134 lines
3.4 KiB
Python
134 lines
3.4 KiB
Python
"""
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Job Schema Definitions
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Source of truth for job data models.
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TranscodeJob and ChunkJob share common lifecycle fields by convention.
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"""
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from dataclasses import dataclass, field
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from datetime import datetime
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from enum import Enum
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from typing import Any, Dict, List, Optional
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from uuid import UUID
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class JobStatus(str, Enum):
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"""Status of a transcode/trim job."""
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PENDING = "pending"
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PROCESSING = "processing"
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COMPLETED = "completed"
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FAILED = "failed"
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CANCELLED = "cancelled"
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@dataclass
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class TranscodeJob:
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"""
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A transcoding or trimming job in the queue.
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Jobs can either:
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- Transcode using a preset (full re-encode)
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- Trim only (stream copy with -c:v copy -c:a copy)
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A trim-only job has no preset and uses stream copy.
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"""
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id: UUID
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# Input
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source_asset_id: UUID
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# Configuration
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preset_id: Optional[UUID] = None
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preset_snapshot: Dict[str, Any] = field(
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default_factory=dict
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) # Copy at creation time
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# Trimming (optional)
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trim_start: Optional[float] = None # seconds
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trim_end: Optional[float] = None # seconds
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# Output
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output_filename: str = ""
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output_path: Optional[str] = None
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output_asset_id: Optional[UUID] = None
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# Status & Progress
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status: JobStatus = JobStatus.PENDING
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progress: float = 0.0 # 0.0 to 100.0
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current_frame: Optional[int] = None
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current_time: Optional[float] = None # seconds processed
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speed: Optional[str] = None # "2.5x"
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error_message: Optional[str] = None
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# Worker tracking
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celery_task_id: Optional[str] = None
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execution_arn: Optional[str] = None # AWS Step Functions execution ARN
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priority: int = 0 # Lower = higher priority
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# Timestamps
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created_at: Optional[datetime] = None
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started_at: Optional[datetime] = None
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completed_at: Optional[datetime] = None
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@property
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def is_trim_only(self) -> bool:
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"""Check if this is a trim-only job (stream copy, no transcode)."""
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return self.preset_id is None and (
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self.trim_start is not None or self.trim_end is not None
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)
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class ChunkJobStatus(str, Enum):
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"""Status of a chunk pipeline job."""
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PENDING = "pending"
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CHUNKING = "chunking"
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PROCESSING = "processing"
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COLLECTING = "collecting"
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COMPLETED = "completed"
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FAILED = "failed"
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CANCELLED = "cancelled"
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@dataclass
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class ChunkJob:
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"""
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A chunk pipeline job — splits a media file into chunks and processes them
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through a concurrent worker pool.
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"""
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id: UUID
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# Input
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source_asset_id: UUID
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# Configuration
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chunk_duration: float = 10.0 # seconds
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num_workers: int = 4
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max_retries: int = 3
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processor_type: str = "ffmpeg" # "ffmpeg", "checksum", "simulated_decode", "composite"
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# Status & Progress
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status: ChunkJobStatus = ChunkJobStatus.PENDING
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progress: float = 0.0 # 0.0 to 100.0
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total_chunks: int = 0
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processed_chunks: int = 0
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failed_chunks: int = 0
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retry_count: int = 0
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error_message: Optional[str] = None
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# Result stats
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throughput_mbps: Optional[float] = None
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elapsed_seconds: Optional[float] = None
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# Worker tracking
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celery_task_id: Optional[str] = None
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priority: int = 0 # Lower = higher priority
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# Timestamps
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created_at: Optional[datetime] = None
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started_at: Optional[datetime] = None
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completed_at: Optional[datetime] = None
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