Refactor imports and enhance timestamp handling in API and test files
- Removed redundant import statements in api.py and prepare_worker.py for cleaner code.
- Updated timestamp format in test cases to include timezone information for consistency.
- Adjusted test configurations to align with new API structure for improved accuracy in data handling.
Enhance PI Web API integration and update test configurations
- Adjusted execution counts in tests.ipynb for better notebook state management.
- Introduced a new pi_web_api_query structure in tests.ipynb for improved API configuration.
- Updated API class to format timestamps using DATETIME_FORMAT_WITH_TZ.
- Refactored PIWebAPIClient to ensure correct web ID retrieval and emit metrics accurately.
- Streamlined workflow parameters in pi_web_api_scouter.py for clarity and flexibility.
Enhance Activities and API Integration
- Updated Activities class to include API operations for external data ingestion.
- Added API configuration builder to connectors_config.py for environment variable management.
- Integrated API configuration into worker setup.
- Expanded unit tests to cover new API functionality and configuration handling.
- Updated requirements.txt to include pycurl and prometheus-client for enhanced metrics support.
Update .gitignore and refactor metrics.py, activities.py, and gates.py for improved clarity and consistency. Added coverage.xml and cache directories to .gitignore. Standardized string formatting and parameter handling in metrics and activities classes, enhancing code readability. Removed the deprecated faker.py file and adjusted related tests accordingly.
Remove deprecated files and configurations, including .env, Dockerfile, docker-compose.yml, and client-schedule.py. Update README.md to reflect new architecture and features, enhancing clarity on system capabilities and workflows. Adjust values.yaml for image tag and replica count, and improve code documentation across various modules for better maintainability.
Integrate Druid activity into the Activities class, adding support for Druid configuration and initialization. Update worker and connectors configuration to accommodate Druid, enhancing data processing capabilities.
Update environment configuration and refactor activity imports
- Changed Kafka, Redis, and Temporal host configurations to use localhost.
- Updated the version reference for the sientia-dataops-library in requirements.txt.
- Refactored import paths for activities to align with new module structure.
- Removed unused base.py and postgres.py files.
- Updated logger and policies imports to reflect new module locations.
- Adjusted values.yaml for branch and log level settings.
Implement workflows for fake data generation, scouter processing, and core scouter operations
- Added `FakeData` workflow to generate random data and send it to a Kafka topic.
- Implemented `Scouter` workflow to load data from Kafka and trigger the core scouter workflow.
- Created `CoreScouter` workflow to process data through quality gates, aggregation, and export to PostgreSQL.
- Developed comprehensive unit tests for activities and workflows, ensuring proper functionality and error handling.
- Enhanced Redis and Postgres activities with robust testing for data handling and error notifications.
- Introduced quality filters for data validation and implemented tests to verify their functionality.
