jsf

Use jsf along with fake data generators to provide consistent and meaningful fake data for your system.

Main Features

• Provides out of the box data generation from any JSON schema 📦

• Extendable custom data providers using any lambda functions 🔗
• Multi level state for dependant data (eg multiple objects sharing value, such as children with same surname) 🤓
• Inbuilt validation of fake JSON produced ✅
• In memory conversion from JSON Schema to Pydantic Models with generated examples 🤯
• Seamless integration with FastAPI 🚀

Installation

$ pip install jsf

---> 100%

Usage

Basic 😊

from jsf import JSF

faker = JSF(
    {
        "type": "object",
        "properties": {
            "name": {"type": "string", "$provider": "faker.name"},
            "email": {"type": "string", "$provider": "faker.email"},
        },
        "required": ["name", "email"],
    }
)

fake_json = faker.generate()

Results in ...

{
    'name': 'Jesse Phillips', 
    'email': '[email protected]'
}

From JSON file 📁

from jsf import JSF

faker = JSF.from_json("demo-schema.json")
fake_json = faker.generate()

jsf --schema src/tests/data/custom.json --instance wow.json

docker run -v $PWD:/data challisa/jsf jsf --schema /data/custom.json --instance /data/example.json

FastAPI Integration 🚀

Create a file main.py with:

from jsf import JSF
from fastapi import FastAPI

app = FastAPI(docs_url="/")
generator = JSF.from_json("custom.json")


@app.get("/generate", response_model=generator.pydantic())
def read_root():
    return generator.generate()

Run the server with:

$ uvicorn main:app --reload

INFO:     Uvicorn running on http://127.0.0.1:8000 (Press CTRL+C to quit)
INFO:     Started reloader process [28720]
INFO:     Started server process [28722]
INFO:     Waiting for application startup.
INFO:     Application startup complete.

Credits

• This repository is a Python port of json-schema-faker with some minor differences in implementation.

License

• MIT License