Upload app.py

app.py

@@ -14,12 +14,20 @@ RECEIVER_URL = os.getenv("RECEIVER_URL", "").rstrip("/")
 MOVE, OFFSET, HORIZONS = .0008, .0004, (5, 15, 30)
 MODELS = None
 
+def epoch_seconds(value):
+    value = float(value)
+    if value > 1e14: return int(value / 1e6)
+    if value > 1e11: return int(value / 1e3)
+    return int(value)
+
 def get_candles():
     """Incrementally backfill Delta candles from the newest stored timestamp."""
     now = int(time.time())
     old = pd.read_parquet(LIVE_DATA) if LIVE_DATA.exists() else pd.DataFrame()
+    if len(old) and epoch_seconds(old.epoch.max()) < 1577836800:
+        old = pd.DataFrame()
     if len(old):
-        start = int(old.epoch.max()) + 60
+        start = epoch_seconds(old.epoch.max()) + 60
     else:
         base = pd.read_parquet(DATA, columns=["timestamp"])
         start = int(pd.to_datetime(base.timestamp, utc=True).astype("int64").max() // 10**9) + 60
@@ -31,10 +39,11 @@ def get_candles():
         batch=r.json().get("result", [])
         if not batch: break
         rows.extend(batch)
-        latest=max(int(q["time"]) for q in batch)
+        latest=max(epoch_seconds(q["time"]) for q in batch)
         if latest < start: break
         start=max(end, latest+60)
     fresh=pd.DataFrame(rows).rename(columns={"time":"epoch"})
+    if len(fresh): fresh["epoch"] = fresh["epoch"].map(epoch_seconds)
     live=pd.concat([old,fresh],ignore_index=True) if len(old) or len(fresh) else pd.DataFrame()
     if len(live):
         live=live.drop_duplicates("epoch",keep="last").sort_values("epoch").reset_index(drop=True)
@@ -89,7 +98,7 @@ def tick():
     for si in range(2):
         for hi,horizon in enumerate(HORIZONS): probs[si,hi]=MODELS[si,horizon].predict_proba(x[i:i+1])[0,1]
     score=3/(1/(probs+1e-6)).sum(axis=1); si=int(np.argmax(score)); side="LONG" if si==0 else "SHORT"
-    row=d.iloc[i]; event={"event":"tick","symbol":SYMBOL,"candle":{"time":datetime.fromtimestamp(int(row.epoch),timezone.utc).isoformat(),"open":float(row.open),"high":float(row.high),"low":float(row.low),"close":float(row.close)},"signal":None,"probs":probs.tolist(),"score":float(score[si]),"source":"exact-hybrid-multihorizon"}
+    row=d.iloc[i]; candle_epoch=epoch_seconds(row.epoch); event={"event":"tick","symbol":SYMBOL,"candle":{"time":datetime.fromtimestamp(candle_epoch,timezone.utc).isoformat(),"epoch":candle_epoch,"open":float(row.open),"high":float(row.high),"low":float(row.low),"close":float(row.close)},"signal":None,"probs":probs.tolist(),"score":float(score[si]),"source":"exact-hybrid-multihorizon"}
     if np.isfinite(x[i]).all(): event["signal"]={"side":side,"price":float(row.close),"score":float(score[si]),"offset":OFFSET,"target":MOVE}
     event["data_last_updated"] = event["candle"]["time"]
     event["live_cache_rows"] = int(len(live))