Skip to main content

Render 3rd party workflows in Airflow

Project description

https://raw.githubusercontent.com/astronomer/astronomer-cosmos/main/docs/_static/cosmos-logo.svg

fury ossrank downloads pre-commit.ci status

Run your dbt Core projects as Apache Airflow DAGs and Task Groups with a few lines of code. Benefits include:

  • Run dbt projects against Airflow connections instead of dbt profiles

  • Native support for installing and running dbt in a virtual environment to avoid dependency conflicts with Airflow

  • Run tests immediately after a model is done to catch issues early

  • Utilize Airflow’s data-aware scheduling to run models immediately after upstream ingestion

  • Turn each dbt model into a task/task group complete with retries, alerting, etc.

Quickstart

Check out the Quickstart guide on our docs.

Example Usage

You can render an Airflow Task Group using the DbtTaskGroup class. Here’s an example with the jaffle_shop project:

from pendulum import datetime

from airflow import DAG
from airflow.operators.empty import EmptyOperator
from cosmos import DbtTaskGroup, ProfileConfig, ProjectConfig
from cosmos.profiles import PostgresUserPasswordProfileMapping

profile_config = ProfileConfig(
    profile_name="default",
    target_name="dev",
    profile_mapping=PostgresUserPasswordProfileMapping(
        conn_id="airflow_db",
        profile_args={"schema": "public"},
    ),
)

with DAG(
    dag_id="extract_dag",
    start_date=datetime(2022, 11, 27),
    schedule="@daily",
):
    e1 = EmptyOperator(task_id="pre_dbt")

    dbt_tg = DbtTaskGroup(
        project_config=ProjectConfig("jaffle_shop"),
        profile_config=profile_config,
    )

    e2 = EmptyOperator(task_id="post_dbt")

    e1 >> dbt_tg >> e2

This will generate an Airflow Task Group that looks like this:

/docs/_static/jaffle_shop_task_group.png

Community

  • Join us on the Airflow Slack at #airflow-dbt

Changelog

We follow Semantic Versioning for releases. Check CHANGELOG.rst for the latest changes.

Contributing Guide

All contributions, bug reports, bug fixes, documentation improvements, enhancements are welcome.

A detailed overview an how to contribute can be found in the Contributing Guide.

As contributors and maintainers to this project, you are expected to abide by the Contributor Code of Conduct.

License

Apache License 2.0

Project details


Release history Release notifications | RSS feed

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

astronomer_cosmos-1.0.2a1.tar.gz (40.8 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

astronomer_cosmos-1.0.2a1-py3-none-any.whl (62.8 kB view details)

Uploaded Python 3

File details

Details for the file astronomer_cosmos-1.0.2a1.tar.gz.

File metadata

  • Download URL: astronomer_cosmos-1.0.2a1.tar.gz
  • Upload date:
  • Size: 40.8 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.1 CPython/3.11.4

File hashes

Hashes for astronomer_cosmos-1.0.2a1.tar.gz
Algorithm Hash digest
SHA256 1ee3831e223f2a2f8294af5f154903014502d1b9dcfed0b15bebd1f4a7a12df2
MD5 ddefda79540775984664c72f93a42fd4
BLAKE2b-256 45a53d6fd97e29d7149472fa01b0c97ca9394027dac1ea0e1fe18c2405e20a28

See more details on using hashes here.

File details

Details for the file astronomer_cosmos-1.0.2a1-py3-none-any.whl.

File metadata

File hashes

Hashes for astronomer_cosmos-1.0.2a1-py3-none-any.whl
Algorithm Hash digest
SHA256 baaeabf7b5c7dadb865aa30a0c3db074c133968d3d62cbe1ea39d555585205f7
MD5 4c7804579ad1b55b6f41bb80ddb2ed30
BLAKE2b-256 9b948ffee45d9647f01810e2fbe6d0449dbf83b5a79c6053cb01c3af9765177c

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page