src/endpoints/handlers/bett.py

@@ -15,9 +15,9 @@ matrix_clock_api: str = "http://192.168.178.84:8000"
 
 empty_weight: Optional[float] = None
 local_history = []
-history_max_length: int = 24 * 60 * 60 # 24 hours
-min_noticable_difference: float= 25  # In kg
-show_scale_countdown: int = 0   # Number of updates for the scale, until return to clock
+history_max_length: int = 24 * 60 * 60  # 24 hours
+min_noticable_difference: float = 25  # In kg
+show_scale_countdown: int = 0  # Number of updates for the scale, until return to clock
 
 average_person_weight: float = 75
 
@@ -29,7 +29,6 @@ leg_capacity_limit_patterns = [
 ]
 
 
-
 def get_clusters(data: list[float], min_delta: float) -> dict:
     clusters = {}
     for point in data:
@@ -40,13 +39,13 @@ def get_clusters(data: list[float], min_delta: float) -> dict:
         clusters[point] = [point]
     return clusters
 
+
 def show_time():
     r.post(f"{matrix_clock_api}/time")
 
-def show_scale(weight:float):
-    r.post(f"{matrix_clock_api}/message", json={
-	"message": f"{weight:3.1f}kg"
-})
+
+def show_scale(weight: float):
+    r.post(f"{matrix_clock_api}/message", json={"message": f"{weight:3.1f}kg"})
 
 
 def is_capacity_reached() -> bool:
@@ -65,15 +64,18 @@ def is_capacity_reached() -> bool:
             is_warning_active = False
             show_time()
         return
-    
+
     is_warning_active = True
-    r.post(f"{matrix_clock_api}/pattern?pattern={highest_limit["pattern"]}&step_ms={highest_limit["duration"]}&contrast=255")
+    r.post(
+        f"{matrix_clock_api}/pattern?pattern={highest_limit['pattern']}&step_ms={highest_limit['duration']}&contrast=255"
+    )
+
 
 def check_for_change():
     # Check for capicity limits
     if is_capacity_reached():
         return
-    
+
     global show_scale_countdown
     latest = local_history[-1]
     if show_scale_countdown > 0 and show_scale_countdown % 3 == 0:
@@ -93,12 +95,12 @@ def check_for_change():
     if empty_weight is None:
         clusters = get_clusters(local_history)
         empty_weight = min([median(cluster) for cluster in clusters.values()])
-    
+
     # Determine number of people
     number_of_people = round((latest["total"] - empty_weight) / average_person_weight)
-    
+
     if number_of_people == 1 and weight_increased:
-        show_scale_countdown = 60   # Should be a multiple of 3
+        show_scale_countdown = 60  # Should be a multiple of 3
     elif number_of_people >= 2 and weight_increased:
         show_scale_countdown = 0
         show_time()