Remove complete time series aggregation example and add data collection service implementation

- Deleted `example_complete_series_aggregation.py` as it is no longer needed.
- Introduced `data_collection_service.py`, a production-ready service for cryptocurrency market data collection with clean logging and robust error handling.
- Added configuration management for multiple trading pairs and exchanges, supporting health monitoring and graceful shutdown.
- Created `data_collection.json` for service configuration, including exchange settings and logging preferences.
- Updated `CandleProcessingConfig` to reflect changes in timeframes for candle processing.
- Enhanced documentation to cover the new data collection service and its configuration, ensuring clarity for users.

tasks/tasks-crypto-bot-prd.md

@@ -12,6 +12,7 @@
 - `database/init/schema_clean.sql` - Copy of clean schema for Docker initialization
 - `data/base_collector.py` - Abstract base class for all data collectors with standardized interface, error handling, data validation, health monitoring, and auto-restart capabilities
 - `data/collector_manager.py` - Centralized collector management with health monitoring, auto-recovery, and coordinated lifecycle management
+- `data/collection_service.py` - Production-ready data collection service with clean logging, multi-exchange support, and robust error handling
 - `data/__init__.py` - Data collection package initialization
 - `data/okx_collector.py` - OKX API integration for real-time market data collection
 - `data/aggregator.py` - OHLCV candle aggregation and processing
@@ -26,6 +27,9 @@
 - `config/strategies/` - Directory for JSON strategy parameter files
 - `config/settings.py` - Centralized configuration settings using Pydantic
 - `scripts/dev.py` - Development setup and management script
+- `scripts/start_data_collection.py` - Simple script to start the data collection service with clean output
+- `scripts/production_clean.py` - Clean production OKX data collector script (adapted for service development)
+- `scripts/monitor_clean.py` - Clean database monitor for production data collection status
 - `scripts/init_database.py` - Database initialization and verification script
 - `scripts/test_models.py` - Test script for SQLAlchemy models integration verification
 - `utils/logger.py` - Enhanced unified logging system with verbose console output, automatic cleanup, and configurable retention [USE THIS FOR ALL LOGGING]
@@ -35,12 +39,14 @@
 - `tests/test_strategies.py` - Unit tests for strategy implementations
 - `tests/test_bot_manager.py` - Unit tests for bot management functionality
 - `tests/test_data_collection.py` - Unit tests for data collection and aggregation
+- `tests/test_data_collection_service.py` - Comprehensive unit tests for the DataCollectionService (25 tests)
 - `tests/test_base_collector.py` - Comprehensive unit tests for the BaseDataCollector abstract class (13 tests)
 - `tests/test_collector_manager.py` - Comprehensive unit tests for the CollectorManager with health monitoring (14 tests)
 - `tests/test_logging_enhanced.py` - Comprehensive unit tests for enhanced logging features (16 tests)
 - `tests/test_indicators.py` - Comprehensive unit tests for technical indicators module (18 tests)
 - `docs/setup.md` - Comprehensive setup guide for new machines and environments
 - `docs/logging.md` - Complete documentation for the enhanced unified logging system
+- `docs/data-collection-service.md` - Complete documentation for the data collection service with usage examples, configuration, and deployment guide
 - `docs/components/technical-indicators.md` - Complete documentation for the technical indicators module with usage examples and integration guide
 
 ## Tasks
@@ -66,8 +72,8 @@
   - [x] 2.4 Implement Redis channels for real-time data distribution
   - [x] 2.5 Create data storage layer for OHLCV data in PostgreSQL
   - [x] 2.6 Add technical indicators calculation (SMA, EMA, RSI, MACD, Bollinger Bands)
-  - [ ] 2.7 Implement data recovery and reconnection logic for API failures
-  - [ ] 2.8 Create data collection service with proper logging
+  - [x] 2.7 Implement data recovery and reconnection logic for API failures (DEFERRED: Basic reconnection exists, comprehensive historical data recovery moved to section 13.0 for future implementation)
+  - [x] 2.8 Create data collection service with proper logging
   - [ ] 2.9 Unit test data collection and aggregation logic
 
 - [ ] 3.0 Basic Dashboard for Data Visualization and Analysis
@@ -176,6 +182,9 @@
   - [ ] 13.5 Add caching layer for frequently accessed market data
   - [ ] 13.6 Optimize data retention and archival strategies
   - [ ] 13.7 Implement horizontal scaling for high-volume trading scenarios
+  - [ ] 13.8 Implement comprehensive data recovery with OKX REST API for historical backfill
+  - [ ] 13.9 Add gap detection and automatic data recovery during reconnections
+  - [ ] 13.10 Implement data integrity validation and conflict resolution for recovered data