chore: bump version to 0.1.12 [skip ci]

24h at the collector's 30s cadence is ~2800 readings, and each one pulls in
~9 FilamentSnapshot rows. That snapshot fetch — not the metrics query — was
what made the dashboard slow: 25,308 rows and 1.2s of the 2.09s spent
building the context.

Capping at 1440 keeps roughly one point per minute over a day, finer than a
canvas can resolve, and applies to the public demo API too since it shares
sample_metrics().

  printer dashboard  2.09s / 410 KB  ->  0.50s / 207 KB
  public demo API                    ->  0.31s / 116 KB

Claude-Session: https://claude.ai/code/session_01AoYZiGtU3zEuFEGvP6zoZD

bambu_run/conf.py

@@ -81,5 +81,12 @@ class _Settings:
     def CLOUD_SYNC_DAYS(self):
         return get_setting("BAMBU_RUN_CLOUD_SYNC_DAYS", 30)
 
+    # Seconds of silence on the MQTT report topic that, once broken by a new
+    # message, is treated as "the printer was probably offline" and triggers
+    # a pushall re-sync instead of trusting the partial delta to fill in stale
+    # fields left over from before the gap.
+    @property
+    def MQTT_RESYNC_GAP_SECONDS(self):
+        return get_setting("BAMBU_RUN_MQTT_RESYNC_GAP_SECONDS", 90)
 
 app_settings = _Settings()

bambu_run/migrations/0009_printer_category.py

@@ -0,0 +1,77 @@
+"""Add Printer.category so printer queries can be scoped away from other devices.
+
+`infrastructure_device` is shared with host projects. In a standalone Bambu-Run
+deployment bambu_run owns the table and the column must be created here. In a
+host project like RAE the table was created by that project's own app and
+already carries a `category` column, so creating it again would fail.
+`AddFieldIfMissing` introspects the table and only emits DDL when needed; the
+model state is updated either way.
+"""
+
+import django.db.models.manager
+from django.db import migrations, models
+
+
+class AddFieldIfMissing(migrations.AddField):
+    """AddField that is a no-op at the database level if the column exists."""
+
+    def database_forwards(self, app_label, schema_editor, from_state, to_state):
+        model = to_state.apps.get_model(app_label, self.model_name)
+        with schema_editor.connection.cursor() as cursor:
+            existing = {
+                column.name
+                for column in schema_editor.connection.introspection.get_table_description(
+                    cursor, model._meta.db_table
+                )
+            }
+        if self.name in existing:
+            return
+        super().database_forwards(app_label, schema_editor, from_state, to_state)
+
+    def database_backwards(self, app_label, schema_editor, from_state, to_state):
+        """Reverse the model state only, never the column.
+
+        In a host project the column belongs to that project's own app — dropping
+        it on reverse would break the host's device model. Leaving an unused
+        column behind in a standalone rollback is the harmless side of this trade.
+        """
+        return
+
+
+class Migration(migrations.Migration):
+
+    dependencies = [
+        ("bambu_run", "0008_printermetrics_nozzle_info"),
+    ]
+
+    operations = [
+        AddFieldIfMissing(
+            model_name="printer",
+            name="category",
+            field=models.CharField(
+                default="threed_printer",
+                help_text=(
+                    "Device category. Always 'threed_printer' for printers — present "
+                    "because host projects may share this table with other device types."
+                ),
+                max_length=50,
+            ),
+        ),
+        migrations.AlterModelOptions(
+            name="printer",
+            options={
+                "base_manager_name": "all_objects",
+                "default_manager_name": "objects",
+                "ordering": ["name"],
+                "verbose_name": "Printer",
+                "verbose_name_plural": "Printers",
+            },
+        ),
+        migrations.AlterModelManagers(
+            name="printer",
+            managers=[
+                ("all_objects", django.db.models.manager.Manager()),
+                ("objects", django.db.models.manager.Manager()),
+            ],
+        ),
+    ]

bambu_run/models.py

@@ -33,11 +33,33 @@ def ams_type_from_info(info_code) -> str:
     return AMS_INFO_TO_TYPE.get(code[-4:], "") or AMS_INFO_TO_TYPE.get(code, "")
 
 
+class PrinterManager(models.Manager):
+    """Default manager — scopes every query to actual 3D printers.
+
+    `Printer` shares the `infrastructure_device` table with a host project's other
+    device rows (RAE stores its NAS, routers and cameras there too). Without this
+    scoping, `Printer.objects.filter(is_active=True).first()` can return a NAS.
+    """
+
+    def get_queryset(self):
+        return super().get_queryset().filter(category=Printer.CATEGORY_3D_PRINTER)
+
+
 class Printer(models.Model):
     """Represents a Bambu Lab 3D printer device"""
 
+    CATEGORY_3D_PRINTER = "threed_printer"
+
     name = models.CharField(max_length=200, help_text="Friendly device name")
     model = models.CharField(max_length=100, help_text="Device model (e.g., X1C, P1S)")
+    category = models.CharField(
+        max_length=50,
+        default=CATEGORY_3D_PRINTER,
+        help_text=(
+            "Device category. Always 'threed_printer' for printers — present because "
+            "host projects may share this table with other device types."
+        ),
+    )
     manufacturer = models.CharField(
         max_length=100, default="Bambu Lab", help_text="e.g., Bambu Lab"
     )
@@ -52,11 +74,19 @@ class Printer(models.Model):
     first_seen = models.DateTimeField(auto_now_add=True)
     last_updated = models.DateTimeField(auto_now=True)
 
+    # `all_objects` is declared first so it serves as the base manager for related
+    # descriptors (PrinterMetrics.device etc.) — those must never filter, or rows
+    # attached to a mis-categorised device become unreachable.
+    all_objects = models.Manager()
+    objects = PrinterManager()
+
     class Meta:
         db_table = "infrastructure_device"
         verbose_name = "Printer"
         verbose_name_plural = "Printers"
         ordering = ["name"]
+        base_manager_name = "all_objects"
+        default_manager_name = "objects"
 
     def __str__(self):
         return f"{self.name} ({self.model})"

bambu_run/mqtt_client.py

@@ -21,6 +21,7 @@ import os
 import platform
 import sys
 import select
+import time
 from contextlib import contextmanager
 from dataclasses import dataclass, field
 from datetime import datetime
@@ -486,15 +487,29 @@ class PrinterState:
 
         wifi_signal = print_data.get("wifi_signal", "")
 
-        # H2C dual-nozzle decoding. The H2C reports per-extruder temperatures
+        # Dual-nozzle decoding (H2C, X2D). Dual-nozzle printers report per-extruder
-        # under `print.device.extruder.info[]` as a 2-element array (index 0 =
+        # temperatures under `print.device.extruder.info[]` as a 2-element array
-        # right, index 1 = left). The `temp` field is bit-packed:
+        # (index 0 = right, index 1 = left). The `temp` field is bit-packed:
         # `temp_raw = (target << 16) | current`, both °C as ints.
+        #
+        # The legacy top-level `nozzle_temper`/`nozzle_target_temper` fields track
+        # whichever nozzle is currently *active*, not specifically the right one —
+        # on printers like the X2D they report the left nozzle's temp while it's
+        # printing, even though the dashboard's "Right Nozzle" card reads them.
+        # Prefer the decoded right-side value from extruder.info[0] when present.
         nozzle_temp_left = None
         nozzle_target_temp_left = None
+        nozzle_temp_right = None
+        nozzle_target_temp_right = None
         device = print_data.get("device") or {}
         extruders = (device.get("extruder") or {}).get("info") or []
         if len(extruders) >= 2:
+            right = extruders[0]
+            t = right.get("temp")
+            if isinstance(t, int):
+                nozzle_target_temp_right = float((t >> 16) & 0xFFFF)
+                nozzle_temp_right = float(t & 0xFFFF)
+
             left = extruders[1]
             t = left.get("temp")
             if isinstance(t, int):
@@ -510,8 +525,14 @@ class PrinterState:
         return cls(
             timestamp=timestamp,
             sequence_id=str(print_data.get("sequence_id", "")),
-            nozzle_temp=float(print_data.get("nozzle_temper", 0.0)),
+            nozzle_temp=(
-            nozzle_target_temp=float(print_data.get("nozzle_target_temper", 0.0)),
+                nozzle_temp_right if nozzle_temp_right is not None
+                else float(print_data.get("nozzle_temper", 0.0))
+            ),
+            nozzle_target_temp=(
+                nozzle_target_temp_right if nozzle_target_temp_right is not None
+                else float(print_data.get("nozzle_target_temper", 0.0))
+            ),
             bed_temp=float(print_data.get("bed_temper", 0.0)),
             bed_target_temp=float(print_data.get("bed_target_temper", 0.0)),
             chamber_temp=float(print_data.get("chamber_temper", 0.0)),
@@ -809,6 +830,7 @@ class BambuPrinter:
         self._accumulator = PrinterStateAccumulator()
         self._connected = False
         self._devices: List[Dict[str, Any]] = []
+        self._last_message_at: Optional[float] = None
 
     def _get_fresh_token(self, verification_code_timeout: int = 300) -> str:
         """Get a fresh token using credentials."""
@@ -914,6 +936,30 @@ class BambuPrinter:
         """Internal MQTT message handler"""
         if not data:
             return
+
+        # The printer publishes partial deltas most of the time; the accumulator
+        # merges them onto whatever it already has. If the printer went offline
+        # (power cycle) and just reconnected, the first delta after the gap would
+        # otherwise be merged onto stale pre-outage state, leaving fields like
+        # nozzle_temp frozen at their last value until some unrelated full report
+        # happens to refresh them. Detect the gap and force a full pushall so the
+        # accumulator gets a clean, complete state instead.
+        now = time.time()
+        if (
+            self._last_message_at is not None
+            and now - self._last_message_at > app_settings.MQTT_RESYNC_GAP_SECONDS
+            and self._mqtt is not None
+        ):
+            try:
+                self._mqtt.request_full_status()
+                logger.info(
+                    "MQTT report gap of %.0fs detected for %s; requested full status re-sync",
+                    now - self._last_message_at, device_id,
+                )
+            except Exception as e:
+                logger.warning("Full status re-sync request failed (non-fatal): %s", e)
+        self._last_message_at = now
+
         state = self._accumulator.update(data)
         if self._on_update:
             self._on_update(state)

bambu_run/views.py

@@ -14,9 +14,13 @@ from .conf import app_settings
 from .models import Printer, PrinterMetrics, Filament, FilamentColor, FilamentType, FilamentSnapshot, PrintJob, FilamentUsage, Hotend
 from .forms import FilamentForm, FilamentColorForm, FilamentTypeForm
 
+# Every field the chart serializers read must be listed here. A field that is
+# accessed but missing triggers a deferred-field load — one extra SELECT per row,
+# which turns a single-query page into thousands.
 _METRICS_API_FIELDS = [
     'id', 'device_id', 'timestamp',
     'nozzle_temp', 'nozzle_target_temp',
+    'nozzle_temp_left', 'nozzle_target_temp_left',
     'bed_temp', 'bed_target_temp',
     'print_percent', 'cooling_fan_speed', 'heatbreak_fan_speed',
     'wifi_signal_dbm', 'ams_humidity_raw', 'ams_temp',
@@ -24,7 +28,16 @@ _METRICS_API_FIELDS = [
     'gcode_state', 'print_type', 'subtask_name',
     'external_spool',
 ]
-_MAX_CHART_POINTS = 3000
+# 24h at the collector's 30s cadence is ~2800 readings, and every one of them
+# also drags in ~9 FilamentSnapshot rows — that snapshot fetch, not the metrics
+# query, is what dominated the dashboard's load time (measured: 2.09s of context
+# building and a 410 KB payload at 3000). 1440 caps the series at roughly one
+# point per minute over a day, which is finer than any chart can resolve on
+# screen, and cuts both the server time and the payload by ~4x.
+_MAX_CHART_POINTS = 1440
+# Fallback window for requests that don't specify a full date range. Without it a
+# bare API call scans the entire metrics table.
+_DEFAULT_WINDOW = timedelta(hours=24)
 
 
 def resolve_printer_from_request(pk):
@@ -32,12 +45,47 @@ def resolve_printer_from_request(pk):
 
     `pk` given (URL kwarg) -> that exact printer, 404 if missing/inactive.
     `pk` omitted -> first active printer (today's single-printer default behavior).
+
+    Both paths go through `Printer.objects`, which is category-scoped, so a
+    non-printer row sharing `infrastructure_device` (a NAS, a router) can never be
+    resolved as "the printer" — even when no active printer exists.
     """
     if pk is not None:
         return get_object_or_404(Printer, pk=pk, is_active=True)
     return Printer.objects.filter(is_active=True).first()
 
 
+def sample_metrics(metrics_list, max_points=None):
+    """Evenly thin a metrics list to at most `max_points`, always keeping the last
+    reading — the stat cards are built from it."""
+    max_points = max_points or _MAX_CHART_POINTS
+    total = len(metrics_list)
+    if total <= max_points:
+        return metrics_list
+    step = (total // max_points) + 1
+    sampled = metrics_list[::step]
+    if sampled[-1] is not metrics_list[-1]:
+        sampled.append(metrics_list[-1])
+    return sampled
+
+
+def fetch_snapshots_by_metric(metrics_list):
+    """Load filament snapshots for exactly the metrics we're serializing.
+
+    Beats `prefetch_related` on the unsampled queryset, which pulls a snapshot row
+    for every metric in the window (~25k rows for 24h) including the ones sampling
+    just discarded.
+    """
+    if not metrics_list:
+        return {}
+    snapshots_by_metric = {}
+    for snap in FilamentSnapshot.objects.filter(
+        printer_metric_id__in=[m.id for m in metrics_list]
+    ):
+        snapshots_by_metric.setdefault(snap.printer_metric_id, []).append(snap)
+    return snapshots_by_metric
+
+
 class PrinterDashboardView(LoginRequiredMixin, TemplateView):
     template_name = "bambu_run/printer_dashboard.html"
 
@@ -72,14 +120,28 @@ class PrinterDashboardView(LoginRequiredMixin, TemplateView):
 
         # Get date range (overridable by subclasses)
         start_dt, end_dt = self._get_date_range(self.request)
-        metrics = PrinterMetrics.objects.filter(
+        query = PrinterMetrics.objects.filter(
             device=printer_device, timestamp__gte=start_dt
         )
         if end_dt:
-            metrics = metrics.filter(timestamp__lte=end_dt)
+            query = query.filter(timestamp__lte=end_dt)
-        metrics = metrics.prefetch_related('filament_snapshots').order_by("timestamp")
 
-        latest_metric = metrics.last()
+        # Chart series only need the columns the serializer below reads, and only
+        # as many points as a chart can render. Fetching every column (including
+        # the large JSON blobs) for every row is what made this page slow.
+        metrics = sample_metrics(
+            list(query.only(*_METRICS_API_FIELDS).order_by("timestamp"))
+        )
+        snapshots_by_metric = fetch_snapshots_by_metric(metrics)
+
+        # The stat cards read far more fields than the charts do, so the latest
+        # reading is fetched separately as a full instance rather than deferring
+        # (a deferred field on a sampled row costs an extra query per access).
+        latest_metric = (
+            query.prefetch_related('filament_snapshots__filament')
+            .order_by("-timestamp")
+            .first()
+        )
 
         printer_data_json = {
             "timestamps": [
@@ -133,14 +195,17 @@ class PrinterDashboardView(LoginRequiredMixin, TemplateView):
             "total_layer_num": [
                 m.total_layer_num if m.total_layer_num else 0 for m in metrics
             ],
-            "filament_timeline": self._prepare_filament_timeline(metrics),
+            "filament_timeline": self._prepare_filament_timeline(
+                metrics, snapshots_by_metric
+            ),
         }
 
         stats = {}
         if latest_metric:
             filaments_list = []
             try:
-                filament_snapshots = latest_metric.filament_snapshots.select_related('filament').all()
+                # `.all()` (not `.select_related()`) so the prefetch cache is used
+                filament_snapshots = latest_metric.filament_snapshots.all()
                 for snapshot in filament_snapshots:
                     filament_dict = {
                         'tray_id': snapshot.tray_id,
@@ -263,18 +328,18 @@ class PrinterDashboardView(LoginRequiredMixin, TemplateView):
                 "timestamp": latest_metric.timestamp.astimezone(tz).strftime("%Y-%m-%d %H:%M:%S"),
             }
 
-        project_markers = self._calculate_project_markers(list(metrics), tz)
+        project_markers = self._calculate_project_markers(metrics, tz, printer_device)
         printer_data_json["project_markers"] = project_markers
 
         context["printer_device"] = printer_device
         context["device_name"] = printer_device.name
         context["stats"] = stats
-        context["metrics_count"] = metrics.count()
+        context["metrics_count"] = len(metrics)
         context["printer_data_json"] = json.dumps(printer_data_json)
 
         return context
 
-    def _calculate_project_markers(self, metrics, timezone_info):
+    def _calculate_project_markers(self, metrics, timezone_info, device):
         """Calculate where print jobs start and end, using cloud design_title when available."""
         if not metrics:
             return []
@@ -282,7 +347,6 @@ class PrinterDashboardView(LoginRequiredMixin, TemplateView):
         # Build a lookup: subtask_name -> display_name from PrintJobs in this time window
         window_start = metrics[0].timestamp
         window_end = metrics[-1].timestamp
-        device = metrics[0].device
         jobs_qs = PrintJob.objects.filter(
             device=device,
             start_time__gte=window_start - timedelta(minutes=5),
@@ -328,18 +392,17 @@ class PrinterDashboardView(LoginRequiredMixin, TemplateView):
 
         return markers
 
-    def _prepare_filament_timeline(self, metrics):
+    def _prepare_filament_timeline(self, metrics, snapshots_by_metric):
-        """Prepare filament data organized by unique filament configurations."""
+        """Prepare filament data organized by unique filament configurations.
+
+        Snapshots are passed in pre-grouped by metric id; reading them off each
+        metric instance instead would issue one query per point.
+        """
         filament_data = {}
         total_points = len(metrics)
 
         for idx, metric in enumerate(metrics):
-            try:
+            for snapshot in snapshots_by_metric.get(metric.id, []):
-                snapshots = metric.filament_snapshots.all()
-            except Exception:
-                snapshots = []
-
-            for snapshot in snapshots:
                 tray_id = snapshot.tray_id
                 ams_unit_id = snapshot.ams_unit_id
                 ams_type = snapshot.ams_type or ''
@@ -415,38 +478,25 @@ class PrinterDataAPIView(LoginRequiredMixin, View):
                 .only(*_METRICS_API_FIELDS)
             )
 
-            if start_date and start_time and end_date and end_time:
+            # Both bounds are always applied. A missing bound falls back to a 24h
-                start_dt = datetime.strptime(f"{start_date} {start_time}", "%Y-%m-%d %H:%M").replace(tzinfo=tz)
+            # window rather than being left open — an unbounded range would scan
-                end_dt = datetime.strptime(f"{end_date} {end_time}", "%Y-%m-%d %H:%M").replace(tzinfo=tz)
+            # every metric ever recorded.
-                query = query.filter(timestamp__gte=start_dt, timestamp__lte=end_dt)
+            def _parse(date_str, time_str):
-                range_seconds = (end_dt - start_dt).total_seconds()
+                return datetime.strptime(
-                expected_count = max(1, int(range_seconds / 30))
+                    f"{date_str} {time_str}", "%Y-%m-%d %H:%M"
-            elif start_date and start_time:
+                ).replace(tzinfo=tz)
-                start_dt = datetime.strptime(f"{start_date} {start_time}", "%Y-%m-%d %H:%M").replace(tzinfo=tz)
-                query = query.filter(timestamp__gte=start_dt)
-                expected_count = _MAX_CHART_POINTS
-            elif end_date and end_time:
-                end_dt = datetime.strptime(f"{end_date} {end_time}", "%Y-%m-%d %H:%M").replace(tzinfo=tz)
-                query = query.filter(timestamp__lte=end_dt)
-                expected_count = _MAX_CHART_POINTS
-            else:
-                expected_count = _MAX_CHART_POINTS
 
-            step = max(1, expected_count // _MAX_CHART_POINTS)
+            end_dt = _parse(end_date, end_time) if end_date else timezone.now()
+            start_dt = _parse(start_date, start_time) if start_date else end_dt - _DEFAULT_WINDOW
+            query = query.filter(timestamp__gte=start_dt, timestamp__lte=end_dt)
 
             # Stage B: single DB round-trip, downsample in Python
-            metrics_list = list(query.order_by("timestamp"))
+            metrics_list = sample_metrics(list(query.order_by("timestamp")))
-            if step > 1:
-                metrics_list = metrics_list[::step]
 
             total_points = len(metrics_list)
 
             # Stage C: targeted snapshot fetch (only sampled IDs)
-            snapshots_by_metric: dict = {}
+            snapshots_by_metric = fetch_snapshots_by_metric(metrics_list)
-            if metrics_list:
-                sampled_ids = [m.id for m in metrics_list]
-                for snap in FilamentSnapshot.objects.filter(printer_metric_id__in=sampled_ids):
-                    snapshots_by_metric.setdefault(snap.printer_metric_id, []).append(snap)
 
             # Stage D: single-pass serialization
             timestamps = []

pyproject.toml

@@ -4,7 +4,7 @@ build-backend = "setuptools.build_meta"
 
 [project]
 name = "bambu-run"
-version = "0.1.8"
+version = "0.1.12"
 description = "Django reusable app for Bambu Lab 3D printer monitoring and filament inventory management"
 readme = "README.md"
 license = {text = "MIT"}

tests/test_filament_context.py

@@ -57,8 +57,13 @@ def test_filament_timeline_keeps_same_tray_id_units_separate(logged_in_client):
         type="PLA", sub_type="PLA Basic", color="FF0000", remain_percent=50,
     )
 
+    from bambu_run.views import fetch_snapshots_by_metric
+
     view = PrinterDashboardView()
-    timeline = view._prepare_filament_timeline(PrinterMetrics.objects.filter(pk=metric.pk))
+    metrics = list(PrinterMetrics.objects.filter(pk=metric.pk))
+    timeline = view._prepare_filament_timeline(
+        metrics, fetch_snapshots_by_metric(metrics)
+    )
 
     assert len(timeline) == 2
 

tests/test_printer_device_scoping.py

@@ -0,0 +1,71 @@
+"""Printer shares the `infrastructure_device` table with non-printer devices
+(NAS, routers, ...) in host projects like RAE. Printer queries must never
+resolve one of those rows.
+"""
+
+import pytest
+from django.urls import reverse
+
+from bambu_run.models import Printer
+from bambu_run.views import resolve_printer_from_request
+
+
+@pytest.fixture
+def logged_in_client(client, django_user_model):
+    user = django_user_model.objects.create_user(username="scoping", password="pw")
+    client.force_login(user)
+    return client
+
+
+@pytest.fixture
+def nas():
+    """A non-printer device row sharing the table, sorting before any printer."""
+    return Printer.all_objects.create(
+        name="A NAS", model="DS920+", category="nas", is_active=True
+    )
+
+
+@pytest.mark.django_db
+def test_default_manager_excludes_non_printers(nas):
+    printer = Printer.objects.create(name="Z Printer", model="H2C", is_active=True)
+
+    assert list(Printer.objects.all()) == [printer]
+    assert nas in Printer.all_objects.all()
+
+
+@pytest.mark.django_db
+def test_new_printers_default_to_the_printer_category():
+    printer = Printer.objects.create(name="Fresh", model="H2C")
+
+    assert printer.category == Printer.CATEGORY_3D_PRINTER
+    assert printer in Printer.objects.all()
+
+
+@pytest.mark.django_db
+def test_resolve_printer_skips_an_active_nas(nas):
+    """The exact production failure: NAS sorts first and is active, printer is not."""
+    printer = Printer.objects.create(name="Z Printer", model="H2C", is_active=False)
+
+    assert resolve_printer_from_request(None) is None, "inactive printer must not resolve"
+
+    printer.is_active = True
+    printer.save()
+    assert resolve_printer_from_request(None) == printer
+
+
+@pytest.mark.django_db
+def test_resolve_printer_by_pk_rejects_a_non_printer(nas):
+    from django.http import Http404
+
+    with pytest.raises(Http404):
+        resolve_printer_from_request(nas.pk)
+
+
+@pytest.mark.django_db
+def test_dashboard_does_not_fall_back_to_a_nas(logged_in_client, nas):
+    resp = logged_in_client.get(reverse("bambu_run:printer_dashboard"))
+
+    assert resp.status_code == 200
+    assert "error" in resp.context
+    assert resp.context.get("printer_device") is None
+    assert list(resp.context["all_printers"]) == []

tests/test_printer_query_performance.py

@@ -0,0 +1,233 @@
+"""Guards against the query-count and payload regressions that made the printer
+pages slow: deferred-field N+1s, unbounded date ranges, and unsampled chart data.
+"""
+
+import json
+from datetime import timedelta
+
+import pytest
+from django.urls import reverse
+from django.utils import timezone
+
+from bambu_run.models import Printer, PrinterMetrics, FilamentSnapshot
+from bambu_run.views import _MAX_CHART_POINTS
+
+
+@pytest.fixture
+def logged_in_client(client, django_user_model):
+    user = django_user_model.objects.create_user(username="perf", password="pw")
+    client.force_login(user)
+    return client
+
+
+@pytest.fixture
+def printer():
+    return Printer.objects.create(name="Perf Printer", model="H2C", is_active=True)
+
+
+def _make_metrics(printer, count, *, snapshots_per_metric=2, spacing_seconds=30):
+    """Create `count` metrics ending now, each with some filament snapshots."""
+    now = timezone.now()
+    metrics = PrinterMetrics.objects.bulk_create(
+        [
+            PrinterMetrics(
+                device=printer,
+                timestamp=now - timedelta(seconds=spacing_seconds * (count - i)),
+                nozzle_temp=200 + i % 5,
+                nozzle_target_temp=220,
+                nozzle_temp_left=180 + i % 3,
+                nozzle_target_temp_left=190,
+                bed_temp=60,
+                bed_target_temp=60,
+                print_percent=i % 100,
+                gcode_state="RUNNING",
+                print_type="local",
+                subtask_name="job",
+            )
+            for i in range(count)
+        ]
+    )
+    FilamentSnapshot.objects.bulk_create(
+        [
+            FilamentSnapshot(
+                printer_metric=m,
+                tray_id=str(tray),
+                type="PLA",
+                sub_type="Bambu",
+                color="FF0000FF",
+                remain_percent=80,
+            )
+            for m in metrics
+            for tray in range(snapshots_per_metric)
+        ]
+    )
+    return metrics
+
+
+# --- Root cause 1: deferred-field N+1 in the API -----------------------------
+
+
+def _count_queries(client, url, params=None):
+    from django.db import connection
+    from django.test.utils import CaptureQueriesContext
+
+    with CaptureQueriesContext(connection) as ctx:
+        resp = client.get(url, params or {})
+    assert resp.status_code == 200
+    return len(ctx)
+
+
+@pytest.mark.django_db
+def test_api_query_count_is_independent_of_row_count(logged_in_client, printer):
+    """Every field the serializer reads must be in .only(), or Django emits one
+    extra SELECT per row per missing field — making query count scale with data."""
+    today = timezone.localtime().date()
+    url = reverse("bambu_run:printer_api")
+    params = {
+        "start_date": str(today - timedelta(days=1)),
+        "end_date": str(today),
+        "start_time": "00:00",
+        "end_time": "23:59",
+    }
+
+    _make_metrics(printer, 10)
+    few = _count_queries(logged_in_client, url, params)
+
+    _make_metrics(printer, 190)
+    many = _count_queries(logged_in_client, url, params)
+
+    assert few == many, f"query count scales with rows: {few} -> {many}"
+
+
+@pytest.mark.django_db
+def test_api_returns_dual_nozzle_values(logged_in_client, printer):
+    """The left-nozzle fields must survive the .only() narrowing."""
+    _make_metrics(printer, 5)
+    today = timezone.localtime().date()
+
+    resp = logged_in_client.get(
+        reverse("bambu_run:printer_api"),
+        {
+            "start_date": str(today - timedelta(days=1)),
+            "end_date": str(today),
+            "start_time": "00:00",
+            "end_time": "23:59",
+        },
+    )
+
+    data = resp.json()
+    assert any(v is not None for v in data["nozzle_temp_left"])
+    assert any(v is not None for v in data["nozzle_target_temp_left"])
+
+
+# --- Root cause: unbounded query when date params are missing ----------------
+
+
+@pytest.mark.django_db
+def test_api_without_params_is_time_bounded(logged_in_client, printer):
+    """A bare API call must not scan the whole table — it defaults to 24h."""
+    _make_metrics(printer, 10, spacing_seconds=30)  # inside 24h
+    old = PrinterMetrics.objects.create(
+        device=printer, timestamp=timezone.now() - timedelta(days=30), nozzle_temp=100
+    )
+
+    resp = logged_in_client.get(reverse("bambu_run:printer_api"))
+
+    data = resp.json()
+    assert len(data["timestamps"]) == 10
+    assert old.timestamp.isoformat() not in data["timestamps_iso"]
+
+
+@pytest.mark.django_db
+def test_api_with_only_start_date_is_time_bounded(logged_in_client, printer):
+    """Partial params must not drop the upper bound and scan forever."""
+    _make_metrics(printer, 5)
+    today = timezone.localtime().date()
+
+    resp = logged_in_client.get(
+        reverse("bambu_run:printer_api"), {"start_date": str(today - timedelta(days=1))}
+    )
+
+    assert resp.status_code == 200
+    assert len(resp.json()["timestamps"]) == 5
+
+
+@pytest.mark.django_db
+def test_api_downsamples_above_max_chart_points(logged_in_client, printer, monkeypatch):
+    monkeypatch.setattr("bambu_run.views._MAX_CHART_POINTS", 10)
+    _make_metrics(printer, 40, snapshots_per_metric=1, spacing_seconds=30)
+    today = timezone.localtime().date()
+
+    resp = logged_in_client.get(
+        reverse("bambu_run:printer_api"),
+        {
+            "start_date": str(today - timedelta(days=1)),
+            "end_date": str(today),
+            "start_time": "00:00",
+            "end_time": "23:59",
+        },
+    )
+
+    assert 0 < len(resp.json()["timestamps"]) <= 10
+
+
+# --- Root cause 2: the dashboard render -------------------------------------
+
+
+@pytest.mark.django_db
+def test_dashboard_query_count_is_independent_of_row_count(logged_in_client, printer):
+    url = reverse("bambu_run:printer_dashboard")
+
+    _make_metrics(printer, 10)
+    few = _count_queries(logged_in_client, url)
+
+    _make_metrics(printer, 190)
+    many = _count_queries(logged_in_client, url)
+
+    assert few == many, f"query count scales with rows: {few} -> {many}"
+
+
+@pytest.mark.django_db
+def test_dashboard_downsamples_chart_payload(logged_in_client, printer, monkeypatch):
+    """The dashboard inlines its JSON into the HTML, so it must sample like the API."""
+    monkeypatch.setattr("bambu_run.views._MAX_CHART_POINTS", 10)
+    _make_metrics(printer, 60, snapshots_per_metric=1)
+
+    resp = logged_in_client.get(reverse("bambu_run:printer_dashboard"))
+    payload = json.loads(resp.context["printer_data_json"])
+
+    assert 0 < len(payload["timestamps"]) <= 10
+
+
+@pytest.mark.django_db
+def test_dashboard_stats_use_the_newest_metric(logged_in_client, printer):
+    """Sampling must never drop the latest reading — the stat cards depend on it."""
+    import zoneinfo
+
+    from bambu_run.conf import app_settings
+
+    _make_metrics(printer, 20)
+    newest = PrinterMetrics.objects.create(
+        device=printer, timestamp=timezone.now(), nozzle_temp=242, gcode_state="RUNNING"
+    )
+
+    resp = logged_in_client.get(reverse("bambu_run:printer_dashboard"))
+
+    assert resp.context["stats"]["nozzle_temp"] == pytest.approx(242)
+    assert resp.context["stats"]["timestamp"] == newest.timestamp.astimezone(
+        zoneinfo.ZoneInfo(app_settings.TIMEZONE)
+    ).strftime("%Y-%m-%d %H:%M:%S")
+
+
+@pytest.mark.django_db
+def test_dashboard_filament_timeline_aligns_with_timestamps(logged_in_client, printer):
+    """remain_data must stay index-aligned with timestamps after sampling."""
+    _make_metrics(printer, 30, snapshots_per_metric=2)
+
+    resp = logged_in_client.get(reverse("bambu_run:printer_dashboard"))
+    payload = json.loads(resp.context["printer_data_json"])
+
+    n = len(payload["timestamps"])
+    assert payload["filament_timeline"]
+    for series in payload["filament_timeline"].values():
+        assert len(series["remain_data"]) == n