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airflow-manual/airflow-docker/CHANGELOG.md
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2025-10-19 20:17:29 +03:00

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# CHANGELOG - Educational Airflow Setup
## 📋 Summary of Changes Made
### 1. Fixed Docker Compose Structure
- Removed duplicate `services:` sections
- Added missing service definitions (postgres-metadata, postgres-training, airflow-webserver, airflow-scheduler, airflow-init)
- Configured proper service dependencies and health checks
### 2. Created Hardcoded Environment Variables
- `.env` file with all necessary credentials:
- Airflow: admin/admin
- PostgreSQL metadata: airflow/airflow
- PostgreSQL training: student/student
### 3. Implemented Educational DAG Examples
**Level 1: Basic Concepts**
- `hello_world_dag.py` - Simple PythonOperator tasks with dependencies
**Level 2: Intermediate Integration**
- `sql_basic_dag.py` - PostgreSQL operations
- `file_operations_dag.py` - File processing and CSV operations
**Level 3: Advanced Features**
- `data_processing_dag.py` - ETL pipeline with multiple steps
**Level 4: Conditional Logic**
- `branching_dag.py` - BranchPythonOperator and conditional execution
**Level 5: Error Handling**
- `error_handling_dag.py` - Task retries and error management
### 4. Sample Data Files
- `customers.csv` - Customer data for exercises
- `orders.csv` - Order data for practical work
### 5. Database Configuration
- PostgreSQL for Airflow metadata (port 5433)
- PostgreSQL for training exercises (port 5432)
### 6. Configuration Files
- `requirements.txt` - Essential Python packages
- Updated `README.md` with comprehensive setup instructions
## 🎯 Key Features for Beginners
### Simplified Setup
- All environment variables hardcoded in `.env`
- Clear port mappings and access credentials
### Progressive Learning
- From basic "Hello World" to advanced ETL pipelines
- Hands-on exercises with real data
### Technical Specifications
- Airflow version: 2.9.2
- PostgreSQL version: 16
- LocalExecutor for simplicity
## 🚀 Quick Start Commands
```bash
# Start all services
docker-compose up -d
# Access interfaces
- Airflow UI: http://localhost:8080
- Training PostgreSQL: localhost:5432
- Metadata PostgreSQL: localhost:5433