Demonstrate Git and build workflow

Q: Demonstrate Git and build workflow

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.

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Question

End-to-End Git and Tooling Workflow (Feature Branch + CI)

Context

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.

Task

Show the exact steps and commands to:

Prepare your IDE and SDK locally (install/check Git, Python, virtualenv; open in IDE).
Clone the repository.
Create and switch to a feature branch.
Initialize the project and build from scratch (install dependencies; package if applicable).
Add and run unit tests locally.
Commit with meaningful messages.
Push to the remote feature branch.
Open a pull request.
Configure CI to run the test suite on every push and pull request.

Include commands and any minimal files needed (e.g., YAML for CI). Call out assumptions you make.

Demonstrate Git and build workflow

End-to-End Git and Tooling Workflow (Feature Branch + CI)

Context

Task

Solution

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Demonstrate Git and build workflow

Overview

End-to-End Git and Tooling Workflow (Feature Branch + CI)

Context

Task

Solution

Comments (0)