ptrie alternatives and similar packages
Based on the "Data Structures" category.
Alternatively, view ptrie alternatives based on common mentions on social networks and blogs.
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gods
GoDS (Go Data Structures) - Sets, Lists, Stacks, Maps, Trees, Queues, and much more -
go-datastructures
A collection of useful, performant, and threadsafe Go datastructures. -
golang-set
A simple, battle-tested and generic set type for the Go language. Trusted by Docker, 1Password, Ethereum and Hashicorp. -
gocache
☔️ A complete Go cache library that brings you multiple ways of managing your caches -
boomfilters
Probabilistic data structures for processing continuous, unbounded streams. -
gostl
Data structure and algorithm library for go, designed to provide functions similar to C++ STL -
hyperloglog
HyperLogLog with lots of sugar (Sparse, LogLog-Beta bias correction and TailCut space reduction) brought to you by Axiom -
trie
Data structure and relevant algorithms for extremely fast prefix/fuzzy string searching. -
ttlcache
An in-memory cache with item expiration and generics [Moved to: https://github.com/jellydator/ttlcache] -
go-geoindex
Go native library for fast point tracking and K-Nearest queries -
hilbert
Go package for mapping values to and from space-filling curves, such as Hilbert and Peano curves. -
Bloomfilter
Face-meltingly fast, thread-safe, marshalable, unionable, probability- and optimal-size-calculating Bloom filter in go -
go-adaptive-radix-tree
Adaptive Radix Trees implemented in Go -
goconcurrentqueue
Go concurrent-safe, goroutine-safe, thread-safe queue -
cuckoo-filter
Cuckoo Filter go implement, better than Bloom Filter, configurable and space optimized 布谷鸟过滤器的Go实现,优于布隆过滤器,可以定制化过滤器参数,并进行了空间优化 -
ring
Package ring provides a high performance and thread safe Go implementation of a bloom filter. -
go-rquad
:pushpin: State of the art point location and neighbour finding algorithms for region quadtrees, in Go -
set
A simple Set data structure implementation in Go (Golang) using LinkedHashMap. -
nan
Zero allocation Nullable structures in one library with handy conversion functions, marshallers and unmarshallers -
goset
Set is a useful collection but there is no built-in implementation in Go lang.
Access the most powerful time series database as a service
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README
Trie (Prefix tree)
This library is compatible with Go 1.11+
Please refer to [CHANGELOG.md
](CHANGELOG.md) if you encounter breaking changes.
Motivation
The goal of this project is to provide serverless prefix tree friendly implementation. where one function can easily building tree and publishing to some cloud storge. Then the second load trie to perform various operations.
Introduction
A trie (prefix tree) is a space-optimized tree data structure in which each node that is merged with its parent. Unlike regular trees (where whole keys are from their beginning up to the point of inequality), the key at each node is compared chunk by chunk,
Prefix tree has the following application:
- text document searching
- rule based matching
- constructing associative arrays for string keys
Character comparision complexity:
- Brute Force: O(d n k)
- Prefix Trie: O(d log(k))
Where
- d: number of characters in document
- n: number of keywords
- k: average keyword length
Usage
trie := ptrie.New()
for key, value := pairs {
if err = trie.Put(key, value);err != nil {
log.Fatal(err)
}
}
//...
has := trie.Has(key)
value, has := trie.Get(key)
//...
matched := trie.MatchAll(input, func(key []byte, value interface{}) bool {
fmt.Printf("matched: key: %s, value %v\n", key, value)
return true
})
- Building
trie := ptrie.New()
for key, value := pairs {
if err = trie.Put(key, value);err != nil {
log.Fatal(err)
}
}
writer := new(bytes.Buffer)
if err := trie.Encode(writer);err != nil {
log.Fatal(err)
}
encoded := write.Bytes()
//write encode data
- Loading
//V type can be any type
var v *V
trie := ptrie.New()
trie.UseType(reflect.TypeOf(v))
if err := trie.Decode(reader);err != nil {
log.Fatal(err)
}
- Traversing (range map)
trie.Walk(func(key []byte, value interface{}) bool {
fmt.Printf("key: %s, value %v\n", key, value)
return true
})
- Lookup
has := trie.Has(key)
value, has := trie.Get(key)
- MatchPrefix
var input []byte
...
matched := trie.MatchPrefix(input, func(key []byte, value interface{}) bool {
fmt.Printf("matched: key: %s, value %v\n", key, value)
return true
})
- MatchAll
var input []byte
...
matched := trie.MatchAll(input, func(key []byte, value interface{}) bool {
fmt.Printf("matched: key: %s, value %v\n", key, value)
return true
})
Benchmark
The benchmark count all words that are part of the following extracts:
[Lorem Ipsum](test/lorem.txt)
- Short: avg line size: 20, words: 13
- Long: avg line size: 711, words: 551
Benchmark_LoremBruteForceShort-8 500000 3646 ns/op
Benchmark_LoremTrieShort-8 500000 2376 ns/op
Benchmark_LoremBruteForceLong-8 1000 1612877 ns/op
Benchmark_LoremTrieLong-8 10000 119990 ns/op
[Hamlet](test/hamlet.txt)
- Short: avg line size: 20, words: 49
- Long: avg line size: 41, words: 105
Benchmark_HamletBruteForceShort-8 30000 44306 ns/op
Benchmark_HamletTrieShort-8 100000 18530 ns/op
Benchmark_HamletBruteForceLong-8 10000 226836 ns/op
Benchmark_HamletTrieLong-8 50000 39329 ns/op
Code coverage
License
The source code is made available under the terms of the Apache License, Version 2, as stated in the file LICENSE
.
Individual files may be made available under their own specific license, all compatible with Apache License, Version 2. Please see individual files for details.
Credits and Acknowledgements
Library Author: Adrian Witas
*Note that all licence references and agreements mentioned in the ptrie README section above
are relevant to that project's source code only.