import json
import numpy as np
import pandas as pd
from pandas.io.json import json_normalize
import argparse
import sys

counter = 1
my_dict = dict()

def flatten_json(y):
    global my_dict
    out = []
    def flatten(x, pom=1, name=''):
        global my_dict, counter
        if type(x) is dict:
            for a in x:
                flatten(x[a], pom, name + a + '_')
        elif type(x) is list:
            i = 0
            for a in x:
                flatten(a, pom, name + str(i) + '_')
                i += 1
        elif name=='new row':
            counter+=1
            out.append(my_dict)
            my_dict = {}
        else:
            check = int(name[name.find('_') + 1])
            if check < counter:
                my_dict[name[:-1]] = str(x)
            else:
                flatten(x, pom+1, 'new row')
                my_dict[name[:-1]] = str(x)


    flatten(y)

    out.append(my_dict)
    my_dict = {}

    return out


if __name__ == '__main__':
    parser = argparse.ArgumentParser(description='Converting json files into csv for Tableau processing')
    parser.add_argument(
        "-j", "--json", dest="json", help="/Users/viktorija/PycharmProjects/json_conv_csv/", metavar="FILE", required=True)

    args = parser.parse_args()

    with open(args.json, "r") as inputFile:  # open json file
        json_data = json.loads(inputFile.read())  # load json content

    flat_json = flatten_json(json_data)

    final_data = json_normalize(flat_json)
    with open(args.json.replace(".json", ".csv"), "w") as outputFile:  # open csv file
    # saving DataFrame to csv
        final_data.to_csv(outputFile, encoding='utf8', index=False)