Add database connection pooling

Only load graphs when they come into view
Add defer to hyperscript
2026-02-04 00:03:03 +11:00 · 2026-02-03 23:52:59 +11:00 · 2026-02-03 23:52:21 +11:00 · 2026-02-03 23:51:52 +11:00 · 2026-02-03 23:36:58 +11:00 · 2026-02-03 23:36:30 +11:00
14 changed files with 47 additions and 2224 deletions
@@ -22,12 +22,16 @@ from flask_htmx import HTMX
 import minify_html
 import os
 from dotenv import load_dotenv
+from flask_compress import Compress

 # Load environment variables from .env file in non-production environments
 if os.environ.get('FLASK_ENV') != 'production':
    load_dotenv()

 app = Flask(__name__)
+app.config['COMPRESS_REGISTER'] = True
+app.config['SEND_FILE_MAX_AGE_DEFAULT'] = 31536000 # 1 year
+Compress(app)
 app.config.from_pyfile('config.py')
 app.secret_key = os.environ.get('SECRET_KEY', '2a661781919643cb8a5a8bc57642d99f')
 jinja_partials.register_extensions(app)
@@ -1,10 +1,11 @@
 import os
 import psycopg2
+from psycopg2 import pool
 from psycopg2.extras import RealDictCursor
 from datetime import datetime
 from dateutil.relativedelta import relativedelta
 from urllib.parse import urlparse
-from flask import g
+from flask import g, current_app
 from features.exercises import Exercises
 from features.people_graphs import PeopleGraphs
 from features.person_overview import PersonOverview
@@ -16,6 +17,8 @@ from utils import get_exercise_graph_model


 class DataBase():
+    _pool = None
+
    def __init__(self, app=None):
        self.stats = Stats(self.execute)
        self.exercises = Exercises(self.execute)
@@ -25,29 +28,29 @@ class DataBase():
        self.schema = Schema(self.execute)
        self.activityRequest = Activity(self.execute)

-        db_url = urlparse(os.environ['DATABASE_URL'])
-        # if db_url is null then throw error
-        if not db_url:
+        if not os.environ.get('DATABASE_URL'):
            raise Exception("No DATABASE_URL environment variable set")

-    def getDB(self):
-        db = getattr(g, 'database', None)
-        if db is None:
+        if DataBase._pool is None:
            db_url = urlparse(os.environ['DATABASE_URL'])
-            g.database = psycopg2.connect(
+            DataBase._pool = pool.ThreadedConnectionPool(
+                1, 20, # minconn, maxconn
                database=db_url.path[1:],
                user=db_url.username,
                password=db_url.password,
                host=db_url.hostname,
                port=db_url.port
            )
-            db = g.database
-        return db

-    def close_connection(exception):
-        db = getattr(g, 'database', None)
+    def getDB(self):
+        if 'database' not in g:
+            g.database = self._pool.getconn()
+        return g.database
+
+    def close_connection(self, exception=None):
+        db = g.pop('database', None)
        if db is not None:
-            db.close()
+            self._pool.putconn(db)

    def execute(self, query, args=(), one=False, commit=False):
        conn = self.getDB()
@@ -17,4 +17,5 @@ Flask-Bcrypt==1.0.1
 email-validator==2.2.0
 requests==2.26.0
 polars>=0.20.0
-pyarrow>=14.0.0
+pyarrow>=14.0.0
+Flask-Compress==1.13
@@ -12,7 +12,7 @@

    <link href="/static/css/style.css" rel="stylesheet">
    <script src="/static/js/htmx.min.js" defer></script>
-    <script src="/static/js/hyperscript.min.js"></script>
+    <script src="/static/js/hyperscript.min.js" defer></script>
 </head>

 <body>
@@ -130,8 +130,12 @@
            <div class="overflow-x-auto rounded-lg">
                <div class="align-middle inline-block min-w-full">
                    <div class="shadow overflow-hidden sm:rounded-lg">
-                        <div class="w-full mt-2 pb-2 aspect-video">
-                            {{ render_partial('partials/sparkline.html', **exercise.graph) }}
+                        <div class="w-full mt-2 pb-2 aspect-video"
+                            hx-get="{{ url_for('get_exercise_progress_for_user', person_id=person.id, exercise_id=exercise.id, min_date=min_date, max_date=max_date) }}"
+                            hx-trigger="intersect once" hx-swap="outerHTML">
+                            <div class="flex items-center justify-center h-full bg-gray-50 rounded-lg">
+                                <div class="text-sm text-gray-400 animate-pulse font-medium">Loading graph...</div>
+                            </div>
                        </div>

                        <table class="min-w-full divide-y divide-gray-200">
@@ -105,7 +105,13 @@

        <div class="mt-4 mb-4 w-full grid grid-cols-1 2xl:grid-cols-2 gap-4">
            {% for graph in exercise_progress_graphs %}
-            {{ render_partial('partials/sparkline.html', **graph.progress_graph) }}
+            <div hx-get="{{ url_for('get_exercise_progress_for_user', person_id=person_id, exercise_id=graph.exercise_id, min_date=min_date, max_date=max_date) }}"
+                hx-trigger="intersect once" hx-swap="outerHTML">
+                <div class="flex items-center justify-center h-48 bg-gray-50 rounded-lg">
+                    <div class="text-sm text-gray-400 animate-pulse font-medium">Loading {{ graph.exercise_name }}...
+                    </div>
+                </div>
+            </div>
            {% endfor %}
        </div>

@@ -48,18 +48,22 @@ def get_exercise_graph_model(title, estimated_1rm, repetitions, weight, start_da

    best_fit_points = []
    try:
-        if len(relative_positions) > 1:  # Ensure there are enough points for polyfit
-            # Fit a polynomial of the given degree
-            coeffs = np.polyfit(relative_positions, estimated_1rm_scaled, degree)
+        # Filter out NaNs if any (though scaled values shouldn't have them if ranges are correct)
+        mask = ~np.isnan(estimated_1rm_scaled)
+        x_fit = relative_positions[mask]
+        y_fit = estimated_1rm_scaled[mask]
+        
+        # Ensure we have enough unique X positions for the given degree
+        if len(np.unique(x_fit)) > degree: 
+            coeffs = np.polyfit(x_fit, y_fit, degree)
            poly_fit = np.poly1d(coeffs)
            y_best_fit = poly_fit(relative_positions)
            best_fit_points = list(zip(y_best_fit.tolist(), relative_positions.tolist()))
        else:
-            raise ValueError("Not enough data points for polyfit")
-    except (np.linalg.LinAlgError, ValueError) as e:
-        # Handle cases where polyfit fails
+            best_fit_points = []
+    except (np.linalg.LinAlgError, ValueError, TypeError) as e:
+        # Handle cases where polyfit fails or input is invalid
        best_fit_points = []
-        m, b = 0, 0

    # Prepare data for plots
    repetitions_data = {
Author	SHA1	Message	Date
Peter Stockings	b4121eada7	Add database connection pooling	2026-02-04 00:03:03 +11:00
Peter Stockings	a6a71f3139	Only load graphs when they come into view	2026-02-03 23:52:59 +11:00
Peter Stockings	9998616946	Add defer to hyperscript	2026-02-03 23:52:21 +11:00
Peter Stockings	c20f2e2f85	Added safety checks to the graph regression logic in utils.py. This stops those "illegal value" server warnings and makes the math more efficient for small datasets	2026-02-03 23:51:52 +11:00
Peter Stockings	ec8d7f6825	Add asset caching	2026-02-03 23:36:58 +11:00
Peter Stockings	2e79ad1b8b	Remove more unused js and css	2026-02-03 23:36:30 +11:00
Peter Stockings	d223bdeebc	Add compression	2026-02-03 23:25:13 +11:00
Peter Stockings	9a2ce6754a	Remove unused js libs	2026-02-03 23:24:49 +11:00