- Introduced `BaseDataCollector` and `CollectorManager` classes for standardized data collection and centralized management.
- Added health monitoring features, including auto-restart capabilities and detailed status reporting for collectors.
- Updated `env.template` to include new logging and health check configurations.
- Enhanced documentation in `docs/data_collectors.md` to provide comprehensive guidance on the new data collection system.
- Added unit tests for `BaseDataCollector` and `CollectorManager` to ensure reliability and functionality.
- Updated `.gitignore` to exclude log files from version control.
- Added `pytest` as a dependency in `pyproject.toml` for testing purposes.
- Included `pytest` in `uv.lock` to ensure consistent dependency management.
- Introduced comprehensive documentation for the new unified logging system in `docs/logging.md`, detailing features, usage, and configuration options.
- Introduced `alembic.ini` for Alembic configuration, enabling structured database migrations.
- Created `database/migrations/env.py` to manage migration environment and database URL retrieval.
- Added migration script template `database/migrations/script.py.mako` for generating migration scripts.
- Updated `.gitignore` to exclude migration versions from version control.
- Enhanced `setup.md` documentation to include details on the migration system and commands for managing migrations.
- Introduced `database/redis_manager.py` to manage Redis connections, including synchronous and asynchronous clients.
- Implemented pub/sub messaging capabilities for real-time data distribution, with structured channel definitions for market data, bot signals, and system health.
- Added configuration options for Redis connection pooling and error handling, ensuring robust integration with the Crypto Trading Bot Platform.
- Updated `docker-compose.yml` to remove hardcoded passwords, relying on environment variables for PostgreSQL and Redis configurations.
- Modified `env.template` to reflect new password settings and ensure secure handling of sensitive information.
- Introduced a new `database/connection.py` file for improved database connection management, including connection pooling and session handling.
- Updated `database/models.py` to align with the new schema in `schema_clean.sql`, utilizing JSONB for optimized data storage.
- Enhanced `setup.md` documentation to clarify the initialization process and emphasize the importance of the `.env` file for configuration.
- Added a new `scripts/init_database.py` script for automated database initialization and verification, ensuring all tables are created as expected.
- Added new SQLAlchemy models in `database/models.py` for market data, trades, bots, signals, and performance tracking.
- Updated `docker-compose.yml` to use TimescaleDB for PostgreSQL and configured shared preload libraries.
- Created new schema files: `schema.sql` for the complete database setup and `schema_clean.sql` for a simplified version without hypertables.
- Updated documentation in `setup.md` to reflect changes in database initialization and service setup.
