Automate 5 Essential GitHub Operations with Python

Managing your GitHub repositories and projects can become time-consuming, especially when you have multiple ongoing projects. In this article, we will explore five essential GitHub operations that can be automated using Python. We'll be using the popular PyGithub library to interact with the GitHub API.

Table of Contents

  1. Setting up PyGithub
  2. Creating a Repository
  3. Labeling Issues
  4. Automating Pull Requests
  5. Managing Collaborators
  6. Closing Issues

Setting up PyGithub

Before we begin, you need to install the PyGithub library. You can install it using pip:

pip install PyGithub

Next, you'll need to create a GitHub Personal Access Token with the appropriate permissions for the tasks you want to automate.

Now, we can start by importing the library and authenticating with our access token:

from github import Github

g = Github("your_access_token")

Creating a Repository

Creating a repository is a common task, and automating it can save you a lot of time. With the PyGithub library, it's incredibly simple:

user = g.get_user()
repo = user.create_repo("MyNewRepository")

This code snippet will create a new repository with the name "MyNewRepository."

Labeling Issues

Managing and organizing issues by applying labels can be easily automated. Let's say we want to label all issues with the word "bug" in the title:

repo = g.get_repo("your_username/your_repository")
issues = repo.get_issues(state="open")

for issue in issues:
    if "bug" in issue.title.lower():

This code fetches all open issues in your repository and adds the "bug" label to any issues containing the word "bug" in the title.

Automating Pull Requests

Creating and managing pull requests can be automated using Python as well. Let's say you want to automatically create a pull request to merge a feature branch into the main branch:

repo = g.get_repo("your_username/your_repository")
base_branch = "main"
head_branch = "feature_branch"
pull_request = repo.create_pull(title="Merge feature branch", body="Merging the feature branch into the main branch.", head=head_branch, base=base_branch)

This code snippet creates a pull request with the specified title and body, requesting to merge the feature_branch into the main branch.

Managing Collaborators

Adding collaborators to your repository can be automated too. Here's how you can add a collaborator with "push" access:

repo = g.get_repo("your_username/your_repository")
collaborator_username = "new_collaborator"
repo.add_to_collaborators(collaborator_username, permission="push")

This code snippet invites the specified user to collaborate on your repository with "push" access.

Closing Issues

Closing issues programmatically is another helpful automation. Let's say you want to close all issues that have been labeled as "wontfix":

repo = g.get_repo("your_username/your_repository")
issues = repo.get_issues(state="open")

for issue in issues:
    labels = issue.get_labels()
    for label in labels:
        if == "wontfix":

This code snippet closes all open issues with the "wontfix" label.

In conclusion, automating essential GitHub operations using Python can save you a significant amount of time and help you manage your projects more efficiently. The PyGithub library makes it easy to interact with the GitHub API, enabling you to focus on writing automation scripts for your specific needs.

An AI coworker, not just a copilot

View VelocityAI