from pathlib import Path from typing import Union import json import re import pandas as pd PACKAGE_ROOT = Path(__file__).parent.parent #PACKAGE_PARENT = '..' #SCRIPT_DIR = os.path.dirname(os.path.realpath(os.path.join(os.getcwd(), os.path.expanduser(__file__)))) #sys.path.append(os.path.normpath(os.path.join(SCRIPT_DIR, PACKAGE_PARENT))) #PACKAGE_ROOT = os.path.dirname(os.path.abspath(__file__)) class App: """Globally visible variables.""" # System loop = None # asyncio main loop sched = None # Scheduler analyzer = None # Store and analyze data # Connector client client = None # WebSocket for push notifications bm = None conn_key = None # Socket signal = None, # Latest signal "BUY", "SELL" # # State of the server (updated after each interval) # # State 0 or None or empty means ok. String and other non empty objects mean error error_status = 0 # Networks, connections, exceptions etc. what does not allow us to work at all server_status = 0 # If server allow us to trade (maintenance, down etc.) account_status = 0 # If account allows us to trade (funds, suspended etc.) trade_state_status = 0 # Something wrong with our trading logic (wrong use, inconsistent state etc. what we cannot recover) # Trade status transaction = None status = None # BOUGHT, SOLD, BUYING, SELLING order = None # Latest or current order order_time = None # Order submission time # Available assets for trade # Can be set by the sync/recover function or updated by the trading algorithm base_quantity = "0.04108219" # BTC owned (on account, already bought, available for trade) quote_quantity = "1000.0" # USDT owned (on account, available for trade) # # Trader. Status data retrieved from the server. Below are examples only. # system_status = {"status": 0, "msg": "normal"} # 0: normal，1：system maintenance symbol_info = {} account_info = {} # # Constant configuration parameters # config = { "actions": ["notify"], # Values: notify, trade # Binance "api_key": "", "api_secret": "", # Telegram "telegram_bot_token": "", # Source address of messages "telegram_chat_id": "", # Destination address of messages # # Naming conventions # "merge_file_name": "data", "feature_file_name": "features", "matrix_file_name": "matrix", "predict_file_name": "predictions", # predict, predict-rolling "signal_file_name": "signals", "signal_models_file_name": "signal_models", "time_column": "timestamp", # File locations "data_folder": "C:/DATA_ITB", # Location for all source and generated data/models # ============================================== # === DOWNLOADER, MERGER and (online) READER === # Symbol determines sub-folder and used in other identifiers "symbol": "BTCUSDT", # BTCUSDT ETHUSDT ^gspc # This parameter determines the time raster (granularity) for the data # Currently 1m for binance, and 1d for yahoo are supported (only workdays) "freq": "1m", # This list is used for downloading and then merging data # "folder" is symbol name for downloading. prefix will be added column names during merge "data_sources": [ {"folder": "BTCUSDT", "file": "klines", "column_prefix": ""} ], # ========================== # === FEATURE GENERATION === # What columns to pass to which feature generator and how to prefix its derived features # Each executes one feature generation function applied to columns with the specified prefix "feature_sets": [ {"column_prefix": "", "generator": "binance_main", "feature_prefix": ""} ], # Parameters of some feature generators # They influence generated feature names (below) "base_window": 360, "averaging_windows": [1, 10, 60], "area_windows": [10, 60], # ======================== # === LABEL GENERATION === "label_sets": [ {"column_prefix": "", "generator": "highlow", "feature_prefix": ""}, ], # highlow label parameter: max (of high) and min (of low) for this horizon ahead "highlow_horizon": 60, # 1 hour prediction # =========================== # === MODEL TRAIN/PREDICT === # predict off-line and on-line # This number of tail rows will be excluded from model training "label_horizon": 60, "train_length": int(0.5 * 525_600), # train set maximum size. algorithms may decrease this length # List all features to be used for training/prediction by selecting them from the result of reature generation # Remove: "_std_1", "_trend_1" "train_features": [ "close_1", "close_10", "close_60", "close_std_10", "close_std_60", "volume_1", "volume_10", "volume_60", "span_1", "span_10", "span_60", "trades_1", "trades_10", "trades_60", "tb_base_1", "tb_base_10", "tb_base_60", "close_area_10", "close_area_60", "close_trend_10", "close_trend_60", "volume_trend_10", "volume_trend_60" ], # Models (for each algorithm) will be trained for these target labels "labels": [ "high_10", "high_15", "high_20", "high_25", "high_30", #"high_01", "high_02", "high_03", "high_04", "high_05", #"low_01", "low_02", "low_03", "low_04", "low_05", "low_10", "low_15", "low_20", "low_25", "low_30" ], # algorithm names defined in the model store "algorithms": ["lc"], # ONLINE (PREDICTION) PARAMETERS # Minimum history length required to compute derived features # It is used in online mode where we need to maintain data window of this size or larger # Take maximum aggregation windows from feature generation code (and add something to be sure that we have all what is needed) # Basically, should be equal to base_window "features_horizon": 10180, # ========================= # === SIGNAL GENERATION === # These predicted columns (scores) will be used for generating buy/sell signals "buy_labels": ["high_10_lc", "high_15_lc", "high_20_lc"], "sell_labels": ["low_10_lc", "low_15_lc", "low_20_lc"], # It defines how signal scores, trade signals, and notification signals will be generated # from point-wise prediction scores for two groups of labels "signal_model": { # First, aggregation in group over various algorithms and label parameters "buy_point_threshold": None, # Second, produce boolean column (optional) "buy_window": 3, # Third, aggregate in time # Now we have the final score "buy_signal_threshold": 0.65, # To decide whether to buy/sell after all aggregations/combinations "buy_notify_threshold": 0.05, # To decide whether to notify (can be an option of individual users/consumers) "combine": "", # "no_combine", "relative", "difference" Find relative/difference "sell_point_threshold": None, "sell_window": 3, "sell_signal_threshold": 0.65, "sell_notify_threshold": 0.05, "trade_icon_step": 0.1, # For each step, one icon added "notify_frequency_minutes": 10, # 1m, 5m, 10m, 15m etc. Minutes will be divided by this number }, # ===================== # === TRADER SERVER === "base_asset": "", # BTC ETH "quote_asset": "", "trader": { # For debugging: determine what parts of code will be executed "no_trades_only_data_processing": False, # in market or out of market processing is excluded (all below parameters ignored) "test_order_before_submit": False, # Send test submit to the server as part of validation "simulate_order_execution": False, # Instead of real orders, simulate their execution (immediate buy/sell market orders and use high price of klines for limit orders) "percentage_used_for_trade": 99, # in % to the available USDT quantity, that is, we will derive how much BTC to buy using this percentage "limit_price_adjustment": -0.0001, # Limit price of orders will be better than the latest close price (0 means no change, positive - better for us, negative - worse for us) # Signal model (trade strategy) - currently NOT USED "sell_timeout": 70, # Seconds "percentage_sell_price": 1.018, # our planned profit per trade via limit sell order (part of the model) }, # ================== # === COLLECTORS === "collector": { "folder": "DATA", "flush_period": 300, # seconds "depth": { "folder": "DEPTH", "symbols": ["BTCUSDT", "ETHBTC", "ETHUSDT", "IOTAUSDT", "IOTABTC", "IOTAETH"], "limit": 100, # Legal values (depth): '5, 10, 20, 50, 100, 500, 1000, 5000' <100 weight=1 "freq": "1m", # Binance standard frequency: 5s, 1m etc. }, "stream": { "folder": "STREAM", # Stream formats: # For kline channel: @kline_, Event type: "e": "kline", Symbol: "s": "BNBBTC" # For depth channel: @depth[@100ms], Event type: NO, Symbol: NO # btcusdt@ticker "channels": ["kline_1m", "depth20"], # kline_1m, depth20, depth5 "symbols": ["BTCUSDT", "ETHBTC", "ETHUSDT", "IOTAUSDT", "IOTABTC", "IOTAETH"], # "BTCUSDT", "ETHBTC", "ETHUSDT", "IOTAUSDT", "IOTABTC", "IOTAETH" } }, } def data_provider_problems_exist(): if App.error_status != 0: return True if App.server_status != 0: return True return False def problems_exist(): if App.error_status != 0: return True if App.server_status != 0: return True if App.account_status != 0: return True if App.trade_state_status != 0: return True return False def load_config(config_file): if config_file: config_file_path = PACKAGE_ROOT / config_file with open(config_file_path, encoding='utf-8') as json_file: #conf_str = json.load(json_file) conf_str = json_file.read() # Remove everything starting with // and till the line end conf_str = re.sub(r"//.*$", "", conf_str, flags=re.M) conf_json = json.loads(conf_str) App.config.update(conf_json) if __name__ == "__main__": pass