flatten_json.py

import json
import csv

# REPLACE THIS with json input
#input = '{"Parent": "Roy", "Children": [{"Name": "Todd"}, {"Name": "Shirley"}]}'

f = open("my.json", "r")
contents = f.read()

obj = json.loads(contents)

def flatten_object(obj, tree = []):
    flattened_obj = {}

    if type(obj) != dict and type(obj) != list:
        fq_name = '.'.join(tree)
        flattened_obj[fq_name] = obj
        return flattened_obj

    for index, value in enumerate(obj):
        # For dicts, value is the key of the item in the dict, eg. {1: 'One', 2: 'Two'} yields values of 1 and 2
        # For lists, value is the actual item eg. [1,2,3] yields values of 1, 2, and 3
        #if (type(obj) == dict):
        #    value = obj[value]

        # The fully-qualified name of the node is based on new_tree, which
        # is a list of ancestor nodes of the current node. For dictionaries, we use the dictionary key
        # as the name of the node, and for lists we use the index.
        new_tree = list(tree)
        if (type(obj) is dict):
            new_tree.append(str(value))
        else:
            new_tree.append(str(index))

        if type(obj) is dict:
            # value is a dictionary key. recurse on the object referenced by value
            flattened_obj.update(flatten_object(obj[value], new_tree))
        elif type(obj) is list:
            flattened_obj.update(flatten_object(value, new_tree))

    return flattened_obj

object_map = flatten_object(obj)

with open("flattened.csv", "w") as output_file:
    fieldnames = [key for key in object_map.keys()]
    print fieldnames
    writer = csv.DictWriter(output_file, fieldnames)
    writer.writeheader()
    for key in object_map.keys():
        row = dict()
        row[key] = object_map[key]
        writer.writerow(row)