Cookiecutter PyPackage is a cookiecutter template that generates a modern Python package project with production-ready tooling. It produces a src-layout package with a Typer CLI, pytest tests, Ruff linting, ty type checking, uv dependency management, and a justfile task runner. The generated project includes security-hardened GitHub Actions workflows for CI, PyPI publishing via Trusted Publishers, documentation deployment with Zensical, CodeQL and zizmor security scanning, and Dependabot for dependency updates. The template itself is a Python package with a CLI wrapper around cookiecutter, a development watcher for live template iteration, and a comprehensive post-generation hook that optionally sets up a GitHub repository, enables Pages, and creates the PyPI environment. The codebase demonstrates strong engineering practices: comprehensive test coverage, clear separation of concerns, and thoughtful security defaults. It is actively maintained with recent commits and a well-documented changelog.
This repository is a CLI tool (`api-platform`) that scaffolds new API Platform projects. It generates Symfony or Laravel project skeletons with optional Docker infrastructure, Next.js PWA, React-admin SPA, and AI agent instruction files. The tool configures API formats (JSON-LD, JSON:API, HAL) and documentation viewers (Swagger UI, ReDoc, Scalar). It fetches Docker files from a pinned commit of `dunglas/symfony-docker` and patches compose.yaml for CORS headers. The codebase is well-structured with clean abstractions, idempotent patching patterns, and comprehensive test coverage. It demonstrates professional PHP engineering using Symfony Console components and modern PHP features.
Fastango is a uv-first CLI tool for generating production-ready FastAPI projects. It provides two template styles (simple, mvc), a curated integration catalog spanning auth, databases, payments, AI, observability, and deployment, and an interactive terminal playground for selecting components. The tool also includes a constrained AI generation mode that converts natural-language prompts into validated project plans using only supported templates, skills, presets, and integrations, rejecting unsafe or unsupported suggestions. Architecturally, Fastango uses a modular scaffold engine: a mutable ScaffoldPlan accumulates dependencies, files, environment variables, and documentation; a TemplateRenderer renders Jinja2 templates from packaged directories and inline specifications; and an IntegrationRegistry resolves aliases, conflicts, and preset expansions before applying integrations. The generator module separates deterministic rules from optional LLM provider adapters (Anthropic, OpenAI), merging suggestions after validation against the same registry. The codebase demonstrates strong engineering practices: type hints throughout, Pydantic v2 for configuration, Protocol-based integration contracts, and comprehensive tests including smoke tests for generated projects. The safety model—where provider output is always validated against a allowlist before writing files—is a notable design decision that prevents arbitrary code generation. The integration catalog is declarative and extensible, making it straightforward to add new integrations without writing imperative code.