How does this skill handle large datasets?

It provides specific patterns for using the PostgreSQL COPY command for efficiency and integrates with DVC (Data Version Control) to manage files larger than 1MB outside of the main Git repository.

Does this replace the Supabase CLI?

No, it complements the Supabase CLI by providing more granular control, such as progress monitoring for large files and advanced data generation scripts that the standard CLI doesn't offer natively.

Are the seeding scripts idempotent?

Yes, the recommended templates use 'ON CONFLICT DO NOTHING' clauses to ensure that running the seeds multiple times won't result in duplicate errors or corrupted data.

Can I generate mock data automatically?

Yes, the skill includes helper scripts that use the Faker library to generate realistic test data (users, transactions, etc.) based on your specific database schema.

Supabase Database Seeding Toolkit

Name: Supabase Database Seeding Toolkit
Author: ninyawee

byninyawee

数据库管理

Streamlines the population of Supabase databases with automated seed data generation, bulk loading, and lookup table management.

关于

This skill provides a comprehensive toolkit for managing database seeds within Supabase projects, offering automated scripts for generating mock data via Faker and executing seed files with progress monitoring. It establishes clear patterns for different data types—ranging from small lookup tables with idempotency logic to massive datasets requiring COPY commands and DVC (Data Version Control) tracking—ensuring consistent, reproducible development environments and robust testing workflows for engineering teams.

主要功能

Automated seed generation using schema-aware Python scripts and Faker data.
Standardized directory structure with numbered execution ordering for data integrity.
Idempotent seed templates utilizing INSERT ... ON CONFLICT logic for safe reruns.
DVC integration for tracking and versioning massive seed files outside of Git.
Efficient bulk loading patterns for large datasets using PostgreSQL COPY commands.
0 GitHub stars

使用场景

Managing static reference data and lookup tables consistently across staging and production.
Populating local development environments with realistic mock data for UI/UX testing.
Version controlling large-scale datasets that exceed standard Git file size recommendations.

关于

主要功能

Automated seed generation using schema-aware Python scripts and Faker data.
Standardized directory structure with numbered execution ordering for data integrity.
Idempotent seed templates utilizing INSERT ... ON CONFLICT logic for safe reruns.
DVC integration for tracking and versioning massive seed files outside of Git.
Efficient bulk loading patterns for large datasets using PostgreSQL COPY commands.
0 GitHub stars

使用场景

Managing static reference data and lookup tables consistently across staging and production.
Populating local development environments with realistic mock data for UI/UX testing.
Version controlling large-scale datasets that exceed standard Git file size recommendations.