- Changed memory area identifiers in dataset_variables.json and related schemas from lowercase to uppercase (e.g., "db" to "DB").
- Added new plot definition for "CTS306 Conductivimeter" in plot_definitions.json.
- Updated plot_variables.json to include new variables for "HMI_Instrument.QTM306.PVFiltered" and "HMI_Instrument.QTM307.PVFiltered".
- Enhanced dataset-variables.schema.json to enforce required fields based on area and type.
- Improved ui schema for dataset variables to provide clearer guidance on field usage.
- Updated PLC client to utilize new snap7.type module and improved error handling.
- Added support for new data types (DWORD) in PlcDataTypeWidget.
- Updated Dashboard.jsx to reflect changes in memory area identifiers and improve default configurations.
- Upgraded python-snap7 dependency to version 2.0.2 for enhanced functionality.
- Modified system_state.json to reflect changes in connection status and last update timestamp.
- Implemented optimized batch reading logic in optimized_batch_reader.py to support new area mappings.
- Added VSCode configuration files for improved development experience.
- Introduced ConditionalObjectFieldTemplate.jsx for dynamic field visibility based on PLC-specific logic.
- Implemented a new method `_get_disk_usage_safe` in `PLCDataStreamer` to safely retrieve disk usage information using `psutil` and `shutil` with fallbacks for different scenarios.
- Updated the disk usage calculation logic to handle potential errors and log warnings when disk usage retrieval fails.
- Modified the `system_state.json` to reorder active datasets and add a new `plotjuggler_path` entry.
- Added a comprehensive test script `test_disk_space.py` to validate the disk space calculation functionality via the API.
- Modified backend_manager.status to reflect updated timestamps and status.
- Refactored backmanager.py for improved readability and consistency in logging.
- Enhanced instance_manager.py to ensure robust backend instance checks and process management.
- Updated main.py to streamline backend instance verification and improve error handling.
- Adjusted main.spec to consolidate analysis for the main application and backend manager.
- Added a new spec file for comprehensive build configuration.
- Updated system_state.json with new timestamps and dataset order.
- Improved rotating_logger.py to enhance log file cleanup messages.
- Added backmanager.py to monitor backend health and restart if necessary.
- Introduced backend_manager.status to track the state of the backend.
- Updated system_state.json to reflect changes in active datasets.
- Modified rotating_logger.py for improved log messages.
- Enhanced main.spec to support separate executables for main application and backend manager.
- Created backmanager.spec and backmanager_config.json for backend manager configuration.
- Added build_all.bat for streamlined build process.
- Implemented `test_simple_read_multi_vars.py` to validate read_multi_vars functionality with detailed logging and error handling.
- Created `test_snap7v2_comprehensive.py` for extensive testing of snap7 v2, covering various PLC variable types, performance comparisons, data consistency checks, and stress testing.
- Integrated existing backend components and optimized reading methods, with comprehensive reporting and logging features.
- Added `use_optimized_reading` parameter to dataset definitions for per-dataset control over reading methods.
- Updated JSON schema and UI schema to include the new parameter with appropriate descriptions and defaults.
- Modified `ConfigManager`, `PLCClient`, and `PLCDataStreamer` to handle the new optimization setting.
- Enhanced batch reading logic to prioritize dataset-specific settings over global configurations.
- Improved logging to indicate which reading method is being used for each dataset.
- Created comprehensive tests to validate the new functionality and ensure backward compatibility.
- Added documentation detailing the new feature, its benefits, and usage examples.
- Introduced `test_optimized_reader.py` to validate the functionality and configuration of `OptimizedBatchReader`.
- Created `test_pe_pa_fixed.py` to test the corrected PE/PA reading functionality using appropriate Snap7 area codes.
- Developed `test_real_plc.py` to assess the performance of optimized batch reading against legacy methods with actual PLC configurations.
- Implemented `test_simple_validation.py` for a final validation of core functionalities, ensuring correct implementation of PE/PA area codes and batch reading.
- Added OptimizedBatchReader class to handle batch reading of PLC variables using snap7's read_multi_vars function.
- Introduced automatic chunking to respect S7 PDU limits, allowing for efficient handling of large variable lists.
- Replaced the existing read_variables_batch method in PLCClient with the new optimized implementation.
- Updated system_state.json to reflect the latest last_update timestamp.
- Removed commented-out code related to the previous batch reading method.
- Increased time_window in plot_definitions.json from 10 to 60.
- Added external_path function in config_manager.py to handle paths for records and logs, ensuring compatibility with both development and PyInstaller executable environments.
- Updated PLCDataStreamer to use the new get_csv_directory_path method for retrieving the records directory.
- Refactored main.py to include get_records_directory function for consistent records directory path retrieval.
- Modified system_state.json to set should_connect to false and updated last_update timestamp.
- Refactored performance monitoring initialization for better readability.
- Added critical validation to ensure buffered data matches current dataset variables, preventing CSV corruption.
- Implemented logging for data inconsistencies and buffer clearing during variable modifications.
- Improved error handling and logging during CSV flushing and dataset reading.
- Enhanced UDP streaming error handling and logging.
- Updated threading management for CSV flushing and dataset streaming.
- Added comprehensive performance metrics recording for dataset reads and writes.
feat: Localize historical plot management components
- Integrated i18n support in PlotHistoricalManager, PlotHistoricalSession, and TimePointSelector components.
- Translated various UI strings related to historical plots, time selection, and console logs into English, Spanish, and Italian.
- Improved user experience by providing localized messages for actions and statuses.
fix: Update system state configuration
- Changed `should_connect` to true and added active datasets to the system state.
- Updated the last update timestamp and specified the path for PlotJuggler.
- Changed sampling interval for "Fast" dataset from 0.1 to 0.5 seconds.
- Updated variable definitions for "Fast" dataset, including renaming and modifying properties for AUX Blink and M50 variables.
- Adjusted plot definitions to reduce time window from 36 to 10 seconds.
- Enhanced plot variables to ensure correct labeling and enablement of variables.
- Increased inter-read delay in PLCClient for improved stability and added batch reading functionality to optimize variable reads.
- Implemented asynchronous CSV writing system in DataStreamer to reduce I/O operations and improve performance.
- Updated ChartjsPlot component to modify refresh rates for real-time data handling.
- Adjusted system state to disable automatic connection and clear active datasets.
- Se creó el archivo PERFORMANCE_MONITORING.md que detalla el sistema de monitoreo de rendimiento en tiempo real, incluyendo métricas, logs y APIs de monitoreo.
- Se desarrolló el archivo PRIORITY_SYSTEM.md que describe la arquitectura de prioridades para asegurar que el recording de CSV tenga máxima prioridad.
- Se implementó el PerformanceMonitor en core/performance_monitor.py para registrar métricas de rendimiento, incluyendo tiempos de lectura, uso de CPU y errores.
- Se creó el PriorityThreadManager en core/priority_manager.py para gestionar la prioridad de los hilos y asegurar que las operaciones de recording no sean interrumpidas.
- Se implementó un sistema de logging rotativo en core/rotating_logger.py que permite la rotación automática de archivos de log y limpieza de archivos antiguos.
- Introduced `useCoordinatedConnection` and `useCoordinatedPolling` hooks to manage data fetching and state synchronization between tabs.
- Refactored `DatasetCompleteManager`, `PlotRealtimeViewer`, and `VariableSelectorWidget` components to utilize SSE and polling for live data updates.
- Added `TabCoordinationDemo` component to visualize tab coordination status and leadership.
- Updated `Dashboard` to leverage coordinated polling for status updates, improving performance and reducing redundant connections.
- Enhanced `TabCoordinator` utility to manage leadership and data broadcasting between tabs effectively.
- Enhanced session ID generation to include browser tab identifiers, allowing multiple instances of the same plot in different tabs.
- Updated PlotManager to manage sessions more effectively, including cleanup of inactive sessions.
- Modified frontend components to handle dynamic session IDs and ensure independent operation across tabs.
- Added new API endpoints for retrieving sessions by plot ID and manual cleanup of inactive sessions.
- Improved error handling and logging for better debugging and user experience.
- Updated dataset_variables.json to include new variables and adjust configurations.
- Modified plot_variables.json to add visualization settings for new variables.
- Enhanced ConfigManager to support expansion of symbolic variables, improving variable management.
- Updated PLCClient to handle additional memory types for variable reading.
- Refactored VariableSelectorWidget to utilize expanded dataset variables for better selection.
- Added new API endpoint to retrieve expanded dataset variables.
- Adjusted system_state.json to reflect changes in active datasets and last update timestamp.
- Updated dataset definitions to use a sampling interval of 0.5 seconds.
- Changed plot definitions to reduce the time window to 25 seconds and added a new plot for "Brix".
- Removed deprecated variable configurations from plot variables.
- Refactored ConfigManager to load datasets and variables from new array format, eliminating legacy save methods.
- Updated PLCDataStreamer and PlotManager to reflect changes in dataset and plot management, removing automatic save calls.
- Enhanced ChartjsPlot component to handle variable configurations and session management more efficiently.
- Improved PlotRealtimeSession to ensure backend commands are verified before applying local state changes.
- Adjusted system state to reflect active datasets and connection status.
- Changed dataset_variables schema from object to array format, adding dataset_id property.
- Updated plc schema by removing cleanup_interval_hours and max_hours properties, and added sampling_interval to udp_config.
- Modified plot_variables schema from object to array format, adding plot_id property.
- Enhanced UI schemas for dataset definitions and variables, improving layout and descriptions.
- Updated PLC configuration UI schema to reflect changes in the underlying schema.
- Improved error handling and logging in the ConfigManager for better diagnostics.
- Added helper methods in PLCClient for reconnection status and connection info.
- Unified API endpoints for configuration management, allowing direct file access and validation against schemas.
- Introduced a validation script for schema compliance checks.
Miguel