airflow-provider-duckdb

A DuckDB provider for Airflow. This provider exposes a hook/connection that returns a DuckDB connection.

This works for either local or MotherDuck connections.

Installation

pip install airflow-provider-duckdb

Connection

The connection type is duckdb. It supports setting the following parameters:

Airflow field name	Airflow UI label	Description
host	Path to local database file	Path to local file. Leave blank (with no password) for in-memory database.
schema	MotherDuck database name	Name of the MotherDuck database. Leave blank for default.
password	MotherDuck Service token	MotherDuck Service token. Leave blank for local database.

These have been relabeled in the Airflow UI for clarity.

For example, if you want to connect to a local file:

Airflow field name	Airflow UI label	Value
host	Path to local database file	/path/to/file.db
schema	MotherDuck database name	(leave blank)
password	MotherDuck Service token	(leave blank)

If you want to connect to a MotherDuck database:

Airflow field name	Airflow UI label	Value
host	Path to local database file	(leave blank)
schema	MotherDuck database name	<YOUR_DB_NAME>, or leave blank for default
password	MotherDuck Service token	<YOUR_SERVICE_TOKEN>

Usage

import pandas as pd
import pendulum

from airflow.decorators import dag, task
from duckdb_provider.hooks.duckdb_hook import DuckDBHook


@dag(
    schedule=None,
    start_date=pendulum.datetime(2022, 1, 1, tz="UTC"),
    catchup=False,
)
def duckdb_transform():
    @task
    def create_df() -> pd.DataFrame:
        """
        Create a dataframe with some sample data
        """
        df = pd.DataFrame(
            {
                "a": [1, 2, 3],
                "b": [4, 5, 6],
                "c": [7, 8, 9],
            }
        )
        return df

    @task
    def simple_select(df: pd.DataFrame) -> pd.DataFrame:
        """
        Use DuckDB to select a subset of the data
        """
        hook = DuckDBHook.get_hook('duckdb_default')
        conn = hook.get_conn()

        # execute a simple query
        res = conn.execute("SELECT a, b, c FROM df WHERE a >= 2").df()

        return res

    @task
    def add_col(df: pd.DataFrame) -> pd.DataFrame:
        """
        Use DuckDB to add a column to the data
        """
        hook = DuckDBHook.get_hook('duckdb_default')
        conn = hook.get_conn()

        # add a column
        conn.execute("CREATE TABLE tb AS SELECT *, a + b AS d FROM df")

        # get the table
        return conn.execute("SELECT * FROM tb").df()

    @task
    def aggregate(df: pd.DataFrame) -> pd.DataFrame:
        """
        Use DuckDB to aggregate the data
        """
        hook = DuckDBHook.get_hook('duckdb_default')
        conn = hook.get_conn()

        # aggregate
        return conn.execute("SELECT SUM(a), COUNT(b) FROM df").df()

    create_df_res = create_df()
    simple_select_res = simple_select(create_df_res)
    add_col_res = add_col(simple_select_res)
    aggregate_res = aggregate(add_col_res)


duckdb_transform()