test-data
Generate realistic test data with Faker, create database seeds, manage fixtures, and build factory patterns.
Quellinformationen
- Repository
- ThinkfleetAI/thinkfleet-engine
- Letzte Quellaktivität
- 1. Februar 2026 um 16:21
- Erkannte Sprache von SKILL.md
- Englisch
- Sterne
- 0
- Forks
- 0
Installationsoptionen
Standardmäßig ist der Prompt ausgewählt, der zuerst die Quelle prüft. Sie können zu einem direkten Befehl wechseln oder eine lokale Kopie herunterladen.
Quelldateien prüfen
Lesen Sie SKILL.md und alle von SkillsMP angezeigten Begleitdateien, bevor Sie sich für eine Installation entscheiden.
SKILL.md wird angezeigt
SKILL.md
Quellanweisungen · Schreibgeschützte Vorschau- name
- test-data
- description
- Generate realistic test data with Faker, create database seeds, manage fixtures, and build factory patterns.
- metadata
- {"thinkfleetbot":{"emoji":"🎲","requires":{"anyBins":"[Truncated]"}}}
# 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/`.
Auf GitHub ansehen