HOW CAN I EFFECTIVELY MANAGE MY PYTHON CAPSTONE PROJECT USING GIT AND GITHUB

To start, you’ll need to sign up for a free GitHub account if you don’t already have one. GitHub is a powerful hosting service that allows you to store your project code in a remote Git repository in the cloud. This provides version control capabilities and makes collaboration on the project seamless.

Next, you’ll want to initialize your local project directory as a Git repository by running git init from the command line within your project folder. This tells Git to start tracking changes to files in this directory.

You should then create a dedicated Git branch for development work. The default branch is usually called “main” or “master”. To create a development branch, run git checkout -b dev. This switches your working files to the new branch and tracks changes separately from the main branch.

It’s also recommended to create a basic README.md file that describes your project. Commit this initial file by running git add README.md and then git commit -m “Initial commit”. The commit message should briefly explain what changes you made.

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Now you’re ready to connect your local repository to GitHub. Go to your GitHub account and create a new repository with the same name as your local project folder. Do NOT initialize it with a README, .gitignore, or license.

After creating the empty repository on GitHub, you need to associate the existing local project directory with the new remote repository. Run git remote add origin https://github.com/YOUR_USERNAME/REPO_NAME.git where the URL is the SSH or HTTPS clone link for your new repo.

Push the code to GitHub with git push -u origin main. The -u flag sets the local main branch to track its remote counterpart. This establishes the link between your local working files and the repo on GitHub.

From now on, you’ll create feature branches for new pieces of work rather than committing directly to the development branch. For example, to start work on a user signup flow, do:

git checkout -b feature/user-signup

Make and test your code changes on this feature branch. Commit frequently with descriptive messages. For example:

git add . && git commit -m “Add form markup for user signup”

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Once a feature is complete, you can merge it back into dev to consolidate changes. Checkout dev:

git checkout dev

Then merge and resolve any conflicts:

git merge –no-ff feature/user-signup

This retains the history of the feature branch rather than fast-forwarding.

You may choose to push dev to GitHub regularly to back it up remotely:

git push origin dev

When you’re ready for a release, merge dev into main:

git checkout main
git merge dev

Tag it with the version number:

git tag -a 1.0.0 -m “Version 1.0.0 release”

Then push main and tags to GitHub:

git push origin main –tags

Periodically pull changes from GitHub to incorporate any work from collaborators:

git checkout dev
git pull origin dev

You can also use GitHub’s interface to review code changes in pull requests before merging. Managing a project with Git/GitHub provides version control, easier collaboration, and a remote backup of your code. The branching workflow keeps features isolated until fully tested and merged into dev/main.

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Some additional tips include adding a .gitignore to exclude unnecessary files like virtual environments or build artifacts. Also consider using GitHub’s wiki and issues features to centralize documentation and track tasks/bugs. Communicate progress regularly via commit messages and pull requests for transparency on progress.

Over time your Python project will grow more robust with modular code, testing, documentation, and more as you iterate on features and refine the architecture. Git and GitHub empower you to collaborate seamlessly while maintaining a complete history of changes to the codebase. With diligent version control practices, your capstone project will stay well organized throughout active development.

By establishing good habits of branching, committing regularly, and using robust tools like Git and GitHub – you can far more effectively plan, coordinate and complete large scale Python programming projects from initial planning through to completion and beyond. The structured development workflow will keep your project on the right track from start to finish and make ongoing improvements and collaboration a breeze.

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