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bambuman
6e82cc611e
Implement accurate per-filament usage tracking for Spoolman integration, similar to OpenSpoolman v0.3.0. This replaces the previous single-spool reporting with multi-material aware tracking. Features: - Parse G-code from 3MF files at print start to build per-layer, per-filament cumulative extrusion maps - Store tracking data in new `active_print_spoolman` database table (survives server restarts for long prints) - Report accurate partial usage when prints fail/cancel based on actual layer progress and G-code data - Add "Disable AMS Weight Sync" setting to prevent AMS percentage-based weight estimates from overwriting Spoolman's granular tracking - Add "Report Partial Usage for Failed Prints" toggle (only shown when weight sync is disabled) - Use Spoolman's filament density instead of defaults for mm-to-grams conversion - Prefer tray_uuid over tag_uid for spool identification
43 lines
1.8 KiB
Python
43 lines
1.8 KiB
Python
"""Track Spoolman data for active prints."""
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from sqlalchemy import JSON, ForeignKey, UniqueConstraint
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from sqlalchemy.orm import Mapped, mapped_column
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from backend.app.core.database import Base
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class ActivePrintSpoolman(Base):
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"""Stores Spoolman tracking data for active prints.
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This data is captured at print start and used at print completion
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to report per-filament usage to the correct Spoolman spools.
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Rows are deleted after print completes.
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Key: (printer_id, archive_id) - allows same archive on different printers
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"""
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__tablename__ = "active_print_spoolman"
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__table_args__ = (UniqueConstraint("printer_id", "archive_id", name="uq_printer_archive"),)
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id: Mapped[int] = mapped_column(primary_key=True)
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printer_id: Mapped[int] = mapped_column(ForeignKey("printers.id", ondelete="CASCADE"))
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archive_id: Mapped[int] = mapped_column(ForeignKey("print_archives.id", ondelete="CASCADE"))
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# Per-filament usage from 3MF: [{"slot_id": 1, "used_g": 50.5, "type": "PLA"}, ...]
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filament_usage: Mapped[list] = mapped_column(JSON)
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# AMS tray state at print start: {0: {"tray_uuid": "...", "tag_uid": "..."}, ...}
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ams_trays: Mapped[dict] = mapped_column(JSON)
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# Custom slot-to-tray mapping from queue (optional): [5, -1, 2, -1]
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slot_to_tray: Mapped[list | None] = mapped_column(JSON, nullable=True)
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# Per-layer cumulative usage from G-code parsing (for accurate partial usage)
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# Format: {"0": {0: 125.5}, "1": {0: 250.0, 1: 50.0}, ...}
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# Keys are layer numbers (as strings for JSON), values are filament_id -> mm
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layer_usage: Mapped[dict | None] = mapped_column(JSON, nullable=True)
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# Filament properties (density, diameter per filament slot)
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# Format: {1: {"density": 1.24, "diameter": 1.75, "type": "PLA"}, ...}
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filament_properties: Mapped[dict | None] = mapped_column(JSON, nullable=True)
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