dbt-yamer 0.1.0

A Python package for generating dbt schema.yml files.

dbt-yamer

Overview

dbt-yamer is a Python wrapper designed to simplify and enhance the generation of YAML schema files for dbt projects. With a focus on faster schema YAML and doc block generation, dbt-yamer aids development and helps avoid documentation and contract technical debt. By leveraging this CLI tool built on the dbt context, developers can streamline the management of dbt models and associated metadata.

Key Features

• Automates YAML schema generation for dbt models.
• Integrates doc blocks directly into column descriptions.
• Supports fuzzy matching to map columns to the best documentation blocks.
• CLI tool for seamless usage.

Installation

Prerequisites

Ensure you have the following prerequisites:

• Python 3.8 or higher
• pip (Python package installer)
• dbt
• A working dbt project

Installing dbt-yamer

pip install dbt-yamer

Usage

Command Line Interface (CLI)

The primary interface for dbt-yamer is through the CLI.

Generate YAML Files

Generate YAML schema files for one or more dbt models using the dbt-yamer yaml -m or --models switch:

dbt-yamer yaml -m <model_name1> <model_name2>

Example

To generate YAML for a model named customer_data, run:

dbt-yamer yaml -m customer_data

This command will generate a YAML schema file for the customer_data model, including:

• Column definitions with descriptions.
• Automatically integrated doc blocks for relevant columns.
• Fuzzy-matched documentation for improved accuracy.

Usage Examples

With this updated code, your CLI command can be used as follows:

# By default, loads manifest from target/manifest.json
dbt-yamer yaml -m model_a model_b

# Specifying a custom manifest path
dbt-yamer yaml -m model_a --manifest path/to/another_manifest.json

# Specifying a custom target label (dbt's "target" as in --target <env>)
dbt-yamer yaml -m model_a -t uat

# A combination of manifest, target, and multiple models
dbt-yamer yaml -m model_a -m model_b --manifest path/to/another_manifest.json -t uat

• --manifest defaults to target/manifest.json.
• --target/-t defaults to local environment, but also can be overridden (e.g., -t uat).
• --models/-m requires at least one model name, and you can pass in multiple.

Output

• YAML schema files are created in the same directory as their corresponding .sql files.
• If a schema file already exists, new files are versioned with _v1, _v2, etc.
• Doc blocks are automatically added to column descriptions in the format:

  description: "{{ doc('doc_block_name') }}"
  

Development and Contributing

Development Environment Setup

1. Clone the Repository

   git clone <repository-url>
   cd dbt-yamer
   

2. Create and Activate a Virtual Environment

   python3 -m venv env
   source env/bin/activate  # On Windows: env\Scripts\activate
   

3. Install Development Dependencies

   Instead of pytest, the project uses Makefile commands for setup and testing. Use the following commands:

   To Clean and Restart the Environment:

   make clean restart
   

   This will clean up any existing environment and install the package along with its dependencies.

4. Run Makefile Commands

   Use the provided Makefile for various tasks. For example:

   • make restart: Reinstalls the package.
   • make clean: Removes temporary files and builds.

Contributing Guidelines

1. Feature Development:

   • Create a new branch for your feature or bug fix.

     git checkout -b feature/your-feature-name
     

2. Adhere to Code Standards:

   • Follow PEP 8 guidelines.
   • Use type hints where applicable.
   • Run pylint to ensure code quality.

3. Submit a Pull Request:

   • Push your branch to the repository.

     git push origin feature/your-feature-name
     

   • Open a pull request with a clear description of your changes.

Support

For issues and feature requests, please create an issue in the dbt-yamer GitHub repository.

Authors

• Muizz Lateef
  https://muizzkolapo.github.io/blog/