mxjvsnested-lookup

MIT 2 2 624

58.1 thousand (month) Feb 09 2017 per(1 year, 4 months ago)

209 2 - Public Domain

Feb 09 2022 485.5 thousand (month) 0.2.25(2 years ago)

mxj is a Go library for working with JSON and XML data. It allows you to convert between JSON and XML, merge JSON and XML documents, and extract values from JSON and XML using a simple and intuitive API.

One of the main features of mxj is its ability to work with JSON and XML data in a struct-like manner, allowing you to access values using dot notation.

nested-lookup is a convenient way to parse multi-depth JSON documents which are often encountered in web scraping. Using nested-lookup we can easily extract deeply nested data-field just by providing key value.

The library provides a number of functions for searching and extracting data from nested dictionaries, including:

nested_lookup: search for a key within a nested dictionary and returns the associated value.
nested_update: update a key-value pair within a nested dictionary.
nested_has: check if a key exists within a nested dictionary.
nested_values: returns all the values within a nested dictionary, including values within nested dictionaries.

The library is designed to be flexible and can work with dictionaries of any size and structure, making it a useful tool for working with complex and nested data structures.

Example Use

package main

import (
  "fmt"

  "github.com/clbanning/mxj"
)

func main() {
  // Parse the JSON string
  jsonData := []byte(`
    {
      "name": "John Doe",
      "age": 30,
      "address": {
        "street": "Main St",
        "city": "Anytown",
        "state": "CA",
        "zip": "12345"
      },
      "phones": [
        "555-555-5555",
        "555-555-5556"
      ]
    }
  `)
  mv, err := mxj.NewMapJson(jsonData)
  if err != nil {
    fmt.Println("Error:", err)
    return
  }

  // Extract the name
  name, _ := mv.ValueForPath("name")
  fmt.Println("name:", name)  // "John Doe"

  // Extract the city
  city, _ := mv.ValueForPath("address.city")
  fmt.Println("city:", city)  // "Anytown"

  // Extract all phone numbers
  phones, _ := mv.ValuesForPath("phones")
  for _, phone := range phones {
    fmt.Println("phone:", phone)
  }
  // "555-555-5555"
  // "555-555-5556"
}

from nested_lookup import nested_lookup

my_document = {
   "name" : "Rocko Ballestrini",
   "email_address" : "test1@example.com",
   "other" : {
       "secondary_email" : "test2@example.com",
       "EMAIL_RECOVERY" : "test3@example.com",
       "email_address" : "test4@example.com",
    },
}

# retrieving all keys can be useful in dataset overview
from nested_lookup import get_all_keys
get_all_keys(my_document)
['name', 'email_address', 'other', 'secondary_email', 'EMAIL_RECOVERY', 'email_address']

# key/value stats can also be useful for data overview: 
from nested_lookup import get_occurrence_of_key, get_occurrence_of_value, get_occurrences_and_values
data = {"products": [{"category": "t-shirt"},{"category": "underwear"},{"category": "t-shirt"}]}

get_occurrence_of_key(data, key='category')
3
get_occurrence_of_value(data, value='t-shirt')
2
get_occurrences_and_values([data], "t-shirt")  # count t-shirt products
{
  't-shirt': {
    'occurrences': 2,
    'values': [{'category': 't-shirt'}, {'category': 't-shirt'}]
    }
  }

# it can also be used to delete/alter values:
from nested_lookup import nested_alter
data = {"products": [{"price": 10}, {"price": 14}]}

nested_alter(data, "price", lambda price: price * 1.4)
{'products': [{'price': 14.0}, {'price': 19.599999999999998}]}

nested_delete(data, "price")
{'products': [{}, {}]}