Add options to filter epoch for exercise progress graphs (1M, 3M, 6M, All), however if there isnt data in a selected epoch the endpoint returns 404. Havent bothered to look into to it, probs should clean up code as well

app.py

@@ -413,7 +413,9 @@ def get_exercise_progress_for_user(person_id, exercise_id):
         'min_date'), '%Y-%m-%d')
     max_date = convert_str_to_date(request.args.get(
         'max_date'), '%Y-%m-%d')
-    exercise_progress = db.get_exercise_progress_for_user(person_id, exercise_id, min_date, max_date)
+    epoch = request.args.get('epoch', default='All')
+
+    exercise_progress = db.get_exercise_progress_for_user(person_id, exercise_id, min_date, max_date, epoch)
 
     if not exercise_progress:
         abort(404)

db.py

@@ -3,6 +3,7 @@ import psycopg2
 import numpy as np
 from psycopg2.extras import RealDictCursor
 from datetime import datetime
+from dateutil.relativedelta import relativedelta
 from urllib.parse import urlparse
 from flask import g
 
@@ -450,7 +451,14 @@ class DataBase():
             'SELECT exercise_id, name FROM exercise')
         return exercises
     
-    def get_exercise_progress_for_user(self, person_id, exercise_id, min_date=None, max_date=None):
+    def get_exercise_progress_for_user(self, person_id, exercise_id, min_date=None, max_date=None, epoch='all'):
+        today = datetime.now()
+        if epoch == '1M':
+            min_date = today - relativedelta(months=1)
+        elif epoch == '3M':
+            min_date = today - relativedelta(months=3)
+        elif epoch == '6M':
+            min_date = today - relativedelta(months=6)
         # Execute SQL query to fetch topset data for a specific person and exercise
         topsets = self.execute("""
             SELECT 
@@ -484,7 +492,7 @@ class DataBase():
         start_dates = [t['start_date'] for t in topsets]
         messages = [f'{t["repetitions"]} x {t["weight"]}kg ({t["estimated_1rm"]}kg E1RM) on {t["start_date"].strftime("%d %b %y")}' for t in topsets]
 
-        exercise_progress = get_exercise_graph_model(topsets[0]['exercise_name'], estimated_1rm, repetitions, weight, start_dates, messages)
+        exercise_progress = get_exercise_graph_model(topsets[0]['exercise_name'], estimated_1rm, repetitions, weight, start_dates, messages, epoch, person_id, exercise_id)
 
         return exercise_progress
     

templates/partials/sparkline.html

@@ -47,11 +47,24 @@
     <!-- Popover content will be dynamically inserted here -->
     </div>
     <h4 class="text-l font-semibold text-blue-400 text-center">{{ title }}</h4>
-    <h2 class="text-xs font-semibold text-blue-200 mb-2 text-center" style='font-family: "Computer Modern Sans", sans-serif;'>
+    <h2 class="text-xs font-semibold text-blue-200 mb-1 text-center" style='font-family: "Computer Modern Sans", sans-serif;'>
         {% if best_fit_formula %}
         y = {{ best_fit_formula.slope }}x {% if best_fit_formula.intercept != 0 %}+ {{ best_fit_formula.intercept }}{% endif %}, {{ best_fit_formula.kg_per_week }} kg/week, {{ best_fit_formula.kg_per_month }} kg/month
         {% endif %}
     </h2>
+    <div class="inline-flex rounded-md shadow-sm w-full items-center justify-center mb-1">
+        {% for epoch in epochs %}
+            <div
+            {% if selected_epoch == epoch %} 
+                class="px-4 py-2 text-sm font-medium text-blue-700 bg-white border border-gray-200 rounded-s-lg hover:bg-gray-100 focus:z-10 focus:ring-2 focus:ring-blue-700 focus:text-blue-700 dark:bg-gray-800 dark:border-gray-700 dark:text-white dark:hover:text-white dark:hover:bg-gray-700 dark:focus:ring-blue-500 dark:focus:text-white"
+            {% else %}
+                class="px-4 py-2 text-sm font-medium text-gray-900 bg-white border border-gray-200 rounded-e-lg hover:bg-gray-100 hover:text-blue-700 focus:z-10 focus:ring-2 focus:ring-blue-700 focus:text-blue-700 dark:bg-gray-800 dark:border-gray-700 dark:text-white dark:hover:text-white dark:hover:bg-gray-700 dark:focus:ring-blue-500 dark:focus:text-white cursor-pointer"
+                hx-get='{{ url_for("get_exercise_progress_for_user", person_id=person_id,  exercise_id=exercise_id, epoch=epoch) }}' hx-target="#svg-plot-{{ unique_id }}" hx-swap="outerHTML" hx-trigger="click"
+            {% endif %}>
+                {{ epoch}}
+            </div>
+        {% endfor %}
+    </div>
     <svg viewBox="0 0 {{ (vb_width + 2*margin) | int }} {{ (vb_height + 2*margin) | int }}" preserveAspectRatio="none">
         {% for plot in plots %}
         <g class="{{ plot.label }}" style="fill: {{ plot.color }}; stroke: {{ plot.color }};">

utils.py

@@ -52,8 +52,11 @@ def get_topsets_for_person(person_topsets):
         weight = [t['Weight'] for t in exercise_topsets]
         start_dates = [t['StartDate'] for t in exercise_topsets]
         messages = [f'{t["Repetitions"]} x {t["Weight"]}kg ({t["Estimated1RM"]}kg E1RM) on {t["StartDate"].strftime("%d %b %y")}' for t in exercise_topsets]
+        epoch = 'All'
+        person_id = exercise_topsets[0]['PersonId']
+        exercise_id = exercise_topsets[0]['ExerciseId']       
 
-        exercise_progress = get_exercise_graph_model(exercise_topsets[0]['ExerciseName'], estimated_1rm, repetitions, weight, start_dates, messages)
+        exercise_progress = get_exercise_graph_model(exercise_topsets[0]['ExerciseName'], estimated_1rm, repetitions, weight, start_dates, messages, epoch, person_id, exercise_id)
 
         exercises_topsets.append({
             'ExerciseId': e['ExerciseId'],
@@ -236,7 +239,7 @@ def get_date_info(input_date, selected_view):
             'end_date': last_day_of_year,
         }
 
-def get_exercise_graph_model(title, estimated_1rm, repetitions, weight, start_dates, messages):
+def get_exercise_graph_model(title, estimated_1rm, repetitions, weight, start_dates, messages, epoch, person_id, exercise_id):
     min_date, max_date = min(start_dates), max(start_dates)
     min_e1rm, max_e1rm = min(estimated_1rm), max(estimated_1rm)
     min_reps, max_reps = min(repetitions), max(repetitions)
@@ -318,7 +321,11 @@ def get_exercise_graph_model(title, estimated_1rm, repetitions, weight, start_da
         'plots': [repetitions, weight, estimated_1rm],
         'best_fit_points': best_fit_points,
         'best_fit_formula': best_fit_formula,
-        'plot_labels': plot_labels
+        'plot_labels': plot_labels,
+        'epochs': ['1M', '3M', '6M', 'All'],
+        'selected_epoch': epoch,
+        'person_id': person_id,
+        'exercise_id': exercise_id
     }
 
 def get_workout_counts(workouts, period='week'):