From ae34386835efb9c0f01845908bb4c55910fbaa02 Mon Sep 17 00:00:00 2001
From: Peter Stockings <pstockings@jadeworld.com>
Date: Sun, 22 Oct 2023 14:46:22 +1100
Subject: [PATCH] Show formatted name for attribute label on graphs

---
 app.py | 27 ++++++++++++++-------------
 1 file changed, 14 insertions(+), 13 deletions(-)

diff --git a/app.py b/app.py
index df9b48e..8be77d5 100644
--- a/app.py
+++ b/app.py
@@ -216,6 +216,11 @@ def create_workout(user_id):
 
 @app.route('/user/<int:user_id>/workouts/graph', methods=['GET'])
 def graph_user_workouts(user_id):
+    attributes = request.args.getlist(
+        'attributes', type=str)
+    if not attributes:
+        return ""
+
     if htmx:
         return f"""
         <img src="{request.full_path}"
@@ -234,17 +239,9 @@ def graph_user_workouts(user_id):
     end_date = request.args.get(
         'end_date', default=most_recent_workout_date, type=toDate)
 
-    attributes = request.args.getlist(
-        'attributes', type=str)
-    if not attributes:
-        return ""
-
     period = request.args.get('period', default='day', type=str)
 
-    user_data = generate_user_data(user)
-    title = f'{format_key_values(user_data["attributes"], attributes)} over {get_value_from_key(user_data["periods"], period)} ({start_date.strftime("%d/%m/%y")} - {end_date.strftime("%d/%m/%y")})'
-
-    return plot_averaged_attributes(workouts, start_date, end_date, period, attributes, title)
+    return plot_averaged_attributes(workouts, user, start_date, end_date, period, attributes)
 
 
 def daterange(start_date, end_date, delta=timedelta(days=1)):
@@ -345,7 +342,7 @@ def create_user_graph(x_values, y_data, filename, x_label='Time', title=None):
     return response
 
 
-def plot_averaged_attributes(workouts_list, start_date, end_date, period, attributes, title):
+def plot_averaged_attributes(workouts_list, user, start_date, end_date, period, attributes):
     """Creates a graph for averaged attributes over a period.
 
     Parameters:
@@ -356,6 +353,9 @@ def plot_averaged_attributes(workouts_list, start_date, end_date, period, attrib
     Returns:
     - Flask Response object containing the image of the graph.
     """
+    user_data = generate_user_data(user)
+    title = f'{format_key_values(user_data["attributes"], attributes)} over {get_value_from_key(user_data["periods"], period)} ({start_date.strftime("%d/%m/%y")} - {end_date.strftime("%d/%m/%y")})'
+
     # Fetching the data
     averaged_attributes = average_workout_attributes_per_period(
         workouts_list, start_date, end_date, period, attributes)
@@ -365,8 +365,8 @@ def plot_averaged_attributes(workouts_list, start_date, end_date, period, attrib
 
     y_data = {}
     for attribute in attributes:
-        y_data[attribute] = [averaged_attributes[date][attribute]
-                             for date in x_values]
+        y_data[get_value_from_key(user_data["attributes"], attribute)] = [averaged_attributes[date][attribute]
+                                                                          for date in x_values]
 
     # Creating the graph
     return create_user_graph(x_values, y_data, filename=f"average_attributes_over_{period}", title=title)
@@ -632,7 +632,8 @@ def generate_calendar_monthly_view(workouts, selected_date):
     start_date, end_date = get_month_bounds(selected_date)
 
     # Build a lookup dictionary for faster access
-    workout_lookup = {w['start_time_date']: w for w in workouts if start_date <= w['start_time_date'] <= end_date}
+    workout_lookup = {w['start_time_date']
+        : w for w in workouts if start_date <= w['start_time_date'] <= end_date}
 
     current_date = datetime.now().date()
     days_of_month = [