Python Development UK: Django and FastAPI Apps, Data and Automation

Where Python fits in our work

Our main web stack is PHP and Laravel, with Node.js for real-time and integration work. Python is the tool we reach for when the job is mainly about data or AI:

• Data processing. Reading exports from several systems, cleaning and matching them, and producing a report or a reconciled dataset.
• Automation. Replacing repetitive manual jobs with scheduled scripts: renaming and filing documents, generating spreadsheets, pulling data from portals with an API.
• AI and machine learning. Most AI tooling, from LLM SDKs to document parsing libraries, is Python-first. See AI integration.
• Web applications in Django, especially where the system is data-heavy or must sit alongside Python data tools.

We also maintain and extend Python and Django systems others have built. A common starting point is a script one person wrote to solve a problem, which has quietly become something the business depends on. We put it into version control, add tests and logging, move credentials out of the code and run it on a proper schedule, so it no longer depends on one laptop being switched on.

Django for web applications

Django is a mature Python web framework with an ORM, migrations, authentication, a built-in admin interface and strong security defaults. The admin alone can save a lot of build time on internal systems, giving staff a working back office for managing records from day one.

Django 6.0 arrived on 3 December 2025, according to the Django project. It added template partials for reusable fragments, a built-in background tasks framework, Content Security Policy configuration and a modernised email API. Django 5.2 is the current long-term support release and receives security fixes until April 2028, so it remains a sensible base for systems that prefer fewer upgrades.

We build Django apps with class-based views where they help, Django REST Framework or Django Ninja for APIs, PostgreSQL for data, and pytest for tests.

FastAPI for APIs and integration services

When we need a lean, fast API, often as a layer between systems or in front of an AI model, we use FastAPI. Request and response models are defined with Pydantic, which validates every input and generates OpenAPI documentation automatically, so the people integrating with your API always have accurate docs.

FastAPI is asynchronous, so it handles many concurrent requests to slow external services efficiently. Combined with a task queue for longer jobs, it suits webhook receivers, data sync services and AI endpoints that call a model provider. See API development.

Data, reporting and automation

A lot of valuable business work is moving data between places and making sense of it. Typical projects:

• Monthly reports that combine accounts, CRM and stock data into one view, delivered automatically rather than assembled by hand.
• Reconciliation jobs that match payments to invoices, or supplier statements to purchase orders, and flag the exceptions for a person to review.
• Imports that take messy supplier spreadsheets, clean them and load them into your shop or ERP.
• Scheduled scripts that pull data from APIs and portals and save it where your team needs it.

We use pandas or Polars for the data work, keep the logic in tested functions rather than notebooks, and run jobs on a schedule with logging and alerts. If the results need a front end, we feed a dashboard.

AI and document processing

Python is where most practical AI work happens. We use it to build tools that read invoices, delivery notes and contracts and pull out structured data, classify incoming emails and documents, or answer questions over your own knowledge base. Each tool is designed with checks: confidence thresholds, a human review step for uncertain results, and logs of what the model was asked and what it returned. See AI document processing.

We are careful about data protection. Personal data is minimised before it is sent to any model provider, and we choose providers and settings that do not train on your data.

Starting a Python project

Whether it is a Django app, an API, an automation script or an AI tool, we start with a free chat about the problem and the data involved. For existing Python code we review it first. Then you get a fixed-price quote for an agreed scope, and the code is yours. Get in touch.

What we deliver

• Django web applications with admin, permissions and reporting
• FastAPI services and APIs with typed request and response models
• Data pipelines that import, clean, reconcile and report on business data
• Automation of repetitive file, spreadsheet and email tasks
• AI integrations: document extraction, classification and LLM-powered tools
• Upgrades of older Django and Python projects to supported versions

How it works and what it costs

Every project gets a fixed-price quote after a free initial chat and a short scoping stage. You own the code and the data.

1. Free chat

   Tell us the problem in plain English: what you do now, what goes wrong and what "better" looks like. No charge, no obligation.

2. Scoping

   We map the processes, systems and data involved, agree what is in and out, and write it down so there are no surprises.

3. Fixed-price quote

   You get a fixed price for the agreed scope, or a phased plan for bigger builds, so you can start small and prove it works.

4. Build and test

   We build in short stages you can see and try, test against real data, then go live carefully with a rollback plan.

5. Hand over and look after

   You own the code and the data. We can host it, support it and keep improving it, or hand it to your own team.

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