BSD-3-Clause licensed
Maintained by [email protected]
This version can be pinned in stack with:random-,6460

Module documentation for

The Haskell Standard Library

Random Number Generation


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This library provides a basic interface for (splittable) pseudo-random number generators.

The API documentation can be found here:

An older version of this library is included with GHC in the haskell98 package. This newer version is included in the Haskell Platform.

Please report bugs in the GitHub issue tracker (no longer in the GHC trac).



  • Fix support for ghc-9.2 #99
  • Fix performance regression for ghc-9.0 #101
  • Add uniformEnumM and uniformEnumRM
  • Add initStdGen #103
  • Add globalStdGen #117
  • Add runStateGenST_
  • Ensure that default implementation of ShortByteString generation uses unpinned memory. #116
  • Fix #54 with #68 - if exactly one value in the range of floating point is infinite, then uniformRM/randomR returns that value.
  • Add default implementation of uniformM that uses Generic #70
  • Random instance for CBool #77
  • Addition of TGen and TGenM #95
  • Addition of tuple instances for Random up to 7-tuple #72


  1. Breaking change which mostly maintains backwards compatibility, see “Breaking Changes” below.
  2. Support for monadic generators e.g. mwc-random.
  3. Monadic adapters for pure generators (providing a uniform monadic interface to pure and monadic generators).
  4. Faster in all cases except one by more than x18 (N.B. x18 not 18%) and some cases (depending on the type) faster by more than x1000 - see below for benchmarks.
  5. Passes a large number of random number test suites:
  6. Better quality split as judged by these tests. Again see random-quality for details on how to do this yourself.
  7. Unbiased generation of ranges.
  8. Updated tests and benchmarks.
  9. Continuous integration.

Breaking Changes

Version 1.2.0 introduces these breaking changes:

  • requires base >= 4.8 (GHC-7.10)
  • StdGen is no longer an instance of Read
  • randomIO and randomRIO were extracted from the Random class into separate functions

In addition, there may be import clashes with new functions, e.g. uniform and uniformR.


Version 1.2.0 introduces genWord64, genWord32 and similar methods to the RandomGen class. The significantly slower method next and its companion genRange are now deprecated.

Issues Addressed

Issue Number Description Comment
25 The seeds generated by split are not independent Fixed: changed algorithm to SplitMix, which provides a robust split operation
26 Add Random instances for tuples Addressed: added Uniform instances for up to 6-tuples
44 Add Random instance for Natural Addressed: added UniformRange instance for Natural
51 Very low throughput Fixed: see benchmarks below
53 incorrect distribution of randomR for floating-point numbers (*)
55 System/Random.hs:43:1: warning: [-Wtabs] Fixed: No more tabs
58 Why does random for Float and Double produce exactly 24 or 53 bits? (*)
59 read :: StdGen fails for strings longer than 6 Addressed: StdGen is no longer an instance of Read


(*) 1.2 samples more bits but does not sample every Float or Double. There are methods to do this but they have some downsides; see here for a fuller discussion.


Here are some benchmarks run on a 3.1 GHz Intel Core i7. The full benchmarks can be run using e.g. stack bench. The benchmarks are measured in milliseconds per 100,000 generations. In some cases, the performance is over x1000 times better; the minimum performance increase for the types listed below is more than x36.

Name 1.1 Mean 1.2 Mean
Float 27.819 0.305
Double 50.644 0.328
Integer 42.332 0.332
Word 40.739 0.027
Int 43.847 0.028
Char 17.009 0.462
Bool 17.542 0.027


bump for overflow bug fixes

bump for ticket 8704, build fusion

bump for bug fixes,

bumped version for float/double range bugfix