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Giorgio Lasala
Giorgio Lasala

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Configuring GitHub Codespace for repository analysis 🔎📙(Part 3)

And here we are, at the final step of configuring our environment for repository analysis. This part, where we create a custom configuration for GitHub Codespaces, has been both enjoyable and a valuable learning experience for me. It's interesting how this particular aspect was the one I was least familiar with, yet it has provided me with the opportunity to learn and grow the most.

What is GitHub Codespaces?

GitHub Codespaces provides developers with a cloud-based development environment, allowing for faster onboarding, coding on any device, and maintaining consistency across environments. Its user interface resembles popular IDEs such as Visual Studio Code, but it operates directly within your web browser. To tailor your project to GitHub Codespaces, you can create custom configuration files that ensure a consistent setup for all project users.

Starting with DevContainers

The first thing we're going to configure is DevContainers feature. What is it?

DevContainers is a feature of Visual Studio Code that allows you to define and configure containerized development environments. With DevContainers, you can specify all the dependencies, tools, and settings required for the development environment within a configuration file, known as devcontainer.json.
When you open Codespace with DevContainers configuration, it automatically starts a Docker container with all the preconfigured necessary resources, providing a consistent and isolated development environment.
This is particularly useful for ensuring that all team members have the same configuration and dependencies, facilitating collaboration and quick project startup.


In our case, I have created a devcontainer.json file inside the .devcontainer folder with the following configuration:

  "name": "Mergestat Codespace Project",
  "dockerComposeFile": "docker-compose.yml",
  "workspaceFolder": "/workspaces/${localWorkspaceFolderBasename}",
  "service": "app",
  "remoteUser": "vscode",

  // Configure tool-specific properties.
  "features": {
    "": {}
  "customizations": {
    "codespaces": {
      "openFiles": [
    "vscode": {
      "extensions": [
      "settings": {
        "sqltools.connections": [
            "previewLimit": 50,
            "server": "postgres",
            "port": 5432,
            "driver": "PostgreSQL",
            "name": "mergestat",
            "database": "mergestat",
            "username": "postgres",
            "password": "postgres"

  // Use 'forwardPorts' to make a list of ports inside the container available locally.
  // This can be used to network with other containers or the host.
  "forwardPorts": [5432],

  "initializeCommand": ".devcontainer/",
  // Use 'postCreateCommand' to run commands after the container is created.
  "postCreateCommand": ".devcontainer/"
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Let's analyze the individual sections of the file in detail:

  • name: Specifies the name of the DevContainer configuration.
  • dockerFile: Specifies the path to the Dockerfile/DockerCompose used to build the container image.
  • customizations"/codespaces/openFiles: to open automatically the README file.
  • customizations/vscode/extensions: Lists the Visual Studio Code extensions that should be installed.
  • customizations/vscode/settings: Specifies custom Visual Studio Code settings that should be applied when working in the DevContainer. These settings can include editor preferences, formatting options, and more.
  • forwardPorts: Lists the ports that should be forwarded in Codespace to test and debug your application.

  • initializeCommand/postCreateCommand: Specifies a command that should be executed when the Codespace is initialized and after the container is created. This is used to prepare the environment as explained in greater detail in the following sections.

Docker-compose configuration

In our docker-compose file, we currently have two containers:

  1. The "postgres" container: This container is responsible for starting the PostgreSQL database. It provides the necessary environment for running and managing the database.

  2. The "app" container: This is the main container, built from the Dockerfile. It installs the PostgreSQL tools and will be used to restore the database.


Additionally, in the .devcontainer configuration, we privately expose port 5432 of the "postgres" container using "forwardPorts". This allows us to access the PostgreSQL database running inside the container from the local machine.


Features & VSCode Customization

With just a few lines of code, we can customize our environment in the following ways:

  • Installing the GitHub CLI
  • Installing VSCode extensions for interacting with the database
  • Initializing the default database connection

Bash Scripts for Codespace Configuration

We have two scripts executed at different times. The first script,, is executed before initialization and simply creates the folder where the database will be stored. In reality, this step could be skipped, but it helped me understand the Codespace lifecycle better.

The second script is the more important one. It is executed after initialization and performs essential configurations and setup tasks to ensure the environment is fully prepared.

Let's analyze the script:

workflow_name="Run Analysis"

echo "Get info on latest GitHub Actions run..."
run_id=$(gh run list -w "$workflow_name" -L 1 --json databaseId | jq '.[]| .databaseId')

echo "GitHub Actions latest runId: $run_id"

echo "Download artifacts..."
gh run download $run_id -D $(pwd)/pgdata
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The first part retrieves the artifacts associated with the latest execution of the "Run Analysis" workflow using the GitHub CLI. The artifact is then deposited into a temporary folder.

echo "Starting database restore..."
touch ~/.pgpass
echo "postgres:5432:mergestat:postgres:postgres" > ~/.pgpass
chmod 0600 ~/.pgpass

pg_restore -h postgres -U postgres -d mergestat --clean -x --no-owner $(pwd)/pgdata/pg-dump/backup_mergestat.dump 
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To ensure proper execution of the bash scripts, it is essential to grant the execution permissions using the chmod +x command. This command allows the scripts to be run as executable files and can be executed directly inside Codespace and then committed to repository.

Our Codespace will be:


Next Steps

In addition to incorporating more queries into the repository, one of the future developments I have in mind is to automatically provision a Grafana instance for visualizing the data on a dedicated dashboard as described on MergeStat site.


This would allow us to leverage Grafana's powerful visualization capabilities to gain deeper insights and analysis of the collected data.
By setting up an automated process to deploy and configure Grafana alongside our existing workflow, we can streamline the visualization experience and provide an intuitive interface for monitoring and analyzing the repository data.
This enhancement would further enhance the overall workflow and make it easier to extract meaningful insights from the collected information.

I hope to be able to achieve it before the end of the hackathon 😉!!

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