Python: Deploy with GitHub Actions

How to deploy your Python code using GitHub Actions

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Stackhero offers a ready-to-use Python cloud solution that provides a host of benefits, including:

• Deploy your application in seconds with a simple git push.
• Use your own domain name and benefit from the automatic configuration of HTTPS certificates for enhanced security.
• Enjoy peace of mind with automatic backups, one-click updates, and straightforward, transparent, and predictable pricing.
• Get optimal performance and robust security thanks to a private and dedicated VM.

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GitHub Actions makes it easy to automate tasks, including deploying your Python code directly to your production servers.

In this guide, you will learn how to securely and reliably configure GitHub Actions to deploy your Python code to both staging and production environments.

To keep things organised, you will use two branches: staging and production. Each time you push code to these branches, it will be automatically deployed to the corresponding Stackhero instance.

Having a staging instance is not mandatory. You can follow this guide with just a single production instance. However, to ensure smooth deployments and to deploy to production with confidence, it is strongly recommended to maintain both a staging and a production instance. This practice is an industry standard and a reliable approach that helps you avoid many issues.

Before you begin, make sure you have a GitHub account and a repository hosting your code.

Creating the Python services

Go to your Stackhero dashboard and create two Stackhero services, one for staging and one for production. For clarity, you may wish to name them "Production" and "Staging".

Don't have a Stackhero account yet? You can sign up for free in just two minutes and then create your Python cloud services in just a few clicks.

Example of production and staging services

Configure SSH keys

SSH keys allow GitHub Actions to securely connect to your Python service for code deployment. This step is essential for protecting your Stackhero services.

On your computer, you can generate new SSH keys by running:

ssh-keygen -C "" -f /tmp/ssh_key -N ""

Add the public key

First, display the public key you have just generated:

cat /tmp/ssh_key.pub

Next, in your Stackhero dashboard, select your "production" Python service and click the "Configure" button.

Get service settings

Follow these steps:

1. Under SSH public keys, click on Add a public key.
2. For Description, enter GitHub Action.
3. For Key, paste the public key you have just copied.

Add public key

Add the private key

Go to your GitHub project page, click on Settings, then Environments. Choose New environment.

Configuring GitHub environments

In the Name field, type "production" and confirm.

Setting the environment

Click on the No restriction button and select Selected branches and tags.

Setting environment restrictions

Then, click on Add deployment branch or tag rule, enter "production" in the Name pattern field, and click Add rule.

Setting environment branch Setting environment branch

In the Environment secrets section, click Add secret.

Add secret

Now, display the private key you generated earlier:

cat /tmp/ssh_key

In the secret setup, use STACKHERO_SSH_PRIVATE_KEY as the Name and paste the private key as the Value.

Setting the SSH private key secret

Next, in the Environment variables section, click on Add variable.

Setting variables

Enter STACKHERO_ENDPOINT as the Name and paste your Python service endpoint as the Value. You will find this endpoint in your Stackhero dashboard.

Setting the endpoint variable

If you have customised your service's domain name, use the customised version instead of <XXXXXX>.stackhero-network.com.

Delete the generated keys

For security reasons, it is advisable to delete the SSH keys from your computer now, as you will not need them anymore:

rm /tmp/ssh_key /tmp/ssh_key.pub

Configure the GitHub Actions workflow

In your Git repository, create a directory called .github/workflows if it does not already exist. Then add a file named deploy-to-stackhero.yml inside it.

# File: .github/workflows/deploy-to-stackhero.yml

name: Deploy to Stackhero
run-name: Deploy branch "${{ github.ref_name }}" to Stackhero

on:
  push:
    # List of branches that will trigger the deploy action following a git push.
    # Do not forget to create an environment corresponding to the branch name in GitHub (in "Settings"/"Environments").
    # Then add the corresponding secret "STACKHERO_SSH_PRIVATE_KEY" and variable "STACKHERO_ENDPOINT" in this environment.
    branches: [ "production", "staging" ]

jobs:
  Deploy:
    environment: ${{ github.ref_name }}
    runs-on: ubuntu-latest
    steps:
    - uses: stackhero-io/github-actions-deploy-to-stackhero@v1
      with:
        # The secret "STACKHERO_SSH_PRIVATE_KEY" and the variable "STACKHERO_ENDPOINT" should be defined in the corresponding branch environment on GitHub under "Settings"/"Environments".
        ssh_private_key: ${{ secrets.STACKHERO_SSH_PRIVATE_KEY }}
        endpoint: ${{ vars.STACKHERO_ENDPOINT }}

Once you have added the workflow file, you can commit your changes:

git add -A .
git commit -m "Add GitHub Actions to deploy to Stackhero"

You can create a production branch with:

git checkout -b production

And push your changes to GitHub:

git push --set-upstream origin production

This will push your code to the production branch on GitHub and trigger GitHub Actions, which will deploy your code to your Stackhero instance.

To check your deployment status, simply go to your GitHub project page and click on Actions.

GitHub Actions that deployed to production

That's it. You now have automatic deployments to production using GitHub Actions.

Creating the staging environment

Setting up a staging environment is almost identical to configuring production. You just need to repeat the steps above, replacing production with staging wherever it appears.

After configuring the environment, you can create a staging branch as follows:

git checkout -b staging

Then push your staging branch to GitHub:

git push --set-upstream origin staging

Your staging branch will then be automatically deployed to the Python instance you have dedicated to staging.

Going further

It is recommended to protect the production and staging branches to prevent direct pushes. With this setup, team members will need to create pull requests to the staging branch, which should be reviewed and merged by users with the appropriate permissions. Once changes have been validated on the staging platform, the pull request can be merged into the production branch by an authorised person.

This workflow ensures that only approved changes reach production, while also improving reliability by testing new features on staging before they go live.