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maziggy
856b849ffa
Statistics now aggregate over PrintLogEntry (one row per print event,
the same table backing the global Print Log) rather than PrintArchive
(one row per file). A reprint creates a new PrintLogEntry instead of
overwriting the source archive's runtime fields, so:
- a 100 g successful print + a 10 g failed reprint correctly sums to
110 g / 2 prints / 1 successful / 1 failed in Quick Stats and the
Prometheus /metrics endpoint (previously the failed reprint silently
replaced the source archive's data; totals dropped from 100 g to 10 g)
- the archive's card cost/energy_kwh are preserved on reprints (only
the first run writes them); per-run actuals live on PrintLogEntry
- failed/cancelled/stopped reprints record partial-aware filament: sum
of tracked spool deltas when inventory is set up, else estimate
scaled to progress%, else None — prevents the full slicer estimate
from inflating totals on a print that stopped at 10 % progress
PrintLogEntry gains six columns: archive_id (nullable FK, ON DELETE
SET NULL so log entries survive archive deletion preserving #1343
soft-delete-vs-stats decoupling), cost, energy_kwh, energy_cost,
failure_reason, created_by_id. Idempotent SQLite + Postgres migrations.
New per-archive surface:
- archive list response carries run_count / last_run_at /
total_filament_actual_grams / successful_run_count / failed_run_count
via a single batch JOIN, no N+1
- new GET /archives/{id}/runs endpoint returns every PrintLogEntry for
the archive (ARCHIVES_READ permission, newest-first ordering)
- archive cards render an orange "N prints" badge for archives with
more than one run; clicking the badge opens a dedicated PrintLogModal
with date/status/duration/filament/cost columns plus failure_reason
under failed runs. Also reachable via the context menu's new "Print
Log" entry (works for single-run archives too), and embedded at the
top of the Edit Archive modal for context.
The purge_stats=true delete path now hard-deletes linked PrintLogEntry
rows up front so the archive's contribution truly leaves the totals;
without it, ON DELETE SET NULL would orphan the runs and leave them
counting toward stats.
45 lines
2.2 KiB
Python
45 lines
2.2 KiB
Python
from datetime import datetime
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from sqlalchemy import DateTime, Float, ForeignKey, Integer, String, func
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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 PrintLogEntry(Base):
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"""Independent print log entry. Written when print events occur.
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This is a separate table from archives/queue — clearing the log
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never touches archives or queue items.
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archive_id is a nullable FK so log entries survive archive deletion (ON
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DELETE SET NULL). Aggregating runs per archive — for the per-archive
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"Print Log" view and for statistics that should not double-count
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overwritten archives (#1378) — is done via WHERE archive_id = X.
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"""
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__tablename__ = "print_log_entries"
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id: Mapped[int] = mapped_column(primary_key=True)
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archive_id: Mapped[int | None] = mapped_column(
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ForeignKey("print_archives.id", ondelete="SET NULL"), nullable=True, index=True
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)
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print_name: Mapped[str | None] = mapped_column(String(255))
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printer_name: Mapped[str | None] = mapped_column(String(255))
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printer_id: Mapped[int | None] = mapped_column(Integer)
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status: Mapped[str] = mapped_column(String(20)) # completed, failed, stopped, cancelled, skipped
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started_at: Mapped[datetime | None] = mapped_column(DateTime)
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completed_at: Mapped[datetime | None] = mapped_column(DateTime)
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duration_seconds: Mapped[int | None] = mapped_column(Integer)
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filament_type: Mapped[str | None] = mapped_column(String(50))
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filament_color: Mapped[str | None] = mapped_column(String(50))
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filament_used_grams: Mapped[float | None] = mapped_column(Float)
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cost: Mapped[float | None] = mapped_column(Float)
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energy_kwh: Mapped[float | None] = mapped_column(Float)
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energy_cost: Mapped[float | None] = mapped_column(Float)
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failure_reason: Mapped[str | None] = mapped_column(String(100))
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thumbnail_path: Mapped[str | None] = mapped_column(String(500))
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created_by_id: Mapped[int | None] = mapped_column(ForeignKey("users.id", ondelete="SET NULL"), nullable=True)
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created_by_username: Mapped[str | None] = mapped_column(String(100))
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created_at: Mapped[datetime] = mapped_column(DateTime, server_default=func.now())
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