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HomeBackend DevelopmentGolangLet's take a look at the usage of golang gjson

In the field of modern software development, data processing and data parsing are tasks that developers often encounter. With the emergence and continuous development of new data formats, how to efficiently parse and process these data has become a challenge. In this regard, golang gjson is a very useful tool that can assist us in parsing JSON data easily.

Introduction to gjson

gjson is a go language library for parsing JSON data. It implements the function of quickly parsing JSON data through chained APIs. gjson is concise and easy to use because it only focuses on parts of the JSON data rather than the entire document. In addition, gjson also supports JSON path query. It can provide great convenience when parsing complex JSON data.

Simple usage example

Let us see how to use gjson in golang program. We first need to import the gjson library:

import "github.com/tidwall/gjson"

Then, we can quickly parse the JSON data in the following way:

package main

import (
    "fmt"
    "github.com/tidwall/gjson"
)

func main(){
    data := `{"name": "golang", "version": "1.15.8"}`
    value := gjson.Get(data, "version")
    fmt.Printf("version: %s\n", value.String())
}

In the above code, we retrieve it by using the gjson.Get() function The value named "version" in the JSON data. We can convert the type of the value to a string for output on the console.

Complex usage example

Let us look at a more complex example of parsing complex JSON data through gjson. Consider the JSON file as follows:

{
    "name": "Jack",
    "age": 30,
    "hobbies": [
        {
            "name": "reading",
            "level": 2
        },
        {
            "name": "music",
            "level": 3
        },
        {
            "name": "swimming",
            "level": 1
        }
    ],
    "contact": {
        "email": "jack@example.com",
        "phone": {
            "home": "123456",
            "mobile": "78901234"
        }
    }
}

We can use gjson to access various parts of the JSON data, such as getting the first array element of the hobbies part, the code is as follows:

package main

import (
    "fmt"
    "github.com/tidwall/gjson"
)

func main() {
    data := `{"name": "Jack", "age": 30, "hobbies": [{"name": "reading", "level": 2}, {"name": "music", "level": 3}, {"name": "swimming", "level": 1}], "contact": {"email": "jack@example.com", "phone": {"home": "123456", "mobile": "78901234"}}}`
    hobbies := gjson.Get(data, "hobbies")
    firstHobby := gjson.Get(hobbies.String(), "#0")
    fmt.Printf("first hobby: %s\n", firstHobby.String())
}

In the above code, #0 represents the first element of the array, #1 represents the second element, and so on. We can also select all array elements by wildcard character *. For example, you can get all interest levels using the following code:

package main

import (
    "fmt"
    "github.com/tidwall/gjson"
)

func main() {
    data := `{"name": "Jack", "age": 30, "hobbies": [{"name": "reading", "level": 2}, {"name": "music", "level": 3}, {"name": "swimming", "level": 1}], "contact": {"email": "jack@example.com", "phone": {"home": "123456", "mobile": "78901234"}}}`
    levels := gjson.Get(data, "hobbies.*.level")
    fmt.Printf("hobby levels: %s\n", levels.String())
}

In the above example, we have used . to indicate a deep traversal instead of just traversing the immediate child elements.

gjson can easily read nested JSON data or irregularly structured data, and its API is very intuitive and easy to read. If you want more information and examples, please visit [gjson official website](https://github.com/tidwall/gjson).

Summary

This article introduces the main usage of golang gjson, including simple use cases and complex use cases. Using gjson can improve our code writing efficiency when processing JSON data. gjson is one of the simplest and easiest-to-use JSON parsing libraries in the golang community. One of the great things about gjson is that its API is relatively simple and can be used with other libraries to build applications. Because gjson can provide efficient JSON parsing performance, it is easier to maintain excellent performance in big data parsing scenarios.

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