This question evaluates proficiency with version control workflows, local development and build toolchains, continuous integration configuration, and reproducible testing practices in the context of a Machine Learning Engineer working on a Python project.
You are given a repository URL and asked to demonstrate a pragmatic, reproducible workflow from local setup to CI. Assume a typical backend/ML Python project, GitHub as the remote, and a Unix-like environment (macOS/Linux). If the actual stack differs, adapt the steps accordingly.
Show the exact steps and commands to:
Include commands and any minimal files needed (e.g., YAML for CI). Call out assumptions you make.
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