Files
hyper/clp_hedger/clp_scalper_hedger.py

735 lines
33 KiB
Python

import os
import time
import logging
import sys
import math
import json
import threading
from dotenv import load_dotenv
from web3 import Web3
# --- FIX: Add project root to sys.path to import local modules ---
current_dir = os.path.dirname(os.path.abspath(__file__))
project_root = os.path.dirname(current_dir)
sys.path.append(project_root)
# Now we can import from root
from logging_utils import setup_logging
from eth_account import Account
from hyperliquid.exchange import Exchange
from hyperliquid.info import Info
from hyperliquid.utils import constants
# Load environment variables from .env in current directory
dotenv_path = os.path.join(current_dir, '.env')
if os.path.exists(dotenv_path):
load_dotenv(dotenv_path)
else:
# Fallback to default search
load_dotenv()
setup_logging("normal", "SCALPER_HEDGER")
# --- CONFIGURATION ---
COIN_SYMBOL = "ETH"
CHECK_INTERVAL = 4 # Optimized for speed (was 5)
LEVERAGE = 5 # 3x Leverage
STATUS_FILE = "hedge_status.json"
RPC_URL = os.environ.get("MAINNET_RPC_URL") # Required for Uniswap Monitor
# Uniswap V3 Pool (Arbitrum WETH/USDC 0.05%)
UNISWAP_POOL_ADDRESS = "0xC31E54c7a869B9FcBEcc14363CF510d1c41fa443"
UNISWAP_POOL_ABI = json.loads('[{"inputs":[],"name":"slot0","outputs":[{"internalType":"uint160","name":"sqrtPriceX96","type":"uint160"},{"internalType":"int24","name":"tick","type":"int24"},{"internalType":"uint16","name":"observationIndex","type":"uint16"},{"internalType":"uint16","name":"observationCardinality","type":"uint16"},{"internalType":"uint16","name":"observationCardinalityNext","type":"uint16"},{"internalType":"uint8","name":"feeProtocol","type":"uint8"},{"internalType":"bool","name":"unlocked","type":"bool"}],"stateMutability":"view","type":"function"}]')
# --- STRATEGY ZONES (Percent of Range Width) ---
# Bottom Hedge Zone: Covers entire range (0.0 to 1.5) -> Always Active
ZONE_BOTTOM_HEDGE_LIMIT = 1
# Close Zone: Disabled (Set > 1.0)
ZONE_CLOSE_START = 10.0
ZONE_CLOSE_END = 11.0
# Top Hedge Zone: Disabled/Redundant
ZONE_TOP_HEDGE_START = 10.0
# --- ORDER SETTINGS ---
PRICE_BUFFER_PCT = 0.0001 # 0.2% price move triggers order update (Relaxed for cost)
MIN_THRESHOLD_ETH = 0.0025 # Minimum trade size in ETH (~$60, Reduced frequency)
MIN_ORDER_VALUE_USD = 10.0 # Minimum order value for API safety
class UniswapPriceMonitor:
def __init__(self, rpc_url, pool_address):
self.w3 = Web3(Web3.HTTPProvider(rpc_url))
self.pool_contract = self.w3.eth.contract(address=pool_address, abi=UNISWAP_POOL_ABI)
self.latest_price = None
self.running = True
self.thread = threading.Thread(target=self._loop, daemon=True)
self.thread.start()
def _loop(self):
logging.info("Uniswap Monitor Started.")
while self.running:
try:
slot0 = self.pool_contract.functions.slot0().call()
sqrt_price_x96 = slot0[0]
# Price = (sqrtPriceX96 / 2^96)^2 * 10^(18-6) (WETH/USDC)
# But typically WETH is token1? Let's verify standard Arbitrum Pool.
# 0xC31E... Token0=WETH, Token1=USDC.
# Price = (sqrt / 2^96)^2 * (10^12) -> This gives USDC per ETH? No, Token1/Token0.
# Wait, usually Token0 is WETH (18) and Token1 is USDC (6).
# P = (1.0001^tick) * 10^(decimals0 - decimals1)? No.
# Standard conversion: Price = (sqrtRatioX96 / Q96) ** 2
# Adjusted for decimals: Price = Price_raw / (10**(Dec0 - Dec1)) ? No.
# Price (Quote/Base) = (sqrt / Q96)^2 * 10^(BaseDec - QuoteDec)
# Let's rely on standard logic: Price = (sqrt / 2^96)^2 * 10^(12) for ETH(18)/USDC(6)
raw_price = (sqrt_price_x96 / (2**96)) ** 2
price = raw_price * (10**(18-6)) # 10^12
# If Token0 is WETH, price is USDC per WETH.
# Note: If the pool is inverted (USDC/WETH), we invert.
# On Arb, WETH is usually Token0?
# 0x82aF... < 0xaf88... (WETH < USDC). So WETH is Token0.
# Price is Token1 per Token0.
self.latest_price = 1 / price if price < 1 else price # Sanity check, ETH should be > 2000
except Exception as e:
# logging.error(f"Uniswap Monitor Error: {e}")
pass
time.sleep(5)
def get_price(self):
return self.latest_price
def get_active_automatic_position():
if not os.path.exists(STATUS_FILE):
return None
try:
with open(STATUS_FILE, 'r') as f:
data = json.load(f)
for entry in data:
if entry.get('type') == 'AUTOMATIC' and entry.get('status') == 'OPEN':
return entry
except Exception as e:
logging.error(f"ERROR reading status file: {e}")
return None
def update_position_zones_in_json(token_id, zones_data):
"""Updates the active position in JSON with calculated zone prices and formats the entry."""
if not os.path.exists(STATUS_FILE): return
try:
with open(STATUS_FILE, 'r') as f:
data = json.load(f)
updated = False
for i, entry in enumerate(data):
if entry.get('type') == 'AUTOMATIC' and entry.get('status') == 'OPEN' and entry.get('token_id') == token_id:
# Merge Zones
for k, v in zones_data.items():
entry[k] = v
# Format & Reorder
open_ts = entry.get('timestamp_open', int(time.time()))
opened_str = time.strftime('%H:%M %d/%m/%y', time.localtime(open_ts))
# Reconstruct Dict in Order
new_entry = {
"type": entry.get('type'),
"token_id": entry.get('token_id'),
"opened": opened_str,
"status": entry.get('status'),
"entry_price": round(entry.get('entry_price', 0), 2),
"target_value": round(entry.get('target_value', 0), 2),
# Amounts might be string or float or int. Ensure float.
"amount0_initial": round(float(entry.get('amount0_initial', 0)), 4),
"amount1_initial": round(float(entry.get('amount1_initial', 0)), 2),
"range_upper": round(entry.get('range_upper', 0), 2),
"zone_top_start_price": entry.get('zone_top_start_price'),
"zone_close_top_price": entry.get('zone_close_top_price'),
"zone_close_bottom_price": entry.get('zone_close_bottom_price'),
"zone_bottom_limit_price": entry.get('zone_bottom_limit_price'),
"range_lower": round(entry.get('range_lower', 0), 2),
"static_long": entry.get('static_long', 0.0),
"timestamp_open": open_ts,
"timestamp_close": entry.get('timestamp_close')
}
data[i] = new_entry
updated = True
break
if updated:
with open(STATUS_FILE, 'w') as f:
json.dump(data, f, indent=2)
logging.info(f"Updated JSON with Formatted Zone Prices for Position {token_id}")
except Exception as e:
logging.error(f"Error updating JSON zones: {e}")
def round_to_sig_figs(x, sig_figs=5):
if x == 0: return 0.0
return round(x, sig_figs - int(math.floor(math.log10(abs(x)))) - 1)
def round_to_sz_decimals(amount, sz_decimals=4):
return round(abs(amount), sz_decimals)
class HyperliquidStrategy:
def __init__(self, entry_amount0, entry_amount1, target_value, entry_price, low_range, high_range, start_price, static_long=0.0):
self.entry_amount0 = entry_amount0
self.entry_amount1 = entry_amount1
self.target_value = target_value
self.entry_price = entry_price
self.low_range = low_range
self.high_range = high_range
self.static_long = static_long
self.start_price = start_price
self.gap = max(0.0, entry_price - start_price)
self.recovery_target = entry_price + (2 * self.gap)
self.current_mode = "NORMAL"
self.last_switch_time = 0
logging.info(f"Strategy Init. Start Px: {start_price:.2f} | Gap: {self.gap:.2f} | Recovery Tgt: {self.recovery_target:.2f}")
try:
sqrt_P = math.sqrt(entry_price)
sqrt_Pa = math.sqrt(low_range)
sqrt_Pb = math.sqrt(high_range)
self.L = 0.0
# Method 1: Use Amount0 (WETH)
if entry_amount0 > 0:
# If amount is huge (Wei), scale it. If small (ETH), use as is.
if entry_amount0 > 1000: amount0_eth = entry_amount0 / 10**18
else: amount0_eth = entry_amount0
denom0 = (1/sqrt_P) - (1/sqrt_Pb)
if denom0 > 0.00000001:
self.L = amount0_eth / denom0
logging.info(f"Calculated L from Amount0: {self.L:.4f}")
# Method 2: Use Amount1 (USDC)
if self.L == 0.0 and entry_amount1 > 0:
if entry_amount1 > 100000: amount1_usdc = entry_amount1 / 10**6
else: amount1_usdc = entry_amount1
denom1 = sqrt_P - sqrt_Pa
if denom1 > 0.00000001:
self.L = amount1_usdc / denom1
logging.info(f"Calculated L from Amount1: {self.L:.4f}")
# Method 3: Fallback Heuristic
if self.L == 0.0:
logging.warning("Amounts missing or 0. Using Target Value Heuristic.")
max_eth_heuristic = target_value / low_range
denom_h = (1/sqrt_Pa) - (1/sqrt_Pb)
if denom_h > 0:
self.L = max_eth_heuristic / denom_h
logging.info(f"Calculated L from Target Value: {self.L:.4f}")
else:
logging.error("Critical: Denominator 0 in Heuristic. Invalid Range?")
self.L = 0.0
except Exception as e:
logging.error(f"Error calculating liquidity: {e}")
sys.exit(1)
def get_pool_delta(self, current_price):
if current_price >= self.high_range: return 0.0
if current_price <= self.low_range:
sqrt_Pa = math.sqrt(self.low_range)
sqrt_Pb = math.sqrt(self.high_range)
return self.L * ((1/sqrt_Pa) - (1/sqrt_Pb))
sqrt_P = math.sqrt(current_price)
sqrt_Pb = math.sqrt(self.high_range)
return self.L * ((1/sqrt_P) - (1/sqrt_Pb))
def calculate_rebalance(self, current_price, current_short_position_size):
pool_delta = self.get_pool_delta(current_price)
# --- Over-Hedge Logic ---
overhedge_pct = 0.0
range_width = self.high_range - self.low_range
if range_width > 0:
price_pct = (current_price - self.low_range) / range_width
# If below 0.8 (80%) of range
if price_pct < 0.8:
# Formula: 0.75% boost for every 0.1 drop below 0.8
# Example: At 0.6 (60%), diff is 0.2. (0.2/0.1)*0.0075 = 0.015 (1.5%)
overhedge_pct = ((0.8 - max(0.0, price_pct)) / 0.1) * 0.0075
raw_target_short = pool_delta + self.static_long
# Apply Boost
adjusted_target_short = raw_target_short * (1.0 + overhedge_pct)
target_short_size = adjusted_target_short
diff = target_short_size - abs(current_short_position_size)
return {
"current_price": current_price,
"pool_delta": pool_delta,
"target_short": target_short_size,
"current_short": abs(current_short_position_size),
"diff": diff,
"action": "SELL" if diff > 0 else "BUY",
"mode": "OVERHEDGE" if overhedge_pct > 0 else "NORMAL",
"overhedge_pct": overhedge_pct
}
class ScalperHedger:
def __init__(self):
self.private_key = os.environ.get("SCALPER_AGENT_PK")
self.vault_address = os.environ.get("MAIN_WALLET_ADDRESS")
if not self.private_key:
logging.error("No SCALPER_AGENT_PK found in .env")
sys.exit(1)
self.account = Account.from_key(self.private_key)
self.info = Info(constants.MAINNET_API_URL, skip_ws=True)
self.exchange = Exchange(self.account, constants.MAINNET_API_URL, account_address=self.vault_address)
try:
logging.info(f"Setting leverage to {LEVERAGE}x (Cross)...")
self.exchange.update_leverage(LEVERAGE, COIN_SYMBOL, is_cross=True)
except Exception as e:
logging.error(f"Failed to update leverage: {e}")
self.strategy = None
self.sz_decimals = self._get_sz_decimals(COIN_SYMBOL)
self.active_position_id = None
self.active_order = None
# --- Start Uniswap Monitor ---
self.uni_monitor = UniswapPriceMonitor(RPC_URL, UNISWAP_POOL_ADDRESS)
logging.info(f"Scalper Hedger initialized. Agent: {self.account.address}")
def _init_strategy(self, position_data):
try:
entry_amount0 = position_data.get('amount0_initial', 0)
entry_amount1 = position_data.get('amount1_initial', 0)
target_value = position_data.get('target_value', 50.0)
entry_price = position_data['entry_price']
lower = position_data['range_lower']
upper = position_data['range_upper']
static_long = position_data.get('static_long', 0.0)
start_price = self.get_market_price(COIN_SYMBOL)
if start_price is None:
logging.warning("Waiting for initial price to start strategy...")
return
self.strategy = HyperliquidStrategy(
entry_amount0=entry_amount0,
entry_amount1=entry_amount1,
target_value=target_value,
entry_price=entry_price,
low_range=lower,
high_range=upper,
start_price=start_price,
static_long=static_long
)
logging.info(f"Strategy Initialized for Position {position_data['token_id']}.")
self.active_position_id = position_data['token_id']
except Exception as e:
logging.error(f"Failed to init strategy: {e}")
self.strategy = None
def _get_sz_decimals(self, coin):
try:
meta = self.info.meta()
for asset in meta["universe"]:
if asset["name"] == coin:
return asset["szDecimals"]
return 4
except: return 4
def get_order_book_levels(self, coin):
try:
l2_snapshot = self.info.l2_snapshot(coin)
if l2_snapshot and 'levels' in l2_snapshot:
bids = l2_snapshot['levels'][0]
asks = l2_snapshot['levels'][1]
if bids and asks:
best_bid = float(bids[0]['px'])
best_ask = float(asks[0]['px'])
mid = (best_bid + best_ask) / 2
return {'bid': best_bid, 'ask': best_ask, 'mid': mid}
# Fallback
px = self.get_market_price(coin)
return {'bid': px, 'ask': px, 'mid': px}
except:
px = self.get_market_price(coin)
return {'bid': px, 'ask': px, 'mid': px}
def get_market_price(self, coin):
try:
mids = self.info.all_mids()
if coin in mids: return float(mids[coin])
except: pass
return None
def get_order_book_mid(self, coin):
try:
l2_snapshot = self.info.l2_snapshot(coin)
if l2_snapshot and 'levels' in l2_snapshot:
bids = l2_snapshot['levels'][0]
asks = l2_snapshot['levels'][1]
if bids and asks:
best_bid = float(bids[0]['px'])
best_ask = float(asks[0]['px'])
return (best_bid + best_ask) / 2
return self.get_market_price(coin)
except:
return self.get_market_price(coin)
def get_funding_rate(self, coin):
try:
meta, asset_ctxs = self.info.meta_and_asset_ctxs()
for i, asset in enumerate(meta["universe"]):
if asset["name"] == coin:
return float(asset_ctxs[i]["funding"])
return 0.0
except: return 0.0
def get_current_position(self, coin):
try:
user_state = self.info.user_state(self.vault_address or self.account.address)
for pos in user_state["assetPositions"]:
if pos["position"]["coin"] == coin:
return {
'size': float(pos["position"]["szi"]),
'pnl': float(pos["position"]["unrealizedPnl"])
}
return {'size': 0.0, 'pnl': 0.0}
except: return {'size': 0.0, 'pnl': 0.0}
def get_open_orders(self):
try:
return self.info.open_orders(self.vault_address or self.account.address)
except: return []
def cancel_order(self, coin, oid):
logging.info(f"Cancelling order {oid}...")
try:
return self.exchange.cancel(coin, oid)
except Exception as e:
logging.error(f"Error cancelling order: {e}")
def place_limit_order(self, coin, is_buy, size, price):
logging.info(f"🕒 PLACING LIMIT: {coin} {'BUY' if is_buy else 'SELL'} {size} @ {price:.2f}")
reduce_only = is_buy
try:
# Gtc order (Maker) -> Changed to Alo to force Maker
limit_px = round_to_sig_figs(price, 5)
# Use 'Alo' (Add Liquidity Only) to ensure Maker rebate.
# If price crosses spread, order is rejected (safe cost-wise).
order_result = self.exchange.order(coin, is_buy, size, limit_px, {"limit": {"tif": "Alo"}}, reduce_only=reduce_only)
status = order_result["status"]
if status == "ok":
response_data = order_result["response"]["data"]
if "statuses" in response_data:
status_obj = response_data["statuses"][0]
if "error" in status_obj:
logging.error(f"Order API Error: {status_obj['error']}")
return None
# Parse OID from nested structure
oid = None
if "resting" in status_obj:
oid = status_obj["resting"]["oid"]
elif "filled" in status_obj:
oid = status_obj["filled"]["oid"]
logging.info("Order filled immediately.")
if oid:
logging.info(f"✅ Limit Order Placed: OID {oid}")
return oid
else:
logging.warning(f"Order placed but OID not found in: {status_obj}")
return None
else:
logging.error(f"Order Failed: {order_result}")
return None
except Exception as e:
logging.error(f"Exception during trade: {e}")
return None
def manage_orders(self):
"""
Checks open orders.
Returns: True if an order exists and is valid (don't trade), False if no order (can trade).
"""
open_orders = self.get_open_orders()
my_orders = [o for o in open_orders if o['coin'] == COIN_SYMBOL]
if not my_orders:
self.active_order = None
return False
if len(my_orders) > 1:
logging.warning("Multiple open orders found. Cancelling all for safety.")
for o in my_orders:
self.cancel_order(COIN_SYMBOL, o['oid'])
self.active_order = None
return False
order = my_orders[0]
oid = order['oid']
order_price = float(order['limitPx'])
current_mid = self.get_order_book_mid(COIN_SYMBOL)
pct_diff = abs(current_mid - order_price) / order_price
if pct_diff > PRICE_BUFFER_PCT:
logging.info(f"Price moved {pct_diff*100:.3f}% > {PRICE_BUFFER_PCT*100}%. Cancelling/Replacing order {oid}.")
self.cancel_order(COIN_SYMBOL, oid)
self.active_order = None
return False
else:
logging.info(f"Pending Order {oid} @ {order_price:.2f} is within range ({pct_diff*100:.3f}%). Waiting.")
return True
def close_all_positions(self):
logging.info("Closing all positions (Market Order)...")
try:
# Cancel open orders first
open_orders = self.get_open_orders()
for o in open_orders:
if o['coin'] == COIN_SYMBOL:
self.cancel_order(COIN_SYMBOL, o['oid'])
price = self.get_market_price(COIN_SYMBOL)
pos_data = self.get_current_position(COIN_SYMBOL)
current_pos = pos_data['size']
if current_pos == 0: return
is_buy = current_pos < 0
final_size = round_to_sz_decimals(abs(current_pos), self.sz_decimals)
if final_size == 0: return
price = self.get_market_price(COIN_SYMBOL) # Get mid price for safety fallback
pos_data = self.get_current_position(COIN_SYMBOL)
current_pos = pos_data['size']
if current_pos == 0: return
is_buy_to_close = current_pos < 0
final_size = round_to_sz_decimals(abs(current_pos), self.sz_decimals)
if final_size == 0: return
# --- ATTEMPT MAKER CLOSE (Alo) ---
try:
book_levels = self.get_order_book_levels(COIN_SYMBOL)
TICK_SIZE = 0.1
if is_buy_to_close: # We are short, need to buy to close
maker_price = book_levels['bid'] - TICK_SIZE
else: # We are long, need to sell to close
maker_price = book_levels['ask'] + TICK_SIZE
logging.info(f"Attempting MAKER CLOSE (Alo): {COIN_SYMBOL} {'BUY' if is_buy_to_close else 'SELL'} {final_size} @ {maker_price:.2f}")
order_result = self.exchange.order(COIN_SYMBOL, is_buy_to_close, final_size, round_to_sig_figs(maker_price, 5), {"limit": {"tif": "Alo"}}, reduce_only=True)
status = order_result["status"]
if status == "ok":
response_data = order_result["response"]["data"]
if "statuses" in response_data and "resting" in response_data["statuses"][0]:
logging.info(f"✅ MAKER CLOSE Order Placed (Alo). OID: {response_data['statuses'][0]['resting']['oid']}")
return
elif "statuses" in response_data and "filled" in response_data["statuses"][0]:
logging.info(f"✅ MAKER CLOSE Order Filled (Alo). OID: {response_data['statuses'][0]['filled']['oid']}")
return
else:
# Fallback if Alo didn't rest or fill immediately in an expected way
logging.warning(f"Alo order result unclear: {order_result}. Falling back to Market Close.")
elif status == "error":
if "Post only order would have immediately matched" in order_result["response"]["data"]["statuses"][0].get("error", ""):
logging.warning("Alo order would have immediately matched. Falling back to Market Close for guaranteed fill.")
else:
logging.error(f"Alo order failed with unknown error: {order_result}. Falling back to Market Close.")
else:
logging.warning(f"Alo order failed with status {status}. Falling back to Market Close.")
except Exception as e:
logging.error(f"Exception during Alo close attempt: {e}. Falling back to Market Close.", exc_info=True)
# --- FALLBACK TO MARKET CLOSE (Ioc) for guaranteed fill ---
logging.info(f"Falling back to MARKET CLOSE (Ioc): {COIN_SYMBOL} {'BUY' if is_buy_to_close else 'SELL'} {final_size} @ {price:.2f} (guaranteed)")
self.exchange.order(COIN_SYMBOL, is_buy_to_close, final_size, round_to_sig_figs(price * (1.05 if is_buy_to_close else 0.95), 5), {"limit": {"tif": "Ioc"}}, reduce_only=True)
self.active_position_id = None
logging.info("✅ MARKET CLOSE Order Placed (Ioc).")
except Exception as e:
logging.error(f"Error closing positions: {e}", exc_info=True)
def run(self):
logging.info(f"Starting Scalper Monitor Loop. Interval: {CHECK_INTERVAL}s")
while True:
try:
active_pos = get_active_automatic_position()
# Check Global Enable Switch
if not active_pos or not active_pos.get('hedge_enabled', True):
if self.strategy is not None:
logging.info("Hedge Disabled or Position Closed. Closing remaining positions.")
self.close_all_positions()
self.strategy = None
else:
pass
time.sleep(CHECK_INTERVAL)
continue
if self.strategy is None or self.active_position_id != active_pos['token_id']:
logging.info(f"New position {active_pos['token_id']} detected or strategy not initialized. Initializing strategy.")
self._init_strategy(active_pos)
if self.strategy is None:
time.sleep(CHECK_INTERVAL)
continue
if self.strategy is None: continue
# --- ORDER MANAGEMENT ---
if self.manage_orders():
time.sleep(CHECK_INTERVAL)
continue
# 2. Market Data
book_levels = self.get_order_book_levels(COIN_SYMBOL)
price = book_levels['mid']
if price is None:
time.sleep(5)
continue
funding_rate = self.get_funding_rate(COIN_SYMBOL)
pos_data = self.get_current_position(COIN_SYMBOL)
current_pos_size = pos_data['size']
current_pnl = pos_data['pnl']
# --- SPREAD MONITOR LOG ---
uni_price = self.uni_monitor.get_price()
spread_text = ""
if uni_price:
diff = price - uni_price
pct = (diff / uni_price) * 100
spread_text = f" | Sprd: {pct:+.2f}% (H:{price:.0f}/U:{uni_price:.0f})"
# 3. Calculate Logic
calc = self.strategy.calculate_rebalance(price, current_pos_size)
diff_abs = abs(calc['diff'])
# --- LOGGING OVERHEDGE ---
oh_text = ""
if calc.get('overhedge_pct', 0) > 0:
oh_text = f" | 🔥 OH: +{calc['overhedge_pct']*100:.2f}%"
# 4. Dynamic Threshold Calculation
sqrt_Pa = math.sqrt(self.strategy.low_range)
sqrt_Pb = math.sqrt(self.strategy.high_range)
max_potential_eth = self.strategy.L * ((1/sqrt_Pa) - (1/sqrt_Pb))
# Use MIN_THRESHOLD_ETH from config
rebalance_threshold = max(MIN_THRESHOLD_ETH, max_potential_eth * 0.05)
# 5. Determine Hedge Zone
clp_low_range = self.strategy.low_range
clp_high_range = self.strategy.high_range
range_width = clp_high_range - clp_low_range
# Calculate Prices for Zones
# If config > 9, set to None (Disabled Zone)
zone_bottom_limit_price = (clp_low_range + (range_width * ZONE_BOTTOM_HEDGE_LIMIT)) if ZONE_BOTTOM_HEDGE_LIMIT <= 9 else None
zone_close_bottom_price = (clp_low_range + (range_width * ZONE_CLOSE_START)) if ZONE_CLOSE_START <= 9 else None
zone_close_top_price = (clp_low_range + (range_width * ZONE_CLOSE_END)) if ZONE_CLOSE_END <= 9 else None
zone_top_start_price = (clp_low_range + (range_width * ZONE_TOP_HEDGE_START)) if ZONE_TOP_HEDGE_START <= 9 else None
# Update JSON with zone prices if they are None (initially set by uniswap_manager.py)
if active_pos.get('zone_bottom_limit_price') is None:
update_position_zones_in_json(active_pos['token_id'], {
'zone_top_start_price': round(zone_top_start_price, 2) if zone_top_start_price else None,
'zone_close_top_price': round(zone_close_top_price, 2) if zone_close_top_price else None,
'zone_close_bottom_price': round(zone_close_bottom_price, 2) if zone_close_bottom_price else None,
'zone_bottom_limit_price': round(zone_bottom_limit_price, 2) if zone_bottom_limit_price else None
})
# Check Zones (Handle None)
# If zone price is None, condition fails safe (False)
in_close_zone = False
if zone_close_bottom_price is not None and zone_close_top_price is not None:
in_close_zone = (price >= zone_close_bottom_price and price <= zone_close_top_price)
in_hedge_zone = False
if zone_bottom_limit_price is not None and price <= zone_bottom_limit_price:
in_hedge_zone = True
if zone_top_start_price is not None and price >= zone_top_start_price:
in_hedge_zone = True
# --- Execute Logic ---
if in_close_zone:
logging.info(f"ZONE: CLOSE ({price:.2f} in {zone_close_bottom_price:.2f}-{zone_close_top_price:.2f}). PNL: ${current_pnl:.2f}. Closing all hedge positions.")
self.close_all_positions()
time.sleep(CHECK_INTERVAL)
continue
elif in_hedge_zone:
# HEDGE NORMALLY
if diff_abs > rebalance_threshold:
trade_size = round_to_sz_decimals(diff_abs, self.sz_decimals)
min_trade_size = MIN_ORDER_VALUE_USD / price
if trade_size < min_trade_size:
logging.info(f"Idle. Trade size {trade_size} < Min Order Size {min_trade_size:.4f} (${MIN_ORDER_VALUE_USD:.2f}). PNL: ${current_pnl:.2f}{spread_text}{oh_text}")
elif trade_size > 0:
logging.info(f"⚡ THRESHOLD TRIGGERED ({diff_abs:.4f} >= {rebalance_threshold:.4f}). In Hedge Zone. PNL: ${current_pnl:.2f}{spread_text}{oh_text}")
# Execute Passively for Alo
# Force 1 tick offset (0.1) away from BBO to ensure rounding doesn't cause cross
# Sell at Ask + 0.1, Buy at Bid - 0.1
TICK_SIZE = 0.1
is_buy = (calc['action'] == "BUY")
if is_buy:
exec_price = book_levels['bid'] - TICK_SIZE
else:
exec_price = book_levels['ask'] + TICK_SIZE
self.place_limit_order(COIN_SYMBOL, is_buy, trade_size, exec_price)
else:
logging.info(f"Trade size rounds to 0. Skipping. PNL: ${current_pnl:.2f}{spread_text}{oh_text}")
else:
logging.info(f"Idle. Diff {diff_abs:.4f} < Threshold {rebalance_threshold:.4f}. In Hedge Zone. PNL: ${current_pnl:.2f}{spread_text}{oh_text}")
else:
# MIDDLE ZONE (IDLE)
pct_position = (price - clp_low_range) / range_width
logging.info(f"Idle. In Middle Zone ({pct_position*100:.1f}%). PNL: ${current_pnl:.2f}{spread_text}{oh_text}. No Actions.")
time.sleep(CHECK_INTERVAL)
except KeyboardInterrupt:
logging.info("Stopping Hedger...")
self.close_all_positions()
break
except Exception as e:
logging.error(f"Loop Error: {e}", exc_info=True)
time.sleep(10)
if __name__ == "__main__":
hedger = ScalperHedger()
hedger.run()