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Purely functional, persistent and efficient vector and hash-map data structures for Haskell
Haskell
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Data Fix constraints
benchmarks Use the Hashable typeclass, scrap passing in hash functions
tests Use the Hashable typeclass, scrap passing in hash functions
.gitignore Added .gitignore
LICENSE
README.md Renamed (hopefully for the last time) to HamtMap
Setup.hs
hamtmap.cabal Fix constraints

README.md

Hash Array Mapped Tries

One of the prominent features of the Clojure language are a set of immutable data structures with efficient manipulation operations. One of the most innovative and important is the persistent hash map based on the hash array mapped trie (HAMT).

This project is a port of this structure to Haskell, as Data.HamtMap. The interface has been kept as consistent as possible with Data.Map.

Basic usage

Here's a demo of what you can do with a HamtMap:

ghci> :m + Data.HamtMap
ghci> empty Data.HashTable.hashString
        -- an empty HamtMap (requires a key hash function)
fromList hashFn []

ghci> insert "foo" 1 it
fromList hashFn [("foo",1)]

ghci> insert "bar" 42 it
fromList hashFn [("foo",1),("bar",42)]

ghci> insert "qux" 123 it
fromList hashFn [("qux",12),("foo",1),("bar",42)]

ghci> insert "qux" 13 it  -- inserting an existing key overwrites by default
fromList hashFn [("qux",13),("foo",1),("bar",42)]

ghci> let a = it
ghci> a ! "foo"
1

ghci> a ! "baz"  -- using (!) is unsafe
*** Exception: array index out of range: element not in the map

ghci> Data.HamtMap.lookup "bar" a
Just 42

ghci> Data.HamtMap.lookup "baz" a  -- 'lookup' returns a safe Maybe
Nothing

ghci> adjust succ "foo" a  -- apply a function to a value
fromList hashFn [("qux",13),("foo",2),("bar",42)]

ghci> Data.HamtMap.map succ a  -- apply a function to all values
fromList hashFn [("qux",14),("foo",2),("bar",43)]

ghci> keys a
["qux","foo","bar"]

ghci> elems a
[13,1,42]

ghci> fromList Data.HashTable.hashString [("a", 1), ("b", 2), ("c", 3)]
fromList hashFn [("b",2),("c",3),("a",1)]

ghci> toList it
[("b",2),("c",3),("a",1)]

Installation

To try it yourself, just do the usual:

$ runghc Setup.hs configure --user
$ runghc Setup.hs build
$ runghc Setup.hs install

Performance

The single-element operations for the hash map have logarithmic asymtotic runtime complexity. However, it is implemented as a 32-ary tree, which means it never exceeds a depth of 7 nodes, so you can treat them as constant-time operations (for relatively large constants).

How it works

I wrote this code after reading the following explanatory blog posts on how the Clojure version works. They should also provide a decent birds-eye overview of my Haskell implementation.

To do

  • Match Data.Map in completeness
  • Performance tuning
    • Efficient implementations of (//), etc. based on fromList
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