Effortless Test Data: Generate Random Data with Python and FastAPI

Install below packages

pip install fastapi faker uvicorn

1. create a file called datagen.py

import faker
import random
import datetime
import json

# Create a faker instance
fake = faker.Faker()


def generate_data():
    """Generates random data in the specified format"""
    data = {}
    # Generate numeric id
    data["id"] = random.randint(1000, 9999)
    # Generate uuid
    data["uid"] = fake.uuid4()
    # Generate password
    data["password"] = fake.password()
    # Generate first and last names
    data["first_name"] = fake.first_name()
    data["last_name"] = fake.last_name()
    # Generate username
    data["username"] = data["first_name"] + "." + data["last_name"].lower()
    # Generate email
    data["email"] = data["username"] + "@email.com"
    # Generate avatar url using faker image url
    data["avatar"] = fake.image_url()
    # Randomly choose gender
    data["gender"] = random.choice(["Male", "Female", "Non-binary"])
    # Generate phone number
    data["phone_number"] = fake.phone_number()
    # Generate social security number (replace with any other identifier if needed)
    data["social_insurance_number"] = "".join([str(random.randint(0, 9)) for _ in range(9)])
    # Generate date of birth
    data["date_of_birth"] = fake.date_of_birth()

    # Generate employment data
    data["employment"] = {}
    data["employment"]["title"] = fake.job().title()


    # Generate address data
    data["address"] = {}
    data["address"]["city"] = fake.city()
    data["address"]["street_name"] = fake.street_name()
    data["address"]["street_address"] = fake.street_address()
    data["address"]["zip_code"] = fake.postcode()
    data["address"]["state"] = fake.state()
    data["address"]["country"] = fake.country()
    # Generate random latitude and longitude within a reasonable range
    data["address"]["coordinates"] = {"lat": random.uniform(20, 50), "lng": random.uniform(-130, -70)}

    # Generate credit card data (replace with any other data if needed)
    data["credit_card"] = {}
    data["credit_card"]["cc_number"] = fake.credit_card_number()

    # Generate subscription data
    data["subscription"] = {}
    data["subscription"]["plan"] = random.choice(["Bronze", "Silver", "Gold"])
    data["subscription"]["status"] = random.choice(["Active", "Inactive"])
    data["subscription"]["payment_method"] = random.choice(["Paypal", "Credit Card", "Direct Debit"])
    data["subscription"]["term"] = random.choice(["Monthly", "Annual"])

    return data


print(type(generate_data()))

2. create a file called main.py

from fastapi import FastAPI
from fastapi.responses import RedirectResponse
import uvicorn
from datagen import generate_data

app = FastAPI()


@app.get("/", include_in_schema=False)
async def redirect_to_docs():
    return RedirectResponse(url="/docs")


@app.get('/v2/random-data')
def random_data():
    return generate_data()


if __name__ == '__main__':
    uvicorn.run(app)

3. run the main.py , it will looks like below

4. open http://127.0.0.1:8000/v2/random-data , to see data

{
"id": 9035,
"uid": "9e197861-ca0e-429f-a214-aee970a780cc",
"password": "8*yJqjDG+1",
"first_name": "Michele",
"last_name": "Keith",
"username": "Michele.keith",
"email": "Michele.keith@email.com",
"avatar": "https://dummyimage.com/939x636",
"gender": "Female",
"phone_number": "(286)253-6593",
"social_insurance_number": "113907158",
"date_of_birth": "1965-07-20",
"employment": {
"title": "Horticulturist, Amenity"
},
"address": {
"city": "South Tammy",
"street_name": "Melissa Bypass",
"street_address": "213 Martinez Bypass",
"zip_code": "61506",
"state": "Arkansas",
"country": "Montenegro",
"coordinates": {
"lat": 34.228540911718014,
"lng": -79.26243589606341
}
},
"credit_card": {
"cc_number": "3528772760847005"
},
"subscription": {
"plan": "Gold",
"status": "Inactive",
"payment_method": "Paypal",
"term": "Monthly"
}
}

GitHub - sateesh-py/random-data-generator: random-data-generator

FastAPI - Swagger UI

Thank You.