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        "author": "Max Goodridge",
        "author_email": "max.goodridge@hotmail.co.uk",
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            "Development Status :: 3 - Alpha",
            "Intended Audience :: Developers",
            "License :: OSI Approved :: Apache Software License",
            "Programming Language :: Python :: 3.5",
            "Programming Language :: Python :: 3.6",
            "Programming Language :: Python :: 3.7",
            "Topic :: Software Development :: Libraries :: Python Modules"
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        "description": "# Workflows\nWorkflows are a cleaner way of implementing DAGs using a Django-inspired class-based syntax.\n\n## Simple Example\nLet's create a single Airflow DAG, whose name is a camelcased version of the class name, and whose operator dependencies are in the order they are defined.\n\nThere is an option to override the default [`dependencies`](https://github.com/maxg203/airflow-workflows/blob/master/workflows.py#L165) method implementation to customise the dependency chain for your use case.\n\n```python\nimport workflows\n\n\nclass ExampleWorkflow(workflows.Workflow):\n    class Meta:\n        schedule_interval = '0 9 * * *'\n\n    do_something_useful = workflows.PythonOperator(\n        python_callable=lambda **kwargs: print('something useful'),\n    )\n    something_else = workflows.PythonOperator(\n        python_callable=lambda **kwargs: print('Something not useful'),\n    )\n\n\nglobals()[ExampleWorkflow.DAG.dag_id] = ExampleWorkflow.DAG\n```\n\n\n## Dynamic DAG Example\nLet's create (in this case three) DAGs, created dynamically and based on the `ExampleWorkflow` class as implemented above. In other words, they will share the same DAG metadata (so schedule in this case).\n\n```python\nimport workflows\n\nworkflow_names = [\n    'Test1',\n    'Test2',\n    'Test3',\n]\n\nfor workflow in workflow_names:\n    WorkflowClass = workflows.create_workflow(\n        workflow,\n        base=ExampleWorkflow,\n    )\n    globals()[WorkflowClass.DAG.dag_id] = WorkflowClass.DAG\n```",
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        "keywords": "airflow,DAG,workflows,ETL",
        "license": "apache-2.0",
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        "name": "airflow-workflows",
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        "summary": "Provides a powerful, Django-inspired class-based DAG syntax for Apache Airflow.",
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