Python development services
What we reach for when the work is data, automation or a model API.
We build Python backends and services: Django applications with an admin your operations team will genuinely use, FastAPI services for typed JSON APIs and AI integration, and the scheduled pipelines that move data between systems while everyone is asleep. Type hints throughout, and a monitored failure path for every job.
Where Python fits
Python is a general-purpose language with established libraries for web applications, data processing, scientific work and automation. The choice should follow the workload and the team maintaining it. Compare Node and Laravel when the project is primarily a business application with an existing JavaScript or PHP team.
Django or FastAPI
Django suits applications that need a data model, authentication, permissions and an administrative interface. Those built-in capabilities can reduce custom work, but the admin still needs permissions, validation and a workflow that fits its users.
FastAPI suits API services. Its documented features include request validation and OpenAPI-based documentation. Generated clients can help keep interfaces consistent when schema generation, client updates and integration tests are part of the release process. Type annotations alone do not keep independently deployed systems in sync.
Data and automation requirements
Bring examples of the files, records or events the system must handle. Define ownership, access rules, validation and the action to take when an import is incomplete. For scheduled jobs, discuss retries, duplicate prevention, alerting and a way to check the output. See workflow automation for the wider delivery scope.
Performance and handover
Measure representative workloads before choosing a concurrency model, cache or queue. CPU time, database access and external API latency create different constraints; there is no single memory or speed comparison that settles every Python project. Agree the supported runtime, deployment process, tests and maintenance responsibilities before handover.
What we build with Python
Django business applications
Internal systems with roles, approvals and audit trails, plus a generated admin your operations team can run without filing a ticket.
FastAPI services
Typed JSON APIs with generated OpenAPI documentation, sitting in front of a database or a handful of third-party systems.
AI and model integrations
Retrieval pipelines, embeddings, document processing and agent workflows against hosted models, with evaluation before release.
Explore →Data pipelines and reporting
Scheduled extraction, cleaning and loading between CRMs, spreadsheets, warehouses and dashboards, where a failure wakes somebody rather than nobody.
Scraping and monitoring
Compliant collection of pricing, catalogue or listing data, with change detection and rate limits that keep you off a block list.
Automation of manual processes
The overnight jobs, reconciliations and report generation currently occupying somebody's first two hours every morning.
Our Python stack, by layer
Python compared with the alternatives
Django vs Laravel
Both are batteries-included frameworks for database-backed applications and both are genuinely good. Laravel has cheaper hosting almost everywhere and a much larger PHP hiring pool. Django's generated admin and Python's data libraries take it when the same project also carries reporting, scraping or model work.
FastAPI vs Node.js for an API
Node handles very high concurrency a little more cheaply and lets you share types with a TypeScript front-end, which is worth real money on a small team. FastAPI wins the moment the service touches data science, document processing or model APIs, because the Python libraries are simply better and better maintained.
Python vs a no-code automation tool
For a straightforward two-system sync, n8n or Make is cheaper and faster to change, and we build those too. Write Python when the logic branches properly, when per-task pricing starts to hurt at your volume, or when the transformation needs to live under version control with tests around it.
Python, answered
Django or FastAPI, which should we use?
Django when there is a database schema, user roles and back-office screens. The generated admin alone saves weeks of work nobody enjoys. FastAPI when you are building a service other applications consume, or anything talking to model APIs. On larger systems we run both: Django for the application, FastAPI for the machine-facing endpoints.
Can Python handle our traffic?
For ordinary business volumes, comfortably. It is slower per request than Go or .NET, so the design carries the load: caching, the right indexes, queues for slow tasks, more instances behind a balancer. If your workload turns out to be compute-bound at scale, we will tell you and use a different tool for that piece.
Do you use Python for AI features?
Yes, it is our default for anything involving retrieval, embeddings or document processing, because the client libraries and tooling are strongest there by some distance. The user-facing part is usually a Next.js interface talking to a Python service over a typed API.
Can you take over an existing Django project?
Yes. The first pass covers Django and dependency versions, migration state, test coverage, and any custom code sitting around authentication and payments, which is where the expensive surprises live. You get a prioritised written plan before we touch a line.
How do you handle scheduled jobs?
Celery with Redis for anything that retries or fans out, plain scheduled tasks with a lock for simple nightly work. Either way it is monitored. A job failing silently for three weeks is worse than never having written it.
Can we hire a Python developer from you?
Yes. Relevant developer profiles start at USD 22/hour or USD 2,900/month for 160 reserved hours. We confirm relevant experience, availability, responsibilities and the final rate after reviewing the work.
A Python service or an automation in mind?
Describe the data and the systems it has to move between. You get an approach and a range back, not a request for a discovery call.