Setup a CI pipeline

1. Obtain Personal access token and add it to GitHub secrets

• Create a new personal access token for your GitHub repository. You may get it by going to Settings -> Developer settings page of your GitHub account. Select Personal access token tab and create a new classic token. Give the token a meaningful name and provide the necessary permissions (e.g., repo and workflow).

• Add this token to your repository’s secrets. Go to Settings within your repository page and select Secrets. Add a new secret by pasting the access token in the Value field and giving a meaning name (e.g., PAT).

2. Add your Designite key to secrets (optional)

Add your Designite key to your GitHub’s repository secrets, if you have Designite’s professional (or academic) license key. Let us call it D_KEY. If your codebase is less than 50,000 lines of code, it won’t impact you. If your project is larger, you will need to specify the license key with this action. Check our licensing page for more information about Designite licenses.

3. Use DPy Action

In this step, we will use DPy Action. Create a folder .github on your root directory of the project and create workflows folder inside the .github folder. Create a workflow file (say actions.yml) in the newly created workflows folder. The contents of the action.yml file depend upon your project language and tasks. A sample action file is provided below.

name: DPy Code Quality

on:
push:
    branches: [main]
pull_request:
    branches: [main]

jobs:
quality:
    runs-on: ubuntu-latest
    steps:
    - name: DPy Action
        uses: DesigniteTools/DPyAction@v1.0.0
        with:
        PAT: ${{ secrets.PAT }}
        D_KEY: ${{ secrets.D_KEY }}

Tip

Check out our post on Streamlining Incremental Code Analysis with GitHub Actions for a more refined use-case.

What you will get?

Once configured, your Python project will be analyzed on each push in the main branch (can be configured differently), and the analysis report will be placed as an Actions artifact in your GitHub account. You can download the artifact later for further analysis.