CI/CD for Splink Demos

This document outlines the CI/CD process implemented for the splink_demos project. CI/CD refers to continuous integration and continuous delivery, a set of practices that enable developers to deliver code changes more frequently and reliably.

Motivation

The primary motivation for implementing CI/CD in this project is to streamline the development and deployment of record linkage solutions using the Splink library. By automating build, test, and deployment processes, we aim to:

• Improve efficiency: Reduce manual effort and shorten the time required to release new features and bug fixes.
• Enhance quality: Implement automated testing to catch errors early in the development cycle and ensure code stability.
• Increase consistency: Standardize the deployment process and reduce the risk of human error.

Implementation

This project leverages GitHub Actions, a powerful platform for automating CI/CD workflows directly within GitHub repositories.

Workflows

The CI/CD process is defined by a set of workflows, which are YAML files that specify the steps to be executed. Currently, the following workflows are implemented:

• Build and Test: This workflow runs every time code is pushed to the repository. It performs the following steps:
  • Install dependencies.
  • Run unit tests.
  • Build documentation.
  • Generate code coverage reports.
• Deployment: This workflow is triggered manually and deploys the project to a designated environment.
  • Build the project.
  • Deploy to the target environment.

Example Workflow (Build and Test)

name: Build and Test
          
          on:
            push:
              branches:
                - main
          
          jobs:
            build-and-test:
              runs-on: ubuntu-latest
              steps:
                - uses: actions/checkout@v3
                - name: Install dependencies
                  run: pip install -r requirements.txt
                - name: Run unit tests
                  run: pytest
                - name: Build documentation
                  run: mkdocs build
                - name: Generate code coverage reports
                  run: coverage report
          

Example Workflow (Deployment)

name: Deployment
          
          on:
            workflow_dispatch:
          
          jobs:
            deploy:
              runs-on: ubuntu-latest
              steps:
                - uses: actions/checkout@v3
                - name: Build the project
                  run: python setup.py sdist bdist_wheel
                - name: Deploy to the target environment
                  run: twine upload dist/*
          

Configuration Options

The configuration options for each workflow can be customized extensively, allowing you to fine-tune the CI/CD process based on project requirements. For instance, you can:

• Define triggering events: Specify which events (e.g., push, pull request, manual trigger) will trigger a workflow.
• Set up environments: Define different environments (e.g., development, testing, production) for deployment.
• Configure dependencies: Specify the dependencies needed for building and testing the project.
• Customize testing procedures: Define various types of tests, including unit tests, integration tests, and end-to-end tests.
• Control deployment processes: Define deployment strategies and configure deployment targets.

Benefits of CI/CD

The implementation of CI/CD in the splink_demos project has several benefits:

• Increased development speed: Automated workflows reduce time spent on manual tasks, allowing developers to focus on code creation.
• Improved code quality: Frequent testing and continuous integration lead to early error detection and improved code stability.
• Reduced risk of deployment failures: Standardized deployment processes minimize human error and ensure consistent deployments.

Conclusion

The CI/CD process implemented for splink_demos empowers the development team to deliver record linkage solutions more effectively and efficiently. By leveraging GitHub Actions and automating workflows, we ensure a smooth and reliable development and deployment cycle.

Top-Level Directory Explanations

examples/ - This directory likely contains examples or sample code for using the project’s components.

examples/athena/ - This subdirectory may contain examples using Amazon Athena, an interactive query service for analyzing data in Amazon S3 using standard SQL.

examples/athena/dashboards/ - This subdirectory may contain Athena dashboard files.

examples/duckdb/ - This subdirectory may contain examples using DuckDB, an open-source in-memory analytic database.

examples/duckdb/dashboards/ - This subdirectory may contain DuckDB dashboard files.

examples/sqlite/ - This subdirectory may contain examples using SQLite, a popular open-source database management system.

examples/sqlite/dashboards/ - This subdirectory may contain SQLite dashboard files.

tutorials/ - This directory may contain tutorials or guides for using the project.