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