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dip finder 4h 2h 15min 5min tfs with linear regression channel filter && 1min tf with CMO filter

xmd79
Dec 15th, 2022
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  1. from binance.client import Client
  2. import matplotlib.pyplot as plt
  3. import numpy as np
  4. from datetime import datetime
  5. import talib as ta
  6. #import statsmodels.api as sm
  7. import os, sys
  8.  
  9. import asyncio
  10.  
  11.  
  12. class Trader:
  13. def __init__(self, file):
  14. self.connect(file)
  15.  
  16. """ Creates Binance client """
  17. def connect(self,file):
  18. lines = [line.rstrip('\n') for line in open(file)]
  19. key = lines[0]
  20. secret = lines[1]
  21. self.client = Client(key, secret)
  22.  
  23. """ Gets all account balances """
  24. def getBalances(self):
  25. prices = self.client.get_withdraw_history()
  26. return prices
  27.  
  28. filename = 'credentials.txt'
  29. trader = Trader(filename)
  30.  
  31.  
  32.  
  33. filtered_pairs1 = []
  34. filtered_pairs2 = []
  35. filtered_pairs3 = []
  36. filtered_pairs4 = []
  37. selected_pair = []
  38. selected_pairCMO = []
  39.  
  40.  
  41. trading_pairs = [
  42. '1INCHUSDT','AAVEUSDT','ACAUSDT','ACHUSDT','ACMUSDT',
  43. 'ADAUSDT','ADXUSDT','AGLDUSDT','AIONUSDT','AKROUSDT',
  44. 'ALCXUSDT','ALGOUSDT','ALICEUSDT','ALPACAUSDT','ALPHAUSDT',
  45. 'ALPINEUSDT','AMPUSDT','ANCUSDT','ANKRUSDT','ANTUSDT',
  46. 'APEUSDT','API3USDT','APTUSDT','ARDRUSDT','ARPAUSDT','ARUSDT',
  47. 'ASRUSDT','ASTRUSDT','ATAUSDT','ATMUSDT','ATOMUSDT',
  48. 'AUCTIONUSDT','AUDIOUSDT','AUTOUSDT','AVAUSDT',
  49. 'AVAXUSDT','AXSUSDT','BADGERUSDT','BAKEUSDT','BALUSDT',
  50. 'BANDUSDT','BARUSDT','BATUSDT','BCHUSDT','BEAMUSDT',
  51. 'BELUSDT','BETAUSDT','BICOUSDT','BIFIUSDT','BLZUSDT','BNBUSDT',
  52. 'BNTUSDT','BNXUSDT','BONDUSDT','BSWUSDT',
  53. 'BTCUSDT','BTSUSDT','BTTCUSDT','BURGERUSDT',
  54. 'C98USDT','CAKEUSDT','CELOUSDT','CELRUSDT','CFXUSDT',
  55. 'CHESSUSDT','CHRUSDT','CHZUSDT','CITYUSDT','CKBUSDT',
  56. 'CLVUSDT','COCOSUSDT','COMPUSDT','COSUSDT','COTIUSDT',
  57. 'CRVUSDT','CTKUSDT','CTSIUSDT','CTXCUSDT','CVCUSDT',
  58. 'CVPUSDT','CVXUSDT','DARUSDT','DASHUSDT','DATAUSDT',
  59. 'DCRUSDT','DEGOUSDT','DENTUSDT','DEXEUSDT','DFUSDT',
  60. 'DGBUSDT','DIAUSDT','DOCKUSDT','DODOUSDT',
  61. 'DOGEUSDT','DOTUSDT','DREPUSDT','DUSKUSDT','DYDXUSDT',
  62. 'EGLDUSDT','ELFUSDT','ENJUSDT','ENSUSDT','EOSUSDT',
  63. 'EPXUSDT','ERNUSDT','ETCUSDT','ETHUSDT','FARMUSDT',
  64. 'FETUSDT','FIDAUSDT','FILUSDT','FIOUSDT','FIROUSDT',
  65. 'FISUSDT','FLMUSDT','FLOWUSDT','FLUXUSDT','FORTHUSDT',
  66. 'FORUSDT','FRONTUSDT','FTMUSDT','FUNUSDT',
  67. 'FXSUSDT','GALAUSDT','GALUSDT','GHSTUSDT','GLMRUSDT',
  68. 'GMTUSDT','GNOUSDT','GRTUSDT','GTCUSDT','GTOUSDT',
  69. 'HARDUSDT','HBARUSDT','HFTUSDT','HIGHUSDT','HIVEUSDT',
  70. 'HOTUSDT','ICPUSDT','ICXUSDT','IDEXUSDT','ILVUSDT',
  71. 'IMXUSDT','INJUSDT','IOSTUSDT','IOTAUSDT','IOTXUSDT',
  72. 'IRISUSDT','JASMYUSDT','JOEUSDT','JSTUSDT','JUVUSDT',
  73. 'KAVAUSDT','KDAUSDT','KEYUSDT','KLAYUSDT','KMDUSDT',
  74. 'KNCUSDT','KP3RUSDT','KSMUSDT','LAZIOUSDT','LDOUSDT','LEVERUSDT',
  75. 'LINAUSDT','LINKUSDT','LITUSDT','LOKAUSDT','LPTUSDT',
  76. 'LRCUSDT','LSKUSDT','LTCUSDT','LTOUSDT','LUNAUSDT','LUNCUSDT','MANAUSDT',
  77. 'MASKUSDT','MATICUSDT','MBLUSDT','MBOXUSDT','MCUSDT',
  78. 'MDTUSDT','MDXUSDT','MFTUSDT','MINAUSDT','MIRUSDT',
  79. 'MITHUSDT','MKRUSDT','MLNUSDT','MOBUSDT','MOVRUSDT',
  80. 'MTLUSDT','MULTIUSDT','NEBLUSDT','NEARUSDT','NEOUSDT',
  81. 'NEXOUSDT','NKNUSDT','NMRUSDT','NULSUSDT','OCEANUSDT',
  82. 'OGNUSDT','OGUSDT','OMGUSDT','OMUSDT','ONEUSDT',
  83. 'ONGUSDT','ONTUSDT','OOKIUSDT','ORNUSDT','OSMOUSDT','OXTUSDT',
  84. 'PAXGUSDT','PEOPLEUSDT','PERLUSDT','PERPUSDT','PHAUSDT','PHBUSDT',
  85. 'PLAUSDT','PNTUSDT','POLSUSDT','POLYXUSDT','PONDUSDT',
  86. 'PORTOUSDT','POWRUSDT','PSGUSDT','PUNDIXUSDT','PYRUSDT',
  87. 'QIUSDT','QNTUSDT','QTUMUSDT','QUICKUSDT','RADUSDT',
  88. 'RAREUSDT','RAYUSDT','REEFUSDT','REIUSDT',
  89. 'RENUSDT','REPUSDT','REQUSDT','RIFUSDT','RLCUSDT',
  90. 'RNDRUSDT','ROSEUSDT','RSRUSDT','RUNEUSDT','RVNUSDT',
  91. 'SANDUSDT','SANTOSUSDT','SCRTUSDT','SCUSDT','SFPUSDT',
  92. 'SHIBUSDT','SKLUSDT','SLPUSDT','SNXUSDT','SOLUSDT',
  93. 'SPELLUSDT','SRMUSDT','STEEMUSDT','STGUSDT','STMXUSDT','STORJUSDT','STPTUSDT',
  94. 'STRAXUSDT','STXUSDT','SUNUSDT','SUPERUSDT','SUSHIUSDT',
  95. 'SXPUSDT','SYSUSDT','TFUELUSDT','THETAUSDT',
  96. 'TKOUSDT','TLMUSDT','TOMOUSDT','TORNUSDT','TRBUSDT',
  97. 'TRIBEUSDT','TROYUSDT','TRUUSDT','TRXUSDT','TUSDT',
  98. 'TVKUSDT','TWTUSDT','UMAUSDT','UNFIUSDT','UNIUSDT',
  99. 'UTKUSDT','VETUSDT','VGXUSDT','VIDTUSDT','VITEUSDT',
  100. 'VOXELUSDT','VTHOUSDT','WANUSDT','WAVESUSDT','WAXPUSDT',
  101. 'WINGUSDT','WINUSDT','WNXMUSDT','WOOUSDT','WRXUSDT',
  102. 'WTCUSDT','XECUSDT','XEMUSDT','XLMUSDT','XMRUSDT',
  103. 'XNOUSDT','XRPUSDT','XTZUSDT','XVGUSDT','XVSUSDT',
  104. 'YFIIUSDT','YFIUSDT','YGGUSDT','ZECUSDT','ZENUSDT',
  105. 'ZILUSDT','ZRXUSDT'
  106. ]
  107.  
  108.  
  109.  
  110. def filter1(pair):
  111.  
  112. interval = '4h'
  113. symbol = pair
  114. klines = trader.client.get_klines(symbol=symbol,interval=interval)
  115. open_time = [int(entry[0]) for entry in klines]
  116. close = [float(entry[4]) for entry in klines]
  117. close_array = np.asarray(close)
  118.  
  119. print("on 4h timeframe " + symbol)
  120.  
  121. x = close
  122. y = range(len(x))
  123.  
  124. best_fit_line1 = np.poly1d(np.polyfit(y, x, 1))(y)
  125. best_fit_line2 = (np.poly1d(np.polyfit(y, x, 1))(y)) * 1.01
  126. best_fit_line3 = (np.poly1d(np.polyfit(y, x, 1))(y)) * 0.99
  127.  
  128. if x[-1] < best_fit_line3[-1] and best_fit_line1[0] <= best_fit_line1[-1]:
  129. filtered_pairs1.append(symbol)
  130. print('found')
  131.  
  132. #plt.figure(figsize=(8,6))
  133. #plt.grid(True)
  134. #plt.plot(x)
  135. #plt.plot(best_fit_line1, '--', color='r')
  136. #plt.plot(best_fit_line2, '--', color='r')
  137. #plt.plot(best_fit_line3, '--', color='r')
  138. #plt.show(block=False)
  139. #plt.pause(6)
  140. #plt.close()
  141.  
  142. elif x[-1] < best_fit_line3[-1] and best_fit_line1[0] >= best_fit_line1[-1]:
  143. filtered_pairs1.append(symbol)
  144. print('found')
  145.  
  146. #plt.figure(figsize=(8,6))
  147. #plt.grid(True)
  148. #plt.plot(x)
  149. #plt.plot(best_fit_line1, '--', color='r')
  150. #plt.plot(best_fit_line2, '--', color='r')
  151. #plt.plot(best_fit_line3, '--', color='r')
  152. #plt.show(block=False)
  153. #plt.pause(6)
  154. #plt.close()
  155.  
  156. else:
  157. print('searching')
  158.  
  159. def filter2(filtered_pairs1):
  160. interval = '2h'
  161. symbol = filtered_pairs1
  162. klines = trader.client.get_klines(symbol=symbol,interval=interval)
  163. open_time = [int(entry[0]) for entry in klines]
  164. close = [float(entry[4]) for entry in klines]
  165. close_array = np.asarray(close)
  166.  
  167. print("on 2h " + symbol)
  168.  
  169. x = close
  170. y = range(len(x))
  171.  
  172. best_fit_line1 = np.poly1d(np.polyfit(y, x, 1))(y)
  173. best_fit_line2 = (np.poly1d(np.polyfit(y, x, 1))(y)) * 1.01
  174. best_fit_line3 = (np.poly1d(np.polyfit(y, x, 1))(y)) * 0.99
  175.  
  176. if x[-1] < best_fit_line3[-1] and best_fit_line1[0] < best_fit_line1[-1]:
  177. filtered_pairs2.append(symbol)
  178. print('found')
  179.  
  180. #plt.figure(figsize=(8,6))
  181. #plt.grid(True)
  182. #plt.plot(x)
  183. #plt.plot(best_fit_line1, '--', color='r')
  184. #plt.plot(best_fit_line2, '--', color='r')
  185. #plt.plot(best_fit_line3, '--', color='r')
  186. #plt.show(block=False)
  187. #plt.pause(6)
  188. #plt.close()
  189.  
  190. if x[-1] < best_fit_line3[-1] and best_fit_line1[0] >= best_fit_line1[-1]:
  191. filtered_pairs2.append(symbol)
  192. print('found')
  193.  
  194. #plt.figure(figsize=(8,6))
  195. #plt.grid(True)
  196. #plt.plot(x)
  197. #plt.plot(best_fit_line1, '--', color='r')
  198. #plt.plot(best_fit_line2, '--', color='r')
  199. #plt.plot(best_fit_line3, '--', color='r')
  200. #plt.show(block=False)
  201. #plt.pause(6)
  202. #plt.close()
  203.  
  204. def filter3(filtered_pairs2):
  205. interval = '15m'
  206. symbol = filtered_pairs2
  207. klines = trader.client.get_klines(symbol=symbol,interval=interval)
  208. open_time = [int(entry[0]) for entry in klines]
  209. close = [float(entry[4]) for entry in klines]
  210. close_array = np.asarray(close)
  211.  
  212. print("on 15m timeframe " + symbol)
  213.  
  214. #min = ta.MIN(close_array, timeperiod=30)
  215. #max = ta.MAX(close_array, timeperiod=30)
  216.  
  217. #real = ta.HT_TRENDLINE(close_array)
  218. #wcl = ta.WCLPRICE(max, min, close_array)
  219.  
  220. print(close[-1])
  221. print()
  222. #print(min[-1])
  223. #print(max[-1])
  224. #print(real[-1])
  225.  
  226. x = close
  227. y = range(len(x))
  228.  
  229. best_fit_line1 = np.poly1d(np.polyfit(y, x, 1))(y)
  230. best_fit_line2 = (np.poly1d(np.polyfit(y, x, 1))(y)) * 1.01
  231. best_fit_line3 = (np.poly1d(np.polyfit(y, x, 1))(y)) * 0.99
  232.  
  233. if x[-1] < best_fit_line1[-1]:
  234. filtered_pairs3.append(symbol)
  235. print('found')
  236.  
  237. #plt.figure(figsize=(8,6))
  238. #plt.title(symbol)
  239. #plt.grid(True)
  240. #plt.plot(close)
  241. #plt.plot(best_fit_line1, '--', color='r')
  242. #plt.plot(best_fit_line2, '--', color='r')
  243. #plt.plot(best_fit_line3, '--', color='r')
  244. #plt.plot(close)
  245. #plt.plot(min)
  246. #plt.plot(max)
  247. #plt.plot(real)
  248. #plt.show(block=False)
  249. #plt.pause(5)
  250. #plt.close()
  251.  
  252. else:
  253. print('searching')
  254.  
  255.  
  256. def filter4(filtered_pairs3):
  257. interval = '5m'
  258. symbol = filtered_pairs3
  259. klines = trader.client.get_klines(symbol=symbol,interval=interval)
  260. open_time = [int(entry[0]) for entry in klines]
  261. close = [float(entry[4]) for entry in klines]
  262. close_array = np.asarray(close)
  263.  
  264. print("on 5m timeframe " + symbol)
  265.  
  266. #min = ta.MIN(close_array, timeperiod=30)
  267. #max = ta.MAX(close_array, timeperiod=30)
  268.  
  269. #real = ta.HT_TRENDLINE(close_array)
  270. #wcl = ta.WCLPRICE(max, min, close_array)
  271.  
  272. print(close[-1])
  273. print()
  274. #print(min[-1])
  275. #print(max[-1])
  276. #print(real[-1])
  277.  
  278. x = close
  279. y = range(len(x))
  280.  
  281. best_fit_line1 = np.poly1d(np.polyfit(y, x, 1))(y)
  282. best_fit_line2 = (np.poly1d(np.polyfit(y, x, 1))(y)) * 1.01
  283. best_fit_line3 = (np.poly1d(np.polyfit(y, x, 1))(y)) * 0.99
  284.  
  285. if x[-1] < best_fit_line1[-1]:
  286. filtered_pairs4.append(symbol)
  287. print('found')
  288.  
  289. #plt.figure(figsize=(8,6))
  290. #plt.title(symbol)
  291. #plt.grid(True)
  292. #plt.plot(close)
  293. #plt.plot(best_fit_line1, '--', color='r')
  294. #plt.plot(best_fit_line2, '--', color='r')
  295. #plt.plot(best_fit_line3, '--', color='r')
  296. #plt.plot(close)
  297. #plt.plot(min)
  298. #plt.plot(max)
  299. #plt.plot(real)
  300. #plt.show(block=False)
  301. #plt.pause(5)
  302. #plt.close()
  303.  
  304. else:
  305. print('searching')
  306.  
  307. def momentum(filtered_pairs4):
  308. interval = '1m'
  309. symbol = filtered_pairs4
  310. klines = trader.client.get_klines(symbol=symbol,interval=interval)
  311. open_time = [int(entry[0]) for entry in klines]
  312. close = [float(entry[4]) for entry in klines]
  313. close_array = np.asarray(close)
  314.  
  315. print()
  316. print("on 1m timeframe " + symbol)
  317.  
  318. real = ta.CMO(close_array, timeperiod=14)
  319. #print(real[-1])
  320.  
  321. if real[-1] < -50:
  322. print('oversold dip found')
  323. selected_pair.append(symbol)
  324. selected_pairCMO.append(real[-1])
  325.  
  326. else:
  327. print('searching')
  328.  
  329.  
  330. for i in trading_pairs:
  331. output = filter1(i)
  332. print(filtered_pairs1)
  333.  
  334. for i in filtered_pairs1:
  335. output = filter2(i)
  336. print(filtered_pairs2)
  337.  
  338. for i in filtered_pairs2:
  339. output = filter3(i)
  340. print(filtered_pairs3)
  341.  
  342. for i in filtered_pairs3:
  343. output = filter4(i)
  344. print(filtered_pairs4)
  345.  
  346. for i in filtered_pairs4:
  347. output = momentum(i)
  348. print(selected_pair)
  349.  
  350. if len(selected_pair) > 1:
  351. print('dips are more then 1 oversold')
  352. print(selected_pair)
  353. #print(selected_pairCMO)
  354.  
  355. if min(selected_pairCMO) in selected_pairCMO:
  356. #print(selected_pairCMO.index(min(selected_pairCMO)))
  357. position = selected_pairCMO.index(min(selected_pairCMO))
  358.  
  359. for id, value in enumerate(selected_pair):
  360. if id == position:
  361. print(selected_pair[id])
  362. #sys.exit()
  363.  
  364. elif len(selected_pair) == 1:
  365. print('1 dip found')
  366. print(selected_pair)
  367. print()
  368. #print(selected_pairCMO)
  369. #sys.exit()
  370.  
  371. else:
  372. print('no oversold dips for the moment, rescan dips...')
  373. print()
  374.  
  375. #print(selected_pair)
  376. #print(selected_pairCMO)
  377. #os.execl(sys.executable, sys.executable, *sys.argv)
  378.  
  379.  
  380.  
  381. sys.exit(0)
  382. sys.exit()
  383. exit()
  384.  
  385.  
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