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1. random :: (Random a, RandomGen g) => g -> (a, g)

   random	System.Random

   The same as randomR, but using a default range determined by the type:

   • For bounded types (instances of Bounded, such as Char), the range is normally the whole type.
   • For floating point types, the range is normally the closed interval [0,1].
   • For Integer, the range is (arbitrarily) the range of Int.

2. random :: (Random a, RandomGen g) => g -> (a, g)

   tf-random	System.Random.TF.Instances

   No documentation available.

3. random :: MTRandom a => MTGen -> IO a

   mersenne-random	System.Random.Mersenne

   The same as randomR, but using a default range determined by the type:

   • For bounded types (instances of Bounded, such as Char), the range is normally the whole type.
   • For fractional types, the range is normally the semi-closed interval [0,1).
   • For Integer, the range is (arbitrarily) the range of Int.

4. module System.Random

   This library deals with the common task of pseudo-random number generation.

5. class Random a

   random	System.Random

   The class of types for which random values can be generated. Most instances of Random will produce values that are uniformly distributed on the full range, but for those types without a well-defined "full range" some sensible default subrange will be selected. Random exists primarily for backwards compatibility with version 1.1 of this library. In new code, use the better specified Uniform and UniformRange instead.

6. class Random a

   tf-random	System.Random.TF.Instances

   No documentation available.

7. module TextShow.System.Random

   TextShow instances for StdGen. Since: 2

8. randomIO :: (Random a, MonadIO m) => m a

   random	System.Random

   A variant of randomM that uses the global pseudo-random number generator globalStdGen.

   >>> import Data.Int
   
   >>> randomIO :: IO Int32
   -1580093805
   

   This function is equivalent to getStdRandom random and is included in this interface for historical reasons and backwards compatibility. It is recommended to use uniformM instead, possibly with the globalStdGen if relying on the global state is acceptable.

   >>> import System.Random.Stateful
   
   >>> uniformM globalStdGen :: IO Int32
   -1649127057
   

9. randomR :: (Random a, RandomGen g) => (a, a) -> g -> (a, g)

   random	System.Random

   Takes a range (lo,hi) and a pseudo-random number generator g, and returns a pseudo-random value uniformly distributed over the closed interval [lo,hi], together with a new generator. It is unspecified what happens if lo>hi, but usually the values will simply get swapped.

   >>> let gen = mkStdGen 2021
   
   >>> fst $ randomR ('a', 'z') gen
   't'
   
   >>> fst $ randomR ('z', 'a') gen
   't'
   

   For continuous types there is no requirement that the values lo and hi are ever produced, but they may be, depending on the implementation and the interval. There is no requirement to follow the Ord instance and the concept of range can be defined on per type basis. For example product types will treat their values independently:

   >>> fst $ randomR (('a', 5.0), ('z', 10.0)) $ mkStdGen 2021
   ('t',6.240232662366563)
   

   In case when a lawful range is desired uniformR should be used instead.

10. randomRIO :: (Random a, MonadIO m) => (a, a) -> m a

    random	System.Random

    A variant of randomRM that uses the global pseudo-random number generator globalStdGen

    >>> randomRIO (2020, 2100) :: IO Int
    2040
    

    Similar to randomIO, this function is equivalent to getStdRandom randomR and is included in this interface for historical reasons and backwards compatibility. It is recommended to use uniformRM instead, possibly with the globalStdGen if relying on the global state is acceptable.

    >>> import System.Random.Stateful
    
    >>> uniformRM (2020, 2100) globalStdGen :: IO Int
    2079
    

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