# Task Management Service - Implementation Summary

## Overview
Implemented a thread pool-based background task service for EU-Utility that replaces the need for plugins to create their own QThreads.

## Files Created

### 1. `core/tasks.py`
The core TaskManager implementation with:

- **Singleton TaskManager class** - Shared across the application
- **ThreadPoolExecutor** - Configurable max workers (default: 4)
- **Task priority levels** - HIGH, NORMAL, LOW
- **Task scheduling**:
  - `run_in_thread()` - Immediate background execution
  - `run_later()` - Delayed execution (ms)
  - `run_periodic()` - Repeating execution at interval
- **Callback support** - `on_complete`, `on_error`
- **Task ID tracking** - UUID-based unique IDs
- **Graceful shutdown** - Wait for tasks or cancel with timeout
- **Qt signal integration** - Thread-safe UI updates

Key signals:
- `task_completed` - (task_id, result)
- `task_failed` - (task_id, error_message)
- `task_started` - (task_id)
- `task_cancelled` - (task_id)
- `task_periodic` - (task_id, iteration, result)

## Files Modified

### 2. `core/plugin_api.py`
Added to PluginAPI:
- `register_task_service()` - Register TaskManager instance
- `run_in_background()` - Run function in thread pool
- `schedule_task()` - Delayed/periodic task scheduling
- `cancel_task()` - Cancel pending/running task
- `get_task_status()` - Query task status
- `wait_for_task()` - Wait for completion
- `connect_task_signal()` - Connect to Qt signals

### 3. `plugins/base_plugin.py`
Added to BasePlugin:
- `run_in_background()` - Background task execution
- `schedule_task()` - Delayed/periodic scheduling
- `cancel_task()` - Task cancellation
- `connect_task_signals()` - Batch signal connection

### 4. `core/main.py`
Changes:
- Import `get_task_manager` from tasks module
- Initialize TaskManager in `_setup_api_services()`
- Register task service with API
- Graceful shutdown in `quit()` - waits for tasks (30s timeout)

## Usage Examples

### Simple Background Task
```python
def heavy_calculation(data):
    return process(data)

task_id = self.run_in_background(
    heavy_calculation,
    large_dataset,
    priority='high',
    on_complete=lambda result: print(f"Done: {result}"),
    on_error=lambda e: print(f"Error: {e}")
)
```

### Delayed Task
```python
task_id = self.schedule_task(
    delay_ms=5000,  # 5 seconds
    func=lambda: print("Hello!"),
    on_complete=lambda _: print("Complete")
)
```

### Periodic Task
```python
task_id = self.schedule_task(
    delay_ms=0,
    func=fetch_data,
    periodic=True,
    interval_ms=30000,  # Every 30 seconds
    on_complete=lambda data: update_ui(data)
)

# Cancel later
self.cancel_task(task_id)
```

### UI Updates (Thread-Safe)
```python
def initialize(self):
    # Connect signals once
    self.connect_task_signals(
        on_completed=self._on_done,
        on_failed=self._on_error
    )

def start_work(self):
    # Run in background
    self.run_in_background(
        self.process_data,
        priority='normal'
    )

def _on_done(self, task_id, result):
    # Runs in main thread - safe to update UI!
    self.status_label.setText(f"Complete: {result}")

def _on_error(self, task_id, error):
    self.status_label.setText(f"Error: {error}")
```

## Benefits

1. **No more QThreads** - Plugins use shared thread pool
2. **Qt signal integration** - Thread-safe UI updates
3. **Priority levels** - HIGH tasks run before LOW
4. **Task tracking** - Monitor and cancel tasks
5. **Graceful shutdown** - Wait for tasks on exit
6. **Error handling** - Centralized error callbacks
7. **Less code** - Simple API vs managing QThreads

## Migration Guide

**Before (with QThread):**
```python
class Worker(QThread):
    finished = pyqtSignal(object)
    
    def run(self):
        result = heavy_work()
        self.finished.emit(result)

worker = Worker()
worker.finished.connect(self.handle_result)
worker.start()
```

**After (with TaskManager):**
```python
task_id = self.run_in_background(
    heavy_work,
    on_complete=self.handle_result
)
```