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sonic's Introduction

Sonic

A blazingly fast JSON serializing & deserializing library, accelerated by JIT(just-in-time compiling) and SIMD(single-instruction-multi-data).

Benchmarks

For all sizes of json and all scenes of usage, Sonic performs almost best.

  • Small (400B, 11 keys, 3 levels) small benchmarks
  • Medium (110KB, 300+ keys, 3 levels, with many quoted-json values) medium benchmarks
  • Large (550KB, 10000+ key, 6 levels) large benchmarks

For a 13KB TwitterJson(cpu i9-9880H, goarch amd64), Sonic is 1.5x faster than json-iterator in decoding, 2.5x faster in encoding.

BenchmarkDecoder_Generic_Sonic-16                          10000             54309 ns/op         240.01 MB/s       46149 B/op        303 allocs/op
BenchmarkDecoder_Generic_StdLib-16                         10000            135268 ns/op          96.36 MB/s       50899 B/op        772 allocs/op
BenchmarkDecoder_Generic_JsonIter-16                       10000             96701 ns/op         134.80 MB/s       55791 B/op       1068 allocs/op
BenchmarkDecoder_Binding_Sonic-16                          10000             29478 ns/op         442.20 MB/s       26062 B/op         34 allocs/op
BenchmarkDecoder_Binding_StdLib-16                         10000            119348 ns/op         109.22 MB/s       10560 B/op        207 allocs/op
BenchmarkDecoder_Binding_JsonIter-16                       10000             37646 ns/op         346.25 MB/s       14673 B/op        385 allocs/op
BenchmarkEncoder_Generic_Sonic-16                          10000             25894 ns/op         503.39 MB/s       19096 B/op         42 allocs/op
BenchmarkEncoder_Generic_JsonIter-16                       10000             50275 ns/op         259.27 MB/s       13432 B/op         77 allocs/op
BenchmarkEncoder_Generic_StdLib-16                         10000            154901 ns/op          84.15 MB/s       48173 B/op        827 allocs/op
BenchmarkEncoder_Binding_Sonic-16                          10000              7373 ns/op        1768.04 MB/s       13861 B/op          4 allocs/op
BenchmarkEncoder_Binding_JsonIter-16                       10000             23223 ns/op         561.31 MB/s        9489 B/op          2 allocs/op
BenchmarkEncoder_Binding_StdLib-16                         10000             19512 ns/op         668.07 MB/s        9477 B/op          1 allocs/op

More detail see ast/search_test.go, decoder/decoder_test.go, encoder/encoder_test.go,

Usage

Marshal/Unmarshal

The behaviors are mostly consistent with encoding/json, except some uncommon escaping and key sorting (see issue4)

import "github.com/bytedance/sonic"

// Marshal
output, err := sonic.Marshal(&data) 
// Unmarshal
err := sonic.Unmarshal(input, &data) 

Get

Search partial json by given pathes, which must be non-negative integer or string or nil

import "github.com/bytedance/sonic"

input := []byte(`{"key1":[{},{"key2":{"key3":[1,2,3]}}]}`)

// no path, returns entire json
root, err := sonic.Get(input)
raw := root.Raw() // == string(input)

// multiple pathes
root, err := sonic.Get(input, "key1", 1, "key2")
sub := root.Get("key3").Index(2).Int64() // == 3

Returned ast.Node supports:

  • secondary search: Get(), Index(), GetByPath()
  • type assignment: Int64(), Float64(), String(), Number(), Bool(), Map(), Array()
  • children traversal: Values(), Properties()
  • supplement: Set(), SetByIndex(), Add(), Cap(), Len()

Use Number/Use Int64

import "github.com/bytedance/sonic/decoder"

input := `1`
var data interface{}

// default float64
dc := decoder.NewDecoder(input) 
dc.Decode(&data) // data == float64(1)
// use json.Number
dc = decoder.NewDecoder(input)
dc.UseNumber()
dc.Decode(&data) // data == json.Number("1")
// use int64
dc = decoder.NewDecoder(input)
dc.UseInt64()
dc.Decode(&data) // data == int64(1)

root, err := sonic.GetFromString(input)
// Get json.Number
jn := root.Number()
jm := root.InterfaceUseNumber().(json.Number) // jn == jm
// Get float64
fn := root.Float64()
fm := root.Interface().(float64) // jn == jm

Tips

Pretouch

Since Sonic uses JIT(just-in-time) compiling for decoder/encoder, huge schema may cause request-timeout. For better stability, we suggest to use Pretouch() for more-than-10000-field schema(struct) before Marshal()/Unmarshal().

import (
    "reflect"
    "github.com/bytedance/sonic"
)

func init() {
    var v HugeStruct
    err := sonic.Pretouch(reflect.TypeOf(v))
}

Pass string or []byte?

For alignment to encoding/json, we provide API to pass []byte as arguement, but the string-to-bytes copy is conducted at the same time considering safety, which may lose performance when origin json is huge. Therefore, you can use UnmarshalString, GetFromString to pass string, as long as your origin data is string or nocopy-cast is safe for your []byte.

Avoid repeating work

Get() overlapping pathes from the same root may cause repeating parsing. Instead of using Get() several times, you can use parser and searcher together like this:

import "github.com/bytedance/sonic"

root, err := sonic.GetByString(_TwitterJson, "statuses", 3, "user")
a = root.GetByPath( "entities","description")
b = root.GetByPath( "entities","url")
c = root.GetByPath( "created_at")

No need to worry about the overlaping or overparsing of a, b and c, because the inner parser of their root is lazy-loaded.

Better performance for generic deserializing

In most cases of fully-load generic json, Unmarshal() performs better than ast.Loads(). But if you only want to search a partial json and convert it into interface{} (or map[string]interface{}, []interface{}), we advise you to combine Get() and Unmarshal():

import "github.com/bytedance/sonic"

node, err := sonic.GetByString(_TwitterJson, "statuses", 3, "user")
var user interface{}
err = sonic.UnmarshalString(node.Raw(), &user)

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