dbt-depp 0.1.4

DBT Enexis Python Postgres adapter - Run python scripts from any dbt project.

DEPP - DBT Python Postgres Adapter

This package support for running python models in dbt for postgres directly within your dbt project Inspired on dbt-fal but made to be both extremely high performance and fully typed Also supports polars dataframe besides pandas and more are comming soon

Features

• Run Python scripts as dbt models
• Python Docs string are automatically added as descriptin in docs (more doc improvement soon)
• Python models are fully typed
• Currently support for both pandas and polars dataframes (more comming soon)
• Blazing performance using connectorx, asyncpg
• Seamless integration with PostgreSQL databases (more comming soon)

Installation

Install using uv (recommended):

uv add depp

Or using pip:

pip install depp

Quick Start

1. Add to your profiles.yml: Make sure to both add a db_profile with all your details and add your database and schema

your_project:
  target: dev
  outputs:
    dev:
      type: depp
      db_profile: dev_postgres
      database: example_db
      schema: test
      
    dev_postgres:
      type: postgres
      host: localhost
      user: postgres
      password: postgres
      port: 5432
      database: example_db
      schema: test
      threads: 1

2. Create Python models in your dbt project:

# models/my_python_model.py
import polars as pl

def model(dbt, session):
    dbt.config(library="polars")
    # Your Python logic here
    df = pl.DataFrame({'column1': [1, 2, 3], 'column2': ['a', 'b', 'c']})
    return df

3. dbt run!

Development

This project uses uv for dependency management:

# Install dependencies
uv sync

# Run tests
uv run pytest

# Build package
uv build

Requirements

• Python >= 3.12
• dbt-core >= 1.10.0
• PostgreSQL database

License

This project is open source and available under the MIT License.

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.