BinanceStream_209
♡
Basics
mode: spot
outdated
Methods
_calculate_new_value
buy
check_buy
check_sell
class_init
execute_buy
execute_sell
get
get_pair
get_path
handle_dcm_message
heartbeat
init
init_pair_info
new_candle
new_ob
new_ticker
open_trades
process_message
sell
set
set_ft
set_instance
Other
binance
talipp
5 related strategies (⧉ identical code, ≈ similar name)
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 301 302 303 304 305 306 307 308 309 310 311 312 313 314 315 316 317 318 319 320 321 322 323 324 325 326 327 328 329 330 331 332 333 334 335 336 337 338 339 340 341 342 343 344 345 346 347 348 349 350 351 352 353 354 355 356 357 358 359 360 361 362 363 364 365 366 367 | import time from talipp.indicators.Indicator import Indicator from binance import Client from binance import ThreadedWebsocketManager, ThreadedDepthCacheManager from datetime import datetime, timedelta from freqtrade.strategy.interface import IStrategy, SellCheckTuple, SellType from freqtrade.persistence import Trade from pandas import DataFrame time_map={ "1m":60, "5m":5*60, "15m":15*60, "30m":30*60, "1h":60*60, } keys_map={ "o":1, "h": 2, "l":3, "c":4, "v":5 } _register = {} class BasePairInfo: ft= None last_time_refresh_trade_count=datetime.now()-timedelta(days=60) _data={} last_check = None _open_trades=[] def __init__(self,pair): self.buy_signal=0 self.pair=pair self.sell_signal=0 self.should_buy=False self.should_sell=False self.last_check = datetime.now() @classmethod def get(cls,pair): key=pair.replace("/","") res = cls._data.get(key,None) return res @classmethod def set(cls,pair,val): key=pair.replace("/","") cls._data[key]=val @classmethod def heartbeat(cls): now = datetime.now() if cls.last_check is None: cls.last_check = now return if(now - cls.last_check)>timedelta(minutes=5): for key,val in cls._data.items(): if(now - val.last_check)>timedelta(minutes=5): if BaseIndicator.twm is not None: BaseIndicator.twm.stop() if OrderBook.dcm is not None: OrderBook.dcm.stop() exit(0) cls.last_check = now def open_trades(self,force=False,pair = None): trade_filter = [] trade_filter.append(Trade.is_open.is_(True)) if force or not BasePairInfo._open_trades or (datetime.now()-BasePairInfo.last_time_refresh_trade_count) > timedelta(seconds=20): query = Trade.get_trades() BasePairInfo._open_trades = query.populate_existing().filter(*trade_filter).all() BasePairInfo.last_time_refresh_trade_count=datetime.now() if pair: found_trade = None for trade in BasePairInfo._open_trades : if trade.pair.replace("/","") == pair.replace("/",""): found_trade = trade return found_trade return BasePairInfo._open_trades def execute_sell(self, price, reason): sell_reason=SellCheckTuple(sell_type=reason) with self.ft._sell_lock: trade=self.open_trades(force=True,pair=self.pair) if not trade: return if price is None: price = self.ft.get_sell_rate(trade.pair, True) for a in trade.orders: if a.status == 'open': return if trade and trade.is_open: self.ft.execute_sell(trade,price,sell_reason) try: pass except Exception as e: print(e) def execute_buy(self,price): found_trade=self.open_trades(force=True,pair=self.pair) if found_trade: return stake_amount = self.ft.wallets.get_trade_stake_amount(self.pair) try: self.ft.execute_buy(self.pair,stake_amount,price) except Exception as e: print(e) def buy(self,price=None): if self.ft: self.execute_buy(price) else: self.should_buy=True def check_buy(self): res=self.should_buy self.should_buy=False return res def sell(self,price=None,reason = SellType.SELL_SIGNAL): if self.ft: self.execute_sell(price,reason) else: self.should_sell=True def check_sell(self): res=self.should_sell self.should_sell=False return res @classmethod def set_ft(cls,ft): cls.ft=ft class BinanceStream_209(IStrategy): _pair_info={} _init=False @classmethod def set_instance(cls,inst): cls.instance=inst def new_ob(self,pair_info,ob): pass def new_candle(self,pair_info): pass def init(self): if self._init: return def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame: return dataframe def set_ft(self,ft): self.ft=ft BasePairInfo.set_ft(ft) def heartbeat(self): BasePairInfo.heartbeat() def bot_loop_start(self, **kwargs) -> None: self.init() self.heartbeat() def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame: pair=metadata["pair"] shoud_buy=self.get_pair(pair).check_buy() if shoud_buy: self.unlock_pair(pair) dataframe.loc[dataframe.index.max(),"buy"]=1 else: dataframe.loc[dataframe.index.max(),"buy"]=0 return dataframe def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame: pair=metadata["pair"] shoud_sell=self.get_pair(pair).check_sell() if shoud_sell: dataframe.loc[dataframe.index.max(),"sell"]=1 else: dataframe.loc[dataframe.index.max(),"sell"]=0 return dataframe def get_pair(self,pair): res = BasePairInfo.get(pair) if res is None: BinanceStream.set_instance(self) BasePairInfo.set(pair,BasePairInfo(pair)) self.init_pair_info(BasePairInfo.get(pair)) return BasePairInfo.get(pair) def init_pair_info(self,pair_info): pass def check_buy(self,pair): return BasePairInfo.get(pair).check_buy() def check_sell(self,pair): return BasePairInfo.get(pair).check_sell() def sell(self,pair,price=None,reason = SellType.SELL_SIGNAL): BasePairInfo.get(pair).sell(price,reason) def new_ticker(self,pair_info,ticker): """ Message format: { "e": "kline", // Event type "E": 123456789, // Event time "s": "BNBBTC", // Symbol "k": { "t": 123400000, // Kline start time "T": 123460000, // Kline close time "s": "BNBBTC", // Symbol "i": "1m", // Interval "f": 100, // First trade ID "L": 200, // Last trade ID "o": "0.0010", // Open price "c": "0.0020", // Close price "h": "0.0025", // High price "l": "0.0015", // Low price "v": "1000", // Base asset volume "n": 100, // Number of trades "x": false, // Is this kline closed? "q": "1.0000", // Quote asset volume "V": "500", // Taker buy base asset volume "Q": "0.500", // Taker buy quote asset volume "B": "123456" // Ignore } } """ pass ohlcv=["o","h","l","c","v"] class OrderBook: dcm=None _class_init= False _backtesting=False @classmethod def class_init(cls): cls._class_init=True if not cls._backtesting: cls.dcm = ThreadedDepthCacheManager() cls.dcm.setDaemon(True) cls.dcm.start() def __init__(self,symbol,max_depth=500,currency=None): self.strat=BinanceStream.instance if(OrderBook._class_init == False): OrderBook.class_init() self.symbol=symbol.replace("/","") if currency is not None: self.data_symbol=symbol.split("/")[0]+currency else: self.data_symbol=self.symbol while True: try: self.dcm.start_depth_cache(callback=self.handle_dcm_message, symbol=self.data_symbol,limit=max_depth) break except : print(f"Starting order book for {symbol}.") time.sleep(0.5) def handle_dcm_message(self,depth_cache): t=datetime.fromtimestamp(depth_cache.update_time/1e3) if datetime.now()>(t+timedelta(seconds=1)): return self.cache=depth_cache self.strat.new_ob(self.strat.get_pair(self.symbol),depth_cache) class SimpleIndicator(Indicator): def _calculate_new_value(self): if len(self.input_values) > 0: return self.input_values return None class BaseIndicator: _class_init=False registered={} _backtesting=False not_initialized=True twm=None @classmethod def class_init(cls): cls._class_init=True if not cls._backtesting: cls.twm = ThreadedWebsocketManager() cls.twm.setDaemon(True) cls.twm.start() def _calculate_new_value(self): if len(self.input_values) > 0: return self.input_values return None def __init__(self,symbol,prefetch=True,timeframe="1m",min_hist=100,currency=None): if(BaseIndicator._class_init == False): BaseIndicator.class_init() self.strat=BinanceStream.instance self.symbol=symbol.replace("/","") if currency is not None: self.data_symbol=symbol.split("/")[0]+currency else: self.data_symbol=self.symbol self.prefetch=prefetch self.timeframe =timeframe self.min_hist=min_hist self.path = BaseIndicator.get_path(symbol, timeframe) for f in ohlcv: setattr(self, f, SimpleIndicator()) if not self._backtesting: self.sock=self.twm.start_kline_socket(callback=self.process_message, symbol=self.data_symbol,interval=timeframe) time.sleep(0.5) def process_message(self, msg): if msg['e'] == 'error': print("socket error!!!") else: k=msg["k"] pi=self.strat.get_pair(self.symbol) pi.last_check=datetime.now() if self.not_initialized and self.prefetch: client = Client() tf=time_map[self.timeframe]*1000 end=int(k["t"])+2*tf start=end-tf*self.min_hist res=client.get_klines(symbol=self.data_symbol, interval=self.timeframe,startTime=start,endTime=end) for a in res: for f in ohlcv: val = a[keys_map[f]] getattr(self, f).add_input_value(float(val)) self.strat.new_candle(pi) self.not_initialized = False else: if k["x"]: for f in ohlcv: indicator=getattr(self, f) indicator.add_input_value(float(k[f])) if(len(indicator)>2*self.min_hist): indicator.purge_oldest(self.min_hist) self.strat.new_candle(pi) else: t=datetime.fromtimestamp(int(msg["E"])/1e3) if datetime.now()>(t+timedelta(seconds=1)): return self.strat.new_ticker(pi,k) @staticmethod def get_path(symbol, interval): return f'{symbol.lower()}@kline_{interval}' |
Strategy League — fixed backtest that feeds the ranking
The fixed-params backtest (33 pairs · 20210101-20260101) — the only run that feeds the Strategy League ranking.
Backtests — over a market period
Backtest this strategy over a chosen crypto-cycle period. These don't affect the League ranking, and need that period's candle data downloaded.
Log in or sign up to run backtests.
| Period | Range | Total % | Win % | Max DD | Trades | |
|---|---|---|---|---|---|---|
| 2020 · DeFi Summer & Pre-Halving Rally | 20200101-20210101 | not run | ||||
| 2021 · Institutional Bull Market | 20210101-20220101 | not run | ||||
| 2022 · Post-Bull Crash & Macro Tightening | 20220101-20230101 | not run | ||||
| 2023–2024 · Recovery & ETF Anticipation | 20230101-20250101 | not run | ||||
| 2025–2026 · Current Cycle | 20250101-20260101 | not run | ||||
Walk forward
Out-of-sample backtest on recent data · 33 pairs · 20260101-20260701.
Backtest trust check
Static source analysis — instant, does not run the strategy. Flags future-data leaks, backtest-realism problems, and indicators worth a second look.
Lookahead analysis
freqtrade lookahead-analysis: detects strategies peeking at future candles.