Can I control the amount of data generated?

Yes, you can specify the volume of data required, such as generating 50 users or 1,000 transaction records, to fit your specific testing needs.

What file formats can the skill produce?

It can generate standard SQL insert scripts as well as programming language scripts, such as JavaScript for use with TypeORM or other ORMs.

Is the generated data realistic?

Yes, it uses Faker libraries to generate contextually appropriate data like real names, email addresses, and phone numbers rather than random strings.

Can I use this for automated testing?

Absolutely. It is ideal for creating idempotent seed scripts that can be run as part of a setup process for unit, integration, or end-to-end tests.

How does this skill handle table relationships?

The skill analyzes your database schema to identify foreign keys and ensures that generated data maintains referential integrity across all related tables.

Database Data Seeder Generator

Name: Database Data Seeder Generator
Author: BbgnsurfTech

byBbgnsurfTech

•

데이터베이스 관리

Generates realistic, relationally consistent test data and database seed scripts for development and testing environments.

소개

This skill automates the complex task of populating databases by analyzing schemas and generating high-quality mock data using Faker libraries. It identifies table structures and foreign key constraints to ensure that generated data maintains relational integrity across your entire database. Whether you need to fill a local development environment, prepare a staging server for a demo, or create idempotent scripts for automated testing, this skill streamlines the process by outputting ready-to-use SQL or JavaScript seed files.

주요 기능

Analyzes database schemas to map table structures and constraints
Maintains complex relational integrity and foreign key dependencies
Supports configurable data volumes for varied testing scales
Leverages Faker libraries to generate realistic and diverse mock data
Generates scripts in multiple formats including SQL and JavaScript
1 GitHub stars

사용 사례

Populating a fresh development environment with realistic user and transaction data
Generating large datasets to perform application load testing and performance benchmarking
Creating idempotent seed scripts for CI/CD pipelines and automated integration tests

소개

주요 기능

Analyzes database schemas to map table structures and constraints
Maintains complex relational integrity and foreign key dependencies
Supports configurable data volumes for varied testing scales
Leverages Faker libraries to generate realistic and diverse mock data
Generates scripts in multiple formats including SQL and JavaScript
1 GitHub stars

사용 사례

Populating a fresh development environment with realistic user and transaction data
Generating large datasets to perform application load testing and performance benchmarking
Creating idempotent seed scripts for CI/CD pipelines and automated integration tests