choosing-pattern

Select pgdbm deployment patterns based on project topology and migration constraints.

Updated Jul 28, 2025

Search Tags:#architecture #deployment-patterns #pattern-selection #decision-guide #choose-pattern #migration-management #pgdbm

Ready to run

npx skills add https://github.com/juanre/pgdbm --skill choosing-pattern

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: choosing-pattern
Source: https://github.com/juanre/pgdbm/tree/main/skills/choosing-pattern
Command: npx skills add https://github.com/juanre/pgdbm --skill choosing-pattern

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill helps you quickly determine the most suitable pgdbm deployment pattern (Standalone, Dual-Mode Library, or Shared Pool) based on your project context, ensuring correct architecture decisions from the start.

Core Features & Use Cases

Decision-tree guidance to select the optimal pattern based on deployment topology, reuse needs, and service boundaries.
Scenario coverage for single-service apps, multi-service monoliths, and libraries published to PyPI.
Migration and isolation awareness to ensure migrations run per pattern and schemas stay properly isolated.

Quick Start

Ask the skill to evaluate your deployment context and return the recommended pgdbm pattern along with a brief rationale and the key migration implications.

Frequently Asked Questions about choosing-pattern

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I choose the right pgdbm deployment pattern for my project?▼

Deployment pattern selection depends on your architecture topology, service boundaries, and migration needs. The choosing-pattern Skill evaluates whether you need Standalone, Dual-Mode Library, or Shared Pool based on your specific project context, ensuring migrations run correctly per pattern and schemas stay isolated.

What are the differences between Standalone, Dual-Mode Library, and Shared Pool pgdbm patterns?▼

Standalone runs independently per service with isolated migrations. Dual-Mode Library publishes reusable code for multi-service architectures with per-service migration handling. Shared Pool centralizes connections across services. Pattern choice depends on deployment topology, reuse requirements, and whether schemas need isolation.

Can I use pgdbm patterns with a multi-service architecture?▼

Yes, pgdbm patterns scale from single-service apps to multi-service monoliths and distributed systems. The Skill evaluates your deployment topology and service boundaries to recommend Dual-Mode Library or Shared Pool patterns that maintain proper migration isolation and connection management across services.

How do migration and schema isolation work across pgdbm deployment patterns?▼

Each pattern enforces different migration handling: Standalone runs migrations per service with full isolation, Dual-Mode Library handles migrations per service when the library is consumed, and Shared Pool manages centralized migrations with schema constraints. The Skill ensures your pattern matches your isolation requirements.

Should I publish pgdbm as a library or run it as a shared pool?▼

Publishing to PyPI as Dual-Mode Library suits multi-service projects needing reusable code with per-service migrations. Shared Pool works better for tightly coupled architectures requiring centralized connection management. The Skill recommends based on your reuse needs and deployment topology.