sum No documentation available.
module Generic.Data.Function.Traverse.
Sum traverse over generic sum types. Disambiguates constructors by prepending sum tags. Note that the sum tag approach has efficiency limitations. You may design a constructor disambiguation schema which permits "incrementally" parsing, rather than parsing some whole thing then comparing to each option, which will be faster. If you wish to perform such sum tag handling yourself, but still want the free generics, Generic.Data.FOnCstr can do this for you.
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gogol-datastore Gogol.Datastore Sum of the values of the requested property. * Only numeric values will be aggregated. All non-numeric values including NULL are skipped. * If the aggregated values contain NaN, returns NaN. Infinity math follows IEEE-754 standards. * If the aggregated value set is empty, returns 0. * Returns a 64-bit integer if all aggregated numbers are integers and the sum result does not overflow. Otherwise, the result is returned as a double. Note that even if all the aggregated values are integers, the result is returned as a double if it cannot fit within a 64-bit signed integer. When this occurs, the returned value will lose precision. * When underflow occurs, floating-point aggregation is non-deterministic. This means that running the same query repeatedly without any changes to the underlying values could produce slightly different results each time. In those cases, values should be stored as integers over floating-point numbers. See: newSum smart constructor.