add large_trans.

main.py

@@ -3,23 +3,28 @@ import bn
 import settings
 import time
 import strategy.crossover as crossover
+import strategy.large_trans as lt
 
 # 获取交易所交易对
 symbols = bn.symbols()
 
 
 for s in symbols:
+    # 1m
+    schedule.every(1).minutes.do(lt.strategy_run)
+
+
     # 5m
     # schedule.every(5).minutes.do(crossover.strategy_run, symbol=s, interval='5m')
    
     # 30m
-    schedule.every(30).minutes.do(crossover.strategy_run, symbol=s, interval='30m')
+    # schedule.every(30).minutes.do(crossover.strategy_run, symbol=s, interval='30m')
 
     # 1h
-    schedule.every(1).hours.do(crossover.strategy_run, symbol=s, interval='1h')
+    # schedule.every(1).hours.do(crossover.strategy_run, symbol=s, interval='1h')
 
     # 4h
-    schedule.every(4).hours.do(crossover.strategy_run, symbol=s, interval='4h')
+    # schedule.every(4).hours.do(crossover.strategy_run, symbol=s, interval='4h')
 
 print(f'监控开始... ChatID: {settings.chat_id}')
 while True:

settings.py

@@ -4,4 +4,17 @@ import os
 telegram_bot_key='5863718864:AAFijN65_SbbGQ0WDBggzKJw2SIcZVTVrPw'
 
 #
-chat_id = os.getenv("TQ_CHAT_ID", "@cyber4trading")
+chat_id = os.getenv("TQ_CHAT_ID", "@cyber4trading")
+
+
+#oklink
+oklink_host = 'https://www.oklink.com'
+oklink_apikey='ca822b3f-2e1e-479c-8649-c1f9b62a740d'
+oklink_api_headers = {
+    'Ok-Access-Key' : oklink_apikey 
+}
+
+
+#whaleAlert
+whaleAlert_apikey='gPkElMPR8Hpe5LxjKisR4YSFzxRxMLj6'
+whaleAlert_max_limit = os.getenv('TQ_WHALEALERT_MAX_USD_AMOUNT',2000 * 20000)

strategy/large_trans.py

@@ -0,0 +1,26 @@
+
+import requests
+import settings
+from datetime import datetime, timedelta
+import time
+import tg
+
+
+def strategy_run():
+    # 获取上一分钟的timestamp
+    last_min = datetime.now() - timedelta(minutes=1)
+    ts = time.mktime(last_min.timetuple())
+
+    url = f'https://api.whale-alert.io/v1/transactions?api_key={settings.whaleAlert_apikey}&start={int(ts)}'
+    resp = requests.get(url).json()
+
+    data = resp['transactions']
+    
+    for ts in data:
+        usd = int(ts['amount_usd'])
+        if ts['to']['owner_type'] == 'exchange' and ts['from']['owner_type'] == 'unknown' and usd > settings.whaleAlert_max_limit:
+            from_text = 'unknown wallet'
+            content = f"🚨 {ts['amount']} #{ts['symbol']} ({ts['amount_usd']} USD) 从 {from_text} 转入 #{ts['to']['owner']}"
+
+            print(content)
+            tg.send_message(settings.chat_id, content)

test.py

@@ -2,30 +2,34 @@ import bn
 import pandas as pd
 import mplfinance as mpf
 import datetime as dt
+import strategy.large_trans as lt
 
-def binanceDataFrame(klines):
-    df = pd.DataFrame(klines.reshape(-1,12),dtype=float, columns = ('Open Time',
-                                                                    'Open',
-                                                                    'High',
-                                                                    'Low',
-                                                                    'Close',
-                                                                    'Volume',
-                                                                    'Close time',
-                                                                    'Quote asset volume',
-                                                                    'Number of trades',
-                                                                    'Taker buy base asset volume',
-                                                                    'Taker buy quote asset volume',
-                                                                    'Ignore'))
+# def binanceDataFrame(klines):
+#     df = pd.DataFrame(klines.reshape(-1,12),dtype=float, columns = ('Open Time',
+#                                                                     'Open',
+#                                                                     'High',
+#                                                                     'Low',
+#                                                                     'Close',
+#                                                                     'Volume',
+#                                                                     'Close time',
+#                                                                     'Quote asset volume',
+#                                                                     'Number of trades',
+#                                                                     'Taker buy base asset volume',
+#                                                                     'Taker buy quote asset volume',
+#                                                                     'Ignore'))
 
-    df['Open Time'] = pd.to_datetime(df['Open Time'], unit='ms')
+#     df['Open Time'] = pd.to_datetime(df['Open Time'], unit='ms')
 
 
-    return df
+#     return df
 
 
-klines = bn.klines('BTCUSDT', '1h')
+# klines = bn.klines('BTCUSDT', '1h')
 
-df = pd.DataFrame(klines,dtype=float)
-df.columns = ['Open time', 'Open', 'High', 'Low', 'Close', 'Volume', 'ctime', 'Quote asset volume', 'Number of trades', 'Taker buy base asset volume', 'Taker buy quote asset volume', 'Can be ignored']
-df.index = [dt.datetime.fromtimestamp(x/1000.0) for x in df.ctime]
-mpf.plot(df, type='line')
+# df = pd.DataFrame(klines,dtype=float)
+# df.columns = ['Open time', 'Open', 'High', 'Low', 'Close', 'Volume', 'ctime', 'Quote asset volume', 'Number of trades', 'Taker buy base asset volume', 'Taker buy quote asset volume', 'Can be ignored']
+# df.index = [dt.datetime.fromtimestamp(x/1000.0) for x in df.ctime]
+# mpf.plot(df, type='line')
+
+
+lt.strategy_run()