05/23 update codes, add build scripts

core/analyzer.py

@@ -6,27 +6,41 @@ Each function takes game_id and returns structured Python data
 (dicts / lists) — no UI concerns here.
 """
 
+import math
 from collections import Counter
 from itertools import combinations
 
 from db.models import get_all_draws_numbers, get_game_by_id
 
 
-def frequency_analysis(game_id, last_n=None):
+def frequency_analysis(game_id, last_n=None, decay: float = 0.0):
     """
-    Count appearances of each main ball.
+    Count (or weight) appearances of each main ball.
     last_n: restrict to the most recent N draws (None = all).
-    Returns {number: count} sorted high → low.
+    decay:  exponential recency weight per draw step (0 = uniform / off).
+            With decay=0.01 the draw 69 steps back carries ~50% of the
+            latest draw's weight; draws >300 steps back are near-zero.
+    Returns {number: count_or_weight} sorted high → low.
     """
-    draws = get_all_draws_numbers(game_id)   # ASC order
+    draws = get_all_draws_numbers(game_id)   # ASC order, oldest first
     if last_n and last_n > 0:
         draws = draws[-last_n:]
 
-    counter = Counter()
-    for draw in draws:
-        counter.update(draw["numbers"])
+    if not decay:
+        counter = Counter()
+        for draw in draws:
+            counter.update(draw["numbers"])
+        return dict(sorted(counter.items(), key=lambda kv: kv[1], reverse=True))
 
-    return dict(sorted(counter.items(), key=lambda kv: kv[1], reverse=True))
+    # Decayed path: newest draw (i = n-1) gets weight 1.0; older draws decay
+    n = len(draws)
+    freq: dict[int, float] = {}
+    for i, draw in enumerate(draws):
+        w = math.exp(-decay * (n - 1 - i))
+        for num in draw["numbers"]:
+            freq[num] = freq.get(num, 0.0) + w
+
+    return dict(sorted(freq.items(), key=lambda kv: kv[1], reverse=True))
 
 
 def gap_analysis(game_id):