sajad-dev/Backend
1
0
Fork 0
Code Issues Pull Requests Actions Packages Projects Releases Wiki Activity

UPDATE

Browse Source
This commit is contained in:
Mohammad Sajad Pourajam
2026-04-29 01:27:16 +03:30
parent a75c4ca9c8
commit f0f2ac34b7
20 changed files with 2840 additions and 65 deletions
Download Patch File Download Diff File Expand all files Collapse all files
sensor_7_in_1/services.py
+288 -20
View File
@@ -1,6 +1,8 @@
from copy import deepcopy
from datetime import timedelta
from sensor_external_api.services import get_farm_sensor_map_for_logs, get_sensor_external_request_logs_for_farm
from django.utils import timezone
from .mock_data import (
ANOMALY_DETECTION_CARD,
@@ -81,6 +83,59 @@ SENSOR_FIELDS = [
MIN_REQUIRED_SENSOR_FIELDS = 4
MAX_HISTORY_ITEMS = 20
MAX_CHART_POINTS = 7
COMPARISON_CHART_RANGES = {"7d": 7, "30d": 30}
VALUES_LIST_RANGES = {"1h": timedelta(hours=1), "24h": timedelta(hours=24), "7d": timedelta(days=7)}
RADAR_CHART_RANGES = {"today": timedelta(days=1), "7d": timedelta(days=7), "30d": timedelta(days=30)}
PERSIAN_WEEKDAYS = {
0: "دوشنبه",
1: "سه شنبه",
2: "چهارشنبه",
3: "پنج شنبه",
4: "جمعه",
5: "شنبه",
6: "یکشنبه",
}
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",
}
COMPARISON_CHART_PRIMARY_FIELDS = ("moisture", "temperature", "humidity", "ph", "ec", "nitrogen", "phosphorus", "potassium")
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"),
]
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),
]
def _to_float(value):
@@ -107,6 +162,16 @@ def _extract_payload(payload):
return payload
def _extract_numeric_payload(payload):
payload = _extract_payload(payload)
numeric_payload = {}
for key, value in payload.items():
numeric_value = _to_float(value)
if numeric_value is not None:
numeric_payload[key] = numeric_value
return numeric_payload
def _extract_readings(payload):
payload = _extract_payload(payload)
readings = {}
@@ -151,46 +216,69 @@ def _get_sensor_context(farm=None):
if farm is None:
return None
primary_sensor = get_primary_soil_sensor(farm=farm)
if primary_sensor is None:
return None
try:
logs_queryset = get_sensor_external_request_logs_for_farm(farm_uuid=farm.farm_uuid)
logs_queryset = get_sensor_external_request_logs_for_farm(
farm_uuid=farm.farm_uuid,
physical_device_uuid=primary_sensor.physical_device_uuid,
)
except ValueError:
return None
candidate_log = None
candidate_readings = {}
for log in logs_queryset[:MAX_HISTORY_ITEMS]:
readings = _extract_readings(log.payload)
if len(readings) >= MIN_REQUIRED_SENSOR_FIELDS:
candidate_log = log
candidate_readings = readings
break
if candidate_log is None:
return None
history = []
for log in logs_queryset.filter(physical_device_uuid=candidate_log.physical_device_uuid)[:MAX_HISTORY_ITEMS]:
for log in logs_queryset[:MAX_HISTORY_ITEMS]:
readings = _extract_readings(log.payload)
if readings:
history.append((log, readings))
if not history:
history = [(candidate_log, candidate_readings)]
return None
farm_sensor_map = get_farm_sensor_map_for_logs(logs=[candidate_log])
latest_log, latest_readings = history[0]
farm_sensor_map = get_farm_sensor_map_for_logs(logs=[latest_log])
farm_sensor = farm_sensor_map.get(
(candidate_log.farm_uuid, candidate_log.sensor_catalog_uuid, candidate_log.physical_device_uuid)
)
(latest_log.farm_uuid, latest_log.sensor_catalog_uuid, latest_log.physical_device_uuid)
) or primary_sensor
return {
"farm_sensor": farm_sensor,
"latest_log": history[0][0],
"latest_readings": history[0][1],
"latest_log": latest_log,
"latest_readings": latest_readings,
"previous_readings": history[1][1] if len(history) > 1 else {},
"history": history,
}
def get_primary_soil_sensor(*, farm):
soil_sensors = list(
farm.sensors.select_related("sensor_catalog")
.order_by("created_at", "id")
)
def _sensor_priority(sensor):
sensor_type = (sensor.sensor_type or "").lower()
catalog_code = (sensor.sensor_catalog.code if sensor.sensor_catalog else "").lower()
catalog_name = (sensor.sensor_catalog.name if sensor.sensor_catalog else "").lower()
sensor_name = (sensor.name or "").lower()
haystack = " ".join([sensor_type, catalog_code, catalog_name, sensor_name])
if "sensor-7-in-1" in catalog_code or "soil_7_in_1" in sensor_type:
return 0
if "7 in 1" in haystack or "7-in-1" in haystack or "7in1" in haystack:
return 1
if "soil" in haystack:
return 2
return 3
prioritized_sensors = sorted(soil_sensors, key=_sensor_priority)
if prioritized_sensors and _sensor_priority(prioritized_sensors[0]) < 3:
return prioritized_sensors[0]
return soil_sensors[0] if soil_sensors else None
def _build_sensor_meta(context, fallback_sensor):
sensor = deepcopy(fallback_sensor)
if not context:
@@ -434,3 +522,183 @@ def get_sensor_7_in_1_summary_data(farm=None):
"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):
if range_value == "7d":
return PERSIAN_WEEKDAYS[bucket_date.weekday()]
return bucket_date.strftime("%m/%d")
def _format_percent_change(current_value, baseline_value):
if not baseline_value:
return "+0.0%"
percent_change = ((current_value - baseline_value) / baseline_value) * 100
return f"{percent_change:+.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 not numeric_payload:
continue
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:
payload = grouped_logs[bucket_date]
normalized_payload = {}
for key, value in payload.items():
normalized_key = _normalize_comparison_chart_field(key)
normalized_payload[normalized_key] = value
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_field = ordered_field_names[0]
primary_data = series_map[primary_field]
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},
],
}