A production web process
Run a production HTTP server such as Gunicorn or Uvicorn, bind it to 0.0.0.0 and read the assigned port from the environment. Pin dependencies so the same revision builds consistently.
Deploy and host a Python app with your coding agent
Put an existing Django, Flask or FastAPI app online from Claude Code, Cursor or Codex. Use GitHub or push directly to aidrop Git.
THE DEPLOYMENT CONTRACT
What the app needs in production
Your coding agent can inspect and change the repository. aidrop builds the committed revision and runs it when these requirements are explicit.
Durable data outside the container
Python apps can use managed PostgreSQL on Pro and above. Run migrations as an explicit deployment step and keep uploaded files in external object storage.
RUNTIME CHECKLIST
Make the build predictable
The exact framework matters less than a clear production contract. These are the details your agent should verify before the first build.
Installpip install -r requirements.txt or the repository's locked equivalent
StartGunicorn for Django/Flask or Uvicorn for FastAPI
ImportPoint the server at the correct application module and object
NetworkListen on 0.0.0.0 and the PORT provided at runtime
HealthReturn a successful response from a lightweight HTTP route
# Django
gunicorn config.wsgi:application --bind 0.0.0.0:$PORT
# Flask
gunicorn "app:create_app()" --bind 0.0.0.0:$PORT
# FastAPI
uvicorn app.main:app --host 0.0.0.0 --port $PORTFIRST-BUILD BLOCKERS
What usually needs fixing
Your agent can resolve these in the repository before it hands back a public address.
The development server starts
Replace flask run or manage.py runserver with Gunicorn or another production server.
The application import is wrong
Confirm the Python module path and exported WSGI or ASGI application object.
Migrations happen implicitly
Make schema migrations an explicit, reviewable deployment step.
Uploads use the local filesystem
Use external object storage for durable user uploads and generated files.
FROM GIT TO HTTPS
One deployment path your next session can repeat
Connect GitHub or use aidrop Git. Every build keeps the revision and log with the Project, while a successful deployment keeps the same public address for the next change.
Deployment checklist
- Pinned dependencies and production command
- Environment values kept outside Git
- Health endpoint answers on the assigned port
- Public HTTPS address after a successful build
ASK YOUR CODING AGENT
Start with a concrete deployment request
Deploy this Python app on aidrop. Identify whether it uses Django, Flask or FastAPI, then check its production server, import path, PORT binding, pinned dependencies, migrations, values and health endpoint. Use its existing Dockerfile if it is production-ready; otherwise configure a source build.
Connect Claude Code, Cursor or CodexCan I deploy Django, Flask and FastAPI on aidrop?
Yes. Each works when the repository has pinned dependencies and a production WSGI or ASGI server that binds to 0.0.0.0 and the assigned port.
Can aidrop deploy my existing Python Dockerfile?
Yes. Your coding agent can deploy an existing production-ready Dockerfile with an explicit build context. The running container must follow the same network and durable-data requirements.
How should I run Python database migrations?
Treat migrations as an explicit deployment action rather than hiding them in application startup. Your agent can inspect the framework, run the appropriate command and verify the result before the new version serves traffic.
Where should a Python app store uploaded files?
Do not rely on the app container's local filesystem for durable uploads. Put them in external object storage and keep its credentials in Project values.
Host your Python app
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