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Binance_Ichimoku_Scanner_With_Chikou_DOWN.py
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Binance_Ichimoku_Scanner_With_Chikou_DOWN.py
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# Not maintained anymore ; Instead, use https://github.com/reuniware/Binance-and-FTX-API-Work/blob/main/Binance_Ichimoku_Scanner_With_Chikou.py
import glob, os
from datetime import datetime
from datetime import timedelta
from binance.client import Client
from binance.enums import HistoricalKlinesType
import binance
import pandas as pd
import requests
import threading
import time
import ta
import math
from enum import Enum
class ScanType(Enum):
UP = 0
DOWN = 1
# Set this variable to ScanType.UP for scanning uptrend assets or to ScanType.DOWN for scanning downtrend assets
scan_type = ScanType.DOWN
# Set this variable to False to scan in spot mode
scan_futures = True
def log_to_results(str_to_log):
fr = open("results.txt", "a")
fr.write(str_to_log + "\n")
fr.close()
def log_to_errors(str_to_log):
fr = open("errors.txt", "a")
fr.write(str_to_log + "\n")
fr.close()
def log_to_trades(str_to_log):
fr = open("trades.txt", "a")
fr.write(str_to_log + "\n")
fr.close()
def log_to_evol(str_to_log):
fr = open("evol.txt", "a")
fr.write(str_to_log + "\n")
fr.close()
if os.path.exists("results.txt"):
os.remove("results.txt")
if os.path.exists("errors.txt"):
os.remove("errors.txt")
if os.path.exists("trades.txt"):
os.remove("trades.txt")
if os.path.exists("evol.txt"):
os.remove("evol.txt")
for fg in glob.glob("CS_*.txt"):
os.remove(fg)
# print("Scanning type = ", scan_type.name)
# log_to_results("Scanning type = " + scan_type.name)
HISTORY_RESOLUTION_1MINUTE = 60
HISTORY_RESOLUTION_3MINUTE = 60 * 3
HISTORY_RESOLUTION_5MINUTE = 60 * 5
HISTORY_RESOLUTION_15MINUTE = 60 * 15
HISTORY_RESOLUTION_30MINUTE = 60 * 30
HISTORY_RESOLUTION_HOUR = 60 * 60
HISTORY_RESOLUTION_4HOUR = 60 * 60 * 4
HISTORY_RESOLUTION_DAY = 60 * 60 * 24
results_count = 0
stop_thread = False
list_results = []
array_futures = []
def my_thread(name):
global client, list_results, results_count, stop_thread
log_to_evol(str(datetime.now()))
while not stop_thread:
dict_evol = {}
new_results_found = False
info_binance = Client().get_all_tickers()
#print(info_binance)
#exit()
df = pd.DataFrame(info_binance)
df.set_index('symbol')
for index, row in df.iterrows():
symbol = row['symbol']
symbol_type = "n/a" #row['type']
#print(symbol)
# filtering symbols to scan here
if not symbol.endswith('USDT') or symbol.endswith("DOWNUSDT") or symbol.endswith("UPUSDT"):
continue
#if symbol != 'BANDUSDT':
#continue
if scan_futures:
print(symbol, "trying to scan in futures")
else:
print(symbol, "trying to scan")
# if symbol.endswith("BEAR/USD") or symbol.endswith("BULL/USD") or symbol.endswith("HEDGE/USD") or symbol.endswith():
# continue
# Define the resolution for data downloading and scanning on the line below
history_resolution = HISTORY_RESOLUTION_30MINUTE # define the resolution used for the scan here
if history_resolution == HISTORY_RESOLUTION_1MINUTE:
interval_for_klinesT = Client.KLINE_INTERVAL_1MINUTE
elif history_resolution == HISTORY_RESOLUTION_3MINUTE:
interval_for_klinesT = Client.KLINE_INTERVAL_3MINUTE
elif history_resolution == HISTORY_RESOLUTION_5MINUTE:
interval_for_klinesT = Client.KLINE_INTERVAL_5MINUTE
elif history_resolution == HISTORY_RESOLUTION_15MINUTE:
interval_for_klinesT = Client.KLINE_INTERVAL_15MINUTE
elif history_resolution == HISTORY_RESOLUTION_30MINUTE:
interval_for_klinesT = Client.KLINE_INTERVAL_30MINUTE
elif history_resolution == HISTORY_RESOLUTION_HOUR:
interval_for_klinesT = Client.KLINE_INTERVAL_1HOUR
elif history_resolution == HISTORY_RESOLUTION_4HOUR:
interval_for_klinesT = Client.KLINE_INTERVAL_4HOUR
elif history_resolution == HISTORY_RESOLUTION_DAY:
interval_for_klinesT = Client.KLINE_INTERVAL_1DAY
else:
print("What should I set for Client KLINE_INTERVAL ?")
exit()
days_ago_for_klinest = "80 day ago UTC" # for daily download by default
if interval_for_klinesT == Client.KLINE_INTERVAL_1MINUTE:
days_ago_for_klinest = "120 minute ago UTC"
elif interval_for_klinesT == Client.KLINE_INTERVAL_3MINUTE:
days_ago_for_klinest = "360 minute ago UTC"
elif interval_for_klinesT == Client.KLINE_INTERVAL_5MINUTE:
days_ago_for_klinest = "800 minute ago UTC"
elif interval_for_klinesT == Client.KLINE_INTERVAL_15MINUTE:
days_ago_for_klinest = "1200 minute ago UTC"
elif interval_for_klinesT == Client.KLINE_INTERVAL_30MINUTE:
days_ago_for_klinest = "2400 minute ago UTC"
elif interval_for_klinesT == Client.KLINE_INTERVAL_1HOUR:
days_ago_for_klinest = "80 hour ago UTC"
elif interval_for_klinesT == Client.KLINE_INTERVAL_4HOUR:
days_ago_for_klinest = "320 hour ago UTC"
try:
#klinesT = Client().get_historical_klines(symbol, interval_for_klinesT, "09 May 2022")
if scan_futures:
klinesT = Client().get_historical_klines(
symbol, interval_for_klinesT, days_ago_for_klinest, klines_type=HistoricalKlinesType.FUTURES)
else:
klinesT = Client().get_historical_klines(
symbol, interval_for_klinesT, days_ago_for_klinest)
dframe = pd.DataFrame(klinesT,
columns=[
'timestamp', 'open', 'high', 'low',
'close', 'volume', 'close_time',
'quote_av', 'trades', 'tb_base_av',
'tb_quote_av', 'ignore'
])
del dframe['ignore']
del dframe['close_time']
del dframe['quote_av']
del dframe['trades']
del dframe['tb_base_av']
del dframe['tb_quote_av']
dframe['close'] = pd.to_numeric(dframe['close'])
dframe['high'] = pd.to_numeric(dframe['high'])
dframe['low'] = pd.to_numeric(dframe['low'])
dframe['open'] = pd.to_numeric(dframe['open'])
dframe = dframe.set_index(dframe['timestamp'])
dframe.index = pd.to_datetime(dframe.index, unit='ms')
except requests.exceptions.HTTPError:
print(
"Erreur (HTTPError) tentative obtention données historiques pour "
+ symbol)
log_to_errors(
"Erreur (HTTPError) tentative obtention données historiques pour "
+ symbol)
continue
except requests.exceptions.ConnectionError:
print(
"Erreur (ConnectionError) tentative obtention données historiques pour "
+ symbol)
log_to_errors(
"Erreur (ConnectionError) tentative obtention données historiques pour "
+ symbol)
continue
except binance.exceptions.BinanceAPIException:
# in case the symbol does not exist in futures then this exception is thrown
continue
# a = time.time()
# my_time = time.strftime('%Y-%m-%d %H:%M:%S', time.localtime(a))
# my_time_2 = time.strftime('%Y-%m-%d %H:%M:%S', time.localtime(a - delta_time))
#dframe = pd.DataFrame(data)
# dframe['time'] = pd.to_datetime(dframe['time'], unit='ms')
# print(dframe)
try:
dframe['ICH_SSA'] = ta.trend.ichimoku_a(dframe['high'],
dframe['low'],
window1=9,
window2=26).shift(26)
dframe['ICH_SSB'] = ta.trend.ichimoku_b(dframe['high'],
dframe['low'],
window2=26,
window3=52).shift(26)
dframe['ICH_KS'] = ta.trend.ichimoku_base_line(
dframe['high'], dframe['low'])
dframe['ICH_TS'] = ta.trend.ichimoku_conversion_line(
dframe['high'], dframe['low'])
dframe['ICH_CS'] = dframe['close'].shift(-26)
except KeyError as err:
print(err)
continue
for indexdf, rowdf in dframe.iterrows():
openp = rowdf['open']
high = rowdf['high']
low = rowdf['low']
close = rowdf['close']
ssa = rowdf['ICH_SSA']
ssb = rowdf['ICH_SSB']
ks = rowdf['ICH_KS']
ts = rowdf['ICH_TS']
# cs = rowdf['ICH_CS']
try:
cs = dframe['ICH_CS'].iloc[
-26 - 1] # chikou span concernant bougie n en cours
cs2 = dframe['ICH_CS'].iloc[
-26 - 2] # chikou span concernant bougie n-1
#ssbchikou = dframe['ICH_SSB'].iloc[-26 - 1 + 2]
#ssbchikou2 = dframe['ICH_SSB'].iloc[-26 - 2 + 2]
#ssbchikou3 = dframe['ICH_SSB'].iloc[-26 - 3 + 2]
ssbchikou = dframe['ICH_SSB'].iloc[-52]
ssbchikou2 = dframe['ICH_SSB'].iloc[-52 - 1]
ssbchikou3 = dframe['ICH_SSB'].iloc[-52 - 2]
ssachikou = dframe['ICH_SSA'].iloc[-26 + 1]
ssachikou2 = dframe['ICH_SSA'].iloc[-26 - 1]
ssachikou3 = dframe['ICH_SSA'].iloc[-26 - 2]
closechikou = dframe['close'].iloc[-26]
closechikou2 = dframe['close'].iloc[-26 - 1]
openchikou = dframe['open'].iloc[-26]
openchikou2 = dframe['open'].iloc[-26 - 1]
lowchikou = dframe['low'].iloc[-26]
lowchikou2 = dframe['low'].iloc[-26 - 1]
highchikou = dframe['high'].iloc[-26]
highchikou2 = dframe['high'].iloc[-26 - 1]
kijunchikou = dframe['ICH_KS'].iloc[-26 - 1 + 1]
kijunchikou2 = dframe['ICH_KS'].iloc[-26 - 2 + 1]
kijunchikou3 = dframe['ICH_KS'].iloc[-26 - 3 + 1]
tenkanchikou = dframe['ICH_TS'].iloc[-26 - 1 + 1]
tenkanchikou2 = dframe['ICH_TS'].iloc[-26 - 2 + 1]
tenkanchikou3 = dframe['ICH_TS'].iloc[-26 - 3 + 1]
except IndexError as error:
print(symbol + " EXCEPTION " + str(error))
log_to_errors(symbol + " EXCEPTION " + str(error) + '\n')
# quit(0)
continue
#timestamp = pd.to_datetime(rowdf['time'], unit='ms')
timestamp = pd.to_datetime(rowdf['timestamp'], unit='ms')
error_nan_values = False
# To check the values of Ichimoku data (use TradingView with Ichimoku Cloud to compare them)
#print(str(timestamp) + " " + symbol + " closecs=" + str(closechikou) + " closecs2=" + str(closechikou2) + " CS=" + str(cs) + " CS2=" + str(cs2) + " SSBCS=" + str(ssbchikou) + " SSBCS2=" + str(ssbchikou2) + " SSBCS3=" + str(ssbchikou3) + " KSCS=" + str(kijunchikou)+ " KSCS2=" + str(kijunchikou2)+ " KSCS3=" + str(kijunchikou3) + " TSCS=" + str(tenkanchikou)+ " TSCS2=" + str(tenkanchikou2)+ " TSCS3=" + str(tenkanchikou3) + " SSACS=" + str(ssachikou) + " SSACS2=" + str(ssachikou2) + " SSACS3=" + str(ssachikou3))
#exit()
if math.isnan(closechikou) or math.isnan(
closechikou2
) or math.isnan(cs) or math.isnan(cs2) or math.isnan(
ssbchikou) or math.isnan(ssbchikou2) or math.isnan(
ssbchikou3
) or math.isnan(kijunchikou) or math.isnan(
kijunchikou2
) or math.isnan(kijunchikou3) or math.isnan(
tenkanchikou
) or math.isnan(tenkanchikou2) or math.isnan(
tenkanchikou3) or math.isnan(
ssachikou) or math.isnan(
ssbchikou2) or math.isnan(ssachikou3):
print(symbol + " THERE ARE NAN VALUES IN ICHIMOKU DATA")
log_to_errors(symbol +
" THERE ARE NAN VALUES IN ICHIMOKU DATA" +
'\n')
error_nan_values = True
# quit(0)
if error_nan_values:
continue
filename = "CS_" + symbol.replace('/', '_') + ".txt"
if os.path.exists(filename):
os.remove(filename)
# now_cs = datetime.datetime_result_min() - timedelta(hours=4 * 26)
# # print("now_cs=" + str(now_cs))
# # quit(0)
# if timestamp.year == now_cs.year and timestamp.month == now_cs.year and timestamp.day == now_cs.day and timestamp.hour == now_cs.hour:
# print(str(cs))
data_minute = timestamp.minute
data_hour = timestamp.hour
data_day = timestamp.day
data_month = timestamp.month
data_year = timestamp.year
if history_resolution == HISTORY_RESOLUTION_1MINUTE:
datetime_result_min = datetime.now() - timedelta(minutes=1)
elif history_resolution == HISTORY_RESOLUTION_3MINUTE:
#datetime_result_min = datetime.now() - timedelta(minutes=15)
datetime_result_min = datetime.now() - timedelta(minutes=3)
elif history_resolution == HISTORY_RESOLUTION_5MINUTE:
#datetime_result_min = datetime.now() - timedelta(minutes=15)
datetime_result_min = datetime.now() - timedelta(minutes=5)
elif history_resolution == HISTORY_RESOLUTION_15MINUTE:
#datetime_result_min = datetime.now() - timedelta(hours=1)
datetime_result_min = datetime.now() - timedelta(
minutes=15)
elif history_resolution == HISTORY_RESOLUTION_30MINUTE:
#datetime_result_min = datetime.now() - timedelta(hours=1)
datetime_result_min = datetime.now() - timedelta(
minutes=30)
elif history_resolution == HISTORY_RESOLUTION_HOUR:
datetime_result_min = datetime.now() - timedelta(hours=1)
elif history_resolution == HISTORY_RESOLUTION_4HOUR:
datetime_result_min = datetime.now() - timedelta(hours=4)
elif history_resolution == HISTORY_RESOLUTION_DAY:
datetime_result_min = datetime.now() - timedelta(hours=24)
else:
datetime_result_min = datetime.now() - timedelta(
hours=1) # We should never get here
datetime_result_min_minute = datetime_result_min.minute
datetime_result_min_hour = datetime_result_min.hour
datetime_result_min_day = datetime_result_min.day
datetime_result_min_month = datetime_result_min.month
datetime_result_min_year = datetime_result_min.year
# if math.isnan(ssa):
# print(symbol, "ssa is null")
#
# if math.isnan(ssb):
# print(symbol, "ssb is null")
evol_co = round(((close - openp) / openp) * 100, 4)
scan = True
if history_resolution == HISTORY_RESOLUTION_1MINUTE:
result_ok = data_day == datetime_result_min_day and data_month == datetime_result_min_month and data_year == datetime_result_min_year and data_hour == datetime_result_min_hour and data_minute >= datetime_result_min_minute
elif history_resolution == HISTORY_RESOLUTION_3MINUTE:
result_ok = data_day == datetime_result_min_day and data_month == datetime_result_min_month and data_year == datetime_result_min_year and data_hour == datetime_result_min_hour and data_minute >= datetime_result_min_minute
elif history_resolution == HISTORY_RESOLUTION_5MINUTE:
# print("comparing : " + str(data_hour) + " " + str(data_minute) + " to " + str(datetime_result_min_hour) + " " + str(datetime_result_min_minute))
result_ok = data_day == datetime_result_min_day and data_month == datetime_result_min_month and data_year == datetime_result_min_year and data_hour == datetime_result_min_hour and data_minute >= datetime_result_min_minute
elif history_resolution == HISTORY_RESOLUTION_15MINUTE:
result_ok = data_day == datetime_result_min_day and data_month == datetime_result_min_month and data_year == datetime_result_min_year and data_hour == datetime_result_min_hour and data_minute >= datetime_result_min_minute
elif history_resolution == HISTORY_RESOLUTION_30MINUTE:
result_ok = data_day == datetime_result_min_day and data_month == datetime_result_min_month and data_year == datetime_result_min_year and data_hour == datetime_result_min_hour and data_minute >= datetime_result_min_minute
elif history_resolution == HISTORY_RESOLUTION_HOUR:
result_ok = data_day == datetime_result_min_day and data_month == datetime_result_min_month and data_year == datetime_result_min_year and data_hour > datetime_result_min_hour #and data_minute >= datetime_result_min_minute
else:
result_ok = data_day == datetime_result_min_day and data_month == datetime_result_min_month and data_year == datetime_result_min_year and data_hour >= datetime_result_min_hour
#if symbol == "ETHUSDT":
# print ("ETHUSDT SSACHIKOU = " + str(ssachikou))
# print ("ETHUSDT SSBCHIKOU = " + str(ssbchikou))
if scan:
if result_ok:
# if openp < ssb < close or openp > ssb and close > ssb:
# Define your own criterias for filtering assets on the line below
if scan_type == ScanType.UP:
condition_is_satisfied = openp > ks and close > ks and close > ts and close > openp and close > ssa and close > ssb and cs > highchikou and cs > kijunchikou and cs > ssbchikou and cs > ssachikou and cs > tenkanchikou
elif scan_type == ScanType.DOWN:
condition_is_satisfied = openp < ks and close < ks and close < ts and close < openp and close < ssa and close < ssb and cs < lowchikou and cs < kijunchikou and cs < ssbchikou and cs < ssachikou and cs < tenkanchikou
if condition_is_satisfied:
cs_results = ""
if scan_type == ScanType.UP:
if cs > ssbchikou:
cs_results += "* CS > SSBCHIKOU - "
if cs > ssachikou:
cs_results += "* CS > SSACHIKOU - "
if cs > kijunchikou:
cs_results += "* CS > KSCHIKOU - "
if cs > tenkanchikou:
cs_results += "* CS > TSCHIKOU - "
if cs > closechikou:
cs_results += "* CS > CLOSECHIKOU - "
if cs > highchikou:
cs_results += "* CS > HIGHCHIKOU - "
# if cs_results != "":
# log_to_results(cs_results)
# print(timestamp, symbol, "O", openp, "H", high, "L", low, "C", close, "SSA", ssa, "SSB", ssb, "KS", ks, "TS", ts, "CS", cs, "EVOL%", evol_co)
elif scan_type == ScanType.DOWN:
if cs < ssbchikou:
cs_results += "* CS < SSBCHIKOU - "
if cs < ssachikou:
cs_results += "* CS < SSACHIKOU - "
if cs < kijunchikou:
cs_results += "* CS < KSCHIKOU - "
if cs < tenkanchikou:
cs_results += "* CS < TSCHIKOU - "
if cs < closechikou:
cs_results += "* CS < CLOSECHIKOU - "
if cs < highchikou:
cs_results += "* CS < LOWCHIKOU - "
# if cs_results != "":
# log_to_results(cs_results)
# print(timestamp, symbol, "O", openp, "H", high, "L", low, "C", close, "SSA", ssa, "SSB", ssb, "KS", ks, "TS", ts, "CS", cs, "EVOL%", evol_co)
# print("")
str_result = str(
timestamp
) + " " + symbol + " " + symbol_type + " SSA=" + str(
ssa
) + " SSB=" + str(ssb) + " KS=" + str(
ks
) + " TS=" + str(ts) + " O=" + str(
openp
) + " H=" + str(high) + " L=" + str(
low
) + " SSBCS=" + str(ssbchikou) # + " C=" + str(close) + " CS=" + str(cs) + " EVOL%=" + str(evol_co) # We don't concatenate the variable parts (for comparisons in list_results)
if not (str_result in list_results):
if not new_results_found:
new_results_found = True
results_count = results_count + 1
list_results.append(str_result)
# print(cs_results)
str_result = cs_results + "\n" + str(
results_count
) + " " + str_result + " C=" + str(
close
) + " CS=" + str(cs) + " EVOL(C/O)%=" + str(
evol_co
) # We add the data with variable parts
if scan_futures:
str_result += "\nhttps://fr.tradingview.com/chart/4hWFksx8/?symbol=BINANCE%3A" + symbol + "PERP"
else:
str_result += "\nhttps://fr.tradingview.com/chart/4hWFksx8/?symbol=BINANCE%3A" + symbol
print(str_result + "\n")
log_to_results(str_result + "\n")
dict_evol[symbol] = evol_co
else:
# if result_ok:
print(timestamp, symbol, "O", openp, "H", high, "L", low,
"C", close, "SSA", ssa, "SSB", ssb, "KS", ks, "TS",
ts, "CS", cs, "SSB CS", ssbchikou)
str_result = str(timestamp) + " " + symbol + " O=" + str(
openp) + " H=" + str(high) + " L=" + str(
low) + " C=" + str(close) + " SSA=" + str(
ssa) + " SSB=" + str(ssb) + " KS=" + str(
ks) + " TS=" + str(ts) + " CS=" + str(
cs) + " SSB CS=" + str(ssbchikou) + " EVOL%(C/O)=" + str(evol_co)
log_to_results(str_result)
if new_results_found:
log_to_results(100 * '*' + "\n")
new_dict = sorted(dict_evol.items(), key=lambda kv: (kv[1], kv[0]))
print(str(datetime.now()) + " " + str(new_dict))
log_to_evol(str(datetime.now()) + " " + str(new_dict))
# Remove the line below to scan in loop
#stop_thread = True
x = threading.Thread(target=my_thread, args=(1, ))
x.start()
# array_futures = []
# if scan_futures:
# interval_for_klinesT = Client.KLINE_INTERVAL_1MINUTE
# days_ago_for_klinest = "1 minute ago UTC"
# info_binance = Client().get_all_tickers()
# df = pd.DataFrame(info_binance)
# df.set_index('symbol')
# for index, row in df.iterrows():
# symbol = row['symbol']
# try:
# print("trying", symbol)
# klinesT = Client().get_historical_klines(
# symbol, interval_for_klinesT, days_ago_for_klinest, klines_type=HistoricalKlinesType.FUTURES)
# array_futures.append(symbol)
# except binance.exceptions.BinanceAPIException:
# # in case the symbol does not exist in futures then this exception is thrown
# continue
#history_resolution = HISTORY_RESOLUTION_1MINUTE # define the resolution used for the scan here
# delta_time = 0
# if history_resolution == HISTORY_RESOLUTION_1MINUTE: # using this resolution seems not ok, must be improved
# #delta_time = 60 * 5
# delta_time = 60
# elif history_resolution == HISTORY_RESOLUTION_3MINUTE:
# delta_time = 60 * 3
# elif history_resolution == HISTORY_RESOLUTION_5MINUTE: # using this resolution seems not ok, must be improved
# #delta_time = 60 * 5 * 25
# delta_time = 60 * 5
# elif history_resolution == HISTORY_RESOLUTION_15MINUTE:
# #delta_time = 60 * 60 * 15 * 3
# delta_time = 60 * 60 * 15
# elif history_resolution == HISTORY_RESOLUTION_HOUR:
# #delta_time = 60 * 60 * 3 * 15 * 2
# delta_time = 60 * 60
# elif history_resolution == HISTORY_RESOLUTION_4HOUR:
# #delta_time = 60 * 60 * 3 * 15 * 2 * 4
# delta_time = 60 * 60 * 4
# elif history_resolution == HISTORY_RESOLUTION_DAY:
# delta_time = 60 * 60 * 2000