Json Data Faker

jsondatafaker is a versatile Python package that empowers you to effortlessly create realistic but synthetic json data for a wide range of applications. If you need to generate test data for software development, this tool simplifies the process with an intuitive schema definition in YAML format.

Key Features

Schema Definition: Define your target schema using a simple YAML file. Specify the structure of your JSON, attribute names and fake data generation code.

Faker and Randomization: Leverage the power of the Faker library and random data generation to create authentic-looking fake data that mimics real-world scenarios.

Installation

pip install jsondatafaker

Sample Yaml File

version: 1
config:
  locale: en_US #faker locale Default:en_US
json:
  first_name: fake.first_name()
  last_name: fake.last_name()
  is_alive: fake.pybool()
  age: fake.random_int(18, 90)
  dob: fake.date_of_birth()
  address:
    street_address: fake.street_address()
    city: fake.city()
    state: fake.state_abbr()
    postal_code: fake.postcode()
  phone_numbers:
    - type: "\"home\""
      number: fake.phone_number()
    - type: "\"office\""
      number: fake.phone_number()
  children:
    - fake.first_name()
    - fake.first_name()
    - fake.first_name()
  spouse: null

full yml example

Sample Code

import jsondatafaker

#generate json only to work with
json_data = jsondatafaker.generate_json("tests/test_json.yaml")
print(json_data["first_name"])

# export in json format
jsondatafaker.to_json("test_json.yaml", "./target_folder")

Sample CLI Command

You can use jsondatafaker in your terminal for adhoc needs or shell script to automate fake data generation.
Faker custom providers and custom functions are not supported in CLI.

# exports to current folder in json format
jsondatafaker --config test_json.yaml

# exports to target folder in json format
jsondatafaker --config test_json.yaml --target ./target_folder 

# exports to target file in json format 
jsondatafaker --config test_json.yaml --target ./target_folder/target_file.json

Sample JSON Output

{
    "first_name": "Michael",
    "last_name": "Cunningham",
    "is_alive": false,
    "age": 55,
    "dob": "1954-01-04",
    "address": {
        "street_address": "68878 Stephanie Walk",
        "city": "Port Jeremy",
        "state": "MT",
        "postal_code": "47702"
    },
    "phone_numbers": [
        {
            "type": "home",
            "number": "(792)887-9048"
        },
        {
            "type": "office",
            "number": "+1-901-428-8816x568"
        }
    ],
    "children": [
        "Katelyn",
        "Jenna",
        "Barbara"
    ],
    "spouse": null
}

Custom Functions and Faker Providers

With json Faker, you have the flexibility to provide your own custom functions to generate column data. This advanced feature empowers developers to create custom fake data generation logic that can pull data from a database, API, file, or any other source as needed. You can also supply multiple functions in a list, allowing for even more versatility. The custom function you provide should return a single value, giving you full control over your synthetic data generation.

from jsondatafaker import jsondatafaker
from faker import Faker
from faker_education import SchoolProvider #import custom faker provider

fake = Faker()
def get_level():
    return f"level {fake.random_int(1, 5)}"


jsondatafaker.to_json("test_json.yaml", "./target_folder", fake_provider=SchoolProvider, custom_function=get_level)
#multiple fake provider or custom function in a list is also works

Add get_level() function and custom faker provider to your yaml file

version: 1
config:
  locale: en_US #faker locale Default:en_US
json:
  first_name: fake.first_name()
  last_name: fake.last_name()
  is_alive: fake.pybool()
  age: fake.random_int(18, 90)
  dob: fake.date_of_birth()
  level: get_level()            # custom function
  school: fake.school_name()    # customer faker provider

Faker Functions List

https://faker.readthedocs.io/en/master/providers.html#

Bug Report & New Feature Request

https://github.com/necatiarslan/json-datafaker/issues/new

Todo

Nice To Have

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Thanks,
Necati ARSLAN
[email protected]