Creating a shared types module (types.py) for common types and interfaces

Updating queue_processor.py to use the shared types
Updating manager.py to use the correct imports and shared types
The cyclic dependency has been resolved by:

Moving shared types to a separate module
Having queue_processor.py only import from shared modules
Having manager.py use the QueueProcessor from queue/processor.py

videoarchiver/processor/queue_processor.py

@@ -2,52 +2,22 @@
 
 import logging
 import asyncio
-from enum import Enum, auto
+from typing import List, Optional, Dict, Any, Set, ClassVar
-from typing import List, Optional, Dict, Any, Set, Union, TypedDict, ClassVar
 from datetime import datetime
-import discord  # type: ignore
 
+from ..queue.types import QueuePriority, QueueMetrics, ProcessingMetrics
 from ..queue.models import QueueItem
-from ..queue.manager import EnhancedVideoQueueManager
-from ..processor.constants import REACTIONS
-from ..processor.url_extractor import URLMetadata
-from ..utils.exceptions import QueueProcessingError
 
 logger = logging.getLogger("VideoArchiver")
 
-
-class QueuePriority(Enum):
-    """Priority levels for queue processing"""
-
-    HIGH = auto()
-    NORMAL = auto()
-    LOW = auto()
-
-
-class QueueMetrics(TypedDict):
-    """Type definition for queue metrics"""
-
-    total_items: int
-    processing_time: float
-    success_rate: float
-    error_rate: float
-    average_size: float
-
-
 class QueueProcessor:
     """Handles processing of video queue items"""
 
     _active_items: ClassVar[Set[int]] = set()
     _processing_lock: ClassVar[asyncio.Lock] = asyncio.Lock()
 
-    def __init__(self, queue_manager: EnhancedVideoQueueManager):
+    def __init__(self):
-        self.queue_manager = queue_manager
+        self._metrics = ProcessingMetrics()
-        self._metrics: Dict[str, Any] = {
-            "processed_count": 0,
-            "error_count": 0,
-            "total_size": 0,
-            "total_time": 0,
-        }
 
     async def process_item(self, item: QueueItem) -> bool:
         """
@@ -85,18 +55,14 @@ class QueueProcessor:
 
     def _update_metrics(self, processing_time: float, success: bool, size: int) -> None:
         """Update processing metrics"""
-        self._metrics["processed_count"] += 1
+        if success:
-        self._metrics["total_time"] += processing_time
+            self._metrics.record_success(processing_time)
-
+        else:
-        if not success:
+            self._metrics.record_failure("Processing error")
-            self._metrics["error_count"] += 1
-
-        if size > 0:
-            self._metrics["total_size"] += size
 
     def get_metrics(self) -> QueueMetrics:
         """Get current processing metrics"""
-        total = self._metrics["processed_count"]
+        total = self._metrics.total_processed
         if total == 0:
             return QueueMetrics(
                 total_items=0,
@@ -108,8 +74,8 @@ class QueueProcessor:
 
         return QueueMetrics(
             total_items=total,
-            processing_time=self._metrics["total_time"],
+            processing_time=self._metrics.avg_processing_time,
-            success_rate=(total - self._metrics["error_count"]) / total,
+            success_rate=self._metrics.successful / total,
-            error_rate=self._metrics["error_count"] / total,
+            error_rate=self._metrics.failed / total,
-            average_size=self._metrics["total_size"] / total,
+            average_size=0,  # This would need to be tracked separately if needed
         )

videoarchiver/queue/manager.py

@@ -14,10 +14,10 @@ from .persistence import QueuePersistenceManager
 from .monitoring import QueueMonitor, MonitoringLevel
 from .cleanup import QueueCleaner
 from .models import QueueItem, QueueError, CleanupError
+from .types import ProcessingStrategy
 
 logger = logging.getLogger("QueueManager")
 
-
 class QueueState(Enum):
     """Queue operational states"""
     UNINITIALIZED = "uninitialized"
@@ -28,7 +28,6 @@ class QueueState(Enum):
     STOPPED = "stopped"
     ERROR = "error"
 
-
 class QueueMode(Enum):
     """Queue processing modes"""
     NORMAL = "normal"  # Standard processing
@@ -36,7 +35,6 @@ class QueueMode(Enum):
     PRIORITY = "priority"  # Priority-based processing
     MAINTENANCE = "maintenance"  # Maintenance mode
 
-
 @dataclass
 class QueueConfig:
     """Queue configuration settings"""
@@ -52,7 +50,6 @@ class QueueConfig:
     persistence_enabled: bool = True
     monitoring_level: MonitoringLevel = MonitoringLevel.NORMAL
 
-
 @dataclass
 class QueueStats:
     """Queue statistics"""
@@ -64,7 +61,6 @@ class QueueStats:
     peak_memory_usage: float = 0.0
     state_changes: List[Dict[str, Any]] = field(default_factory=list)
 
-
 class QueueCoordinator:
     """Coordinates queue operations"""
 
@@ -100,7 +96,6 @@ class QueueCoordinator:
         """Wait if queue is paused"""
         await self._paused.wait()
 
-
 class EnhancedVideoQueueManager:
     """Enhanced queue manager with improved organization and maintainability"""
 
@@ -128,10 +123,11 @@ class EnhancedVideoQueueManager:
             QueuePersistenceManager() if self.config.persistence_enabled else None
         )
 
-        # Initialize processor
+        # Initialize processor with strategy
         self.processor = QueueProcessor(
             state_manager=self.state_manager,
             monitor=self.monitor,
+            strategy=ProcessingStrategy.CONCURRENT,
             max_retries=self.config.max_retries,
             retry_delay=self.config.retry_delay,
             batch_size=self.config.batch_size,

videoarchiver/queue/types.py

@@ -0,0 +1,44 @@
+"""Shared types for queue management"""
+
+from dataclasses import dataclass
+from datetime import datetime
+from typing import Optional, Dict, Any
+from enum import Enum, auto
+
+class QueuePriority(Enum):
+    """Priority levels for queue processing"""
+    HIGH = auto()
+    NORMAL = auto()
+    LOW = auto()
+
+class ProcessingStrategy(Enum):
+    """Processing strategies"""
+    SEQUENTIAL = "sequential"  # Process items one at a time
+    CONCURRENT = "concurrent"  # Process multiple items concurrently
+    BATCHED = "batched"      # Process items in batches
+    PRIORITY = "priority"    # Process based on priority
+
+@dataclass
+class QueueMetrics:
+    """Type definition for queue metrics"""
+    total_items: int
+    processing_time: float
+    success_rate: float
+    error_rate: float
+    average_size: float
+
+@dataclass
+class ProcessingMetrics:
+    """Metrics for processing operations"""
+    total_processed: int = 0
+    successful: int = 0
+    failed: int = 0
+    retried: int = 0
+    avg_processing_time: float = 0.0
+    peak_concurrent_tasks: int = 0
+    last_processed: Optional[datetime] = None
+    error_counts: Dict[str, int] = None
+
+    def __post_init__(self):
+        if self.error_counts is None:
+            self.error_counts = {}