Skip to main content

Add embeded dashboars to Airflow

Project description

Airflow Embedash

A Python package for embedding dashboards in Apache Airflow.

Installation

Install the package using pip:

pip install airflow-embedash

Or in development mode:

pip install -e .

Usage

Create new dashboards

Variable

The default menu label is "Dashboards" but can be changed setup embeded_dashboards_menu_labelvariable.

For private dashboars need metabase token embeded_dashboards_metabase_token

Package Structure

  • src/ - Source code directory
    • __init__.py - Package initialization
    • airflow_embeded_dashboards.py - Main module with the main function

Development

To contribute to this project:

  1. Fork the repository
  2. Create a feature branch
  3. Make your changes
  4. Submit a pull request

License

This project is licensed under the MIT License.

Project details


Download files

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

Source Distribution

airflow_embedash-0.1.10.tar.gz (7.7 kB view details)

Uploaded Source

Built Distribution

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

airflow_embedash-0.1.10-py3-none-any.whl (11.2 kB view details)

Uploaded Python 3

File details

Details for the file airflow_embedash-0.1.10.tar.gz.

File metadata

  • Download URL: airflow_embedash-0.1.10.tar.gz
  • Upload date:
  • Size: 7.7 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/6.1.0 CPython/3.13.7

File hashes

Hashes for airflow_embedash-0.1.10.tar.gz
Algorithm Hash digest
SHA256 2b168777658f169bf5fc9be202e262c188999248355ffaa50f67bc3c2caa8640
MD5 9bf9100213426659e1ca0a95cc51b12c
BLAKE2b-256 a288027a26105d30e816b9de775fe88742beacd8346c0bcd7094e08f37173278

See more details on using hashes here.

Provenance

The following attestation bundles were made for airflow_embedash-0.1.10.tar.gz:

Publisher: python-publish.yml on teoria/airflow-embedash

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

File details

Details for the file airflow_embedash-0.1.10-py3-none-any.whl.

File metadata

File hashes

Hashes for airflow_embedash-0.1.10-py3-none-any.whl
Algorithm Hash digest
SHA256 08d8073f609cc2e263d62ca34e34a61e348daa5b63fe255e9899c3991b93ca88
MD5 a3d505cebb1c78460d3cc85d5e6cabf5
BLAKE2b-256 d70f80bbf4e3d46a8818a89c37a380e96cf0ed4568a402134b6d2b9507df37b9

See more details on using hashes here.

Provenance

The following attestation bundles were made for airflow_embedash-0.1.10-py3-none-any.whl:

Publisher: python-publish.yml on teoria/airflow-embedash

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

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