Python development
Backend systems, automation and data work in a language that is quick to write and unusually easy to hand over.
Backend and data
Chosen per project
Maintainable handover
Python’s advantage is breadth. The same language covers a web backend, a data pipeline, an automation script and a machine learning model, which means one team can own a system end to end instead of handing it between specialists.
Django gives you an admin interface, authentication and an ORM on day one. FastAPI gives you a fast, typed, self-documenting API. Which one we reach for depends on whether the system needs a back office.
What we build with Python
Business applications that need an administrative back office quickly
APIs serving data to web and mobile clients
Data processing, reporting and scheduled automation
Machine learning features integrated into an application
Where it fits — and where it does not
Good fit when
Systems combining application logic with data work
Projects that benefit from Django’s built-in admin
Automation of repetitive operational tasks
Anything involving analysis or machine learning
Consider something else when
Extremely high-throughput services where runtime speed dominates
Real-time features better served by an event-driven runtime
Teams with no Python experience and no time to acquire it
One language across several jobs
Python’s value in a business system is that the same codebase and the same team can cover the web application, the data work and the automation around them.
Web backend
Django or FastAPI serving the application.
Admin back office
Internal tooling generated from the data model.
REST API
Typed, documented endpoints for clients.
Python codebase
Shared models, shared utilities, one deployment story.
Data pipelines
Imports, transformations and reconciliation.
Scheduled jobs
Reports, reminders and overnight processing.
Machine learning
Models trained and served from the same stack.
How we work with Python
Framework choice
Django when a back office and ORM save weeks; FastAPI when the deliverable is a fast, typed API.
Typing
Type hints throughout with static checking, which is what keeps a growing Python codebase safe to change.
Data layer
Migrations under version control and queries reviewed for the indexes they will actually need.
Scheduled work
Celery or equivalent for background jobs, with monitoring on failures rather than silent retries.
Our typical Python setup
| Concern | What we use |
|---|---|
| Web framework | Django for full applications, FastAPI for API-first services |
| Database | PostgreSQL through the ORM, with migrations in version control |
| Background jobs | Celery with a broker, monitored for failures |
| Typing | Type hints with mypy or pyright in the pipeline |
| Testing | pytest with fixtures and a real database in integration tests |
| Packaging | Pinned dependencies and containerised deployment |
Frequently asked questions
Django when you want an admin interface, authentication and an ORM out of the box — it can save weeks on a business application. FastAPI when the product is an API consumed by a separate front end and you want typed, self-documenting endpoints.
For the vast majority of business applications the bottleneck is the database, not the language. Where raw throughput genuinely matters, the hot path can be moved elsewhere while the rest of the system stays in Python.
Yes — it has mature libraries for virtually every database, message broker and third-party API, which is part of why it is a common choice for integration work.
Services built with Python
AI/ML Development
Machine learning applied where it measurably beats a simpler solution — and honest advice when it does not.
Custom Software Development
Software shaped around the way your business already works, instead of a packaged product you have to reorganise around.
API Development
The interfaces that let your systems talk to each other, and let partners build on top of what you have.
Web Application Development
Applications that run in the browser, handle real workloads and hold up when several departments depend on them at once.
Tell us what you are trying to build
Describe the problem in plain language and we will tell you what it would take to solve it — the approach, the moving parts and the sensible order to build them in. No obligation either way.