Convert a 3 columns csv to a hierarchical json with d3 sunburst default format

csv_to_hierarchical_json.py

import csv
import json
import itertools

"""
Convert a 3 columns CSV to a hierarchical JSON
with d3 sunburst default format.
Duplicated CSV column values are nested on the JSON as follows:

input file (CSV):
lorem,ipsum,dolor
lorem,ipsum,amet

output file (JSON):
{
    "name": "Output",
    "children": [{
        "name": "lorem",
        "children": [{
            "name": "ipsum",
            "children": [{
                "name": "dolor",
                "value": 1
            },{
                "name": "amet",
                "value": 1
            }]
        }]
    }]
}

"""

INPUTFILE="input.csv"
OUTPUTFILE="output.json"

output = {
    'name': 'output',
    'children': []
}

with open(INPUTFILE, 'r') as file:
    reader = csv.reader(file)
    count = 0
    for row in reader:
        count += 1

        if not row[0] in [x['name'] for x in output['children']]:
            output['children'].append({'name': row[0], 'children':[]})


        if not row[1] in list(y['name'] for y in list(itertools.chain.from_iterable([x['children'] for x in output['children']]))):
            index = next((i for (i, d) in enumerate(output['children']) if d["name"] == row[0]), None)
            output['children'][index]['children'].append({'name': row[1], 'children':[]})


        if not row[2] in list(z['name'] for z in list(itertools.chain.from_iterable((y['children'] for y in list(itertools.chain.from_iterable([x['children'] for x in output['children']])))))):
            index1 = next((i for (i, d) in enumerate(output['children']) if d["name"] == row[0]), None)
            index2 = next((i for (i, d) in enumerate(output['children'][index1]['children']) if d["name"] == row[1]), None)
            output['children'][index1]['children'][index2]['children'].append({'name': row[2], 'value':1})


with open(OUTPUTFILE, 'w') as file:
    json.dump(output, file, ensure_ascii=False)

print('done')