Refactor: review, fix, and test entire codebase
Live node: - Fix null-handling for open_ords and get_fills requests - Cap equity_history, strategy_equity at 600-1000 entries (memory leak fix) - Dynamic strategy count in startup log - Loop error recovery: catch exceptions, backoff 5s, continue Dashboard server: - Fix backtest detail API: check HISTORICAL_DIR first - This was causing all historical detail views to show zeros Tests (5 suites, all passing): 1. Signal generation: Mean Reversion VWAP + Momentum + Pairs + OBI 2. Backtest: SPX mean reversion on 500-point series 3. Hurst/VPIN: 15 signals from 280 dollar bars 4. Memory guard: RSS monitoring, GC thresholds 5. Dashboard API: historical listing + SPX detail 38 backtests on dashboard, 2 SPX entries with real trade data.
This commit is contained in:
ramseshk
+60
-27
@@ -279,7 +279,7 @@ async def main():
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log.info(f" BTC: bid=${btc_bid:,.0f} ask=${btc_ask:,.0f} (spread=${btc_ask-btc_bid:.1f})")
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log.info(f" ETH: bid=${eth_bid:,.0f} ask=${eth_ask:,.0f} (spread=${eth_ask-eth_bid:.1f})")
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log.info(f" Mode: POST-ONLY at best bid/ask | Maker: 0.02%")
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log.info(f" 7 strategies | A-S is DUAL-SIDED quoting")
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log.info(f" {len(STRATEGIES)} strategies | A-S is DUAL-SIDED quoting")
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log.info(f" Dashboard: https://ftdt.io/cv")
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log.info("="*60)
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@@ -292,7 +292,7 @@ async def main():
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except: pass
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log.info(f"Cleared {len(open_ords)} stale orders")
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existing = get_fills(addr)
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existing = get_fills(addr) or []
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for f in existing: seen_fills.add(f.get("tid",0))
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log.info(f"Tracking {len(seen_fills)} existing fills")
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@@ -304,21 +304,30 @@ async def main():
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try:
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while True:
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try:
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tick += 1
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prices = get_mark_prices()
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btc = prices.get("BTC",0); eth = prices.get("ETH",0)
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if btc>0: btc_prices.append(btc)
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if eth>0: eth_prices.append(eth)
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btc = prices.get("BTC", 0)
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eth = prices.get("ETH", 0)
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if btc > 0:
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btc_prices.append(btc)
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if eth > 0:
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eth_prices.append(eth)
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# Process fills
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fills = get_fills(addr); new_fills=0
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fills = get_fills(addr)
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new_fills = 0
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for f in fills:
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tid = f.get("tid", 0)
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if tid in seen_fills: continue
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if tid in seen_fills:
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continue
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seen_fills.add(tid)
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side=f.get("side",""); sz=float(f.get("sz",0)); px=float(f.get("px",0))
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closed_pnl=float(f.get("closedPnl",0)); fee=float(f.get("fee","0"))
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side = f.get("side", "")
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sz = float(f.get("sz", 0))
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px = float(f.get("px", 0))
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closed_pnl = float(f.get("closedPnl", 0))
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fee = float(f.get("fee", "0"))
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# Attribute fill by size (now unique per strategy)
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strat = None
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@@ -326,28 +335,35 @@ async def main():
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if abs(sz - cfg["size"]) < 0.000001:
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strat = n
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break
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if not strat: continue
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if not strat:
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continue
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net = closed_pnl - abs(fee)
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STRATEGIES[strat]["pnl"]+=net; STRATEGIES[strat]["trades_today"]+=1
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STRATEGIES[strat]["pnl"] += net
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STRATEGIES[strat]["trades_today"] += 1
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STRATEGIES[strat]["fee_paid"] += abs(fee)
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if closed_pnl>0: STRATEGIES[strat]["wins"]+=1
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if closed_pnl > 0:
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STRATEGIES[strat]["wins"] += 1
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STRATEGIES[strat]["pnl_pct"] = STRATEGIES[strat]["pnl"] / STRATEGIES[strat]["allocation"] * 100
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strategy_equity[strat].append({"t": time.time(), "v": STRATEGIES[strat]["allocation"] + STRATEGIES[strat]["pnl"]})
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if len(strategy_equity[strat]) > 1000:
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strategy_equity[strat][:] = strategy_equity[strat][-600:]
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trades_log.append({"time": datetime.now().strftime("%H:%M:%S"), "strategy": strat, "side": "BUY" if side == "B" else "SELL", "size": sz, "price": px, "pnl": round(net, 4), "fee": round(abs(fee), 4)})
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new_fills += 1
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# Signals every 5 ticks
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if tick%5==0: compute_signals()
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if tick % 5 == 0:
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compute_signals()
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# Execute ALL strategies every 4 seconds
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if tick >= 3 and tick % 4 == 0:
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btc_bid, btc_ask, btc_mid = get_orderbook("BTC")
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try:
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eth_bid, eth_ask, eth_mid = get_orderbook("ETH")
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except Exception as e:
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except Exception:
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eth_bid = eth_ask = eth_mid = 0
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if btc_bid<=0 or btc_ask<=0: continue
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if btc_bid <= 0 or btc_ask <= 0:
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continue
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for name in names:
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cfg = STRATEGIES[name]
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@@ -356,7 +372,8 @@ async def main():
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bid = btc_bid if coin == "BTC" else eth_bid
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ask = btc_ask if coin == "BTC" else eth_ask
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mid = btc_mid if coin == "BTC" else eth_mid
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if bid<=0 or ask<=0: continue
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if bid <= 0 or ask <= 0:
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continue
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# Check if this strategy has a position; skip if already filled
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has_position = name in active_cloids and tick - active_cloids_times.get(name, 0) < 60
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@@ -372,10 +389,12 @@ async def main():
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# Close on opposing signal
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if has_position and signal:
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prev_signal = active_cloids.get(name, "")
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if ("BUY" in str(signal).upper() and "SELL" in str(prev_signal).upper()) or ("SELL" in str(signal).upper() and "BUY" in str(prev_signal).upper()):
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if ("BUY" in str(signal).upper() and "SELL" in str(prev_signal).upper()) or \
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("SELL" in str(signal).upper() and "BUY" in str(prev_signal).upper()):
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try:
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client.cancel_order(instrument_id=perp.id, client_order_id=ClientOrderId(active_cloids[name]))
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except: pass
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except Exception:
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pass
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del active_cloids[name]
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has_position = False
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@@ -386,21 +405,25 @@ async def main():
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if "BUY" in str(active_cloids[name]).upper() and mid > entry_px * 1.001:
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try:
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client.cancel_order(instrument_id=perp.id, client_order_id=ClientOrderId(active_cloids[name]))
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except: pass
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except Exception:
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pass
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del active_cloids[name]
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has_position = False
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elif "SELL" in str(active_cloids[name]).upper() and mid < entry_px * 0.999:
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try:
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client.cancel_order(instrument_id=perp.id, client_order_id=ClientOrderId(active_cloids[name]))
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except: pass
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except Exception:
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pass
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del active_cloids[name]
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has_position = False
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if has_position: continue # Don't replace existing orders
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if has_position:
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continue # Don't replace existing orders
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# Avellaneda-Stoikov: DUAL-SIDED (always active)
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if name == "Avellaneda-Stoikov":
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cid_bid=ClientOrderId(str(UUID4())); cid_ask=ClientOrderId(str(UUID4()))
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cid_bid = ClientOrderId(str(UUID4()))
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cid_ask = ClientOrderId(str(UUID4()))
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try:
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client.submit_order(instrument_id=perp.id, client_order_id=cid_bid, order_side=OrderSide.BUY, order_type=OrderType.LIMIT, quantity=Quantity.from_str(str(cfg["size"])), price=Price.from_str(str(int(bid))), time_in_force=TimeInForce.GTC, post_only=True)
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client.submit_order(instrument_id=perp.id, client_order_id=cid_ask, order_side=OrderSide.SELL, order_type=OrderType.LIMIT, quantity=Quantity.from_str(str(cfg["size"])), price=Price.from_str(str(int(ask))), time_in_force=TimeInForce.GTC, post_only=True)
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@@ -409,7 +432,8 @@ async def main():
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active_cloids[name] = str(cid_bid)
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active_cloids_times[name] = tick
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active_cloids_px[name] = bid
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except Exception as e: pass
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except Exception:
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pass
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continue
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# For signal-driven strategies: use aggressive offset
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@@ -423,7 +447,8 @@ async def main():
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# No signal/default: skip (don't random-trade)
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continue
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if px_level<=0: continue
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if px_level <= 0:
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continue
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cid = ClientOrderId(str(UUID4()))
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try:
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@@ -443,11 +468,15 @@ async def main():
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active_cloids[name] = str(cid2)
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active_cloids_times[name] = tick
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active_cloids_px[name] = px_level
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except: pass
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except Exception:
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pass
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# Equity
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tp = sum(s["pnl"] for s in STRATEGIES.values())
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if tick%2==0: equity_history.append({"t":time.time(),"v":TOTAL_EQUITY+tp})
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if tick % 2 == 0:
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equity_history.append({"t": time.time(), "v": TOTAL_EQUITY + tp})
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if len(equity_history) > 1000:
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equity_history[:] = equity_history[-600:]
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write_metrics(addr)
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if tick % 20 == 0:
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@@ -457,7 +486,11 @@ async def main():
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log.info(f"Tick {tick:4d} | PnL: ${tp:+.2f} | Trades: {tr:3d} | Fees: ${tf:.4f} | New fills: {new_fills}")
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await asyncio.sleep(1)
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except KeyboardInterrupt: log.info("Stopping...")
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except Exception as loop_err:
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log.error(f"Loop error (tick {tick}): {loop_err}")
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await asyncio.sleep(5) # back off and retry
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except KeyboardInterrupt:
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log.info("Stopping...")
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# Cancel all
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open_ords = requests.post(TESTNET_API, json={"type":"openOrders","user":addr}, timeout=10).json()
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@@ -0,0 +1,161 @@
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#!/usr/bin/env python3
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"""Tests for FTDT Quant Lab — signal generation, backtest, and API validation.
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Run: .venv/bin/python tests/test_system.py (requires venv)"""
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import sys, json, math, os, random, time
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from collections import deque
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sys.path.insert(0, os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
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# ── 1. Signal generation ──
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print("1. Signal Generation Tests")
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print("=" * 40)
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# Test: Mean Reversion signal logic (extracted from live/node.py)
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# Simulate ETH prices with sharp drop
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random.seed(42)
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eth_prices = deque(maxlen=60)
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base = 1800.0
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for _ in range(19):
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eth_prices.append(base + random.uniform(-5, 5))
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eth_prices.append(base - 20.0) # sharp -2σ drop
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mr_signals = []
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w = list(eth_prices)[-20:]
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eth_mr = eth_prices[-1]
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prior = w[:-1]
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sma = sum(prior) / len(prior)
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vstd = math.sqrt(sum((p - sma)**2 for p in prior) / len(prior))
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dev = (eth_mr - sma) / vstd if vstd > 0 else 0
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if dev > 1.0:
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mr_signals.append({"signal": "SELL", "strength": dev})
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elif dev < -1.0:
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mr_signals.append({"signal": "BUY", "strength": abs(dev)})
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assert len(mr_signals) > 0, f"Mean Reversion should fire on -2σ drop, got 0"
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assert mr_signals[0]["signal"] == "BUY", f"Sharp drop below mean should trigger BUY, got {mr_signals[0]}"
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print(f" ✅ Mean Reversion: {mr_signals[0]['signal']} at dev={mr_signals[0]['strength']:.2f}")
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# Test: Momentum breakout (Bollinger)
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w = [100, 101, 102, 103, 104, 105, 106, 107, 108, 109] + [115, 116, 117, 118, 119, 120, 121, 122, 123, 124]
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eth_cur = w[-1]
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sma = sum(w) / len(w)
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std = math.sqrt(sum((p - sma)**2 for p in w) / len(w))
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assert eth_cur > sma + 1.2 * std, f"Expected breakout above 1.2σ band"
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print(f" ✅ Momentum: price {eth_cur} > band {sma + 1.2*std:.1f} — BUY signal")
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# Test: Pairs ratio deviation
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btc_prices = deque([64000 + i * 100 for i in range(20)], maxlen=60)
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eth_prices = deque([1800.0] * 20, maxlen=60)
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ratios = [btc_prices[i] / eth_prices[i] for i in range(-20, 0)]
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mu = sum(ratios) / len(ratios)
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std = math.sqrt(sum((r - mu)**2 for r in ratios) / len(ratios))
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cur = btc_prices[-1] / eth_prices[-1]
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z = (cur - mu) / std if std > 0 else 0
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assert z > 1.2, f"BTC rising vs flat ETH should produce z>1.2, got {z:.2f}"
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print(f" ✅ Pairs Trading: z={z:.2f} — SELL_ETH signal")
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# Test: OBI reversal detection
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btc_list = list(btc_prices)
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ret = (btc_list[-1] - btc_list[-5]) / btc_list[-5]
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assert ret > 0.0004, f"5-tick return should be >0.04% on uptrend"
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print(f" ✅ OBI: 5-tick return {ret*100:.2f}% — SELL (overbought)")
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# ── 2. Backtest Validation ──
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print("\n2. Backtest Validation")
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print("=" * 40)
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import numpy as np
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np.random.seed(7)
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n = 500
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prices = np.cumsum(np.random.randn(n) * 0.01) + 0.35
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equity = 100.0; pos = 0; entry = 0; trades = 0; won = 0
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WINDOW = 20
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for i in range(WINDOW + 1, n):
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prior = prices[i - WINDOW - 1:i - 1]
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mu = float(np.mean(prior))
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sd = float(np.std(prior, ddof=1))
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z = (prices[i] - mu) / sd if sd > 0 else 0
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if pos == 0:
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if z > 1.5: pos = -1; entry = prices[i]
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elif z < -1.5: pos = 1; entry = prices[i]
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elif pos != 0 and (abs(z) < 0.3):
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pnl = (prices[i] / entry - 1) * pos * equity * 0.01
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equity += pnl; trades += 1
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if pnl > 0: won += 1; pos = 0
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pct = (equity / 100.0 - 1) * 100
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assert trades > 0, f"Backtest should produce trades on 500-point series"
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assert won > 0, f"Should have winning trades, got {won}/{trades}"
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print(f" ✅ SPX MR: ${equity:.2f} ({pct:+.2f}%) | {trades} trades | {won/trades*100:.0f}% win")
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# ── 3. Hurst/VPIN ──
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print("\n3. Hurst/VPIN Strategy")
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print("=" * 40)
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from strategies.hurst_vpin import HurstVPINSignal
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np.random.seed(1)
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n = 2000
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trend = np.cumsum(np.random.randn(n) * 50 + 10) + 63000
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sides = ['B' if random.random() < 0.65 else 'A' for _ in range(n)]
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trade_data = [{"px": float(trend[i]), "sz": 0.01, "side": sides[i]} for i in range(n)]
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sg = HurstVPINSignal(notional_threshold=5000.0)
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signals = 0
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for t in trade_data:
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r = sg.add_trade(t["px"], t["sz"], t["side"])
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if r and r["signal"] != "HOLD":
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signals += 1
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assert signals > 0, f"No signals from Hurst/VPIN on trending data"
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assert sg.bar_count >= 50, f"Should build 50+ dollar bars, got {sg.bar_count}"
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print(f" ✅ Hurst/VPIN: {signals} signals, {sg.bar_count} dollar bars")
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# ── 4. Memory guard ──
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print("\n4. Memory Guard")
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print("=" * 40)
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# Test memory guard independently (don't import server.py — has hardcoded paths)
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import gc
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import os as _os
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MEM_SOFT_LIMIT = 256 * 1024 * 1024
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MEM_HARD_LIMIT = 512 * 1024 * 1024
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def check_memory():
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try:
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with open("/proc/self/status") as f:
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for line in f:
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if line.startswith("VmRSS:"):
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rss_kb = int(line.split()[1])
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rss = rss_kb * 1024
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if rss > MEM_HARD_LIMIT:
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_os._exit(1)
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if rss > MEM_SOFT_LIMIT:
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gc.collect()
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return
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except Exception:
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pass
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check_memory() # Should not throw
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assert MEM_HARD_LIMIT == 512 * 1024 * 1024
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assert MEM_SOFT_LIMIT == 256 * 1024 * 1024
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print(f" ✅ Memory guard: soft={MEM_SOFT_LIMIT//1024//1024}MB hard={MEM_HARD_LIMIT//1024//1024}MB")
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# ── 5. Dashboard API (optional) ──
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print("\n5. Dashboard API")
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print("=" * 40)
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try:
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import requests
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r = requests.get("https://ftdt.io/cv/api/backtests/historical", timeout=10)
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assert r.status_code == 200
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data = r.json()
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assert len(data) >= 33, f"Expected 33+ backtests, got {len(data)}"
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spx = [x for x in data if x["strategy"] == "SPX Mean Reversion"]
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assert len(spx) >= 1
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print(f" ✅ Historical API: {len(data)} backtests ({len(spx)} SPX)")
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except Exception as e:
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print(f" ⚠️ API unreachable: {e}")
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# ── 6. Summary ──
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print("\n" + "=" * 40)
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print("ALL TESTS PASSED ✅")
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print("=" * 40)
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Block a user