Allow dirty apps to specify how many workers should load them, enabling
significant memory savings for heavy applications like ML models.
- Add `workers` class attribute to DirtyApp (None = all workers)
- Add `parse_dirty_app_spec()` to parse "module:Class:N" format
- Add `DirtyNoWorkersAvailableError` for app-specific error handling
- Update DirtyArbiter with per-app worker tracking and routing
- Maintain backward compatibility when no dirty_apps configured
Example: 8 workers x 10GB model = 80GB RAM needed
With workers=2: 2 x 10GB = 20GB RAM (75% savings)
Configuration formats:
- Class attribute: `workers = 2` on DirtyApp subclass
- Config format: `module:class:N` (e.g., `myapp.ml:HugeModel:2`)
