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jsonqueryvsjmespath

MIT 3 1 236
58.1 thousand (month) Oct 15 2019 v1.3.3(8 months ago)
2,053 2 55 MIT
1.0.1(1 year, 9 months ago) Feb 09 2022 179.6 million (month)

jsonquery is a Go library that allows you to parse and extract data from JSON documents using JSONPath expressions. JSONPath is similar to XPath, but it is designed specifically for working with JSON documents.

The jsonquery library allows you to traverse the JSON tree structure and extract values using JSONPath expressions. It provides a simple and intuitive API for querying the JSON data, and it is built on top of the popular jsoniter library.

JMESPath (pronounced “james path”) allows you to declaratively specify how to extract elements from a JSON document.

In web scraping, jmespath is a powerful tool for parsing and reshaping large JSON datasets. Jmespath is fast and easily extendible following it's own powerful query language.

For more see the Json parsing introduction section.

Example Use


package main

import (
  "fmt"
  "log"

  "github.com/antchfx/jsonquery"
)

func main() {
  // Parse the JSON string
  doc, err := jsonquery.Parse([]byte(`
    {
      "name": "John Doe",
      "age": 30,
      "address": {
        "street": "Main St",
        "city": "Anytown",
        "state": "CA",
        "zip": "12345"
      },
      "phones": [
        "555-555-5555",
        "555-555-5556"
      ]
    }
  `))
  if err != nil {
    log.Fatal(err)
  }

  // Extract the name
  name := jsonquery.FindOne(doc, "name")
  fmt.Println(name.InnerText())  // "John Doe"

  // Extract the city
  city := jsonquery.FindOne(doc, "address.city")
  fmt.Println(city.InnerText())  // "Anytown"

  // Extract all phone numbers
  phones := jsonquery.Find(doc, "phones[*]")
  for _, phone := range phones {
    fmt.Println(phone.InnerText())
  }
  // "555-555-5555"
  // "555-555-5556"
}
import jmespath

data = {
    "data": {
        "info": {
            "products": [
                {"price": {"usd": 1}, "_type": "product", "id": "123"}, 
                {"price": {"usd": 2}, "_type": "product", "id": "345"}
            ]
        }
    }
}

# easily reshape nested dataset to flat structure:
jmespath.search("data.info.products[*].{id:id, price:price.usd}", data)
[{'id': '123', 'price': 1}, {'id': '345', 'price': 2}]

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