560 lines
27 KiB
Python
560 lines
27 KiB
Python
from copy import deepcopy
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from datetime import timedelta
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import logging
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from django.conf import settings
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from django.db import OperationalError, ProgrammingError, transaction
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from django.utils import timezone
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from external_api_adapter import request as external_api_request
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from external_api_adapter.exceptions import ExternalAPIRequestError
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from notifications.services import create_notification_for_farm_uuid
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from .mock_data import ANOMALY_DETECTION_CARD, AVG_SOIL_MOISTURE, SENSOR_COMPARISON_CHART, SENSOR_RADAR_CHART, SENSOR_VALUES_LIST, SOIL_MOISTURE_HEATMAP
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from .models import FarmSensor, SensorExternalRequestLog
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logger = logging.getLogger(__name__)
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class FarmDataForwardError(Exception):
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pass
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SENSOR_FIELDS = [
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{"id": "soil_moisture", "label": "رطوبت خاک", "unit": "%", "payload_keys": ("soil_moisture", "soilMoisture", "moisture"), "ideal_min": 45.0, "ideal_max": 65.0, "radar_label": "رطوبت"},
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{"id": "soil_temperature", "label": "دمای خاک", "unit": "°C", "payload_keys": ("soil_temperature", "soilTemperature", "temperature"), "ideal_min": 18.0, "ideal_max": 28.0, "radar_label": "دما"},
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{"id": "soil_ph", "label": "pH خاک", "unit": "pH", "payload_keys": ("soil_ph", "soilPh", "ph"), "ideal_min": 6.0, "ideal_max": 7.5, "radar_label": "pH"},
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{"id": "electrical_conductivity", "label": "هدایت الکتریکی", "unit": "dS/m", "payload_keys": ("electrical_conductivity", "electricalConductivity", "ec"), "ideal_min": 0.8, "ideal_max": 1.8, "radar_label": "EC"},
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{"id": "nitrogen", "label": "نیتروژن", "unit": "mg/kg", "payload_keys": ("nitrogen", "n"), "ideal_min": 20.0, "ideal_max": 40.0, "radar_label": "نیتروژن"},
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{"id": "phosphorus", "label": "فسفر", "unit": "mg/kg", "payload_keys": ("phosphorus", "p"), "ideal_min": 10.0, "ideal_max": 25.0, "radar_label": "فسفر"},
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{"id": "potassium", "label": "پتاسیم", "unit": "mg/kg", "payload_keys": ("potassium", "k"), "ideal_min": 15.0, "ideal_max": 35.0, "radar_label": "پتاسیم"},
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]
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MAX_HISTORY_ITEMS = 20
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MAX_CHART_POINTS = 7
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COMPARISON_CHART_RANGES = {"7d": 7, "30d": 30}
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VALUES_LIST_RANGES = {"1h": timedelta(hours=1), "24h": timedelta(hours=24), "7d": timedelta(days=7)}
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RADAR_CHART_RANGES = {"today": timedelta(days=1), "7d": timedelta(days=7), "30d": timedelta(days=30)}
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PERSIAN_WEEKDAYS = {0: "دوشنبه", 1: "سه شنبه", 2: "چهارشنبه", 3: "پنج شنبه", 4: "جمعه", 5: "شنبه", 6: "یکشنبه"}
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COMPARISON_CHART_FIELD_ALIASES = {"soil_moisture": "moisture", "soilMoisture": "moisture", "moisture": "moisture", "soil_temperature": "temperature", "soilTemperature": "temperature", "temperature": "temperature", "humidity": "humidity", "soil_ph": "ph", "soilPh": "ph", "ph": "ph", "electrical_conductivity": "ec", "electricalConductivity": "ec", "ec": "ec", "nitrogen": "nitrogen", "n": "nitrogen", "phosphorus": "phosphorus", "p": "phosphorus", "potassium": "potassium", "k": "potassium"}
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COMPARISON_CHART_PRIMARY_FIELDS = ("moisture", "temperature", "humidity", "ph", "ec", "nitrogen", "phosphorus", "potassium")
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VALUES_LIST_FIELDS = [("moisture", "Moisture", "%"), ("temperature", "Temperature", "°C"), ("humidity", "Humidity", "%"), ("ph", "pH", "pH"), ("ec", "EC", "dS/m"), ("nitrogen", "Nitrogen", "mg/kg"), ("phosphorus", "Phosphorus", "mg/kg"), ("potassium", "Potassium", "mg/kg")]
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RADAR_CHART_FIELDS = [("moisture", "Moisture", 60.0), ("temperature", "Temperature", 26.0), ("humidity", "Humidity", 55.0), ("ph", "PH", 6.5), ("ec", "EC", 1.3), ("nitrogen", "Nitrogen", 42.0), ("potassium", "Potassium", 38.0)]
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def get_sensor_external_request_logs_for_farm(*, farm_uuid, physical_device_uuid=None, sensor_type=None, date_from=None, date_to=None):
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try:
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queryset = SensorExternalRequestLog.objects.filter(farm_uuid=farm_uuid)
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if physical_device_uuid:
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queryset = queryset.filter(physical_device_uuid=physical_device_uuid)
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if sensor_type:
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physical_device_uuids = FarmSensor.objects.filter(farm__farm_uuid=farm_uuid, sensor_type=sensor_type).values_list("physical_device_uuid", flat=True)
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queryset = queryset.filter(physical_device_uuid__in=physical_device_uuids)
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if date_from:
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queryset = queryset.filter(created_at__date__gte=date_from)
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if date_to:
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queryset = queryset.filter(created_at__date__lte=date_to)
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return queryset.order_by("-created_at", "-id")
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except (ProgrammingError, OperationalError) as exc:
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raise ValueError("Sensor external API tables are not migrated.") from exc
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def get_farm_sensor_map_for_logs(*, logs):
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try:
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logs = list(logs)
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if not logs:
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return {}
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farm_sensor_queryset = FarmSensor.objects.select_related("farm", "sensor_catalog").filter(
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farm__farm_uuid__in={log.farm_uuid for log in logs},
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physical_device_uuid__in={log.physical_device_uuid for log in logs},
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).order_by("-created_at", "-id")
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farm_sensor_map = {}
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for farm_sensor in farm_sensor_queryset:
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exact_key = (farm_sensor.farm.farm_uuid, farm_sensor.sensor_catalog.uuid if farm_sensor.sensor_catalog else None, farm_sensor.physical_device_uuid)
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fallback_key = (farm_sensor.farm.farm_uuid, None, farm_sensor.physical_device_uuid)
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farm_sensor_map.setdefault(exact_key, farm_sensor)
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farm_sensor_map.setdefault(fallback_key, farm_sensor)
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return farm_sensor_map
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except (ProgrammingError, OperationalError) as exc:
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raise ValueError("Sensor external API tables are not migrated.") from exc
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def get_latest_sensor_external_request_log(*, farm_uuid, sensor_catalog_uuid, physical_device_uuid):
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try:
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return SensorExternalRequestLog.objects.filter(farm_uuid=farm_uuid, sensor_catalog_uuid=sensor_catalog_uuid, physical_device_uuid=physical_device_uuid).order_by("-created_at", "-id").first()
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except (ProgrammingError, OperationalError) as exc:
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raise ValueError("Sensor external API tables are not migrated.") from exc
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def create_sensor_external_notification(*, physical_device_uuid, payload=None):
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payload = payload or {}
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sensor = FarmSensor.objects.select_related("farm", "farm__current_crop_area", "sensor_catalog").filter(physical_device_uuid=physical_device_uuid).first()
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if sensor is None:
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raise ValueError("Physical device not found.")
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try:
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with transaction.atomic():
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SensorExternalRequestLog.objects.create(
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farm_uuid=sensor.farm.farm_uuid,
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sensor_catalog_uuid=sensor.sensor_catalog.uuid if sensor.sensor_catalog else None,
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physical_device_uuid=sensor.physical_device_uuid,
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payload=payload,
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)
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return create_notification_for_farm_uuid(
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farm_uuid=sensor.farm.farm_uuid,
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title="Sensor external API request",
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message=f"Payload received from device {sensor.physical_device_uuid}.",
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level="info",
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metadata={"farm_uuid": str(sensor.farm.farm_uuid), "sensor_catalog_uuid": str(sensor.sensor_catalog.uuid) if sensor.sensor_catalog else None, "physical_device_uuid": str(sensor.physical_device_uuid), "payload": payload},
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)
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except (ProgrammingError, OperationalError) as exc:
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raise ValueError("Sensor external API tables are not migrated.") from exc
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def forward_sensor_payload_to_farm_data(*, physical_device_uuid, payload=None):
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payload = payload or {}
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sensor = FarmSensor.objects.select_related("farm", "farm__current_crop_area", "sensor_catalog").filter(physical_device_uuid=physical_device_uuid).first()
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if sensor is None:
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raise ValueError("Physical device not found.")
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farm_boundary = _get_farm_boundary(sensor=sensor)
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api_key = getattr(settings, "FARM_DATA_API_KEY", "")
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if not api_key:
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raise FarmDataForwardError("FARM_DATA_API_KEY is not configured.")
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sensor_key = _get_sensor_key(sensor=sensor)
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normalized_sensor_payload = _normalize_sensor_payload(sensor_key=sensor_key, sensor_payload=payload)
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request_payload = {"farm_uuid": str(sensor.farm.farm_uuid), "farm_boundary": farm_boundary, "sensor_key": sensor_key, "sensor_payload": normalized_sensor_payload}
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try:
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response = external_api_request(
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"ai",
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_get_farm_data_path(),
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method="POST",
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payload=request_payload,
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headers={"Accept": "application/json", "Content-Type": "application/json", "X-API-Key": api_key, "Authorization": f"Api-Key {api_key}"},
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)
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except ExternalAPIRequestError as exc:
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raise FarmDataForwardError(f"Farm data API request failed: {exc}") from exc
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if response.status_code >= 400:
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raise FarmDataForwardError(f"Farm data API returned status {response.status_code}: {response.data}")
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return request_payload
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def _get_farm_boundary(*, sensor):
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crop_area = sensor.farm.current_crop_area or sensor.farm.crop_areas.order_by("-created_at", "-id").first()
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if crop_area is None:
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raise FarmDataForwardError("Farm boundary is not configured for this farm.")
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geometry = crop_area.geometry or {}
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if geometry.get("type") == "Feature":
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geometry = geometry.get("geometry") or {}
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if geometry.get("type") != "Polygon":
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raise FarmDataForwardError("Farm boundary geometry must be a Polygon.")
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return geometry
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def _normalize_sensor_payload(*, sensor_key, sensor_payload):
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if not sensor_payload:
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return {}
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if not isinstance(sensor_payload, dict):
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raise FarmDataForwardError("`payload` must be a JSON object.")
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if all(isinstance(value, dict) for value in sensor_payload.values()):
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return sensor_payload
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return {sensor_key: sensor_payload}
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def _get_sensor_key(*, sensor):
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if sensor.sensor_catalog and sensor.sensor_catalog.code:
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return sensor.sensor_catalog.code
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return "sensor-7-1"
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def _get_farm_data_path():
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return getattr(settings, "FARM_DATA_API_PATH", "/api/farm-data/")
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def _to_float(value):
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if value is None or isinstance(value, bool):
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return None
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try:
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return float(value)
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except (TypeError, ValueError):
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return None
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def _extract_payload(payload):
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if not isinstance(payload, dict):
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return {}
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if isinstance(payload.get("payload"), dict):
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payload = payload["payload"]
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if isinstance(payload.get("data"), dict):
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nested = payload["data"]
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if any(any(key in nested for key in field["payload_keys"]) for field in SENSOR_FIELDS):
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payload = nested
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return payload
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def _extract_numeric_payload(payload):
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payload = _extract_payload(payload)
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return {key: numeric_value for key, value in payload.items() if (numeric_value := _to_float(value)) is not None}
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def _extract_readings(payload):
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payload = _extract_payload(payload)
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readings = {}
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for field in SENSOR_FIELDS:
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for key in field["payload_keys"]:
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value = _to_float(payload.get(key))
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if value is not None:
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readings[field["id"]] = value
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break
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return readings
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def _format_number(value):
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if value is None:
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return ""
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if float(value).is_integer():
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return str(int(value))
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return f"{value:.1f}".rstrip("0").rstrip(".")
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def _format_value(value, unit):
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number = _format_number(value)
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if not number:
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return number
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if unit in {"", "pH"}:
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return number
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if unit in {"%", "°C"}:
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return f"{number}{unit}"
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return f"{number} {unit}"
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def _format_range(field):
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lower = _format_number(field["ideal_min"])
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upper = _format_number(field["ideal_max"])
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if field["unit"] in {"", "pH"}:
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return f"{lower}-{upper}"
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return f"{lower}-{upper} {field['unit']}"
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def get_primary_soil_sensor(*, farm):
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soil_sensors = list(farm.sensors.select_related("sensor_catalog").order_by("created_at", "id"))
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def _sensor_priority(sensor):
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sensor_type = (sensor.sensor_type or "").lower()
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catalog_code = (sensor.sensor_catalog.code if sensor.sensor_catalog else "").lower()
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catalog_name = (sensor.sensor_catalog.name if sensor.sensor_catalog else "").lower()
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sensor_name = (sensor.name or "").lower()
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haystack = " ".join([sensor_type, catalog_code, catalog_name, sensor_name])
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if "sensor-7-in-1" in catalog_code or "soil_7_in_1" in sensor_type:
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return 0
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if "7 in 1" in haystack or "7-in-1" in haystack or "7in1" in haystack:
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return 1
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if "soil" in haystack:
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return 2
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return 3
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prioritized_sensors = sorted(soil_sensors, key=_sensor_priority)
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if prioritized_sensors and _sensor_priority(prioritized_sensors[0]) < 3:
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return prioritized_sensors[0]
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return soil_sensors[0] if soil_sensors else None
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def _get_sensor_context(farm=None):
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if farm is None:
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return None
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primary_sensor = get_primary_soil_sensor(farm=farm)
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if primary_sensor is None:
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return None
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try:
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logs_queryset = get_sensor_external_request_logs_for_farm(farm_uuid=farm.farm_uuid, physical_device_uuid=primary_sensor.physical_device_uuid)
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except ValueError:
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return None
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history = []
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for log in logs_queryset[:MAX_HISTORY_ITEMS]:
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readings = _extract_readings(log.payload)
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if readings:
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history.append((log, readings))
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if not history:
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return None
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latest_log, latest_readings = history[0]
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farm_sensor_map = get_farm_sensor_map_for_logs(logs=[latest_log])
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farm_sensor = farm_sensor_map.get((latest_log.farm_uuid, latest_log.sensor_catalog_uuid, latest_log.physical_device_uuid)) or primary_sensor
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return {"farm_sensor": farm_sensor, "latest_log": latest_log, "latest_readings": latest_readings, "previous_readings": history[1][1] if len(history) > 1 else {}, "history": history}
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def _build_sensor_meta(context, fallback_sensor):
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sensor = deepcopy(fallback_sensor)
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if not context:
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return sensor
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farm_sensor = context.get("farm_sensor")
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latest_log = context["latest_log"]
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sensor["physicalDeviceUuid"] = str(latest_log.physical_device_uuid)
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sensor["updatedAt"] = latest_log.created_at.isoformat()
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if farm_sensor is not None:
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sensor["name"] = farm_sensor.name or sensor["name"]
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if farm_sensor.sensor_catalog is not None:
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sensor["sensorCatalogCode"] = farm_sensor.sensor_catalog.code
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return sensor
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def _calculate_status_chip(value):
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if value is None:
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return ("نامشخص", "secondary", "secondary")
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if value >= 60:
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return ("بهینه", "success", "primary")
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if value >= 45:
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return ("متوسط", "warning", "warning")
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return ("کم", "error", "error")
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def get_sensor_7_in_1_values_list_data(farm=None, context=None):
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data = deepcopy(SENSOR_VALUES_LIST)
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context = _get_sensor_context(farm) if context is None else context
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data["sensor"] = _build_sensor_meta(context, data["sensor"])
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if not context:
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return data
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latest_readings = context["latest_readings"]
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previous_readings = context["previous_readings"]
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sensors = []
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for field in SENSOR_FIELDS:
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value = latest_readings.get(field["id"])
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if value is None:
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continue
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previous = previous_readings.get(field["id"])
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change = 0.0 if previous is None else round(value - previous, 2)
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sensors.append({"id": field["id"], "title": _format_value(value, field["unit"]), "subtitle": field["label"], "trendNumber": abs(change), "trend": "positive" if change >= 0 else "negative", "unit": field["unit"]})
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if sensors:
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data["sensors"] = sensors
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return data
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def get_sensor_7_in_1_avg_soil_moisture_data(farm=None, context=None):
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data = deepcopy(AVG_SOIL_MOISTURE)
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context = _get_sensor_context(farm) if context is None else context
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if not context:
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return data
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moisture = context["latest_readings"].get("soil_moisture")
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if moisture is None:
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return data
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chip_text, chip_color, avatar_color = _calculate_status_chip(moisture)
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data["stats"] = _format_value(moisture, "%")
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data["chipText"] = chip_text
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data["chipColor"] = chip_color
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data["avatarColor"] = avatar_color
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return data
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def _score_field(value, field):
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min_value = field["ideal_min"]
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max_value = field["ideal_max"]
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midpoint = (min_value + max_value) / 2
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half_span = max((max_value - min_value) / 2, 0.1)
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distance = abs(value - midpoint)
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if min_value <= value <= max_value:
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return round(max(80.0, 100.0 - ((distance / half_span) * 20.0)), 1)
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overflow = max(0.0, distance - half_span)
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return round(max(0.0, 80.0 - ((overflow / half_span) * 80.0)), 1)
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def get_sensor_7_in_1_radar_chart_data(farm=None, context=None):
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data = deepcopy(SENSOR_RADAR_CHART)
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context = _get_sensor_context(farm) if context is None else context
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if not context:
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return data
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latest_readings = context["latest_readings"]
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scores, labels = [], []
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for field in SENSOR_FIELDS:
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value = latest_readings.get(field["id"])
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if value is None:
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continue
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labels.append(field["radar_label"])
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scores.append(_score_field(value, field))
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if labels:
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data["labels"] = labels
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data["series"] = [{"name": "اکنون", "data": scores}, {"name": "هدف", "data": [100.0] * len(labels)}]
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return data
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def get_sensor_7_in_1_comparison_chart_data(farm=None, context=None):
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data = deepcopy(SENSOR_COMPARISON_CHART)
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context = _get_sensor_context(farm) if context is None else context
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if not context:
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return data
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history = list(reversed(context["history"][:MAX_CHART_POINTS]))
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moisture_points = [(log.created_at.strftime("%m/%d %H:%M"), readings.get("soil_moisture")) for log, readings in history if readings.get("soil_moisture") is not None]
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if not moisture_points:
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return data
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categories = [item[0] for item in moisture_points]
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values = [round(item[1], 2) for item in moisture_points]
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current_value = values[-1]
|
|
baseline_value = values[0] if len(values) > 1 else 55.0
|
|
percent_change = ((current_value - baseline_value) / baseline_value) * 100 if baseline_value else 0.0
|
|
data["currentValue"] = round(current_value, 2)
|
|
data["vsLastWeekValue"] = round(percent_change, 2)
|
|
data["vsLastWeek"] = f"{percent_change:+.1f}%"
|
|
data["categories"] = categories
|
|
data["series"] = [{"name": "رطوبت خاک", "data": values}, {"name": "بازه هدف", "data": [55.0] * len(values)}]
|
|
return data
|
|
|
|
|
|
def _build_anomaly_item(field, value):
|
|
lower = field["ideal_min"]
|
|
upper = field["ideal_max"]
|
|
if lower <= value <= upper:
|
|
return None
|
|
deviation = value - upper if value > upper else value - lower
|
|
severity = "warning"
|
|
span = max(upper - lower, 0.1)
|
|
if abs(deviation) >= span * 0.5:
|
|
severity = "error"
|
|
sign = "+" if deviation > 0 else ""
|
|
return {"sensor": field["label"], "value": _format_value(value, field["unit"]), "expected": _format_range(field), "deviation": f"{sign}{_format_value(deviation, field['unit'])}", "severity": severity}
|
|
|
|
|
|
def get_sensor_7_in_1_anomaly_detection_card_data(farm=None, context=None):
|
|
data = deepcopy(ANOMALY_DETECTION_CARD)
|
|
context = _get_sensor_context(farm) if context is None else context
|
|
if not context:
|
|
return data
|
|
anomalies = []
|
|
for field in SENSOR_FIELDS:
|
|
value = context["latest_readings"].get(field["id"])
|
|
if value is None:
|
|
continue
|
|
anomaly = _build_anomaly_item(field, value)
|
|
if anomaly is not None:
|
|
anomalies.append(anomaly)
|
|
data["anomalies"] = anomalies or [{"sensor": "سنسور 7 در 1 خاک", "value": "نرمال", "expected": "تمام شاخصها در بازه مجاز هستند", "deviation": "0", "severity": "success"}]
|
|
return data
|
|
|
|
|
|
def get_sensor_7_in_1_soil_moisture_heatmap_data(farm=None, context=None):
|
|
data = deepcopy(SOIL_MOISTURE_HEATMAP)
|
|
context = _get_sensor_context(farm) if context is None else context
|
|
if not context:
|
|
return data
|
|
history = list(reversed(context["history"][:MAX_CHART_POINTS]))
|
|
chart_points = [{"x": log.created_at.strftime("%H:%M"), "y": round(readings.get("soil_moisture"), 2)} for log, readings in history if readings.get("soil_moisture") is not None]
|
|
if not chart_points:
|
|
return data
|
|
sensor_name = data["zones"][0]
|
|
farm_sensor = context.get("farm_sensor")
|
|
if farm_sensor is not None and farm_sensor.name:
|
|
sensor_name = farm_sensor.name
|
|
data["zones"] = [sensor_name]
|
|
data["hours"] = [point["x"] for point in chart_points]
|
|
data["series"] = [{"name": sensor_name, "data": chart_points}]
|
|
return data
|
|
|
|
|
|
def get_sensor_7_in_1_summary_data(farm=None):
|
|
context = _get_sensor_context(farm)
|
|
values_list = get_sensor_7_in_1_values_list_data(farm, context=context)
|
|
return {"sensor": values_list["sensor"], "sensorValuesList": values_list, "avgSoilMoisture": get_sensor_7_in_1_avg_soil_moisture_data(farm, context=context), "sensorRadarChart": get_sensor_7_in_1_radar_chart_data(farm, context=context), "sensorComparisonChart": get_sensor_7_in_1_comparison_chart_data(farm, context=context), "anomalyDetectionCard": get_sensor_7_in_1_anomaly_detection_card_data(farm, context=context), "soilMoistureHeatmap": get_sensor_7_in_1_soil_moisture_heatmap_data(farm, context=context)}
|
|
|
|
|
|
def _normalize_comparison_chart_field(field_name):
|
|
return COMPARISON_CHART_FIELD_ALIASES.get(field_name, field_name)
|
|
|
|
|
|
def _format_comparison_category(bucket_date, range_value):
|
|
return PERSIAN_WEEKDAYS[bucket_date.weekday()] if range_value == "7d" else bucket_date.strftime("%m/%d")
|
|
|
|
|
|
def _format_percent_change(current_value, baseline_value):
|
|
if not baseline_value:
|
|
return "+0.0%"
|
|
return f"{((current_value - baseline_value) / baseline_value) * 100:+.1f}%"
|
|
|
|
|
|
def _format_current_value_subtitle(title, value, unit):
|
|
rendered_value = _format_value(value, unit)
|
|
return f"مقدار فعلی: {rendered_value or title}"
|
|
|
|
|
|
def get_sensor_comparison_chart_data(*, farm, physical_device_uuid, range_value):
|
|
days = COMPARISON_CHART_RANGES[range_value]
|
|
start_date = timezone.localdate() - timedelta(days=days - 1)
|
|
try:
|
|
logs_queryset = get_sensor_external_request_logs_for_farm(farm_uuid=farm.farm_uuid, physical_device_uuid=physical_device_uuid, date_from=start_date)
|
|
except ValueError:
|
|
return {"series": [], "categories": [], "currentValue": 0.0, "vsLastWeek": "+0.0%"}
|
|
grouped_logs = {}
|
|
for log in reversed(list(logs_queryset[: days * 24])):
|
|
bucket_date = timezone.localtime(log.created_at).date()
|
|
numeric_payload = _extract_numeric_payload(log.payload)
|
|
if numeric_payload:
|
|
grouped_logs[bucket_date] = numeric_payload
|
|
if not grouped_logs:
|
|
return {"series": [], "categories": [], "currentValue": 0.0, "vsLastWeek": "+0.0%"}
|
|
sorted_dates = sorted(grouped_logs.keys())
|
|
categories = [_format_comparison_category(bucket_date, range_value) for bucket_date in sorted_dates]
|
|
series_map = {}
|
|
for bucket_date in sorted_dates:
|
|
normalized_payload = {_normalize_comparison_chart_field(key): value for key, value in grouped_logs[bucket_date].items()}
|
|
for key, value in normalized_payload.items():
|
|
series_map.setdefault(key, []).append(round(value, 2))
|
|
ordered_field_names = [field_name for field_name in COMPARISON_CHART_PRIMARY_FIELDS if field_name in series_map] + sorted(field_name for field_name in series_map if field_name not in COMPARISON_CHART_PRIMARY_FIELDS)
|
|
series = [{"name": field_name, "data": series_map[field_name]} for field_name in ordered_field_names]
|
|
primary_data = series_map[ordered_field_names[0]]
|
|
return {"series": series, "categories": categories, "currentValue": round(primary_data[-1], 2), "vsLastWeek": _format_percent_change(primary_data[-1], primary_data[0])}
|
|
|
|
|
|
def get_sensor_values_list_data(*, farm, physical_device_uuid, range_value):
|
|
start_time = timezone.now() - VALUES_LIST_RANGES[range_value]
|
|
try:
|
|
logs_queryset = get_sensor_external_request_logs_for_farm(farm_uuid=farm.farm_uuid, physical_device_uuid=physical_device_uuid)
|
|
except ValueError:
|
|
return {"sensors": []}
|
|
logs = list(logs_queryset.filter(created_at__gte=start_time).order_by("created_at", "id"))
|
|
if not logs:
|
|
latest_log = logs_queryset.order_by("-created_at", "-id").first()
|
|
if latest_log is None:
|
|
return {"sensors": []}
|
|
logs = [latest_log]
|
|
earliest_payload, latest_payload = {}, {}
|
|
for log in logs:
|
|
numeric_payload = {_normalize_comparison_chart_field(key): value for key, value in _extract_numeric_payload(log.payload).items()}
|
|
if not numeric_payload:
|
|
continue
|
|
if not earliest_payload:
|
|
earliest_payload = numeric_payload
|
|
latest_payload = numeric_payload
|
|
if not latest_payload:
|
|
return {"sensors": []}
|
|
sensors = []
|
|
for field_name, title, unit in VALUES_LIST_FIELDS:
|
|
current_value = latest_payload.get(field_name)
|
|
if current_value is None:
|
|
continue
|
|
previous_value = earliest_payload.get(field_name, current_value)
|
|
delta = round(current_value - previous_value, 2)
|
|
sensors.append({"title": title, "subtitle": _format_current_value_subtitle(title, current_value, unit), "trendNumber": abs(delta), "trend": "positive" if delta >= 0 else "negative", "unit": unit})
|
|
return {"sensors": sensors}
|
|
|
|
|
|
def get_sensor_radar_chart_data(*, farm, physical_device_uuid, range_value):
|
|
start_time = timezone.now() - RADAR_CHART_RANGES[range_value]
|
|
try:
|
|
logs_queryset = get_sensor_external_request_logs_for_farm(farm_uuid=farm.farm_uuid, physical_device_uuid=physical_device_uuid)
|
|
except ValueError:
|
|
return {"labels": [], "series": []}
|
|
logs = list(logs_queryset.filter(created_at__gte=start_time).order_by("created_at", "id"))
|
|
if not logs:
|
|
latest_log = logs_queryset.order_by("-created_at", "-id").first()
|
|
if latest_log is None:
|
|
return {"labels": [], "series": []}
|
|
logs = [latest_log]
|
|
latest_payload = {}
|
|
for log in logs:
|
|
numeric_payload = {_normalize_comparison_chart_field(key): value for key, value in _extract_numeric_payload(log.payload).items()}
|
|
if numeric_payload:
|
|
latest_payload = numeric_payload
|
|
if not latest_payload:
|
|
return {"labels": [], "series": []}
|
|
labels, current_data, ideal_data = [], [], []
|
|
for field_name, label, ideal_value in RADAR_CHART_FIELDS:
|
|
current_value = latest_payload.get(field_name)
|
|
if current_value is None:
|
|
continue
|
|
labels.append(label)
|
|
current_data.append(round(current_value, 2))
|
|
ideal_data.append(round(ideal_value, 2))
|
|
return {"labels": labels, "series": [{"name": "وضعیت فعلی", "data": current_data}, {"name": "بازه ایده آل", "data": ideal_data}]}
|