mirror of
https://github.com/asavinov/intelligent-trading-bot.git
synced 2026-05-04 16:26:44 +00:00
275 lines
11 KiB
Python
275 lines
11 KiB
Python
from pathlib import Path
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from typing import Union
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import json
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import re
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import pandas as pd
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PACKAGE_ROOT = Path(__file__).parent.parent
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#PACKAGE_PARENT = '..'
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#SCRIPT_DIR = os.path.dirname(os.path.realpath(os.path.join(os.getcwd(), os.path.expanduser(__file__))))
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#sys.path.append(os.path.normpath(os.path.join(SCRIPT_DIR, PACKAGE_PARENT)))
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#PACKAGE_ROOT = os.path.dirname(os.path.abspath(__file__))
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class App:
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"""Globally visible variables."""
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# System
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loop = None # asyncio main loop
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sched = None # Scheduler
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analyzer = None # Store and analyze data
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# Connector client
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client = None
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# WebSocket for push notifications
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bm = None
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conn_key = None # Socket
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signal = None, # Latest signal "BUY", "SELL"
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#
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# State of the server (updated after each interval)
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#
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# State 0 or None or empty means ok. String and other non empty objects mean error
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error_status = 0 # Networks, connections, exceptions etc. what does not allow us to work at all
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server_status = 0 # If server allow us to trade (maintenance, down etc.)
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account_status = 0 # If account allows us to trade (funds, suspended etc.)
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trade_state_status = 0 # Something wrong with our trading logic (wrong use, inconsistent state etc. what we cannot recover)
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# Trade status
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transaction = None
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status = None # BOUGHT, SOLD, BUYING, SELLING
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order = None # Latest or current order
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order_time = None # Order submission time
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# Available assets for trade
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# Can be set by the sync/recover function or updated by the trading algorithm
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base_quantity = "0.04108219" # BTC owned (on account, already bought, available for trade)
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quote_quantity = "1000.0" # USDT owned (on account, available for trade)
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#
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# Trader. Status data retrieved from the server. Below are examples only.
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#
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system_status = {"status": 0, "msg": "normal"} # 0: normal，1：system maintenance
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symbol_info = {}
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account_info = {}
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#
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# Constant configuration parameters
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#
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config = {
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"actions": ["notify"], # Values: notify, trade
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# Binance
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"api_key": "",
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"api_secret": "",
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# Telegram
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"telegram_bot_token": "", # Source address of messages
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"telegram_chat_id": "", # Destination address of messages
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#
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# Naming conventions
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#
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"merge_file_name": "data",
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"feature_file_name": "features",
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"matrix_file_name": "matrix",
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"predict_file_name": "predictions", # predict, predict-rolling
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"signal_file_name": "signals",
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"signal_models_file_name": "signal_models",
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"time_column": "timestamp",
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# File locations
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"data_folder": "C:/DATA_ITB", # Location for all source and generated data/models
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# ==============================================
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# === DOWNLOADER, MERGER and (online) READER ===
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# Symbol determines sub-folder and used in other identifiers
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"symbol": "BTCUSDT", # BTCUSDT ETHUSDT ^gspc
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# This parameter determines the time raster (granularity) for the data
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# Currently 1m for binance, and 1d for yahoo are supported (only workdays)
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"freq": "1m",
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# This list is used for downloading and then merging data
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# "folder" is symbol name for downloading. prefix will be added column names during merge
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"data_sources": [
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{"folder": "BTCUSDT", "file": "klines", "column_prefix": ""}
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],
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# ==========================
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# === FEATURE GENERATION ===
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# What columns to pass to which feature generator and how to prefix its derived features
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# Each executes one feature generation function applied to columns with the specified prefix
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"feature_sets": [
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{"column_prefix": "", "generator": "binance_main", "feature_prefix": ""}
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],
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# Parameters of some feature generators
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# They influence generated feature names (below)
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"base_window": 360,
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"averaging_windows": [1, 10, 60],
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"area_windows": [10, 60],
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# ========================
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# === LABEL GENERATION ===
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"label_sets": [
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{"column_prefix": "", "generator": "highlow", "feature_prefix": ""},
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],
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# highlow label parameter: max (of high) and min (of low) for this horizon ahead
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"highlow_horizon": 60, # 1 hour prediction
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# ===========================
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# === MODEL TRAIN/PREDICT ===
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# predict off-line and on-line
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# This number of tail rows will be excluded from model training
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"label_horizon": 60,
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"train_length": int(0.5 * 525_600), # train set maximum size. algorithms may decrease this length
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# List all features to be used for training/prediction by selecting them from the result of reature generation
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# Remove: "_std_1", "_trend_1"
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"train_features": [
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"close_1", "close_10", "close_60",
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"close_std_10", "close_std_60",
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"volume_1", "volume_10", "volume_60",
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"span_1", "span_10", "span_60",
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"trades_1", "trades_10", "trades_60",
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"tb_base_1", "tb_base_10", "tb_base_60",
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"close_area_10", "close_area_60",
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"close_trend_10", "close_trend_60",
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"volume_trend_10", "volume_trend_60"
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],
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# Models (for each algorithm) will be trained for these target labels
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"labels": [
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"high_10", "high_15", "high_20", "high_25", "high_30",
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#"high_01", "high_02", "high_03", "high_04", "high_05",
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#"low_01", "low_02", "low_03", "low_04", "low_05",
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"low_10", "low_15", "low_20", "low_25", "low_30"
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],
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# algorithm names defined in the model store
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"algorithms": ["lc"],
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# ONLINE (PREDICTION) PARAMETERS
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# Minimum history length required to compute derived features
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# It is used in online mode where we need to maintain data window of this size or larger
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# Take maximum aggregation windows from feature generation code (and add something to be sure that we have all what is needed)
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# Basically, should be equal to base_window
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"features_horizon": 10180,
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# =========================
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# === SIGNAL GENERATION ===
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# These predicted columns (scores) will be used for generating buy/sell signals
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"buy_labels": ["high_10_lc", "high_15_lc", "high_20_lc"],
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"sell_labels": ["low_10_lc", "low_15_lc", "low_20_lc"],
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# It defines how signal scores, trade signals, and notification signals will be generated
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# from point-wise prediction scores for two groups of labels
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"signal_model": {
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# First, aggregation in group over various algorithms and label parameters
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"buy_point_threshold": None, # Second, produce boolean column (optional)
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"buy_window": 3, # Third, aggregate in time
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# Now we have the final score
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"buy_signal_threshold": 0.65, # To decide whether to buy/sell after all aggregations/combinations
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"buy_notify_threshold": 0.05, # To decide whether to notify (can be an option of individual users/consumers)
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"combine": "", # "no_combine", "relative", "difference" Find relative/difference
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"sell_point_threshold": None,
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"sell_window": 3,
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"sell_signal_threshold": 0.65,
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"sell_notify_threshold": 0.05,
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"trade_icon_step": 0.1, # For each step, one icon added
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"notify_frequency_minutes": 10, # 1m, 5m, 10m, 15m etc. Minutes will be divided by this number
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},
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# =====================
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# === TRADER SERVER ===
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"base_asset": "", # BTC ETH
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"quote_asset": "",
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"trader": {
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# For debugging: determine what parts of code will be executed
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"no_trades_only_data_processing": False, # in market or out of market processing is excluded (all below parameters ignored)
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"test_order_before_submit": False, # Send test submit to the server as part of validation
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"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)
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"percentage_used_for_trade": 99, # in % to the available USDT quantity, that is, we will derive how much BTC to buy using this percentage
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"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)
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# Signal model (trade strategy) - currently NOT USED
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"sell_timeout": 70, # Seconds
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"percentage_sell_price": 1.018, # our planned profit per trade via limit sell order (part of the model)
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},
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# ==================
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# === COLLECTORS ===
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"collector": {
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"folder": "DATA",
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"flush_period": 300, # seconds
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"depth": {
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"folder": "DEPTH",
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"symbols": ["BTCUSDT", "ETHBTC", "ETHUSDT", "IOTAUSDT", "IOTABTC", "IOTAETH"],
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"limit": 100, # Legal values (depth): '5, 10, 20, 50, 100, 500, 1000, 5000' <100 weight=1
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"freq": "1m", # Binance standard frequency: 5s, 1m etc.
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},
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"stream": {
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"folder": "STREAM",
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# Stream formats:
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# For kline channel: <symbol>@kline_<interval>, Event type: "e": "kline", Symbol: "s": "BNBBTC"
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# For depth channel: <symbol>@depth<levels>[@100ms], Event type: NO, Symbol: NO
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# btcusdt@ticker
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"channels": ["kline_1m", "depth20"], # kline_1m, depth20, depth5
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"symbols": ["BTCUSDT", "ETHBTC", "ETHUSDT", "IOTAUSDT", "IOTABTC", "IOTAETH"],
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# "BTCUSDT", "ETHBTC", "ETHUSDT", "IOTAUSDT", "IOTABTC", "IOTAETH"
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}
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},
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}
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def data_provider_problems_exist():
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if App.error_status != 0:
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return True
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if App.server_status != 0:
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return True
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return False
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def problems_exist():
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if App.error_status != 0:
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return True
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if App.server_status != 0:
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return True
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if App.account_status != 0:
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return True
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if App.trade_state_status != 0:
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return True
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return False
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def load_config(config_file):
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if config_file:
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config_file_path = PACKAGE_ROOT / config_file
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with open(config_file_path, encoding='utf-8') as json_file:
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#conf_str = json.load(json_file)
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conf_str = json_file.read()
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# Remove everything starting with // and till the line end
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conf_str = re.sub(r"//.*$", "", conf_str, flags=re.M)
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conf_json = json.loads(conf_str)
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App.config.update(conf_json)
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if __name__ == "__main__":
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pass
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