test-data

# Test Data Generation Generate realistic test data for development, testing, and demos. ## Faker (Python) ```bash # Quick generation python3 -c " from faker import Faker import json fake = Faker() users = [{'name': fake.name(), 'email': fake.email(), 'phone': fake.phone_number(), 'address': fake.address(), 'company': fake.company()} for _ in range(10)] print(json.dumps(users, indent=2)) " # Generate CSV python3 -c " from faker import Faker import csv, sys fake = Faker() w = csv.writer(sys.stdout) w.writerow(['name','email','phone','joined']) for _ in range(100): w.writerow([fake.name(), fake.email(), fake.phone_number(), fake.date_between('-2y','today')]) " > test_users.csv # Locale-specific data python3 -c " from faker import Faker fake = Faker('en_US') print(fake.name(), fake.zipcode(), fake.state()) fake_jp = Faker('ja_JP') print(fake_jp.name(), fake_jp.address()) " # Seeded (reproducible) python3 -c " from faker import Faker fake = Faker() Faker.seed(42) print(fake.name()) # Always same result " ``` ## Faker (JavaScript) ```bash # Generate JSON test data node -e " const { faker } = require('@faker-js/faker'); const users = Array.from({length: 10}, () => ({ id: faker.string.uuid(), name: faker.person.fullName(), email: faker.internet.email(), avatar: faker.image.avatar(), createdAt: faker.date.past().toISOString(), })); console.log(JSON.stringify(users, null, 2)); " ``` ## Database Seeding ### PostgreSQL ```bash # Generate and insert directly python3 -c " from faker import Faker fake = Faker() Faker.seed(42) for i in range(100): name = fake.name().replace(\"'\", \"''\") email = fake.email() print(f\"INSERT INTO users (name, email, created_at) VALUES ('{name}', '{email}', '{fake.date_between('-1y', 'today')}');\") " | psql $DATABASE_URL ``` ### JSON fixtures ```bash # Generate fixture file python3 -c " from faker import Faker import json fake = Faker() Faker.seed(42) data = { 'users': [{'id': i, 'name': fake.name(), 'email': fake.email()} for i in range(1, 21)], 'posts': [{'id': i, 'user_id': fake.random_int(1, 20), 'title': fake.sentence(), 'body': fake.paragraph()} for i in range(1, 51)], 'comments': [{'id': i, 'post_id': fake.random_int(1, 50), 'user_id': fake.random_int(1, 20), 'text': fake.sentence()} for i in range(1, 101)] } print(json.dumps(data, indent=2)) " > fixtures/test_data.json ``` ## Specific Data Types ```bash python3 -c " from faker import Faker fake = Faker() # Financial print('CC:', fake.credit_card_number()) print('IBAN:', fake.iban()) print('Price:', fake.pricetag()) # Technical print('IP:', fake.ipv4()) print('MAC:', fake.mac_address()) print('UA:', fake.user_agent()) print('URL:', fake.url()) # Content print('Paragraph:', fake.paragraph()) print('BS:', fake.bs()) print('Job:', fake.job()) # Dates print('Past:', fake.date_between('-1y', 'today')) print('Future:', fake.date_between('today', '+1y')) " ``` ## Notes - Always use `Faker.seed()` for reproducible test data in CI. - Install: `pip install faker` or `npm install @faker-js/faker`. - Never use Faker-generated data that looks like real PII in production databases. - For load testing, generate data in bulk and import via COPY/bulk insert, not row-by-row INSERT. - JSON fixtures are portable across test frameworks. Store them in `fixtures/` or `test/data/`.