You can use Pandas DataFrame to achieve this, with the following Example:

import pandas as pd
csv_file = pd.DataFrame(pd.read_csv("path/to/file.csv", sep = ",", header = 0, index_col = False))
csv_file.to_json("/path/to/new/file.json", orient = "records", date_format = "epoch", double_precision = 10, force_ascii = True, date_unit = "ms", default_handler = None)

First, your JSON has nested objects, so it normally cannot be directly converted to CSV. You need to change that to something like this:

{
    "pk": 22,
    "model": "auth.permission",
    "codename": "add_logentry",
    "content_type": 8,
    "name": "Can add log entry"
},
......]

Here is my code to generate CSV from that:

import csv
import json

x = """[
    {
        "pk": 22,
        "model": "auth.permission",
        "fields": {
            "codename": "add_logentry",
            "name": "Can add log entry",
            "content_type": 8
        }
    },
    {
        "pk": 23,
        "model": "auth.permission",
        "fields": {
            "codename": "change_logentry",
            "name": "Can change log entry",
            "content_type": 8
        }
    },
    {
        "pk": 24,
        "model": "auth.permission",
        "fields": {
            "codename": "delete_logentry",
            "name": "Can delete log entry",
            "content_type": 8
        }
    }
]"""

x = json.loads(x)

f = csv.writer(open("test.csv", "wb+"))

# Write CSV Header, If you dont need that, remove this line
f.writerow(["pk", "model", "codename", "name", "content_type"])

for x in x:
    f.writerow([x["pk"],
                x["model"],
                x["fields"]["codename"],
                x["fields"]["name"],
                x["fields"]["content_type"]])

You will get output as:

pk,model,codename,name,content_type
22,auth.permission,add_logentry,Can add log entry,8
23,auth.permission,change_logentry,Can change log entry,8
24,auth.permission,delete_logentry,Can delete log entry,8