FastAPI service development
Typed routing, dependency injection, async I/O, background tasks and auto-generated OpenAPI schemas your client teams can consume directly.
Typed, tested Python backends that hold up in production.
FastAPI services, data-validation layers and automated test suites — Python backends built to be read, extended and trusted by whoever maintains them next.
What you receive
Overview
Most Python problems we are asked to fix are not language problems. They are missing contracts: an endpoint that accepts whatever arrives, a background job nobody can reproduce locally, a test suite that passes because it asserts almost nothing.
We build Python the other way round. Request and response shapes are declared with Pydantic before a handler exists. Behaviour is pinned by Pytest before it ships. FastAPI gives us typed routing and generated OpenAPI documentation your frontend team can work against on day one.
Technologies
Each choice is made per engagement and written down with its reasoning.
Problems we solve
If one of these describes your situation, this is the right page.
Untyped payloads reach business logic and surface as 500s. We push validation to the boundary so bad input is rejected with a precise, documented error instead of corrupting state.
We write Pytest suites around real behaviour — fixtures, parametrised cases, and database isolation — so a green run is evidence rather than decoration.
Third-party APIs change. We wrap them in typed clients with explicit error handling, retries and logging, so drift shows up as a failing test, not a support ticket.
A one-off script now runs payroll. We turn that into a maintainable service with configuration, structured logging and a rollback path.
Capabilities
Concrete capabilities rather than adjectives. Anything not listed here, we will tell you we do not do.
Typed routing, dependency injection, async I/O, background tasks and auto-generated OpenAPI schemas your client teams can consume directly.
Models for requests, responses, settings and message payloads — validated at the edge, serialised consistently, and reused across services.
Unit, integration and contract tests with fixtures, factories and CI wiring; coverage reporting so gaps are visible rather than assumed.
Resource modelling, pagination, versioning, authentication and rate limiting designed before implementation starts.
PostgreSQL schema design, migrations, query tuning and the ORM or query-builder choice that actually fits the access pattern.
Dockerised services, environment separation, secret handling and pipelines that run the test suite before anything reaches production.
Process
Specific to this service. The wider seven-stage delivery process wraps around it.
We map the entities, access patterns and integration points before any endpoint is written.
Pydantic schemas and route signatures are agreed and published so frontend work can start in parallel.
Each slice ships with its own tests, so progress is demonstrable rather than described.
Load behaviour, error paths, timeouts, retries, logging and authentication are tested explicitly.
CI/CD wiring, environment configuration, documentation and a live walkthrough with your team.
Related work
Entries marked as a content placeholder are reserved for projects whose details are not yet published.
Python DevelopmentOur own client platform: authentication, project tracking, invoicing, real-time messaging and Stripe payments on Next.js and Supabase.
60+ pages deployed · 6 service lines integrated · Real-time client portal
Custom AI AgentsA retrieval-grounded support agent handling FAQs, order status and product questions, with escalation to the human team.
70% fewer support tickets · 24/7 availability · Multilingual languages
Pricing
Indicative tiers. The final scope and a fixed quote are confirmed in writing after discovery — nothing starts on an estimate.
A focused service or integration with a clear boundary.
A full backend: API, database, auth and test suite.
Platform-scale work, multiple services, ongoing delivery.
Questions
The questions we are actually asked about python development, answered without hedging.
FastAPI is our default for API-first work because typing, validation and documentation come from the same source — the Pydantic models. We use Django when you need its admin, ORM and batteries-included conventions for a content-heavy or CRUD-heavy product, and Flask when you are extending something already built on it. The decision is made in discovery, with reasons written down.
That is the point of it. We write tests against behaviour rather than implementation details, use factories instead of brittle fixtures where it helps, and wire the suite into CI so it runs on every change. You get a coverage report and a short document explaining what is covered and what deliberately is not.
Yes. We usually start with a read-only review: dependency state, test coverage, obvious correctness risks and the two or three changes that would most reduce maintenance cost. You get that assessment as a written document before any refactoring is agreed.
You do. Work is delivered in your repository, under your accounts, with no runtime dependency on Hirelyx infrastructure.
Background tasks go through Celery or FastAPI background tasks depending on durability requirements, with Redis or a database-backed queue. Scheduled jobs are idempotent and observable, so a missed run can be replayed safely.
Related solutions
Internal tools, dashboards, APIs and platforms for the parts of your business no off-the-shelf product fits — typed, tested and delivered in your own repository.
02Triage, extraction, drafting and research steps handled by grounded AI inside your existing processes — scoped narrowly, evaluated honestly, and escalated to people by design.
Or browse all six services.
Tell us where you are now and what needs to be true in three months. You will get a written scope and a fixed quote before anything starts.
Prices shown exclude third-party costs such as hosting, model API usage and advertising spend, which are paid directly by you.