FastAPI Development Service
Senior Python engineers building production FastAPI services with async SQLAlchemy, Pydantic, and proper OpenAPI documentation.
Why FastAPI Replaced Flask for New Python Backends
FastAPI is the default modern Python web framework in 2026. It is faster than Flask, has built-in async support, generates OpenAPI docs from your function signatures, and gives you free request validation via Pydantic. Most new Python APIs ship on FastAPI; the codebases still on Flask are usually legacy or shipping plans to migrate.
The catch is that async Python is genuinely harder than sync Python. Mixing async and sync code blocks the event loop. Using a sync database driver inside an async route makes everything slow. Misusing dependency injection causes resource leaks. Engineers who learned FastAPI by following the official tutorial often write code that compiles but bypasses every reason to use the framework in the first place.
Pydantic v2 changed a lot. The validator API is different. Computed fields exist. `model_config` replaces inner `Config` classes. Settings now live in a separate package (`pydantic-settings`). Migrating a Pydantic v1 codebase to v2 is non-trivial — it touches every model, every validator, and every settings class.
The deployment story is also subtler than people assume. Gunicorn with Uvicorn workers vs raw Uvicorn vs Granian — each has different latency profiles. Connection pooling differs by driver. Hot reload in production is a footgun. We have rescued FastAPI apps that ran 30x slower than they should because the connection pool was scoped per-request instead of per-process.
AsyncForge has senior FastAPI engineers shipping production APIs daily. Submit endpoints, async background jobs, Pydantic schema work, or a full FastAPI build. Light delivers in 4 days, Standard in 48 hours, Pro in 1 day.
What You Get
Async-first endpoints
Routes written async/await with async SQLAlchemy 2.0 and asyncpg/aiomysql. No accidental sync calls blocking the event loop. Connection pool sized correctly for the worker model.
Pydantic v2 schemas
Input validation and output serialisation via Pydantic v2 models. Computed fields, model validators, and proper from_attributes for ORM mapping. v1-to-v2 migrations handled.
OpenAPI auto-docs
Swagger UI at /docs, ReDoc at /redoc. Schemas tagged, examples populated, security schemes declared. Always up to date because the docs are derived from the code.
JWT + OAuth auth
Bearer auth with refresh tokens, OAuth providers via Authlib, role/permission dependencies, RFC-correct error responses.
Background tasks
BackgroundTasks for fire-and-forget, Celery or Arq for durable queues, APScheduler for cron-like recurring jobs.
Testing with HTTPX
Pytest with `httpx.AsyncClient` for integration tests against a real test database. Factory fixtures, transaction rollbacks per test, CI-friendly.
Technologies We Use
How It Works With AsyncForge
Subscribe
Pick a tier, project board live.
Submit FastAPI work
Endpoints, schemas, migrations, background jobs.
We deliver
Async-correct code with tests and OpenAPI docs.
Iterate
Unlimited revisions.
Frequently Asked Questions
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