https://github.com/timtadh/data-structures

Go datastructures.
https://github.com/timtadh/data-structures

arraylist avl avl-tree btree data-structures error-handling exceptions hash-tables hashtable immutable linear-hash-table linked-list priority-queue ternary-search-trie tree trie

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Go datastructures.

• Host: GitHub
• URL: https://github.com/timtadh/data-structures
• Owner: timtadh
• License: other
• Created: 2013-12-11T16:13:38.000Z (about 11 years ago)
• Default Branch: master
• Last Pushed: 2022-10-07T08:55:56.000Z (about 2 years ago)
• Last Synced: 2024-08-01T13:32:50.079Z (4 months ago)
• Topics: arraylist, avl, avl-tree, btree, data-structures, error-handling, exceptions, hash-tables, hashtable, immutable, linear-hash-table, linked-list, priority-queue, ternary-search-trie, tree, trie
• Language: Go
• Homepage: http://hackthology.com/data-structures/
• Size: 1.19 MB
• Stars: 415
• Watchers: 24
• Forks: 82
• Open Issues: 3
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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• awesome-ccamel - timtadh/data-structures - Go datastructures. (Go)

README

        
# Go Data Structures

by Tim Henderson ([email protected])

Copyright 2013, Licensed under the BSD 3-clause license. Please reach out to me

directly if you require another licensing option. I am willing to work with you.

## Purpose

To collect many important data structures for usage in go programs. Golang's

standard library lacks many useful and important structures. This library

attempts to fill the gap. I have implemented data-structure's as I have needed

them. If there is a missing structure or even just a missing (or incorrect)

method open an issue, send a pull request, or send an email patch.

The library also provides generic

[types](https://godoc.org/github.com/timtadh/data-structures/types) to allow the

user to swap out various data structures transparently. The interfaces provide

operation for adding, removing, retrieving objects from collections as well as

iterating over the collection using functional iterators.

The tree sub-package provides a variety of generic tree traversals. The tree

traversals and other iterators in the package use a functional iteration

technique [detailed on my blog](

http://hackthology.com/functional-iteration-in-go.html).

I hope you find my library useful. If you are using it drop me a line I would

love to hear about it.

# Current Collection

[![GoDoc](https://godoc.org/github.com/timtadh/data-structures?status.svg)](https://godoc.org/github.com/timtadh/data-structures)

## Lists

### Doubly Linked List [`linked.LinkedList`](https://godoc.org/github.com/timtadh/data-structures/linked#LinkedList)

A simple an extensible doubly linked list. It is

[Equatable](https://godoc.org/github.com/timtadh/data-structures/types#Equatable)

[Sortable](https://godoc.org/github.com/timtadh/data-structures/types#Sortable),

and [Hashable](https://godoc.org/github.com/timtadh/data-structures/types#Hashable)

as are the [Node](https://godoc.org/github.com/timtadh/data-structures/linked#Node)s.

### Array List [`list.List`](https://godoc.org/github.com/timtadh/data-structures/list#List)

Similar to a Java ArrayList or a Python or Ruby "list". There is a version

(called Sortable) which integrates with the `"sort"` package from the standard

library.

### Sorted Array List [`list.Sorted`](https://godoc.org/github.com/timtadh/data-structures/list#Sorted)

Keeps the ArrayList in sorted order for you.

### Sorted Set [`set.SortedSet`](https://godoc.org/github.com/timtadh/data-structures/set#SortedSet)

Built on top of `*list.Sorted`, it provides basic set operations. With

`set.SortedSet` you don't have to write code re-implementing sets with the

`map[type]` datatype. Supports: intersection, union, set difference and overlap

tests.

### Map Set [`set.MapSet`](https://godoc.org/github.com/timtadh/data-structures/set#MapSet)

Construct a

[`types.Map`](https://godoc.org/github.com/timtadh/data-structures/types#Map)

from any [`types.Set`](https://godoc.org/github.com/timtadh/data-structures/types#Set).

### Set Map [`set.SetMap`](https://godoc.org/github.com/timtadh/data-structures/set#SetMap)

Construct a set from any

[`types.Map`](https://godoc.org/github.com/timtadh/data-structures/types#Map).

### Unique Deque [`linked.UniqueDeque`](https://godoc.org/github.com/timtadh/data-structures/linked#UniqueDeque)

A double ended queue that only allows unique items inside. Constructed from a

doubly linked list and a linear hash table.

### Fixed Size Lists

Both `list.List` and `list.Sorted` have alternative constructors which make them

fixed size. This prevents them from growing beyond a certain size bound and is

useful for implementing other data structures on top of them.

### Serialization

`list.List`, `list.Sorted`, and `set.SortedSet` all can be serialized provided

their contents can be serialized. They are therefore suitable for being sent

over the wire. See this

[example](https://github.com/timtadh/data-structures/blob/master/set/example_serialize_test.go)

for how to use the serialization.

## Heaps and Priority Queues

### Binary Heap [`heap/Heap`](https://godoc.org/github.com/timtadh/data-structures/heap#Heap)

This is a binary heap for usage as a priority queue. The priorities are given to

items in the queue on insertion and cannot be changed after insertion. It can be

used as both a min heap and a max heap.

### Unique Priority Queue [`heap/UniquePQ`](https://godoc.org/github.com/timtadh/data-structures/heap#UniquePQ)

A priority queue which only allows unique entries.

## Trees

### AVL Tree [`tree/avl.AvlTree`](https://godoc.org/github.com/timtadh/data-structures/tree/avl#AvlTree)

An [AVL Tree](https://en.wikipedia.org/wiki/AVL_tree) is a height balanced

binary search tree. Insertion and retrieval are both O(log(n)) where n is the

number items in the tree.

### Immutable AVL Tree [`tree/avl.ImmutableAvlTree`](https://godoc.org/github.com/timtadh/data-structures/tree/avl#ImmutableAvlTree)

This version of the classic is immutable and should be thread safe due to

immutability. However, there is a performance hit:

    BenchmarkAvlTree           10000            166657 ns/op

    BenchmarkImmutableAvlTree   5000            333709 ns/op

### Ternary Search Trie [`trie.TST`](https://godoc.org/github.com/timtadh/data-structures/trie#TST)

A [ternary search trie](

http://hackthology.com/ternary-search-tries-for-fast-flexible-string-search-part-1.html)

is a symbol table specialized to byte strings.  Ternary Search Tries (TSTs)

are a particularly fast version of the more common R-Way Trie. They utilize less

memory allowing them to store more data while still retaining all of the

flexibility of the R-Way Trie. TSTs can be used to build a suffix tree for full

text string indexing by storing every suffix of each string in addition to the

string. However, even without storing all of the suffixes it is still a great

structure for flexible prefix searches. For instance, TSTs can be used to

implement extremely fast auto-complete functionality.

### B+Tree [`tree/bptree.BpTree`](https://godoc.org/github.com/timtadh/data-structures/tree/bptree)

A

[B+Tree](http://hackthology.com/lessons-learned-while-implementing-a-btree.html)

is a general symbol table usually used for database indices. This implementation

is not currently thread safe. However, unlike many B+Trees it fully supports

duplicate keys making it suitable for use as a Multi-Map. There is also a

variant which has unique keys, `bptree.BpMap`. B+Trees are storted and efficient

to iterate over making them ideal choices for storing a large amount of data

in sorted order. For storing a **very** large amount of data please utilize the

fs2 version, [fs2/bptree](https://github.com/timtadh/fs2#b-tree). fs2 utilizes

memory mapped files in order to allow you to store more data than your computer

has RAM.

## Hash Tables

### Separate Chaining Hash Table [`hashtable.Hash`](https://godoc.org/github.com/timtadh/data-structures/hashtable#Hash)

See `hashtable/hashtable.go`. An implementation of the classic hash table with

separate chaining to handle collisions.

### Linear Hash Table with AVL Tree Buckets [`hashtable.LinearHash`](https://godoc.org/github.com/timtadh/data-structures/hashtable#LinearHash)

See `hashtables/linhash.go`. An implementation of [Linear

Hashing](http://hackthology.com/linear-hashing.html), a technique usually used

for secondary storage hash tables. Often employed by databases and file systems

for hash indices. This version is mostly instructional see the [accompanying

blog post](

http://hackthology.com/an-in-memory-go-implementation-of-linear-hashing.html).

If you want a disk backed version check out my

[file-structures](https://github.com/timtadh/file-structures) repository. See

the `linhash` directory.

## Exceptions, Errors, and Testing

### Errors [`errors`](https://godoc.org/github.com/timtadh/data-structures/errors)

By default, most errors in Go programs to not track where they were created.

Many programmers quickly discover they need to have stack traces associated with

their errors. This is a light weight package which adds stack traces to errors.

It also provides a very very simple logging function that reports where in your

code your printed out the log. This is not a full featured logging solution but

rather a replacement for using fmt.Printf when debugging.

### Test Support [`test`](https://godoc.org/github.com/timtadh/data-structures/test)

The test package provides two minimal assertions and a way to get random strings

and data. It also seeds the math/rand number generator. I consider this to the

bare minimum of what is often needed when testing go code particularly

data-structures. Since this package seeks to be entirely self contained with no

dependencies no external testing package is used. This package is slowly being

improved to encompass more common functionality between the different tests.

### Exceptions as a Library [`exc`](https://github.com/timtadh/data-structures/tree/master/exc)

- [![GoDoc](https://godoc.org/github.com/timtadh/data-structures/exc?status.svg)](https://godoc.org/github.com/timtadh/data-structures/exc)

- [Explanation of Implementation](http://hackthology.com/exceptions-for-go-as-a-library.html)

- [Explanation of Inheritance](http://hackthology.com/object-oriented-inheritance-in-go.html)

The [`exc`](https://github.com/timtadh/data-structures/tree/master/exc) package

provides support for exceptions. They work very similarly to the way unchecked

exceptions work in Java. They are built on top of the built-in `panic` and

`recover` functions. See the README in the package for more information or

checkout the documentation. They should play nice with the usual way of handling

errors in Go and provide an easy way to create public APIs which return errors

rather than throwing these non-standard exceptions.

## Benchmarks

**Note**: these benchmarsk are fairly old and probably not easy to understand.

Look at the relative difference not the absolute numbers as they are misleading.

Each benchmark does many operations per "test" which makes it difficult to

compare these numbers to numbers found elsewhere.

Benchmarks Put + Remove

    $ go test -v -bench '.*' \

    >   github.com/timtadh/data-structures/hashtable

    >   github.com/timtadh/data-structures/tree/...

    >   github.com/timtadh/data-structures/trie

    BenchmarkGoMap             50000             30051 ns/op

    BenchmarkMLHash            20000             78840 ns/op

    BenchmarkHash              20000             81012 ns/op

    BenchmarkTST               10000            149985 ns/op

    BenchmarkBpTree            10000            185134 ns/op

    BenchmarkAvlTree           10000            193069 ns/op

    BenchmarkImmutableAvlTree   5000            367602 ns/op

    BenchmarkLHash              1000           2743693 ns/op

Benchmarks Put

    BenchmarkGoMap            100000             22036 ns/op

    BenchmarkMLHash            50000             52104 ns/op

    BenchmarkHash              50000             53426 ns/op

    BenchmarkTST               50000             69852 ns/op

    BenchmarkBpTree            20000             76124 ns/op

    BenchmarkAvlTree           10000            142104 ns/op

    BenchmarkImmutableAvlTree  10000            302196 ns/op

    BenchmarkLHash              1000           1739710 ns/op

The performance of the in memory linear hash (MLHash) is slightly improved since

the [blog post](

http://hackthology.com/an-in-memory-go-implementation-of-linear-hashing.html) do

to the usage of an AVL Tree `tree/avltree.go` instead of an unbalanced binary

search tree.

# Related Projects

- [fs2](https://github.com/timtadh/fs2) Memory mapped datastructures. A B+Tree,

  a list, and a platform for implementing more.

- [file-structures](https://github.com/timtadh/file-structures) The previous

  version of fs2 of disk based file-structures. Also includes a linear virtual

  hashing implementation.