python-fastapi-development
Python FastAPI backend development with async patterns, SQLAlchemy, Pydantic, authentication, and production API patterns. Use when building FastAPI backend services.
What this skill does
# Python/FastAPI Development Workflow ## Overview Specialized workflow for building production-ready Python backends with FastAPI, featuring async patterns, SQLAlchemy ORM, Pydantic validation, and comprehensive API patterns. ## When to Use This Workflow Use this workflow when: - Building new REST APIs with FastAPI - Creating async Python backends - Implementing database integration with SQLAlchemy - Setting up API authentication - Developing microservices ## Workflow Phases ### Phase 1: Project Setup #### Skills to Invoke - `app-builder` - Application scaffolding - `python-development-python-scaffold` - Python scaffolding - `fastapi-templates` - FastAPI templates - `uv-package-manager` - Package management #### Actions 1. Set up Python environment (uv/poetry) 2. Create project structure 3. Configure FastAPI app 4. Set up logging 5. Configure environment variables #### Copy-Paste Prompts ``` Use @fastapi-templates to scaffold a new FastAPI project ``` ``` Use @python-development-python-scaffold to set up Python project structure ``` ### Phase 2: Database Setup #### Skills to Invoke - `prisma-expert` - Prisma ORM (alternative) - `database-design` - Schema design - `postgresql` - PostgreSQL setup - `pydantic-models-py` - Pydantic models #### Actions 1. Design database schema 2. Set up SQLAlchemy models 3. Create database connection 4. Configure migrations (Alembic) 5. Set up session management #### Copy-Paste Prompts ``` Use @database-design to design PostgreSQL schema ``` ``` Use @pydantic-models-py to create Pydantic models for API ``` ### Phase 3: API Routes #### Skills to Invoke - `fastapi-router-py` - FastAPI routers - `api-design-principles` - API design - `api-patterns` - API patterns #### Actions 1. Design API endpoints 2. Create API routers 3. Implement CRUD operations 4. Add request validation 5. Configure response models #### Copy-Paste Prompts ``` Use @fastapi-router-py to create API endpoints with CRUD operations ``` ``` Use @api-design-principles to design RESTful API ``` ### Phase 4: Authentication #### Skills to Invoke - `auth-implementation-patterns` - Authentication - `api-security-best-practices` - API security #### Actions 1. Choose auth strategy (JWT, OAuth2) 2. Implement user registration 3. Set up login endpoints 4. Create auth middleware 5. Add password hashing #### Copy-Paste Prompts ``` Use @auth-implementation-patterns to implement JWT authentication ``` ### Phase 5: Error Handling #### Skills to Invoke - `fastapi-pro` - FastAPI patterns - `error-handling-patterns` - Error handling #### Actions 1. Create custom exceptions 2. Set up exception handlers 3. Implement error responses 4. Add request logging 5. Configure error tracking #### Copy-Paste Prompts ``` Use @fastapi-pro to implement comprehensive error handling ``` ### Phase 6: Testing #### Skills to Invoke - `python-testing-patterns` - pytest testing - `api-testing-observability-api-mock` - API testing #### Actions 1. Set up pytest 2. Create test fixtures 3. Write unit tests 4. Implement integration tests 5. Configure test database #### Copy-Paste Prompts ``` Use @python-testing-patterns to write pytest tests for FastAPI ``` ### Phase 7: Documentation #### Skills to Invoke - `api-documenter` - API documentation - `openapi-spec-generation` - OpenAPI specs #### Actions 1. Configure OpenAPI schema 2. Add endpoint documentation 3. Create usage examples 4. Set up API versioning 5. Generate API docs #### Copy-Paste Prompts ``` Use @api-documenter to generate comprehensive API documentation ``` ### Phase 8: Deployment #### Skills to Invoke - `deployment-engineer` - Deployment - `docker-expert` - Containerization #### Actions 1. Create Dockerfile 2. Set up docker-compose 3. Configure production settings 4. Set up reverse proxy 5. Deploy to cloud #### Copy-Paste Prompts ``` Use @docker-expert to containerize FastAPI application ``` ## Technology Stack | Category | Technology | |----------|------------| | Framework | FastAPI | | Language | Python 3.11+ | | ORM | SQLAlchemy 2.0 | | Validation | Pydantic v2 | | Database | PostgreSQL | | Migrations | Alembic | | Auth | JWT, OAuth2 | | Testing | pytest | ## Quality Gates - [ ] All tests passing (>80% coverage) - [ ] Type checking passes (mypy) - [ ] Linting clean (ruff, black) - [ ] API documentation complete - [ ] Security scan passed - [ ] Performance benchmarks met ## Related Workflow Bundles - `development` - General development - `database` - Database operations - `security-audit` - Security testing - `api-development` - API patterns
Related in Backend & APIs
jfrog
IncludedInteract with the JFrog Platform via the JFrog CLI and REST/GraphQL APIs. Use this skill when the user wants to manage Artifactory repositories, upload or download artifacts, manage builds, configure permissions, manage users and groups, work with access tokens, configure JFrog CLI servers, search artifacts, manage properties, set up replication, manage JFrog Projects, run security audits or scans, look up CVE details, query exposures scan results from JFrog Advanced Security, manage release bundles and lifecycle operations, aggregate or export platform data, or perform any JFrog Platform administration task. Also use when the user mentions jf, jfrog, artifactory, xray, distribution, evidence, apptrust, onemodel, graphql, workers, mission control, curation, advanced security, exposures, or any JFrog product name.
cupynumeric-migration-readiness
IncludedPre-migration readiness assessor for porting NumPy to cuPyNumeric. Use BEFORE substantial porting work begins when the user asks whether code will scale on GPU, whether they should migrate to cuPyNumeric, which NumPy patterns transfer cleanly, what must be refactored before porting, or mentions pre-port assessment, scaling analysis, or refactor planning. Inspect the user's source code, look up NumPy usage, cross-reference the cuPyNumeric API support manifest, and distinguish distributed-scaling-friendly patterns from blockers such as unsupported APIs, scalar synchronization, host round-trips, Python/object-heavy control flow, shape/data-dependent branching, and in-place mutation hazards. Produce a verdict of READY, LIGHT REFACTOR, SIGNIFICANT REFACTOR, or NOT RECOMMENDED, with concrete refactor pointers.
alibabacloud-data-agent-skill
IncludedInvoke Alibaba Cloud Apsara Data Agent for Analytics via CLI to perform natural language-driven data analysis on enterprise databases. Data Agent for Analytics is an intelligent data analysis agent developed by Alibaba Cloud Database team for enterprise users. It automatically completes requirement analysis, data understanding, analysis insights, and report generation based on natural language descriptions. This tool supports: discovering data resources (instances/databases/tables) managed in DMS, initiating query or deep analysis sessions, real-time progress tracking, and retrieving analysis conclusions and generated reports. Use this Skill when users need to query databases, analyze data trends, generate data reports, ask questions in natural language, or mention "Data Agent", "data analysis", "database query", "SQL analysis", "data insights".
token-optimizer
IncludedReduce OpenClaw token usage and API costs through smart model routing, heartbeat optimization, budget tracking, and native 2026.2.15 features (session pruning, bootstrap size limits, cache TTL alignment). Use when token costs are high, API rate limits are being hit, or hosting multiple agents at scale. The 4 executable scripts (context_optimizer, model_router, heartbeat_optimizer, token_tracker) are local-only — no network requests, no subprocess calls, no system modifications. Reference files (PROVIDERS.md, config-patches.json) document optional multi-provider strategies that require external API keys and network access if you choose to use them. See SECURITY.md for full breakdown.
resend-cli
IncludedUse this skill when the task is specifically about operating Resend from an AI agent, terminal session, or CI job via the official resend CLI: installing/authenticating the CLI, sending/listing/updating/cancelling emails, batch sends, domains and DNS, webhooks and local listeners, inbound receiving, contacts, topics, segments, broadcasts, templates, API keys, profiles, or debugging Resend CLI/API failures. Trigger on mentions of Resend CLI, `resend`, `resend doctor`, `resend emails send`, `resend domains`, `resend webhooks listen`, `resend emails receiving`, or agent-friendly terminal automation.
alibabacloud-odps-maxframe-coding
IncludedUse this skill for MaxFrame SDK development and documentation navigation on Alibaba Cloud MaxCompute (ODPS). Helps answer MaxFrame API, concept, official example, and supported pandas API questions; create data processing programs; read/write MaxCompute tables; debug jobs (remote or local); and build custom DPE runtime images. Trigger when users mention MaxFrame, MaxCompute with MaxFrame, ODPS table processing, DPE runtime, MaxFrame docs/examples, DataFrame/Tensor operations, or GPU runtime setup. Works for both English and Chinese queries about Alibaba Cloud data processing with MaxFrame.