pytest-dbt-duckdb 0.1.6

pytest-dbt-duckdb is an open-source testing framework that allows you to validate dbt models end-to-end, using DuckDB as an in-memory execution engine. Designed for speed, portability, and CI/CD automation, it enables you to test dbt transformations before deployment, ensuring trust in your data.

PyTest dbt Duckdb 🦆

Fearless testing for dbt models, powered by DuckDB.

What is this?

pytest-dbt-duckdb is an open-source testing framework that allows you to validate dbt models end-to-end, using DuckDB as an in-memory execution engine. Designed for speed, portability, and CI/CD automation, it enables you to test dbt transformations before deployment, ensuring trust in your data.

🩺 Why This Exists

"Assumptions are dangerous." An untested model is a ticking time bomb—silent, unseen, but waiting to fail at the worst possible moment. This library ensures your transformations, dependencies, and outputs are battle-tested before deployment.

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💡 Data must be tested, not trusted.

Modern analytics teams move fast—but in their race to ship, they often skip a crucial step: rigorous testing. A broken transformation can mean misreported revenue, misleading product insights, or silent failures that creep into dashboards.

"Each dbt model untested is a story unfinished."

Here, in the shadows of SQL models and YAML configurations, we forge a guardian—a pytest plugin that ensures every dbt model is battle-tested, validated, and ready before it touches production.

With DuckDB as the testing engine, you can:

• Define test cases with simple YAML scenarios.
• Execute them in DuckDB, locally and instantly—no warehouse needed.
• Integrate with CI/CD pipelines, catching errors before deployment.
• Extend with custom DuckDB functions for specialized assertions.

Data must be tested, not trusted. Let’s test fearlessly.

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🚀 Who is this for?

Whether you are a craftsman of data or a guardian of analytics, this library is your lantern in the dark, guiding you toward precision and reliability.

• Data Engineers → Validate dbt models before they reach production.
• Analytics Engineers → Ensure clean, tested data in dashboards.
• CI/CD Developers → Automate SQL testing in pull requests.

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🎯 Key Features

Feature	Description
✅ Fast Testing	Runs entirely in DuckDB—no warehouse costs.
🛠️ YAML-Based Tests	Define test scenarios using declarative YAML.
♻️ CI/CD Ready	Seamless integration with GitHub Actions, Jenkins, GitLab CI/CD.
🔌 Custom Functions	Extend with user-defined DuckDB functions.
🧪 Snapshot Testing	Compare actual vs. expected outputs with precision.

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How It Works

➡️ See the Usage Section