yaml
2 series
Series
Series · 10 parts
GitHub Actions CI/CD
In this exhilarating first part of a ten-part series on GitHub Actions CI/CD, you embark on creating the "helloci" Python package. It features a simple yet powerful greeting function and a user-friendly CLI entry point. The journey begins with project setup, encapsulating best practices in Python packaging and laying the groundwork for automated tests. Get ready to transform your coding experience!
- 1GitHub Actions CI/CD (1/10): Make It a Package You Can Test
- 2GitHub Actions CI/CD (2/10): Unit Tests — Fast Feedback
- 3GitHub Actions CI/CD (3/10): Quality Gate Before Tests — Lint and Formatting
- 4GitHub Actions CI/CD (4/10): Your First CI Workflow — Run on Every PR
- 5GitHub Actions CI/CD (5/10): Matrix Testing — Multiple Python Versions
- 6GitHub Actions CI/CD (6/10): Integration Tests — Real Dependencies in CI
- 7GitHub Actions CI/CD (7/10): Branch Protection — Make CI a Merge Gate
- 8GitHub Actions CI/CD (8/10): Artifacts — Keep Evidence From a Run
- 9GitHub Actions CI/CD (9/10): Release Workflow — Tag, Build, Publish
- 10GitHub Actions CI/CD (10/10): Going Professional — Split Jobs, Caching, and Nightly Builds
Series · 8 parts
pgmonkey
Alright, so here's the gist: You can get started with pgmonkey in under five minutes. Just set up your project folder, install pgmonkey, and create a YAML config file. After tweaking it for your database, test your connection and run a simple Python query. Easy peasy!
- 1pgmonkey (1/8) — Getting Started
- 2pgmonkey (2/8) — Connection Types
- 3pgmonkey (3/8) — Securing Connections with SSL/TLS
- 4pgmonkey (4/8) — Connection Pooling
- 5pgmonkey (5/8) — Environment Variables and Secrets
- 6pgmonkey (6/8) — The CLI Toolbox
- 7pgmonkey (7/8) — CSV Import and Export
- 8pgmonkey (8/8) — Production Patterns
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