Apache Airflow Postgres Provider

6.6.2 · active · verified Fri Apr 10

The Apache Airflow Postgres Provider offers a comprehensive set of operators, hooks, and sensors for seamless interaction with PostgreSQL databases within Airflow DAGs. It enables tasks such as executing SQL queries, transferring data, and managing database connections. The current version is 6.6.2, and it follows a frequent release cadence to support new Airflow features and address issues.

Warnings

breaking Provider version 6.5.0 and later require Apache Airflow 2.11.0 or newer. Older Airflow versions will not be able to install or run these provider versions.
Fix: Upgrade your Apache Airflow instance to version 2.11.0 or later, or use an older provider version compatible with your Airflow installation.
breaking In provider version 6.6.2 (released March 28, 2026), the `schema` argument in Postgres hooks (e.g., `PostgresHook`) has been renamed to `database`. Using `schema` will now raise an error.
Fix: Update any usage of `schema` in `PostgresHook` or related classes to use `database` instead.
breaking Beginning with provider version 4.0.0, the `get_uri()` method of `PostgresHook` returns a URI with the `postgresql://` prefix instead of the older `postgres://` prefix. This aligns with SQLAlchemy 1.4.0+ requirements.
Fix: Update any code that parses or expects the `postgres://` prefix from `get_uri()` to handle `postgresql://`.
deprecated The `runtime_parameters` argument in `PostgresOperator` was deprecated in favor of passing options via `hook_params` in provider version 5.5.2.
Fix: Migrate from `runtime_parameters` to using `hook_params={'options': {'your_param': 'value'}}` for passing runtime configuration.
gotcha Python 3.7 support was dropped in provider version 5.5.1. The current provider version requires Python >=3.10.
Fix: Ensure your Airflow environment is running on Python 3.10 or higher. Check the `requires_python` field for precise version compatibility.

Install

pip install apache-airflow-providers-postgres Install latest version

Imports

PostgresOperator
```
from airflow.providers.postgres.operators.postgres import PostgresOperator
```
Old import path for Airflow 1.x series; Airflow 2.x and providers use the fully qualified provider path.
PostgresHook
```
from airflow.providers.postgres.hooks.postgres import PostgresHook
```
Old import path for Airflow 1.x (contrib) series; Airflow 2.x and providers use the fully qualified provider path.

Quickstart

This example DAG defines two tasks using the `PostgresOperator`. The first task creates a 'pet' table if it doesn't already exist, and the second task populates it with sample data. Ensure you have an Airflow connection named 'postgres_default' configured in the Airflow UI, pointing to your PostgreSQL instance.

import datetime
from airflow import DAG
from airflow.providers.postgres.operators.postgres import PostgresOperator

with DAG(
    dag_id="postgres_example_dag",
    start_date=datetime.datetime(2023, 1, 1),
    schedule_interval="@once",
    catchup=False,
    tags=["postgres", "example"]
) as dag:
    create_pet_table = PostgresOperator(
        task_id="create_pet_table",
        postgres_conn_id="postgres_default",
        sql="""
            CREATE TABLE IF NOT EXISTS pet (
            pet_id SERIAL PRIMARY KEY,
            name VARCHAR NOT NULL,
            pet_type VARCHAR NOT NULL,
            birth_date DATE NOT NULL,
            owner VARCHAR NOT NULL
            );
        """
    )

    populate_pet_table = PostgresOperator(
        task_id="populate_pet_table",
        postgres_conn_id="postgres_default",
        sql="""
            INSERT INTO pet (name, pet_type, birth_date, owner)
            VALUES ('Fido', 'Dog', '2020-01-01', 'Alice'),
                   ('Whiskers', 'Cat', '2019-05-15', 'Bob');
        """
    )

    create_pet_table >> populate_pet_table

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