json decode: py vs go

数据

{
    "str": "str",
    "int": 1,
    "float": 1.1,
    "str_list": ["a", "b"],
    "dict": {"a": "a", "b": "b"}
}

代码

Python

import json
import time
str_ = """{
    "str": "str",
    "int": 1,
    "float": 1.1,
    "str_list": ["a", "b"],
    "dict": {"a": "a", "b": "b"}
}"""
start = time.clock()
num = 10000000
for i in range(num):
    _ = json.loads(str_)
end = time.clock()
print('num: %d, cost: %s ms' % (num, (end - start) * 1000))

Golang

package main
import (
    "encoding/json"
    "fmt"
    "io"
    "log"
    "strings"
  "time"
)
func Benchmark(name string, times uint, do func()) {
    start := time.Now().UnixNano()
    var i uint = 0
    for ;i < times; i++ {
        do()
    }
    end := time.Now().UnixNano()
    fmt.Printf("run %s %d times, cost: %d ms\n", name, times, (end-start)/int64(time.Millisecond))
}
func parse() {
    const jsonStream = `
{
    "str": "str", 
    "int": 1,
    "float": 1.1,
    "str_list": ["a", "b"],
    "dict": {"a": "a", "b": "b"}
}
`
    type Sub struct {
        A string `json:"a"`
        B string `json:"b"`
    }
    type Message struct {
        Str     string   `json:"str"`
        Int     int      `json:"int"`
        Float   float32  `json:"float"`
        StrList []string `json:"str_list"`
        Sub     Sub      `json:"dict"`
    }
    var dec *json.Decoder
    dec = json.NewDecoder(strings.NewReader(jsonStream))
    for {
        var m Message
        if err := dec.Decode(&m); err == io.EOF {
            break
        } else if err != nil {
            log.Fatal(err)
        }
    }
}
func main() {
    util.Benchmark("parse json", 10000000, parse)
}

结果

Golang 相较于 Python，在 json decode 上有明显优势，肉眼观察发现 Golang 程序的 CPU 利用率比 Python 的要高。