FastAPI services
Typed request and response models with Pydantic, automatic OpenAPI docs, async endpoints where I/O justifies them, and dependency injection for auth and database sessions.
Web & Application Development
Servers, Hosting & DevOps
AI & Automation
Performance, Security & Care
Web & Application Development
Python covers three distinct kinds of work for me: web services with FastAPI or Django, data work with pandas and friends, and the automation glue that runs on a server and stops somebody doing a task by hand every week.
The third category is undervalued. A sixty-line script that reconciles two exports, or watches a directory and pushes files to an API, often returns more than a feature would, and it is cheap to build. I mention it because clients rarely think to ask.
How I work on it
Adjusted to the job, but this is the shape it usually takes.
A lockfile and a defined Python version from the start. "Works on my machine" is almost always a dependency resolution difference.
Type hints on public interfaces and data models, checked in CI. Not dogmatic coverage of every local variable.
Data logic gets unit tests with real awkward sample rows. The empty string, the wrong date format, the duplicate ID.
Deployed under supervision with logging, not left in a terminal session that dies with the SSH connection.
Questions
FastAPI when the deliverable is an API and the consumers are other services or a JavaScript frontend. Django when you want the admin, the ORM, sessions, templates and auth to already exist. That back office is worth a lot on internal tools.
cPanel has a "Setup Python App" feature built on Passenger, and simple WSGI apps do run there. It is workable for low-traffic tools. Anything with Celery workers or heavy dependencies belongs on a VPS.
I do applied work, using existing models through APIs, embeddings and retrieval, classification with off-the-shelf libraries. Training novel models from scratch is a research specialism and I would point you elsewhere for that.