Listen... I've been working my butt off.
unified_bot_logic.py
This bot runs one complete trade cycle at a time and keeps the process guarded from start to finish.
place_order.py.doge_coordination_audit.log
import time
import requests
import os
import json
from fetch_market import get_orderbook_top
from place_order import (
_get_total_open_orders,
buy_peakecoin_gas,
cancel_order,
cancel_oldest_order,
get_balance,
get_open_orders,
place_order,
)
from rc_intelligence import evaluate_tx_window
from strategy import StrategyState
# Feeder accounts that place DOGE buy support orders (non-DOGE bots).
DOGE_FEEDER_ACCOUNTS = {
"paulmoon410",
"dr-animation",
"strangedad",
"peakecoin",
"peakecoin.bnb",
"peakecoin.matic",
}
# Price tuning for cross-bot DOGE coordination.
FEEDER_DOGE_BUY_DISCOUNT_FROM_ASK = 0.01 # 1% below ask by default
DOGE_FEEDER_SELL_UNDERCUT = 0.00005 # 0.005% below feeder bid to increase fill odds
DOGE_REBUY_PREMIUM_OVER_BID = 0.00005 # 0.005% above bid for replenishment
MIN_DOGE_COORD_QTY = 0.0 # allow all DOGE coordination sizes (no minimum)
DOGE_PRICE_STEP = 0.00000001
DOGE_BASE_PROFIT_RATIO = 0.0005
DOGE_PROFIT_RATIO_STEP = 0.00025
DOGE_MAX_PROFIT_RATIO = 0.01
DOGE_HOLD_CYCLES = 50
DOGE_QUICK_REBUY_CYCLES = 1
TOKEN_MICRO_BUY_QTY = 0.00000001
MICRO_BUY_MIN_PROFIT_RATIO = 0.0005 # 0.05% minimum edge for all micro buys
DOGE_CYCLE_MARKET_BUY_QTY = 0.1
PEK_CYCLE_BUY_QTY = 0.00000001
DOGE_STRICT_COORD_ONLY = os.environ.get(
"DOGE_STRICT_COORD_ONLY",
"true",
).lower() in ("1", "true", "yes")
STRICT_DOGE_COORD_CANCEL_UNMATCHED_FEEDER = os.environ.get(
"STRICT_DOGE_COORD_CANCEL_UNMATCHED_FEEDER",
"true",
).lower() in ("1", "true", "yes")
PRICE_TICK = 0.00000001
LTC_PROFIT_STATE_FILE = os.path.join(os.path.dirname(__file__), ".ltc_profit_layer_state.json")
LTC_BUFFER_MIN = 0.0001
LTC_BUFFER_MAX = 0.003
LTC_BUFFER_STEP_UP = 0.00005
LTC_BUFFER_STEP_DOWN = 0.00003
LTC_BUFFER_START = 0.0005
def _round_price(value):
return round(max(0.0, float(value)), 8)
def _load_ltc_profit_state():
default = {"buffer_pct": LTC_BUFFER_START, "last_spread_pct": 0.0, "updated_ts": 0}
try:
if os.path.exists(LTC_PROFIT_STATE_FILE):
with open(LTC_PROFIT_STATE_FILE, "r") as f:
data = json.load(f)
if isinstance(data, dict):
default.update(data)
except Exception:
pass
try:
default["buffer_pct"] = float(default.get("buffer_pct", LTC_BUFFER_START))
except Exception:
default["buffer_pct"] = LTC_BUFFER_START
default["buffer_pct"] = max(LTC_BUFFER_MIN, min(LTC_BUFFER_MAX, default["buffer_pct"]))
return default
def _save_ltc_profit_state(state):
try:
with open(LTC_PROFIT_STATE_FILE, "w") as f:
json.dump(state, f, indent=2)
except Exception:
pass
def _compute_ltc_profit_buffer(bid, ask):
state = _load_ltc_profit_state()
buffer_pct = float(state.get("buffer_pct", LTC_BUFFER_START))
spread_pct = ((float(ask) - float(bid)) / float(ask)) if float(ask) > 0 and float(ask) > float(bid) else 0.0
if spread_pct >= max(0.0005, buffer_pct * 4):
buffer_pct = min(LTC_BUFFER_MAX, buffer_pct + LTC_BUFFER_STEP_UP)
elif spread_pct <= max(0.00015, buffer_pct * 1.5):
buffer_pct = max(LTC_BUFFER_MIN, buffer_pct - LTC_BUFFER_STEP_DOWN)
state["buffer_pct"] = round(buffer_pct, 8)
state["last_spread_pct"] = round(spread_pct, 8)
state["updated_ts"] = int(time.time())
_save_ltc_profit_state(state)
return buffer_pct, spread_pct
def _apply_ltc_profit_layer(buy_quote, sell_quote, bid, ask, buffer_pct):
half_buffer = float(buffer_pct) / 2.0
layered_buy = float(buy_quote) * (1 - half_buffer)
layered_sell = float(sell_quote) * (1 + half_buffer)
# Keep maker-side posture against current top-of-book.
if ask > PRICE_TICK:
layered_buy = min(layered_buy, ask - PRICE_TICK)
if bid > 0:
layered_sell = max(layered_sell, bid + PRICE_TICK)
layered_buy = round(max(0.0, layered_buy), 8)
layered_sell = round(max(0.0, layered_sell), 8)
if layered_sell <= layered_buy:
return buy_quote, sell_quote
return layered_buy, layered_sell
def _default_doge_profit_state():
return {
"phase": "ramp_up",
"current_ratio": DOGE_BASE_PROFIT_RATIO,
"hold_cycles_remaining": 0,
"last_realized_ratio": 0.0,
"last_market_spread_ratio": 0.0,
"pending_rebuy": None,
}
def _ensure_doge_coord_state_shape(state):
normalized = {
"pause_until": 0,
"paused": False,
"reason": "",
"updated_ts": 0,
"profit_window": _default_doge_profit_state(),
}
if isinstance(state, dict):
normalized.update(state)
profit_window = normalized.get("profit_window")
if not isinstance(profit_window, dict):
profit_window = {}
merged_profit = _default_doge_profit_state()
merged_profit.update(profit_window)
normalized["profit_window"] = merged_profit
return normalized
def _compute_feeder_doge_buy_price(doge_bid, doge_ask):
"""Default to 1% below ask; when too tight, fall back to market bid."""
if doge_ask <= 0:
return _round_price(doge_bid) if doge_bid > 0 else 0.0
discounted_ask_price = doge_ask * (1 - FEEDER_DOGE_BUY_DISCOUNT_FROM_ASK)
if doge_bid > 0 and discounted_ask_price <= doge_bid:
proximity_price = doge_ask - DOGE_PRICE_STEP
if proximity_price <= doge_bid:
# Tight spread fallback: place at bid instead of skipping.
return _round_price(doge_bid)
return _round_price(proximity_price)
return _round_price(discounted_ask_price)
def _classify_feeder_price_skip(doge_bid, doge_ask, feeder_buy_price):
if feeder_buy_price > 0:
return "ok"
if doge_ask <= 0 and doge_bid <= 0:
return "quote-unavailable"
if doge_ask > 0 and doge_bid > 0 and (doge_ask - doge_bid) <= DOGE_PRICE_STEP:
return "spread-too-tight"
return "price-guard"
def _compute_doge_rebuy_price(doge_bid, doge_ask, previous_sell_price):
"""Rebuy must stay strictly below the prior DOGE sale price."""
if previous_sell_price <= 0:
return 0.0
profit_ratio = _get_current_doge_profit_ratio()
target_profit_price = previous_sell_price * (1 - profit_ratio)
capped_sell_price = previous_sell_price - DOGE_PRICE_STEP
if capped_sell_price <= 0:
return 0.0
if doge_bid > 0:
candidate = doge_bid * (1 + DOGE_REBUY_PREMIUM_OVER_BID)
elif doge_ask > 0:
candidate = doge_ask - DOGE_PRICE_STEP
else:
candidate = 0.0
if candidate <= 0:
return 0.0
if doge_ask > 0:
candidate = min(candidate, doge_ask - DOGE_PRICE_STEP)
candidate = min(candidate, target_profit_price)
candidate = min(candidate, capped_sell_price)
if candidate <= 0:
return 0.0
return _round_price(candidate)
def _get_current_doge_profit_ratio():
state = _load_doge_coord_state()
try:
ratio = float(state.get("profit_window", {}).get("current_ratio", DOGE_BASE_PROFIT_RATIO))
except Exception:
ratio = DOGE_BASE_PROFIT_RATIO
return max(DOGE_BASE_PROFIT_RATIO, min(DOGE_MAX_PROFIT_RATIO, ratio))
def _get_matching_open_doge_buy(account_name, target_price, target_qty, nodes=None):
if nodes is None:
nodes = [
"https://api.hive-engine.com/rpc/contracts",
"https://herpc.dtools.dev",
"https://engine.rishipanthee.com/rpc",
"https://api2.hive-engine.com/rpc/contracts",
]
try:
orders = get_open_orders(account_name, token="SWAP.DOGE", nodes=nodes)
except Exception:
orders = []
for order in orders:
side = (order.get("type") or order.get("side") or "").lower()
if side != "buy":
continue
try:
price = float(order.get("price") or order.get("tokenPrice") or 0)
qty = float(order.get("quantity") or order.get("tokenQuantity") or 0)
except Exception:
continue
if abs(price - float(target_price)) <= 0.00000002 and qty >= float(target_qty) * 0.5:
return order
return None
def _reset_doge_profit_window(reason, bot_label, state=None):
if state is None:
state = _load_doge_coord_state()
profit_window = state["profit_window"]
profit_window.update(_default_doge_profit_state())
state["updated_ts"] = int(time.time())
_save_doge_coord_state(state)
print(f"[{bot_label}] DOGE profit window reset: reason={reason} ratio={profit_window['current_ratio']:.6f}")
def _record_doge_rebuy_submission(sale_price, rebuy_price, qty, bot_label, reason, state=None):
if state is None:
state = _load_doge_coord_state()
profit_window = state["profit_window"]
realized_ratio = 0.0
if sale_price > 0:
realized_ratio = max(0.0, (float(sale_price) - float(rebuy_price)) / float(sale_price))
profit_window["pending_rebuy"] = {
"sale_price": round(float(sale_price), 8),
"rebuy_price": round(float(rebuy_price), 8),
"qty": round(float(qty), 8),
"reason": reason,
"submitted_ts": int(time.time()),
"cycles_open": 0,
"target_ratio": round(realized_ratio, 8),
}
profit_window["last_realized_ratio"] = realized_ratio
state["updated_ts"] = int(time.time())
_save_doge_coord_state(state)
print(
f"[{bot_label}] DOGE profit window armed: phase={profit_window['phase']} "
f"target_ratio={realized_ratio:.6f} current_ratio={profit_window['current_ratio']:.6f}"
)
def _advance_doge_profit_window(bot_label, nodes):
state = _load_doge_coord_state()
profit_window = state["profit_window"]
current_ratio = max(DOGE_BASE_PROFIT_RATIO, min(DOGE_MAX_PROFIT_RATIO, float(profit_window.get("current_ratio", DOGE_BASE_PROFIT_RATIO))))
phase = profit_window.get("phase", "ramp_up")
pending_rebuy = profit_window.get("pending_rebuy")
market = _get_market_with_retries("SWAP.DOGE", attempts=2, delay_seconds=1.0)
doge_bid = float(market.get("highestBid", 0)) if market else 0.0
doge_ask = float(market.get("lowestAsk", 0)) if market else 0.0
spread_ratio = ((doge_ask - doge_bid) / doge_ask) if doge_ask > 0 and doge_ask > doge_bid else 0.0
profit_window["last_market_spread_ratio"] = round(max(0.0, spread_ratio), 8)
if phase == "hold":
if 0 < spread_ratio < current_ratio:
_reset_doge_profit_window("spread-contracted", bot_label, state=state)
return _load_doge_coord_state()["profit_window"]
remaining = int(profit_window.get("hold_cycles_remaining", DOGE_HOLD_CYCLES) or 0)
remaining = max(0, remaining - 1)
profit_window["hold_cycles_remaining"] = remaining
if remaining == 0:
profit_window["phase"] = "decay"
print(f"[{bot_label}] DOGE profit window entering decay at ratio={current_ratio:.6f}")
elif phase == "decay":
current_ratio = max(DOGE_BASE_PROFIT_RATIO, current_ratio - DOGE_PROFIT_RATIO_STEP)
profit_window["current_ratio"] = round(current_ratio, 8)
if pending_rebuy:
matching_order = _get_matching_open_doge_buy(
DOGE_EXECUTION_ACCOUNT,
pending_rebuy.get("rebuy_price", 0),
pending_rebuy.get("qty", 0),
nodes=nodes,
)
if matching_order:
pending_rebuy["cycles_open"] = int(pending_rebuy.get("cycles_open", 0) or 0) + 1
if profit_window.get("phase") == "ramp_up" and pending_rebuy["cycles_open"] > DOGE_QUICK_REBUY_CYCLES:
profit_window["phase"] = "hold"
profit_window["hold_cycles_remaining"] = DOGE_HOLD_CYCLES
print(
f"[{bot_label}] DOGE profit window hold started: ratio={current_ratio:.6f} "
f"rebuy_open_cycles={pending_rebuy['cycles_open']}"
)
else:
quick_fill = int(pending_rebuy.get("cycles_open", 0) or 0) <= DOGE_QUICK_REBUY_CYCLES
realized_ratio = float(pending_rebuy.get("target_ratio", 0.0) or 0.0)
if quick_fill:
next_ratio = min(DOGE_MAX_PROFIT_RATIO, max(current_ratio, realized_ratio) + DOGE_PROFIT_RATIO_STEP)
profit_window["current_ratio"] = round(next_ratio, 8)
profit_window["phase"] = "ramp_up"
print(
f"[{bot_label}] DOGE profit window increased: {current_ratio:.6f} -> {next_ratio:.6f} "
f"after quick rebuy fill"
)
elif profit_window.get("phase") == "ramp_up":
profit_window["phase"] = "hold"
profit_window["hold_cycles_remaining"] = DOGE_HOLD_CYCLES
print(f"[{bot_label}] DOGE profit window hold confirmed after slow rebuy fill.")
profit_window["pending_rebuy"] = None
state["updated_ts"] = int(time.time())
_save_doge_coord_state(state)
return profit_window
# DOGE execution account used to cross-fill feeder DOGE bids in tandem.
DOGE_EXECUTION_ACCOUNT = os.environ.get("DOGE_EXECUTION_ACCOUNT", "mmoonn")
DOGE_EXECUTION_ACTIVE_KEY = os.environ.get(
"DOGE_EXECUTION_ACTIVE_KEY",
"",
)
DOGE_COORD_STATE_FILE = os.path.join(os.path.dirname(__file__), ".doge_coordination_state.json")
DOGE_COORD_AUDIT_FILE = os.path.join(os.path.dirname(__file__), ".doge_coordination_audit.log")
def _append_doge_audit(event):
"""Append JSONL audit records for DOGE coordination verification."""
try:
record = {"ts": int(time.time()), **event}
with open(DOGE_COORD_AUDIT_FILE, "a", encoding="utf-8") as f:
f.write(json.dumps(record) + "\n")
except Exception:
pass
def _load_doge_coord_state():
try:
if os.path.exists(DOGE_COORD_STATE_FILE):
with open(DOGE_COORD_STATE_FILE, "r") as f:
data = json.load(f)
if isinstance(data, dict):
return _ensure_doge_coord_state_shape(data)
except Exception:
pass
return _ensure_doge_coord_state_shape({})
def _save_doge_coord_state(state):
try:
with open(DOGE_COORD_STATE_FILE, "w") as f:
json.dump(_ensure_doge_coord_state_shape(state), f, indent=2)
except Exception:
pass
def _set_doge_pause(wait_seconds, reason):
now = int(time.time())
state = _load_doge_coord_state()
state["paused"] = True
state["pause_until"] = now + max(30, int(wait_seconds))
state["reason"] = reason
state["updated_ts"] = now
_save_doge_coord_state(state)
def _clear_doge_pause():
now = int(time.time())
state = _load_doge_coord_state()
state["paused"] = False
state["pause_until"] = 0
state["reason"] = ""
state["updated_ts"] = now
_save_doge_coord_state(state)
def _is_doge_pause_active():
state = _load_doge_coord_state()
if not state.get("paused", False):
return False, state
now = int(time.time())
if now >= int(state.get("pause_until", 0) or 0):
return False, state
return True, state
def _sync_doge_pause_with_rc():
"""Auto-clear pause once DOGE execution account can place sell-side tx again."""
decision = evaluate_tx_window(DOGE_EXECUTION_ACCOUNT, action="sell")
allow = bool(decision.get("allow", False))
mode = decision.get("mode")
if allow:
_clear_doge_pause()
return False, decision
if mode in ("critical", "low", "cooldown"):
_set_doge_pause(int(decision.get("wait_seconds", 120) or 120), f"rc-{mode}")
return True, decision
def _is_matching_feeder_buy_visible(feeder_account, target_price, min_qty=0.0, retries=8, delay_seconds=2.0):
"""Wait for a feeder DOGE buy to appear in openOrders or buyBook before cross-filling it."""
nodes = [
"https://api.hive-engine.com/rpc/contracts",
"https://herpc.dtools.dev",
"https://engine.rishipanthee.com/rpc",
"https://api2.hive-engine.com/rpc/contracts",
]
def _matches(price, qty):
try:
return abs(float(price) - float(target_price)) <= 0.00000002 and float(qty) >= float(min_qty) * 0.5
except Exception:
return False
for attempt in range(retries):
try:
open_orders = get_open_orders(feeder_account, token="SWAP.DOGE", nodes=nodes)
except Exception:
open_orders = []
for order in open_orders:
side = (order.get("type") or order.get("side") or "").lower()
price = order.get("price") or order.get("tokenPrice") or 0
qty = order.get("quantity") or order.get("tokenQuantity") or 0
if side == "buy" and _matches(price, qty):
return True
for node in nodes:
try:
payload = {
"jsonrpc": "2.0",
"method": "find",
"params": {
"contract": "market",
"table": "buyBook",
"query": {"account": feeder_account, "symbol": "SWAP.DOGE"},
"limit": 1000,
},
"id": 1,
}
resp = requests.post(node, json=payload, timeout=10)
if resp.status_code != 200:
continue
orders = resp.json().get("result", [])
if not isinstance(orders, list):
continue
for order in orders:
price = order.get("price", 0)
qty = order.get("quantity", order.get("tokenQuantity", 0)) or 0
if _matches(price, qty):
return True
except Exception:
continue
if attempt < retries - 1:
time.sleep(delay_seconds)
return False
def _attempt_doge_cross_fill(feeder_account, feeder_price, feeder_qty, nodes, bot_label):
"""Attempt immediate DOGE-account sell into feeder account's DOGE buy support order."""
if feeder_account == DOGE_EXECUTION_ACCOUNT:
return False
if feeder_account not in DOGE_FEEDER_ACCOUNTS:
print(
f"[{bot_label}] DOGE cross-fill refused: feeder account {feeder_account} "
f"is not in whitelist."
)
return False
# Final pre-trade guard: confirm feeder still has a matching DOGE buy open.
# Use short retries and allow partial remaining quantity to avoid false negatives on propagation.
matching_whitelisted_order = _is_matching_feeder_buy_visible(
feeder_account,
feeder_price,
min_qty=max(0.0, float(feeder_qty) * 0.1),
retries=3,
delay_seconds=1.0,
)
if not matching_whitelisted_order:
print(
f"[{bot_label}] DOGE cross-fill refused: no matching whitelisted feeder order "
f"for account={feeder_account} price={float(feeder_price):.8f}."
)
return False
if DOGE_EXECUTION_ACTIVE_KEY in ("", "your_active_key", None):
print(f"[{bot_label}] DOGE cross-fill skipped: DOGE execution key not configured.")
return False
try:
doge_balance = get_balance(DOGE_EXECUTION_ACCOUNT, "SWAP.DOGE")
except Exception:
doge_balance = 0.0
if doge_balance <= 0:
print(f"[{bot_label}] DOGE cross-fill skipped: {DOGE_EXECUTION_ACCOUNT} has no SWAP.DOGE balance.")
return False
sell_qty = max(0.0, min(float(feeder_qty), doge_balance * 0.15))
if sell_qty <= 0:
print(f"[{bot_label}] DOGE cross-fill skipped: no sellable DOGE quantity.")
return False
if sell_qty < MIN_DOGE_COORD_QTY:
print(
f"[{bot_label}] DOGE cross-fill skipped: quantity {sell_qty:.8f} "
f"below minimum {MIN_DOGE_COORD_QTY:.8f}."
)
return False
sell_price = round(float(feeder_price) * (1 - DOGE_FEEDER_SELL_UNDERCUT), 8)
if sell_price <= 0:
sell_price = round(float(feeder_price), 8)
placed = place_order(
DOGE_EXECUTION_ACCOUNT,
"SWAP.DOGE",
sell_price,
sell_qty,
order_type="sell",
active_key=DOGE_EXECUTION_ACTIVE_KEY,
nodes=nodes,
skip_profit_filters=True,
)
if placed:
_clear_doge_pause()
print(
f"[{bot_label}] DOGE tandem sell submitted from {DOGE_EXECUTION_ACCOUNT}: "
f"{sell_qty:.8f} SWAP.DOGE at {sell_price:.8f} (feeder={feeder_account})"
)
return sell_price
else:
blocked, decision = _sync_doge_pause_with_rc()
if blocked:
print(
f"[{bot_label}] DOGE coordination paused: mode={decision.get('mode')} "
f"wait={decision.get('wait_seconds')}s"
)
print(
f"[{bot_label}] DOGE tandem sell skipped/failed from {DOGE_EXECUTION_ACCOUNT} "
f"at {sell_price:.8f} (feeder={feeder_account})."
)
return 0.0
def _place_doge_rebuy_after_sell(account_name, active_key, nodes, qty, rebuy_price, bot_label, reason, sale_price=0.0):
"""Place one DOGE rebuy after a confirmed sell, not as a standalone periodic buy."""
if qty <= 0 or rebuy_price <= 0:
return False
if qty < MIN_DOGE_COORD_QTY:
print(
f"[{bot_label}] DOGE rebuy skipped ({reason}): quantity {qty:.8f} "
f"below minimum {MIN_DOGE_COORD_QTY:.8f}."
)
return False
if active_key in ("", "your_active_key", None):
print(f"[{bot_label}] DOGE rebuy skipped ({reason}): active key not configured.")
return False
if sale_price > 0 and rebuy_price >= (sale_price - DOGE_PRICE_STEP):
print(
f"[{bot_label}] DOGE rebuy blocked ({reason}): rebuy {rebuy_price:.8f} "
f"is not below sale {sale_price:.8f}."
)
return False
placed = place_order(
account_name,
"SWAP.DOGE",
rebuy_price,
qty,
order_type="buy",
active_key=active_key,
nodes=nodes,
skip_profit_filters=True,
)
if placed:
print(
f"[{bot_label}] DOGE immediate rebuy submitted ({reason}): "
f"{qty:.8f} SWAP.DOGE at {rebuy_price:.8f}"
)
return True
print(f"[{bot_label}] DOGE immediate rebuy skipped ({reason}) (filters/RC/duplicate).")
return False
def _get_highest_feeder_doge_buy(excluded_account=None, token="SWAP.DOGE"):
"""Return highest open DOGE buy price from feeder accounts, excluding caller account."""
nodes = [
"https://api.hive-engine.com/rpc/contracts",
"https://herpc.dtools.dev",
"https://engine.rishipanthee.com/rpc",
"https://api2.hive-engine.com/rpc/contracts",
]
highest = 0.0
for node in nodes:
try:
payload = {
"jsonrpc": "2.0",
"method": "find",
"params": {
"contract": "market",
"table": "buyBook",
"query": {"symbol": token},
"limit": 1000,
},
"id": 1,
}
resp = requests.post(node, json=payload, timeout=10)
if resp.status_code != 200:
continue
orders = resp.json().get("result", [])
if not isinstance(orders, list):
continue
for order in orders:
account = order.get("account")
if account not in DOGE_FEEDER_ACCOUNTS:
continue
if excluded_account and account == excluded_account:
continue
try:
price = float(order.get("price", 0))
if price > highest:
highest = price
except Exception:
continue
return highest
except Exception:
continue
return highest
def _get_market_with_retries(token, attempts=3, delay_seconds=1.5):
"""Fetch top-of-book with short retries to smooth transient RPC gaps."""
last_market = None
for attempt in range(attempts):
try:
last_market = get_orderbook_top(token)
except Exception:
last_market = None
if last_market:
return last_market
if attempt < attempts - 1:
time.sleep(delay_seconds)
return last_market
def _attempt_token_micro_buy(account_name, token, active_key, nodes, ask_price, bot_label, support_sell_price=0.0):
if active_key in ("", "your_active_key", None):
print(f"[{bot_label}] {token} micro buy skipped: HIVE_ACTIVE_KEY not set.")
return False
if ask_price <= 0:
print(f"[{bot_label}] {token} micro buy skipped: market ask unavailable.")
return False
if support_sell_price <= 0:
print(f"[{bot_label}] {token} micro buy skipped: no profitable sell support quote.")
return False
max_buy_price = round(float(support_sell_price) / (1 + MICRO_BUY_MIN_PROFIT_RATIO), 8)
if max_buy_price <= 0:
print(f"[{bot_label}] {token} micro buy skipped: computed max buy price invalid ({max_buy_price}).")
return False
if ask_price > max_buy_price:
print(
f"[{bot_label}] {token} micro buy skipped: ask {ask_price:.8f} exceeds "
f"max profitable buy {max_buy_price:.8f} (sell_support={float(support_sell_price):.8f}, "
f"target={MICRO_BUY_MIN_PROFIT_RATIO:.6f})."
)
return False
placed = place_order(
account_name,
token,
max_buy_price,
TOKEN_MICRO_BUY_QTY,
order_type="buy",
active_key=active_key,
nodes=nodes,
skip_profit_filters=True,
)
if placed:
print(
f"[{bot_label}] {token} guarded micro buy submitted: qty={TOKEN_MICRO_BUY_QTY:.8f} "
f"at {max_buy_price:.8f} (sell_support={float(support_sell_price):.8f}, "
f"target={MICRO_BUY_MIN_PROFIT_RATIO:.6f})"
)
else:
print(f"[{bot_label}] {token} micro buy skipped/failed.")
return bool(placed)
def _attempt_doge_cycle_market_buy(account_name, active_key, nodes, ask_price, bot_label, feeder_bid=0.0, market_bid=0.0):
"""Submit a guarded 0.1 SWAP.DOGE cycle buy only when a profitable re-sell path exists."""
if active_key in ("", "your_active_key", None):
print(f"[{bot_label}] DOGE 0.1 market buy skipped: HIVE_ACTIVE_KEY not set.")
return False
if ask_price <= 0:
print(f"[{bot_label}] DOGE 0.1 market buy skipped: market ask unavailable.")
return False
exit_support_price = max(float(feeder_bid), float(market_bid))
if exit_support_price <= 0:
print(f"[{bot_label}] DOGE cycle buy skipped: no feeder or market bid support available.")
return False
target_profit_ratio = _get_current_doge_profit_ratio()
max_buy_price = round(exit_support_price * (1 - target_profit_ratio), 8)
if max_buy_price <= 0:
print(f"[{bot_label}] DOGE cycle buy skipped: computed buy ceiling invalid ({max_buy_price}).")
return False
if ask_price > max_buy_price:
print(
f"[{bot_label}] DOGE cycle buy skipped: ask {ask_price:.8f} exceeds "
f"max profitable buy {max_buy_price:.8f} (support_bid={exit_support_price:.8f}, "
f"target={target_profit_ratio:.6f})."
)
return False
placed = place_order(
account_name,
"SWAP.DOGE",
max_buy_price,
DOGE_CYCLE_MARKET_BUY_QTY,
order_type="buy",
active_key=active_key,
nodes=nodes,
skip_profit_filters=True,
)
if placed:
print(
f"[{bot_label}] DOGE guarded cycle buy submitted: "
f"qty={DOGE_CYCLE_MARKET_BUY_QTY:.8f} at {max_buy_price:.8f} "
f"(support_bid={exit_support_price:.8f}, target={target_profit_ratio:.6f})"
)
else:
print(f"[{bot_label}] DOGE 0.1 market buy skipped/failed.")
return bool(placed)
def _attempt_pek_cycle_buy(account_name, active_key, nodes, bot_label):
"""Submit a fixed PEK micro-buy once per normal bot cycle."""
if active_key in ("", "your_active_key", None, "Your Active Key Here"):
print(f"[{bot_label}] PEK cycle buy skipped: HIVE_ACTIVE_KEY not set.")
return False
try:
placed = buy_peakecoin_gas(
account_name,
active_key=active_key,
nodes=nodes,
pek_amount=PEK_CYCLE_BUY_QTY,
)
except Exception as e:
print(f"[{bot_label}] PEK cycle buy exception: {e}")
return False
if placed:
print(f"[{bot_label}] PEK cycle buy submitted: qty={PEK_CYCLE_BUY_QTY:.8f}")
else:
print(f"[{bot_label}] PEK cycle buy skipped/failed.")
return bool(placed)
def _cancel_matching_feeder_buy(account_name, active_key, nodes, target_price, target_qty, bot_label):
"""Cancel matching feeder buy if tandem sell could not be submitted."""
matching_order = _get_matching_open_doge_buy(
account_name,
target_price,
target_qty,
nodes=nodes,
)
if not matching_order:
print(
f"[{bot_label}] Feeder cleanup: no matching feeder buy visible to cancel "
f"(price={float(target_price):.8f}, qty={float(target_qty):.8f})."
)
return False
txid = str(matching_order.get("txId") or matching_order.get("txid") or "")
if not txid:
print(f"[{bot_label}] Feeder cleanup: matching order missing txId, cannot cancel.")
return False
cancelled = cancel_order(
account_name=account_name,
order_id=txid,
verbose=False,
nodes=nodes,
active_key=active_key,
side="buy",
)
if cancelled:
print(f"[{bot_label}] Feeder cleanup: cancelled unmatched feeder buy txId={txid}.")
else:
print(f"[{bot_label}] Feeder cleanup: failed to cancel unmatched feeder buy txId={txid}.")
return bool(cancelled)
def _get_valid_market_with_retries(token, attempts=4, delay_seconds=1.25):
"""Fetch market until bid/ask are both present and non-inverted."""
last_market = None
for attempt in range(attempts):
market = _get_market_with_retries(token, attempts=1, delay_seconds=0)
if market:
last_market = market
try:
bid = float(market.get("highestBid", 0) or 0)
ask = float(market.get("lowestAsk", 0) or 0)
except Exception:
bid = 0.0
ask = 0.0
if bid > 0 and ask > 0 and ask >= bid:
return market
if attempt < attempts - 1:
time.sleep(delay_seconds)
return last_market
def run_ltc_style_logic(account_name, token, active_key, nodes, state_file, bot_label):
"""Run the LTC bot trading logic for any token/account.
This intentionally mirrors the LTC flow so all bots can share one strategy.
"""
can_transact = active_key not in ("", "your_active_key", None)
state = StrategyState(state_file)
open_orders_debug = get_open_orders(account_name, token)
print(f"[{bot_label}] Open orders for {token}: {len(open_orders_debug)}")
open_count = _get_total_open_orders(account_name)
print(f"[{bot_label}] Total open orders (all tokens): {open_count}")
if open_count >= 190:
print(f"[{bot_label}] Open orders >= 190: cancelling 3 oldest and skipping ALL buys.")
if not can_transact:
print(f"[{bot_label}] Cancel skipped: HIVE_ACTIVE_KEY not set.")
else:
cancelled_txids = set()
for _ in range(3):
cancelled = cancel_oldest_order(
account_name,
None,
active_key=active_key,
nodes=nodes,
excluded_txids=cancelled_txids,
force_cancel=True,
)
if not cancelled:
break
time.sleep(5)
print("==============================\n")
return
elif open_count >= 100:
print(f"[{bot_label}] Open orders at {open_count}. Between 100 and 189: No cancels, normal trading allowed.")
else:
print(f"[{bot_label}] Open orders < 100: placing new orders only.")
_attempt_pek_cycle_buy(
account_name=account_name,
active_key=active_key,
nodes=nodes,
bot_label=bot_label,
)
market = _get_valid_market_with_retries(token, attempts=4, delay_seconds=1.25)
if not market:
print(f"[{bot_label}] Market fetch failed for {token}. Skipping this cycle.")
print("==============================\n")
return
print(f"[{bot_label}] Market fetch success for {token}.")
bid = float(market.get("highestBid", 0))
ask = float(market.get("lowestAsk", 0))
if bid <= 0 or ask <= 0:
print(
f"[{bot_label}] Market book incomplete for {token} (bid={bid}, ask={ask}). "
f"Skipping this cycle."
)
print("==============================\n")
return
if ask < bid:
print(
f"[{bot_label}] Market book inverted for {token} (bid={bid}, ask={ask}). "
f"Skipping this cycle."
)
print("==============================\n")
return
spread = ask - bid
print(f"[{bot_label}] Bid: {bid}, Ask: {ask}")
hive_balance = get_balance(account_name, "SWAP.HIVE")
token_balance = get_balance(account_name, token)
print(f"[{bot_label}] Balances: HIVE={hive_balance:.4f}, TOKEN={token_balance:.4f}")
token_price = ask if ask > 0 else bid
buy_quote, sell_quote = state.get_adaptive_quote(
bid,
ask,
spread,
token_balance,
hive_balance,
token_price,
)
if token == "SWAP.LTC":
ltc_buffer_pct, ltc_spread_pct = _compute_ltc_profit_buffer(bid, ask)
buy_quote, sell_quote = _apply_ltc_profit_layer(buy_quote, sell_quote, bid, ask, ltc_buffer_pct)
print(
f"[{bot_label}] LTC profit layer: buffer={ltc_buffer_pct:.6f} "
f"spread={ltc_spread_pct:.6f} -> BUY={buy_quote}, SELL={sell_quote}"
)
# Keep DOGE coordination lock aligned with DOGE execution account RC state.
doge_paused, pause_state = _is_doge_pause_active()
doge_rebuy_quote = 0.0
if doge_paused:
# try quick recovery check; clear lock automatically if DOGE sell path is available again
doge_paused, _ = _sync_doge_pause_with_rc()
if doge_paused:
print(
f"[{bot_label}] DOGE coordination paused until {pause_state.get('pause_until')} "
f"reason={pause_state.get('reason')}"
)
# DOGE bot coordination mode:
# - Do not run generic LTC strategy.
# - Sell into feeder bots' DOGE buy support bids.
# - Rebuy slightly above bid, but never cross the ask.
doge_feeder_bid = 0.0
if token == "SWAP.DOGE":
feeder_bid = _get_highest_feeder_doge_buy(excluded_account=account_name, token=token)
doge_feeder_bid = feeder_bid
rebuy_quote = _compute_doge_rebuy_price(bid, ask, sell_quote if sell_quote > 0 else feeder_bid)
doge_rebuy_quote = rebuy_quote
buy_quote = rebuy_quote if rebuy_quote > 0 else (round(bid, 8) if bid > 0 else buy_quote)
if feeder_bid > 0:
feeder_sell = feeder_bid * (1 - DOGE_FEEDER_SELL_UNDERCUT)
sell_quote = round(max(feeder_sell, buy_quote), 8)
print(
f"[{bot_label}] Feeder-coordination: feeder_bid={feeder_bid:.8f} "
f"sell_quote={sell_quote:.8f} buy_quote={buy_quote:.8f}"
)
else:
sell_quote = 0
print(f"[{bot_label}] Feeder-coordination: no feeder bid available, sell leg skipped.")
# Keep LTC's aggressive DOGE side-buy behavior in all bots.
if bid > 0 and token != "SWAP.DOGE":
if doge_paused:
print(f"[{bot_label}] Feeder DOGE buy skipped: DOGE coordination pause active.")
else:
one_percent_hive = hive_balance * 0.01
if one_percent_hive > 0:
doge_bid = 0
doge_ask = 0
try:
doge_market = _get_market_with_retries("SWAP.DOGE", attempts=3, delay_seconds=1.5)
doge_bid = float(doge_market.get("highestBid", 0)) if doge_market else 0
doge_ask = float(doge_market.get("lowestAsk", 0)) if doge_market else 0
except Exception:
pass
# Feeder bots support DOGE bot by posting buy orders near the ask (maker-side).
feeder_buy_price = _compute_feeder_doge_buy_price(doge_bid, doge_ask)
if feeder_buy_price > 0 and doge_bid > 0 and abs(feeder_buy_price - doge_bid) <= DOGE_PRICE_STEP:
print(
f"[{bot_label}] Feeder DOGE tight-spread fallback: using market bid {feeder_buy_price:.8f}."
)
# Strict maker guard: do not place if this could execute immediately as taker.
if doge_ask > 0 and feeder_buy_price >= doge_ask:
print(
f"[{bot_label}] Feeder DOGE buy skipped: computed price {feeder_buy_price:.8f} "
f"is not below ask {doge_ask:.8f}."
)
feeder_buy_price = 0
if feeder_buy_price > 0:
market_buy_qty = round(one_percent_hive / feeder_buy_price, 8)
if market_buy_qty < MIN_DOGE_COORD_QTY:
print(
f"[{bot_label}] Feeder DOGE buy skipped: quantity {market_buy_qty:.8f} "
f"below minimum {MIN_DOGE_COORD_QTY:.8f}."
)
else:
if not can_transact:
print(f"[{bot_label}] Aggressive market buy skipped: HIVE_ACTIVE_KEY not set.")
else:
try:
placed = place_order(
account_name,
"SWAP.DOGE",
feeder_buy_price,
market_buy_qty,
order_type="buy",
active_key=active_key,
nodes=nodes,
skip_profit_filters=True,
)
if placed:
print(
f"[{bot_label}] Feeder DOGE buy: {market_buy_qty} SWAP.DOGE at {feeder_buy_price:.8f} "
f"(near ask, 1% of SWAP.HIVE)"
)
if _is_matching_feeder_buy_visible(account_name, feeder_buy_price, market_buy_qty):
sold_price = _attempt_doge_cross_fill(
feeder_account=account_name,
feeder_price=feeder_buy_price,
feeder_qty=market_buy_qty,
nodes=nodes,
bot_label=bot_label,
)
if sold_price > 0:
doge_bid_for_rebuy = float(doge_market.get("highestBid", 0)) if doge_market else 0
doge_ask_for_rebuy = float(doge_market.get("lowestAsk", 0)) if doge_market else 0
rebuy_price = _compute_doge_rebuy_price(
doge_bid_for_rebuy,
doge_ask_for_rebuy,
sold_price,
)
rebought = _place_doge_rebuy_after_sell(
account_name=DOGE_EXECUTION_ACCOUNT,
active_key=DOGE_EXECUTION_ACTIVE_KEY,
nodes=nodes,
qty=market_buy_qty,
rebuy_price=rebuy_price,
bot_label=bot_label,
reason=f"tandem:{account_name}",
sale_price=sold_price,
)
_append_doge_audit(
{
"event": "feeder_tandem",
"source_bot": bot_label,
"feeder_account": account_name,
"doge_execution_account": DOGE_EXECUTION_ACCOUNT,
"qty": round(float(market_buy_qty), 8),
"feeder_buy_price": round(float(feeder_buy_price), 8),
"tandem_sell_submitted": bool(sold_price > 0),
"rebuy_submitted": bool(rebought),
"tandem_sell_price": round(float(sold_price), 8) if sold_price > 0 else 0,
"rebuy_price": round(float(rebuy_price), 8) if rebuy_price > 0 else 0,
}
)
if sold_price > 0 and rebought:
print(
f"[{bot_label}] DOGE FLOW VERIFIED: tandem sell to feeder {account_name} "
f"and immediate DOGE rebuy both submitted."
)
elif sold_price > 0 and not rebought:
print(
f"[{bot_label}] DOGE FLOW PARTIAL: tandem sell submitted, rebuy not submitted."
)
elif STRICT_DOGE_COORD_CANCEL_UNMATCHED_FEEDER:
_cancel_matching_feeder_buy(
account_name=account_name,
active_key=active_key,
nodes=nodes,
target_price=feeder_buy_price,
target_qty=market_buy_qty,
bot_label=bot_label,
)
else:
print(
f"[{bot_label}] DOGE tandem sell skipped: feeder buy not yet visible in buyBook."
)
if STRICT_DOGE_COORD_CANCEL_UNMATCHED_FEEDER:
_cancel_matching_feeder_buy(
account_name=account_name,
active_key=active_key,
nodes=nodes,
target_price=feeder_buy_price,
target_qty=market_buy_qty,
bot_label=bot_label,
)
else:
print(f"[{bot_label}] Feeder DOGE buy skipped (filters/RC/duplicate).")
except Exception as e:
print(f"[{bot_label}] Aggressive market buy exception: {e}")
else:
skip_reason = _classify_feeder_price_skip(doge_bid, doge_ask, feeder_buy_price)
if skip_reason == "spread-too-tight":
print(
f"[{bot_label}] Feeder DOGE buy skipped: spread too tight for maker bid "
f"(bid={doge_bid}, ask={doge_ask})."
)
elif skip_reason == "quote-unavailable":
print(
f"[{bot_label}] Feeder DOGE buy skipped: SWAP.DOGE quote unavailable "
f"(bid={doge_bid}, ask={doge_ask})."
)
else:
print(
f"[{bot_label}] Feeder DOGE buy skipped: price guard blocked placement "
f"(bid={doge_bid}, ask={doge_ask})."
)
print(f"[{bot_label}] Quotes: BUY={buy_quote}, SELL={sell_quote}")
if token == "SWAP.DOGE":
buy_qty = round(hive_balance * 0.01 / buy_quote, 8) if buy_quote > 0 else 0
sell_qty = round(token_balance * 0.15, 8)
else:
buy_qty = round(hive_balance * 0.20 / buy_quote, 8) if buy_quote > 0 else 0
sell_qty = round(token_balance * 0.20, 8)
open_orders = get_open_orders(account_name, token)
duplicate_buy = any(o.get("type") == "buy" and float(o.get("price", 0)) == buy_quote for o in open_orders)
duplicate_sell = any(o.get("type") == "sell" and float(o.get("price", 0)) == sell_quote for o in open_orders)
if token == "SWAP.MATIC":
duplicate_buy = False
duplicate_sell = False
if token == "SWAP.DOGE":
print(f"[{bot_label}] DOGE buy leg uses immediate rebuy-after-sell only (no standalone buy order).")
if token == "SWAP.DOGE" and doge_paused:
print(f"[{bot_label}] BUY skipped: DOGE coordination pause active until sell path recovers.")
elif token == "SWAP.DOGE":
pass
elif buy_qty > 0 and not duplicate_buy and can_transact:
try:
order_id = place_order(
account_name,
token,
buy_quote,
buy_qty,
order_type="buy",
active_key=active_key,
nodes=nodes,
)
if order_id:
state.track_order(order_id, "buy", buy_quote, buy_qty)
print(f"[{bot_label}] BUY order submitted: {buy_qty} {token} at {buy_quote}")
except Exception:
pass
elif buy_qty > 0 and not duplicate_buy and not can_transact:
print(f"[{bot_label}] BUY skipped: HIVE_ACTIVE_KEY not set.")
if sell_qty > 0 and sell_quote > 0 and not duplicate_sell and can_transact:
if token == "SWAP.DOGE" and sell_qty < MIN_DOGE_COORD_QTY:
print(
f"[{bot_label}] SELL skipped: DOGE quantity {sell_qty:.8f} "
f"below minimum {MIN_DOGE_COORD_QTY:.8f}."
)
print(f"[{bot_label}] Trade cycle for {token} complete.")
print("==============================\n")
return
if token == "SWAP.DOGE" and DOGE_STRICT_COORD_ONLY and doge_rebuy_quote <= 0:
print(
f"[{bot_label}] SELL skipped: strict DOGE mode requires a profitable rebuy quote "
f"before selling into feeder support bids."
)
print(f"[{bot_label}] Trade cycle for {token} complete.")
print("==============================\n")
return
try:
order_id = place_order(
account_name,
token,
sell_quote,
sell_qty,
order_type="sell",
active_key=active_key,
nodes=nodes,
)
if order_id:
state.track_order(order_id, "sell", sell_quote, sell_qty)
print(f"[{bot_label}] SELL order submitted: {sell_qty} {token} at {sell_quote}")
if token == "SWAP.DOGE" and doge_rebuy_quote > 0:
rebought = _place_doge_rebuy_after_sell(
account_name=account_name,
active_key=active_key,
nodes=nodes,
qty=sell_qty,
rebuy_price=doge_rebuy_quote,
bot_label=bot_label,
reason="doge-cycle-sell",
sale_price=sell_quote,
)
_append_doge_audit(
{
"event": "doge_cycle_sell",
"source_bot": bot_label,
"doge_execution_account": account_name,
"qty": round(float(sell_qty), 8),
"sell_price": round(float(sell_quote), 8),
"rebuy_submitted": bool(rebought),
"rebuy_price": round(float(doge_rebuy_quote), 8),
}
)
if rebought:
print(f"[{bot_label}] DOGE FLOW VERIFIED: cycle sell and immediate rebuy both submitted.")
else:
print(f"[{bot_label}] DOGE FLOW PARTIAL: cycle sell submitted, rebuy not submitted.")
except Exception:
pass
elif sell_qty > 0 and sell_quote > 0 and not duplicate_sell and not can_transact:
print(f"[{bot_label}] SELL skipped: HIVE_ACTIVE_KEY not set.")
elif token == "SWAP.DOGE" and sell_quote <= 0:
print(f"[{bot_label}] SELL skipped: no feeder buy support available this cycle.")
# Guarded micro-buy compatibility: only place if minimum-profit edge is available.
if token == "SWAP.DOGE" and DOGE_STRICT_COORD_ONLY:
print(
f"[{bot_label}] Strict DOGE mode active: skipping standalone micro/cycle buys; "
f"coordination sells and profitable rebuys only."
)
else:
_attempt_token_micro_buy(
account_name=account_name,
token=token,
active_key=active_key,
nodes=nodes,
ask_price=ask,
bot_label=bot_label,
support_sell_price=sell_quote,
)
if token == "SWAP.DOGE":
_attempt_doge_cycle_market_buy(
account_name=account_name,
active_key=active_key,
nodes=nodes,
ask_price=ask,
bot_label=bot_label,
feeder_bid=doge_feeder_bid,
market_bid=bid,
)
print(f"[{bot_label}] Trade cycle for {token} complete.")
print("==============================\n")
🤖 PeakeBot — Autonomous Trading System (RC-AWARE)
Independent multi-token trading bot featuring:
RC-aware execution, adaptive delay logic, and self-regulating trade cycles.
📊 Trading bot details:
👉 https://geocities.ws/p/e/peakecoin/trading-bot/peakebot_v0_01.html
💻 Open-source repositories:
👉 https://github.com/paulmoon410
Thanks to and please follow:
For their continued support, guidance, and help expanding the PeakeCoin ecosystem.