{"id":29224757,"url":"https://github.com/shiningflash/apache-airflow-workflow-manager","last_synced_at":"2026-05-17T01:32:19.470Z","repository":{"id":302356544,"uuid":"1012166881","full_name":"shiningflash/apache-airflow-workflow-manager","owner":"shiningflash","description":"Simple Apache Airflow setup with both standalone and Docker-Compose workflows for quick orchestration 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Apache Airflow Workflow Manager\n\nSimple Apache Airflow setup with both standalone and Docker-Compose workflows for quick orchestration experiments.\n\n---\n\n## Getting Started with Standalone Setup\n\n### Create Virtual Environment and Install Airflow\n\n```bash\n$ python -m venv venv\n$ source venv/bin/activate\n$ pip install -r requirements.txt\n````\n\n### Run Airflow Standalone\n\n```bash\n$ airflow standalone\n```\n\nAccess the Airflow UI at: [http://localhost:8080](http://localhost:8080)\n\nGenerated password is stored here:\n\n```bash\n$ cat /Users/\u003cusername\u003e/airflow/simple_auth_manager_passwords.json.generated\n```\n\n---\n\n## Install Apache Airflow using Docker-Compose\n\n### Download Docker-Compose Setup\n\n```bash\n$ curl -LfO 'https://airflow.apache.org/docs/apache-airflow/2.10.0/docker-compose.yaml'\n```\n\n### Review and Modify `docker-compose.yaml` (Optional)\n\n```bash\n$ less docker-compose.yaml\n$ vim docker-compose.yaml\n```\n\n### Initialize Airflow\n\n```bash\n$ docker compose up airflow-init\n```\n\n### Start Airflow Services\n\n```bash\n$ docker compose up\n```\n\nAccess the Airflow UI at: [http://localhost:8080](http://localhost:8080)\n\n**Default Credentials:**\n\n* Username: `airflow`\n* Password: `airflow`\n\n---\n\n## Available DAGs and Their Workflow\n\n| DAG Name               | Description                                   | File                                      | Flow Summary                                      |\n|------------------------|-----------------------------------------------|-------------------------------------------|---------------------------------------------------|\n| `wine_dataset_producer` | Downloads raw wine dataset from GitHub        | `wine_dataset_producer.py`                | `download → save → trigger Dataset`              |\n| `wine_dataset_consumer` | Cleans and persists wine data on trigger      | `wine_dataset_consumer.py`                | `clean → save cleaned → persist to SQLite`       |\n| `census_data_pipeline`  | ETL pipeline using PythonOperators            | `census_data_pipeline.py`                 | `download → transform → validate`                |\n\n### 1. `wine_dataset_producer`\n\n**File:** [`wine_dataset_producer.py`](./dags/wine_dataset_producer.py)  \n**Purpose:** Fetches the raw wine ratings dataset from a GitHub URL and saves it to a local file as a Dataset.\n\n**Tasks:**\n  * Download CSV from GitHub\n  * Save to: `~/airflow/datasets/raw_wine_dataset.csv`\n  * Publish `Dataset` trigger for downstream DAGs\n\n---\n\n### 2. `wine_dataset_consumer`\n\n**File:** [`wine_dataset_consumer.py`](./dags/wine_dataset_consumer.py)  \n**Triggered by:** `wine_dataset_producer` via `Dataset`  \n**Purpose:** Reads, cleans, and persists the wine dataset using virtualenv tasks and SQLite.\n\n**Tasks:**\n  * Clean dataset (drop `grape`, normalize line breaks)\n  * Save cleaned CSV to: `~/airflow/datasets/cleaned_wine_dataset.csv`\n  * Store full dataset and `notes` column into SQLite at: `~/airflow/databases/wine_dataset.db`\n\n---\n\n### 3. `census_data_pipeline`\n\n**File:** [`census_data_pipeline.py`](./dags/census_data_pipeline.py)  \n**Purpose:**   Demonstrates a basic ETL pipeline using Airflow's `PythonOperator`. It fetches census data from a public URL, filters the data, stores it in SQLite, and performs basic validation and statistics.\n\n**Tasks:**\n  *  **`download_data`**: Downloads raw census data from GitHub and stores it at `/tmp/city_census.csv`\n  *  **`transform_data`**: Cleans missing values, filters rows where `weight \u003e 200`, and saves output to both CSV and a SQLite table (`/tmp/census_data.db`)\n  *  **`validate_and_statistics`**: Loads the data from SQLite and runs basic validation and summary stats (e.g., row count and total weight)\n  *  **Flow:** `download_data → transform_data → validate_and_statistics`\n\n---\n\n## License\n\nMIT License\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fshiningflash%2Fapache-airflow-workflow-manager","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fshiningflash%2Fapache-airflow-workflow-manager","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fshiningflash%2Fapache-airflow-workflow-manager/lists"}