Change leadership graph to line and add linear best fit

app/routes/api.py

@@ -1,11 +1,120 @@
-from flask import Blueprint, jsonify, session
+from flask import Blueprint, jsonify, request, session
 from app import SYDNEY_TZ
 from app.auth import login_required
 from app.db import query, query_one
-from datetime import timezone
+from datetime import datetime, timezone
 
 bp = Blueprint("api", __name__, url_prefix="/api")
 
+# Distinct hues for up to 12 users; cycles if more
+_CHART_HUES = [210, 160, 270, 30, 340, 190, 50, 120, 300, 80, 240, 10]
+
+
+@bp.route("/progress-over-time")
+@login_required
+def progress_over_time():
+    """Return per-user % weight lost over time for the leaderboard line chart."""
+    # --- parse optional filters ---
+    start = request.args.get("start")  # ISO date string
+    end = request.args.get("end")
+    user_ids_raw = request.args.get("user_ids", "")
+
+    # Build WHERE fragments
+    where_clauses = ["u.is_private = FALSE"]
+    params = []
+
+    if start:
+        where_clauses.append("c.checked_in_at >= %s")
+        params.append(start)
+    if end:
+        where_clauses.append("c.checked_in_at < (%s::date + interval '1 day')")
+        params.append(end)
+    if user_ids_raw:
+        try:
+            uid_list = [int(x) for x in user_ids_raw.split(",") if x.strip()]
+        except ValueError:
+            uid_list = []
+        if uid_list:
+            placeholders = ",".join(["%s"] * len(uid_list))
+            where_clauses.append(f"u.id IN ({placeholders})")
+            params.extend(uid_list)
+
+    where_sql = " AND ".join(where_clauses)
+
+    rows = query(f"""
+        SELECT
+            u.id                    AS user_id,
+            u.display_name,
+            u.username,
+            u.starting_weight_kg,
+            (SELECT weight_kg FROM checkins
+             WHERE user_id = u.id ORDER BY checked_in_at ASC LIMIT 1) AS first_weight,
+            c.weight_kg,
+            c.checked_in_at
+        FROM checkins c
+        JOIN users u ON u.id = c.user_id
+        WHERE {where_sql}
+        ORDER BY u.id, c.checked_in_at ASC
+    """, params)
+
+    # Group rows by user
+    from collections import OrderedDict
+    users_map = OrderedDict()
+    for r in rows:
+        uid = r["user_id"]
+        if uid not in users_map:
+            start_w = float(r["starting_weight_kg"] or r["first_weight"] or 0)
+            users_map[uid] = {
+                "id": uid,
+                "name": r["display_name"] or r["username"],
+                "start_w": start_w,
+                "data": [],
+            }
+        entry = users_map[uid]
+        w = float(r["weight_kg"])
+        dt = r["checked_in_at"]
+        if dt.tzinfo is None:
+            dt = dt.replace(tzinfo=timezone.utc)
+        entry["data"].append({
+            "date": dt.astimezone(SYDNEY_TZ).strftime("%Y-%m-%d"),
+            "weight": round(w, 1),
+        })
+
+    # Build response with best-fit
+    result = []
+    for idx, (uid, entry) in enumerate(users_map.items()):
+        hue = _CHART_HUES[idx % len(_CHART_HUES)]
+        color = f"hsl({hue}, 70%, 55%)"
+
+        # Simple linear regression (x = day index, y = weight)
+        points = entry["data"]
+        best_fit = {"slope": 0, "intercept": 0}
+        if len(points) >= 2:
+            # Convert dates to day offsets from first point
+            base = datetime.strptime(points[0]["date"], "%Y-%m-%d")
+            xs = [(datetime.strptime(p["date"], "%Y-%m-%d") - base).days for p in points]
+            ys = [p["weight"] for p in points]
+            n = len(xs)
+            sum_x = sum(xs)
+            sum_y = sum(ys)
+            sum_xy = sum(x * y for x, y in zip(xs, ys))
+            sum_x2 = sum(x * x for x in xs)
+            denom = n * sum_x2 - sum_x * sum_x
+            if denom != 0:
+                slope = (n * sum_xy - sum_x * sum_y) / denom
+                intercept = (sum_y - slope * sum_x) / n
+                best_fit = {"slope": round(slope, 4), "intercept": round(intercept, 4)}
+
+        result.append({
+            "id": uid,
+            "name": entry["name"],
+            "color": color,
+            "data": points,
+            "best_fit": best_fit,
+        })
+
+    return jsonify({"users": result})
+
 
 @bp.route("/chart-data/<int:user_id>")
 @login_required