Add CryptoComTrader class and main execution script for trading operations
- Introduced the CryptoComTrader class to handle WebSocket connections for real-time trading data and operations. - Implemented methods for fetching price, order book, user balance, and placing orders. - Added functionality to retrieve candlestick data and available trading instruments. - Created a main script to initialize the trader, fetch instruments, and display candlestick data in a loop. - Integrated Plotly for visualizing candlestick data, enhancing user interaction and data representation.
This commit is contained in:
Simon Moisy
parent
e5c2988d71
commit
3483aaf6d7
229
trader/cryptocom_trader.py
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229
trader/cryptocom_trader.py
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import os
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import time
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import hmac
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import hashlib
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import base64
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import json
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import pandas as pd
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import threading
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from websocket import create_connection, WebSocketTimeoutException
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class CryptoComTrader:
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ENV_URLS = {
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"production": {
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"WS_URL": "wss://deriv-stream.crypto.com/v1/market",
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"WS_PRIVATE_URL": "wss://deriv-stream.crypto.com/v1/user"
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},
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"uat": {
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"WS_URL": "wss://uat-deriv-stream.3ona.co/v1/market",
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"WS_PRIVATE_URL": "wss://uat-deriv-stream.3ona.co/v1/user"
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}
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}
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def __init__(self):
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self.env = os.getenv("CRYPTOCOM_ENV", "UAT").lower()
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urls = self.ENV_URLS.get(self.env, self.ENV_URLS["production"])
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self.WS_URL = urls["WS_URL"]
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self.WS_PRIVATE_URL = urls["WS_PRIVATE_URL"]
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self.api_key = os.getenv("CRYPTOCOM_API_KEY")
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self.api_secret = os.getenv("CRYPTOCOM_API_SECRET")
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self.ws = None
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self.ws_private = None
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self._lock = threading.Lock()
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self._private_lock = threading.Lock()
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self._connect_ws()
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def _connect_ws(self):
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if self.ws is None:
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self.ws = create_connection(self.WS_URL, timeout=10)
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if self.api_key and self.api_secret and self.ws_private is None:
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self.ws_private = create_connection(self.WS_PRIVATE_URL, timeout=10)
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def _send_ws(self, payload, private=False):
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ws = self.ws_private if private else self.ws
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lock = self._private_lock if private else self._lock
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with lock:
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ws.send(json.dumps(payload))
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try:
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resp = ws.recv()
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return json.loads(resp)
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except WebSocketTimeoutException:
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return None
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def _sign(self, params):
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t = str(int(time.time() * 1000))
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params['id'] = t
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params['nonce'] = t
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params['api_key'] = self.api_key
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param_str = json.dumps(params, separators=(',', ':'), sort_keys=True)
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sig = hmac.new(
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bytes(self.api_secret, 'utf-8'),
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msg=bytes(param_str, 'utf-8'),
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digestmod=hashlib.sha256
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).hexdigest()
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params['sig'] = sig
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return params
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def get_price(self):
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"""
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Get the latest ask price for BTC_USDC using WebSocket ticker subscription (one-shot).
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"""
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payload = {
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"id": int(time.time() * 1000),
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"method": "subscribe",
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"params": {"channels": ["ticker.BTC_USDC"]}
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}
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resp = self._send_ws(payload)
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# Wait for ticker update
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while True:
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data = self.ws.recv()
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msg = json.loads(data)
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if msg.get("method") == "ticker.update":
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# 'a' is ask price
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return msg["params"]["data"][0].get("a")
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def get_order_book(self, depth=10):
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"""
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Fetch the order book for BTC_USDC with the specified depth using WebSocket (one-shot).
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Returns a dict with 'bids' and 'asks'.
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"""
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payload = {
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"id": int(time.time() * 1000),
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"method": "subscribe",
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"params": {"channels": [f"book.BTC_USDC.{depth}"]}
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}
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resp = self._send_ws(payload)
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# Wait for book update
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while True:
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data = self.ws.recv()
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msg = json.loads(data)
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if msg.get("method") == "book.update":
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book = msg["params"]["data"][0]
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return {
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"bids": book.get("bids", []),
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"asks": book.get("asks", [])
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}
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def _authenticate(self):
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"""
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Authenticate the private WebSocket connection. Only needs to be done once per session.
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"""
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if not self.api_key or not self.api_secret:
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raise ValueError("API key and secret must be set in environment variables.")
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payload = {
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"id": int(time.time() * 1000),
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"method": "public/auth",
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"api_key": self.api_key,
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"nonce": int(time.time() * 1000),
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}
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# For auth, sig is HMAC_SHA256(method + id + api_key + nonce)
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sig_payload = (
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payload["method"] + str(payload["id"]) + self.api_key + str(payload["nonce"])
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)
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payload["sig"] = hmac.new(
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bytes(self.api_secret, "utf-8"),
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msg=bytes(sig_payload, "utf-8"),
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digestmod=hashlib.sha256,
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).hexdigest()
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resp = self._send_ws(payload, private=True)
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if not resp or resp.get("code") != 0:
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raise Exception(f"WebSocket authentication failed: {resp}")
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def _ensure_private_auth(self):
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if self.ws_private is None:
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self._connect_ws()
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time.sleep(1) # recommended by docs
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self._authenticate()
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def get_balance(self, currency="USDC"):
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"""
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Fetch user balance using WebSocket private API.
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"""
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self._ensure_private_auth()
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payload = {
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"id": int(time.time() * 1000),
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"method": "private/user-balance",
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"params": {},
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"nonce": int(time.time() * 1000),
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}
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resp = self._send_ws(payload, private=True)
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if resp and resp.get("code") == 0:
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balances = resp.get("result", {}).get("data", [])
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if currency:
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return [b for b in balances if b.get("instrument_name") == currency]
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return balances
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return []
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def place_order(self, side, amount):
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"""
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Place a market order using WebSocket private API.
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side: 'BUY' or 'SELL', amount: in BTC
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"""
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self._ensure_private_auth()
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params = {
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"instrument_name": "BTC_USDC",
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"side": side,
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"type": "MARKET",
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"quantity": str(amount),
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}
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payload = {
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"id": int(time.time() * 1000),
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"method": "private/create-order",
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"params": params,
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"nonce": int(time.time() * 1000),
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}
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resp = self._send_ws(payload, private=True)
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return resp
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def buy_btc(self, amount):
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return self.place_order("BUY", amount)
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def sell_btc(self, amount):
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return self.place_order("SELL", amount)
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def get_candlesticks(self, timeframe='1m', count=100):
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"""
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Fetch candlestick (OHLCV) data for BTC_USDC using WebSocket.
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Args:
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timeframe (str): Timeframe for each candle (e.g., '1m', '5m', '15m', '1h', '4h', '1d').
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count (int): Number of candles to fetch (max 1000 per API docs).
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Returns:
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pd.DataFrame: DataFrame with columns ['timestamp', 'open', 'high', 'low', 'close', 'volume']
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"""
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payload = {
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"id": int(time.time() * 1000),
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"method": "public/get-candlestick",
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"params": {
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"instrument_name": "BTC_USDC",
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"timeframe": timeframe,
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"count": count
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}
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}
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resp = self._send_ws(payload)
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candles = resp.get("result", {}).get("data", []) if resp else []
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if not candles:
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return pd.DataFrame(columns=["timestamp", "open", "high", "low", "close", "volume"])
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df = pd.DataFrame(candles)
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df['timestamp'] = pd.to_datetime(df['t'], unit='ms')
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df = df.rename(columns={
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'o': 'open',
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'h': 'high',
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'l': 'low',
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'c': 'close',
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'v': 'volume'
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})
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return df[['timestamp', 'open', 'high', 'low', 'close', 'volume']].sort_values('timestamp')
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def get_instruments(self):
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"""
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Fetch the list of available trading instruments from Crypto.com using WebSocket.
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Returns:
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list: List of instrument dicts.
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"""
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payload = {
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"id": int(time.time() * 1000),
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"method": "public/get-instruments",
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"params": {}
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}
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resp = self._send_ws(payload)
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return resp.get("result", {}).get("data", []) if resp else []
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84
trader/main.py
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84
trader/main.py
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import time
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import plotly.graph_objs as go
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import plotly.io as pio
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from cryptocom_trader import CryptoComTrader
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def plot_candlesticks(df):
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if df.empty:
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print("No data to plot.")
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return None
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# Convert columns to float
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for col in ['open', 'high', 'low', 'close', 'volume']:
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df[col] = df[col].astype(float)
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# Plotly expects datetime for x-axis
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fig = go.Figure(data=[go.Candlestick(
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x=df['timestamp'],
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open=df['open'],
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high=df['high'],
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low=df['low'],
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close=df['close'],
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increasing_line_color='#089981',
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decreasing_line_color='#F23645'
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)])
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fig.update_layout(
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title='BTC/USDC Realtime Candlestick (1m)',
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yaxis_title='Price (USDC)',
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xaxis_title='Time',
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xaxis_rangeslider_visible=False,
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template='plotly_dark'
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)
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return fig
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def main():
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trader = CryptoComTrader()
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pio.renderers.default = "browser" # Open in browser
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# Fetch and print BTC/USDC-related instruments
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instruments = trader.get_instruments()
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btc_usdc_instruments = [
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inst for inst in instruments
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if (
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('BTC' in inst.get('base_ccy', '') or 'BTC' in inst.get('base_currency', '')) and
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('USDC' in inst.get('quote_ccy', '') or 'USDC' in inst.get('quote_currency', ''))
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)
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]
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print("BTC/USDC-related instruments:")
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for inst in btc_usdc_instruments:
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print(inst)
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# Optionally, show balance (private API)
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try:
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balance = trader.get_balance("USDC")
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print("USDC Balance:", balance)
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except Exception as e:
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print("[WARN] Could not fetch balance (private API):", e)
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all_instruments = trader.get_instruments()
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for inst in all_instruments:
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print(inst)
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while True:
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try:
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df = trader.get_candlesticks(timeframe='1m', count=60)
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# fig = plot_candlesticks(df)
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# if fig:
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# fig.show()
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if not df.empty:
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print(df[['high', 'low', 'open', 'close', 'volume']])
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else:
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print("No data to print.")
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time.sleep(10)
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except KeyboardInterrupt:
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print('Exiting...')
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break
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except Exception as e:
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print(f'Error: {e}')
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time.sleep(10)
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if __name__ == '__main__':
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main()
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