def _g_json(cls, path):
name = os.path.split(path)[-1][:-5]
json_dict = sltm.g_config(path)
scraper = Scraper(**json_dict['scraper'])
if json_dict.get('logger'):
scraper.logger = sltc.EasyObj.select_type(**json_dict['logger'])
return scraper, name
def RESOURCE(cls, r, c, x):
'''Loads a resource
Args:
x (str ): resource name.
Returns:
dict : The dict loaded from the JSON resource.
'''
resource_path = join(slst.RESOURCE_FOLDER, x + '.json')
return sltm.g_config(resource_path)
def set_params(root='./'):
settings_dict = sltm.g_config(join(root, '__settings.json'))
_params_list = {
'EXTRACTORS_SEPARATOR': '-->',
'KWARGS_SEPARATOR': '<->',
'ESC_OPEN': '<(',
'ESC_CLOSE': ')>',
'LIST_SEPARATOR': '!!',
'COLLECTIONS_SEPARATOR': '|=|',
}
for param, def_value in _params_list.items():
set_param(param,
settings_dict.get('parameters', {}).get(param, def_value))
set_param('RESOURCE_FOLDER', join(root, 'resources'))
def run_scraper(cls, path, url=None, settings_path=None, is_join=True):
cls._load_customs(path)
settings_path = cls._g_settings_path(path, settings_path)
settings = sltm.g_config(settings_path)
if path.split('.')[-1] == 'json':
scraper, name = cls._g_json(path)
elif path.split('.')[-1] == 'py':
scraper, name = cls._g_py(path)
if url != None:
scraper.start_tasks.clear()
scraper.add_request(url)
scraper.is_single_request = True
try:
cls._start_scraper(name, scraper, settings, is_join)
except Exception as e:
print(traceback.format_exc())
import mplfinance
import matplotlib.dates as mdates
import saltools.misc as sltm
import matplotlib.pyplot as plt
import pandas as pd
import traceback
import engine
import random
import json
import sys
register_matplotlib_converters()
CONFIG_PATH = "ui_config.json"
CONFIGS = sltm.g_config(CONFIG_PATH)
def plot_ohlc(df, axes=None):
show = False
if not axes:
show = True
fig = plt.figure(figsize=(5, 4), dpi=100)
axes = fig.add_subplot(111)
df = df.reset_index()
df["date"] = df["date"].apply(mdates.date2num)
axes.xaxis_date()
axes.xaxis.set_major_formatter(mdates.DateFormatter('%Y-%m-%d %H'))
axes.tick_params(labelrotation=45, labelsize=7)
cl = candlestick_ohlc(ax=axes,
def run(self):
result = {}
results = {}
result['Trade Direction'] = self.direction
result['High Time Frame'] = self.time_frame
result['Ticker'] = self.ticker
clist = []
if self.ticker != '': # If we have supplied a ticker use it
pairs = [self.ticker]
else: # Or do for all tickers in config.json
pairs = sltm.g_config()['pairs']
if self.s_date == '':
self.s_date = datetime.utcnow()
try:
for pair in pairs: # for each ticker in list pairs
AT_HL = False
HTFscore = 0
ITFscore = 0
logging.info({'HTF Parsing DataFrame HTF': pair})
# Get Data from CSV or DB
try:
df = parseCSV(str(self.ticker) + '_HTF.csv')
except FileNotFoundError as e:
logging.info('Could not load data.')
logging.info(
'File {} was not found in current directory, exiting..'
.format(self.ticker + '.csv'))
exit()
time.sleep(0.3)
logging.info('\t+ DataFrame loaded')
time.sleep(0.1)
for row in df.iterrows():
cl = Candle(row, self.htf_params
) # Import each row of DF as a new Candle item
clist.append(cl) # Add each new Candle to a list
## HTF SCAN ##
## ##
HTF = Area(clist, self.htf_params, logging)
logging.info('{} scan HTF..'.format(self.direction))
TradingZone = HTF.HTFfindTradingZone(self.direction)
if TradingZone:
logging.info("\t+ Trading Zone ")
if self.direction == 'Long':
logging.info("\t+ Demand Zone at " + TradingZone[0] +
' - ' + TradingZone[1] + '\n')
TDZTop = TradingZone[3]
# Higher Frame Demand Zone TOP BOTTOM
HTFDZBOT = TradingZone[2]
HTFDZTOP = TradingZone[3]
Now = TradingZone[4]
elif self.direction == 'Short':
logging.info("\t+ Supply Zone at " + TradingZone[0] +
' - ' + TradingZone[1] + '\n')
TSZBot = TradingZone[2]
# Higher Frame Supply Zone TOP BOTTOM
HTFSZBOT = TradingZone[2]
HTFSZTOP = TradingZone[3]
Now = TradingZone[4]
else:
logging.info("\t+ No Trading Zone found..")
logging.info("\t+ Exiting..")
return results
OpposingZone = HTF.HTFfindOpposingZone(self.direction)
if OpposingZone: # If we find Opposing Zone
logging.info("\t+ Opposing Zone ")
if self.direction == 'Long':
logging.info("\t+ Supply Zone at " + OpposingZone[0] +
' - ' + OpposingZone[1] + '\n')
OSZBot = OpposingZone[2]
Now = TradingZone[4]
elif self.direction == 'Short':
logging.info("\t+ Demand Zone at " + OpposingZone[0] +
' - ' + OpposingZone[1] + '\n')
ODZTop = OpposingZone[3]
Now = TradingZone[4]
else: # If we dont find Opposing Zone look for ATH/ATL
logging.info(" No Opposing Zone found.")
logging.info("\t+ Now scanning for All-time High/Low..")
if self.direction == 'Long':
OSZBot = HTF.findAT(self.direction) # SZBot
logging.info("\t+ Found all-time High " + str(OSZBot))
AT_HL = True
elif self.direction == 'Short':
OSZTop = HTF.findAT(self.direction) # DZTop
logging.info("\t+ Found all-time Low " + str(OSZTop))
AT_HL = True
## ##
## ## ## ## ##
## HTF SCORING ##
## ##
if self.direction == 'Long':
curve = {}
for i in range(1, 6):
curve[i] = (i * (OSZBot - TDZTop) / 5) + TDZTop
if Now < curve[2] and Now > curve[1]:
logging.info(
"Current price is Very Low on the curve. Score = 2"
)
result['Curve Level'] = 'Very Low'
HTFscore = 2
elif Now < curve[3] and Now > curve[2]:
logging.info(
"Current price is Low on the curve. Score = 1")
result['Curve Level'] = 'Low'
HTFscore = 1
else:
result['Curve Level'] = 'High/Very High Score 0'
#logging.info("\n Price {}\n SZBot {}\n DZTop {}\n Score {}\n".format(Now, OSZBot, TDZTop, HTFscore))
elif self.direction == 'Short':
curve = {}
for i in range(1, 6):
curve[i] = (i * (TSZBot - ODZTop) / 5) + ODZTop
if Now < curve[5] and Now > curve[4]:
logging.info(
"Current price is Very High on the curve. Score = 2"
)
result['Curve Level'] = 'Very High'
HTFscore = 2
elif Now < curve[4] and Now > curve[3]:
logging.info(
"Current price is High on the curve. Score = 1")
result['Curve Level'] = 'High'
HTFscore = 1
else:
result['Curve Level'] = 'Low/Very Low Score 0'
## ##
## ## ## ## ##
######## ITF ########
# If checkbox is enabled do ITF
if self.checkitf:
# Reset results (except score) to proceed with ITF
clist.clear()
clist = []
logging.info({'ITF Parsing DataFrame ITF': pair})
# Get Data from CSV or DB
try:
df = parseCSV(str(self.ticker) + '_ITF.csv')
except FileNotFoundError as e:
logging.info('Could not load data.')
logging.info(
'File {} was not found in current directory, exiting..'
.format(self.ticker + '_ITF.csv'))
exit()
time.sleep(0.3)
logging.info('\t+ DataFrame loaded')
time.sleep(0.1)
# Calculate SMA EMA
df['sma'] = df['Close'].rolling(20).mean()
df['ema'] = df['Close'].ewm(5).mean()
if self.direction == 'Long':
if self.time_frame == 'Monthly' or self.time_frame == 'Weekly':
if df['ema'][0] > df['sma'][0]:
result['ITF Score'] = '5EMA > 20SMA Score = 1'
ITFscore = 1
else:
result['ITF Score'] = '5EMA < 20SMA Score = 0'
ITFscore = 0
else:
if df['Close'][0] > df['sma'][0]:
result[
'ITF Score'] = 'ClosePrice > 20SMA Score = 1'
ITFscore = 1
else:
result[
'ITF Score'] = 'ClosePrice < 20SMA Score = 0'
ITFscore = 0
elif self.direction == 'Short':
if self.time_frame == 'Monthly' or self.time_frame == 'Weekly':
if df['ema'][0] < df['sma'][0]:
result['ITF Score'] = '5EMA < 20SMA Score = 1'
ITFscore = 1
else:
result['ITF Score'] = '5EMA > 20SMA Score = 0'
ITFscore = 0
else:
if df['Close'][0] < df['sma'][0]:
result[
'ITF Score'] = 'ClosePrice < 20SMA Score = 1'
ITFscore = 1
else:
result[
'ITF Score'] = 'ClosePrice > 20SMA Score = 0'
ITFscore = 0
# Reset results (except score) to proceed with LTF
clist.clear()
clist = []
logging.info({'LTF Parsing DataFrame LTF': pair})
# Get Data from CSV or DB
try:
df = parseCSV(str(self.ticker) + '_LTF.csv')
except FileNotFoundError as e:
logging.info('Could not load data.')
logging.info(
'File {} was not found in current directory, exiting..'
.format(self.ticker + '.csv'))
exit()
time.sleep(0.3)
logging.info('\t+ DataFrame loaded')
time.sleep(0.1)
for row in df.iterrows():
cl = Candle(row, self.htf_params
) # Import each row of DF as a new Candle item
clist.append(cl) # Add each new Candle to a list
AT_HL = False
startFrom = 0 # LTF multiple trading-zone support
## LTF SCAN ##
## ##
LTF = Area(clist, self.ltf_params, logging)
logging.info('{} scan LTF..'.format(self.direction))
while True:
FINscore = 0
result['Zone Overlap'] = False
TradingZone = LTF.LTFfindTradingZone(
self.direction, startFrom)
if TradingZone:
startFrom = TradingZone[
6] # Next run begin from previous zone's end
logging.info("\t+ Trading Zone ")
if self.direction == 'Long':
logging.info("\t+ Demand Zone at " +
TradingZone[0] + ' - ' +
TradingZone[1] + '\n')
TDZTop = TradingZone[3]
TDZBot = TradingZone[2] # TDZBot for RRR
Now = TradingZone[4]
FINscore = FINscore + TradingZone[5]
result['Entry Price at LTF Zone'] = TDZTop
result[
'Date/Time of LO at LTF Zone'] = TradingZone[0]
#logging.info("\n Price {}\n TDZTop {}\n Score {}\n".format(Now, TDZTop, FINscore))
elif self.direction == 'Short':
logging.info("\t+ Supply Zone at " +
TradingZone[0] + ' - ' +
TradingZone[1] + '\n')
TSZBot = TradingZone[2]
TSZTop = TradingZone[3] # TSZTop for RRR
Now = TradingZone[4]
FINscore = FINscore + TradingZone[5]
result['Entry Price at LTF Zone'] = TSZBot
result[
'Date/Time of LO at LTF Zone'] = TradingZone[0]
#logging.info("\n Price {}\n TSZBot {}\n Score {}\n".format(Now, TSZBot, FINscore))
OpposingZone = LTF.LTFfindOpposingZone(self.direction)
if OpposingZone: # If we find Opposing Zone
logging.info("\t+ Opposing Zone ")
if self.direction == 'Long':
logging.info("\t+ Supply Zone at " +
OpposingZone[0] + ' - ' +
OpposingZone[1] + '\n')
OSZBot = OpposingZone[2]
Now = TradingZone[4]
RRR = (OSZBot - TDZTop) / (TDZTop - TDZBot
) # Reward / Risk
elif self.direction == 'Short':
logging.info("\t+ Demand Zone at " +
OpposingZone[0] + ' - ' +
OpposingZone[1] + '\n')
ODZTop = OpposingZone[3]
Now = TradingZone[4]
#print("Here TradingZone SupplyZone Bot = ", TSZBot)
#print("Here TradingZone SupplyZone Top = ", TSZTop)
#print("Here OpposinZone DemandZone Top = ", ODZTop)
RRR = (TSZBot - ODZTop) / (TSZTop - TSZBot
) # Reward / Risk
else: # If we dont find Opposing Zone look for ATH/ATL
logging.info("\t+ No Opposing Zone found.")
logging.info(
"\t+ Now scanning for All-time High/Low..")
if self.direction == 'Long':
OSZBot = HTF.findAT(self.direction) # SZBot
logging.info("\t+ Found all-time High " +
str(OSZBot))
AT_HL = True
RRR = (OSZBot - TDZTop) / (TDZTop - TDZBot
) # Reward / Risk
elif self.direction == 'Short':
OSZTop = HTF.findAT(self.direction) # DZTop
logging.info("\t+ Found all-time Low " +
str(OSZTop))
AT_HL = True
RRR = (ODZTop - TSZBot) / (TSZTop - TSZBot
) # Reward / Risk
# Add ZoneOnZone score
if self.direction == 'Long':
if TDZTop < HTFDZTOP and TDZBot > HTFDZBOT:
FINscore = FINscore + 2
result['Zone Overlap'] = True
elif self.direction == 'Short':
if TSZTop < HTFSZTOP and TSZBot > HTFSZBOT:
FINscore = FINscore + 2
result['Zone Overlap'] = True
# Add RRR score
if RRR > 3:
FINscore = FINscore + 1
elif RRR > 2 and RRR < 3:
FINscore = FINscore + 0.5
result['RRR'] = RRR
# Add HTF score
FINscore = FINscore + HTFscore + ITFscore
result['Score'] = FINscore
result['Leg Out Gap'] = LTF.LOgap
result['# of base Candles'] = LTF.Basings
result['Leg out Rank'] = LTF.LOrank
print(json.dumps(result, indent=4))
else:
#logging.info("\t+ No Trading Zone found.\n")
break
## ##
## ## ## ## ##
# Dereference all Candles and Ranges with __del__
# Go To LTF..
except KeyboardInterrupt:
raise (KeyboardInterrupt)
except Exception as e:
print(e)
traceback.print_exc()
pass
return results