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kucoin-pumpdump-crypto-alerts-telegram-bot-selected-usdt-pars.py
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import os
from dotenv import load_dotenv
import requests
import time
from datetime import datetime, timedelta
import base64
import hashlib
import asyncio
import hmac
import telegram.error
from telegram import Bot
from telegram.error import RetryAfter
import pandas as pd
import pandas_ta as ta
load_dotenv()
# Settings
TELEGRAM_BOT_TOKEN = os.getenv("TELEGRAM_BOT_TOKEN")
CHANNEL_ID = os.getenv("CHANNEL_ID")
API_KEY = os.getenv("API_KEY")
API_SECRET = os.getenv("API_SECRET")
API_PASSPHRASE = os.getenv("API_PASSPHRASE")
API_IP = os.getenv("API_IP")
bot = Bot(token=TELEGRAM_BOT_TOKEN)
DESIRED_PAIRS = [
"1INCH-USDT",
"AAVE-USDT",
"ADA-USDT",
"AEVO-USDT",
"AGIX-USDT",
"AIOZ-USDT",
"ALICE-USDT",
"ALT-USDT",
"AMP-USDT",
"ANKR-USDT",
"APT-USDT",
"AR-USDT",
"ARB-USDT",
"ARPA-USDT",
"ASTR-USDT",
"ATOM-USDT",
"ATOR-USDT",
"AVAX-USDT",
"AXS-USDT",
"AZERO-USDT",
"BAT-USDT",
"BCH-USDT",
"BNB-USDT",
"BOME-USDT",
"BONK-USDT",
"BTC-USDT",
"CAKE-USDT",
"CELO-USDT",
"CHZ-USDT",
"CKB-USDT",
"COMP-USDT",
"CQT-USDT",
"CREAM-USDT",
"CWAR-USDT",
"DASH-USDT",
"DODO-USDT",
"DOGE-USDT",
"DOT-USDT",
"DUSK-USDT",
"ENA-USDT",
"ENJ-USDT",
"ENS-USDT",
"ETC-USDT",
"ETH-USDT",
"FET-USDT",
"FIL-USDT",
"FLOKI-USDT",
"FLOW-USDT",
"FLUX-USDT",
"FTM-USDT",
"GALA-USDT",
"GNO-USDT",
"GRT-USDT",
"GTAI-USDT",
"HBAR-USDT",
"HOPR-USDT",
"ICP-USDT",
"ICX-USDT",
"ILV-USDT",
"IMX-USDT",
"INJ-USDT",
"JASMY-USDT",
"JTO-USDT",
"JUP-USDT",
"KAS-USDT",
"KAVA-USDT",
"KCS-USDT",
"KUJI-USDT",
"LAI-USDT",
"LDO-USDT",
"LINK-USDT",
"LTC-USDT",
"LTO-USDT",
"MAGIC-USDT",
"MANA-USDT",
"MANTA-USDT",
"MASK-USDT",
"MATIC-USDT",
"MAVIA-USDT",
"METIS-USDT",
"MKR-USDT",
"MNT-USDT",
"MOVR-USDT",
"NEAR-USDT",
"NFP-USDT",
"NMR-USDT",
"NOIA-USDT",
"NUM-USDT",
"OCEAN-USDT",
"OGN-USDT",
"OGV-USDT",
"OM-USDT",
"ONDO-USDT",
"ONT-USDT",
"OP-USDT",
"ORAI-USDT",
"ORDI-USDT",
"OSMO-USDT",
"OXT-USDT",
"PENDLE-USDT",
"PEPE-USDT",
"PHA-USDT",
"PIXEL-USDT",
"POLC-USDT",
"POLYX-USDT",
"PRQ-USDT",
"PUNDIX-USDT",
"RAY-USDT",
"REN-USDT",
"RLC-USDT",
"RNDR-USDT",
"ROSE-USDT",
"SAND-USDT",
"SEI-USDT",
"SFP-USDT",
"SFUND-USDT",
"SHIB-USDT",
"SHILL-USDT",
"SNX-USDT",
"SOL-USDT",
"STORJ-USDT",
"STRK-USDT",
"STX-USDT",
"SUI-USDT",
"SUKU-USDT",
"SUSHI-USDT",
"SXP-USDT",
"T-USDT",
"TAO-USDT",
"THETA-USDT",
"TIA-USDT",
"TLM-USDT",
"TLOS-USDT",
"TNSR-USDT",
"TON-USDT",
"TRB-USDT",
"TRX-USDT",
"UNFI-USDT",
"UNI-USDT",
"VR-USDT",
"WAVES-USDT",
"WIF-USDT",
"WIN-USDT",
"WLD-USDT",
"WOO-USDT",
"XLM-USDT",
"XMR-USDT",
"YFI-USDT",
"YGG-USDT",
"ZEC-USDT"
]
def get_headers(method, request_path, body=""):
timestamp = str(int(time.time() * 1000))
str_to_sign = timestamp + method + request_path + (body if body else "")
signature = base64.b64encode(
hmac.new(
API_SECRET.encode("utf-8"), str_to_sign.encode("utf-8"), hashlib.sha256
).digest()
).decode("utf-8")
passphrase = base64.b64encode(
hmac.new(
API_SECRET.encode("utf-8"), API_PASSPHRASE.encode("utf-8"), hashlib.sha256
).digest()
).decode("utf-8")
headers = {
"KC-API-SIGN": signature,
"KC-API-TIMESTAMP": timestamp,
"KC-API-KEY": API_KEY,
"KC-API-PASSPHRASE": passphrase,
"KC-API-KEY-VERSION": "2",
}
return headers
def fetch_market_data():
url = "https://api.kucoin.com/api/v1/market/allTickers"
try:
response = requests.get(
url, headers=get_headers("GET", "/api/v1/market/allTickers")
)
response.raise_for_status()
return response.json()
except requests.RequestException as e:
bot.send_message(chat_id=CHANNEL_ID, text=f"Error fetching data: {e}")
print(f"Error fetching data: {e}")
return None
except Exception as e:
bot.send_message(chat_id=CHANNEL_ID, text=f"Unexpected error: {e}")
print(f"Unexpected error: {e}")
return None
def calculate_indicators(prices_history, minutes_to_evaluate=15, hours_for_trend=4):
"""
Calculates technical indicators for each pair of cryptocurrencies.
Returns a dictionary with the calculated indicators.
"""
current_time = datetime.now()
indicators = {}
evaluation_period = minutes_to_evaluate
# Convert hours to minutes
trend_period = hours_for_trend * 60
for pair, prices in prices_history.items():
prices_df = pd.DataFrame(prices, columns=["price", "time"])
prices_df = prices_df.set_index("time")
# Filter prices for trial and trend periods
prices_evaluation = prices_df.loc[
current_time - timedelta(minutes=evaluation_period): current_time, "price"
]
prices_trend = prices_df.loc[
current_time - timedelta(minutes=evaluation_period + trend_period): current_time, "price"
]
if len(prices_evaluation) >= 1 and len(prices_trend) >= 1:
# Calculate technical indicators
rsi_evaluation = calculate_rsi(prices_evaluation)
rsi_trend = calculate_rsi(prices_trend)
macd_evaluation, signal_evaluation, hist_evaluation = calculate_macd(
prices_evaluation
)
macd_trend, signal_trend, hist_trend = calculate_macd(prices_trend)
indicators[pair] = {
"rsi_evaluation": rsi_evaluation,
"rsi_trend": rsi_trend,
"macd_evaluation": macd_evaluation,
"macd_trend": macd_trend,
"signal_evaluation": signal_evaluation,
"signal_trend": signal_trend,
"hist_evaluation": hist_evaluation,
"hist_trend": hist_trend,
}
else:
print(f"Error calculating indicators for {pair}")
return indicators
def calculate_rsi(prices):
delta = prices.diff()
gain = (delta.where(delta > 0, 0)).mean()
loss = (-delta.where(delta < 0, 0)).mean()
if loss == 0:
return 100
rs = gain / loss
return 100 - (100 / (1 + rs))
def calculate_ema(prices, window):
weights = pd.Series(1.0, index=prices.index)
weights /= weights.sum()
ema = prices.ewm(span=window, min_periods=window).mean()
return ema
def calculate_macd(prices):
ema12 = calculate_ema(prices, 12)
ema26 = calculate_ema(prices, 26)
macd_line = ema12 - ema26
signal_line = calculate_ema(macd_line, 9)
histogram = macd_line - signal_line
return macd_line.iloc[-1], signal_line.iloc[-1], histogram.iloc[-1]
async def send_telegram_message(chat_id, message):
try:
await bot.send_message(chat_id=chat_id, text=message, parse_mode="HTML")
except telegram.error.RetryAfter as e:
print(f"Flood control exceeded. Retrying in {e.retry_after} seconds.")
await asyncio.sleep(e.retry_after)
await send_telegram_message(chat_id, message)
except Exception as e:
print(f"Error sending Telegram message: {e}")
else:
await asyncio.sleep(1)
# 60 minutes and 15 seconds
async def send_donation_message(interval=60 * 60 + 15):
while True:
message = f"💚 Help us push the boundaries of AI-driven analysis! Your contributions fuel our relentless pursuit of innovative trading strategies:\n\n🤲 <b>Every donation propels us forward.</b>\n\n<b>$USDT (TRC-20):</b>\nTGpiWetnYK2VQpxNGPR27D9vfM6Mei5vNA\n\n🫶 <b>Designed to help you.</b>\n🫶 <b>From AIs to human-beans.</b>\n\n🔸 <i>Version 2.0.1 (2024/06/29)</i>⠀"
print(message)
await send_telegram_message(CHANNEL_ID, message)
await asyncio.sleep(interval)
def calculate_variation_and_trend(prices_history, minutes_to_evaluate=15, hours_for_trend=4):
current_time = datetime.now()
variations = {}
evaluation_period = minutes_to_evaluate
# Convert hours to minutes
trend_period = hours_for_trend * 60
for pair, prices in prices_history.items():
prices_in_evaluation_period = [(price, time) for price, time in prices if current_time - time <= timedelta(minutes=evaluation_period)]
trend_start_time = current_time - timedelta(minutes=(evaluation_period + trend_period))
prices_in_trend_period = [(price, time) for price, time in prices if trend_start_time <= time <= trend_start_time + timedelta(minutes=trend_period)]
if len(prices_in_evaluation_period) >= 1 and len(prices_in_trend_period) >= 1:
initial_price_evaluation = prices_in_evaluation_period[0][0]
final_price_evaluation = prices_in_evaluation_period[-1][0]
initial_price_trend = prices_in_trend_period[0][0]
final_price_trend = prices_in_trend_period[-1][0]
variation_evaluation = ((final_price_evaluation - initial_price_evaluation) / initial_price_evaluation) * 100
variation_trend = ((final_price_trend - initial_price_trend) / initial_price_trend) * 100
if variation_evaluation > 0 and variation_trend > 0:
variations[pair] = variation_evaluation
return variations
async def monitor_prices():
prices_history = {}
last_indicators = {}
sold_pairs = {}
monitoring_message_sent = False
while True:
data = fetch_market_data()
if data:
tickers = data["data"]["ticker"]
for ticker in tickers:
symbol = ticker["symbol"]
if symbol in DESIRED_PAIRS:
last_price = ticker.get("last")
if last_price:
price = float(last_price)
if symbol not in prices_history:
prices_history[symbol] = []
prices_history[symbol].append((price, datetime.now()))
# Clear old data
for pair in list(prices_history.keys()):
if len(prices_history[pair]) > 1000:
prices_history[pair] = prices_history[pair][-1000:]
indicators = calculate_indicators(
prices_history, minutes_to_evaluate=15, hours_for_trend=4
)
variations = calculate_variation_and_trend(prices_history, minutes_to_evaluate=15, hours_for_trend=4)
any_signal = False
for pair, pair_indicators in indicators.items():
rsi_evaluation = pair_indicators["rsi_evaluation"]
rsi_trend = pair_indicators["rsi_trend"]
macd_evaluation = pair_indicators["macd_evaluation"]
macd_trend = pair_indicators["macd_trend"]
signal_evaluation = pair_indicators["signal_evaluation"]
signal_trend = pair_indicators["signal_trend"]
hist_evaluation = pair_indicators["hist_evaluation"]
hist_trend = pair_indicators["hist_trend"]
current_price = prices_history[pair][-1][0]
variation = ((current_price - prices_history[pair][0][0]) / prices_history[pair][0][0]) * 100
# Conditions for buy signal
if (
rsi_evaluation > 45
and macd_evaluation > signal_evaluation
and hist_evaluation > 0
and rsi_trend > 45
and macd_trend > signal_trend
and hist_trend > 0
and pair not in sold_pairs
and pair in variations
and variations[pair] > 2
):
message = f"🟢️ <b>STRONG PUMP DETECTED</b> 🟢️\n\n🧧 <b>${pair}</b>\n\n🐋 <b>Price:</b> {current_price:.8f} $USDT\n\n📈 <b>Variation:</b> {variation:.2f}%\n\n🏄♂️ RSI, MACD, and Histogram indicate strong upward momentum\n\n💠 This is an excellent buying opportunity!⠀"
print(message)
await send_telegram_message(CHANNEL_ID, message)
sold_pairs[pair] = True
any_signal = True
# os.system("afplay /System/Library/Sounds/Ping.aiff")
# Conditions for sale sign
elif pair in sold_pairs and (
# -4% drop after buy signal
(rsi_evaluation > 90 and variation < -4)
# RSI high and MACD indicating fall
or (rsi_evaluation > 90 and macd_evaluation < signal_evaluation and macd_trend < signal_trend)
):
message = f"🔴 <b>MOMENTUM DUMPING BELOW</b> 🔴\n\n🧧 <b>${pair}</b>\n\n🦈 <b>Price:</b> {current_price:.8f} $USDT\n\n📉 <b>Variation:</b> {variation:.2f}%\n\n🏄♀️ RSI, MACD, and Histogram indicate weakening upward momentum\n\n💠 Consider selling to mitigate risk!⠀"
print(message)
await send_telegram_message(CHANNEL_ID, message)
del sold_pairs[pair]
any_signal = True
# os.system("afplay /System/Library/Sounds/Glass.aiff")
if not any_signal and not monitoring_message_sent:
message = "📊 <b>MONITORING FOR PUMP ENTRIES</b> 📊\n\n🏄 Once an optimal wave pattern emerges\n\n🔔 You'll be instantly notified to ride the momentum...⠀"
print(message)
await send_telegram_message(CHANNEL_ID, message)
monitoring_message_sent = True
else:
print("Error fetching market data.")
await asyncio.sleep(1)
async def main():
donation_task = asyncio.create_task(send_donation_message())
monitor_task = asyncio.create_task(monitor_prices())
await asyncio.gather(donation_task, monitor_task)
if __name__ == "__main__":
asyncio.run(main())