golang标準庫json與三方包jsoniter序列化效率對比

• 測試代碼
• 測試結果
• 結論
• python2.7 vs python 3.7 vs pypy序列化
• • 結果

學習自：https://studygolang.com/articles/12702

測試代碼

package main

import (
	"encoding/json"
	"fmt"
	"github.com/json-iterator/go"
	"time"
)

type Data struct {
	ceshi  string
	ceshi1 string
	ceshi2 string
	ceshi3 string
}

func main() {
	data := Data{
		ceshi:  "ceshi111111111111111111111111111111111111111",
		ceshi1: "ceshi111111111111111111111111111111111111111",
		ceshi2: "ceshi111111111111111111111111111111111111111",
		ceshi3: "ceshi111111111111111111111111111111111111111",
	}
	t1 := time.Now()
	for i := 0; i < 100000; i++ {
		json.Marshal(&data)
	}
	cost := time.Since(t1).Seconds()
	fmt.Printf("encoding/json, using struct %v 秒\n", cost)

	var jsoner = jsoniter.ConfigCompatibleWithStandardLibrary
	t2 := time.Now()
	for i := 0; i < 100000; i++ {
		jsoner.Marshal(&data)
	}
	cost = time.Since(t2).Seconds()
	fmt.Printf("json-iterator, using struct %v 秒\n", cost)

	data1 := map[string]string{}
	data1["ceshi"] = "ceshi11111111111111111111111"
	data1["ceshi1"] = "ceshi11111111111111111111111"
	data1["ceshi2"] = "ceshi11111111111111111111111"
	data1["ceshi3"] = "ceshi11111111111111111111111"

	t3 := time.Now()
	for i := 0; i < 100000; i++ {
		json.Marshal(&data1)
	}
	cost = time.Since(t3).Seconds()
	fmt.Printf("encoding/json,using map %v秒\n", cost)

	t4 := time.Now()
	for i := 0; i < 100000; i++ {
		jsoner.Marshal(&data1)
	}
	cost = time.Since(t4).Seconds()
	fmt.Printf("json-iterator, using map %v秒\n", cost)
}
           

測試結果

encoding/json, using struct 0.01814627 秒
json-iterator, using struct 0.017017023 秒
encoding/json,using map 0.270127329秒
json-iterator, using map 0.223476829秒
           

結論

使用

json-iterator

庫+

struct

結構體進行序列化，性能最佳

python2.7 vs python 3.7 vs pypy序列化

測試代碼

#encoding:utf-8
import json
import time



data = {}
data["ceshi"] = "ceshi11111111111111111111111"
data["ceshi1"] = "ceshi11111111111111111111111"
data["ceshi2"] = "ceshi11111111111111111111111"
data["ceshi3"] = "ceshi11111111111111111111111"

t1 = time.time()
#python 2.7 用xrange
for i in range(100000):
	j = json.dumps(data)
cost = time.time() - t1
print("python 3.7 序列化耗時 %s"%cost)
           

結果

python 2.7 序列化耗時 0.56022310257秒
python 3.7 序列化耗時 0.57580351829秒
pypy 3.6 序列化耗時 0.1422567367553711秒