Do I need Docker to deploy a Python automation?
Short answer
No. Docker is one way to package a Python app, but it's not required — and for most automations it's overkill. Snapdock auto-detects how your script runs and its dependencies, so you can deploy a Python automation with no Dockerfile, YAML, or build config at all.
Why it happens — and how to fix it.
What Docker actually does
Docker packages your code and its dependencies into a container so it runs the same everywhere. Useful for complex apps — but it means writing and maintaining a Dockerfile, which is exactly the DevOps most builders want to avoid.
You don't need it for a scheduled script
A sync, a report, or a router is a script with a few dependencies. Snapdock reads those dependencies automatically and runs the code on a managed cloud machine — no container to build.
The fix: drop the folder in
Upload the .py, .zip, or repo to Snapdock. It detects the entrypoint and packages, fixes Windows-to-Linux issues, and deploys — no Dockerfile in sight.
Run it on Snapdock — no card to start.
Deploy and run any workflow or automation 24/7 — no servers, no Docker, no YAML.