semvec/pypi-packages huggingface dataset:
dbtmeshification 0.0.1
A dbt companion for unit testing, column-level lineage, and more.
License: MIT
Requires Python: >=3.9
Keywords: dbt, testing, sqlmesh, data, analytics, sqlglot, duckdb

# dbtmeshification

A Python package that enhances `dbt-core` projects with SQLMesh-inspired unit testing capabilities powered by `sqlglot` and `DuckDB`.

## Features

- **CTE-Level Testing**: Test individual CTEs within your dbt models, not just the final output
- **Fast Local Execution**: Run tests in-memory using DuckDB - no data warehouse required
- **Mock Data Support**: Define mock inputs inline in YAML spec files
- **SQL Dialect Transpilation**: Automatically transpile from your dbt dialect to DuckDB
- **Clean CLI**: Simple `mesh test` command integrates into your workflow

## Installation

```bash
pip install dbtmeshification
```

## Quick Start

1. **Ensure your dbt project is compiled**:
   ```bash
   cd your-dbt-project
   dbt compile
   ```

2. **Create a specs directory** in your dbt project:
   ```bash
   mkdir specs
   ```

3. **Write a test spec** (e.g., `specs/my_model.yml`):
   ```yaml
   model: my_model

   tests:
     - name: "test_my_cte"
       target: "my_cte_name"
       mocks:
         - name: "upstream_cte"
           format: "inline"
           content:
             - {id: 1, value: "test"}
             - {id: 2, value: "data"}
       expect:
         format: "inline"
         content:
           - {id: 1, result: "processed"}
   ```

4. **Run tests**:
   ```bash
   mesh test
   ```

## Usage

```bash
# Run all tests
mesh test

# Run tests for a specific model
mesh test --model my_model

# Specify dbt project directory
mesh test --project-dir /path/to/dbt/project

# Specify specs directory
mesh test --specs-dir /path/to/specs

# Use persistent DuckDB file
mesh test --db-file test.db
```

## How It Works

1. Reads your compiled dbt model SQL from `target/manifest.json`
2. Parses the SQL to identify CTEs using `sqlglot`
3. Loads mock data into DuckDB tables
4. Rewrites queries to reference mock tables instead of upstream CTEs
5. Executes tests in DuckDB and compares results

## Requirements

- Python >= 3.8
- dbt-core
- A compiled dbt project (`dbt compile` must be run first)

## Development Status

⚠️ **Alpha Release** - This is an early version. APIs may change.

Current limitations:
- Only inline mock data format supported
- Simple equality-based result comparison
- No support for dbt sources/refs mocking yet

## License

MIT

## Contributing

Issues and pull requests welcome at https://github.com/yourusername/dbtmeshification