Confronta il testo

Trova la differenza tra due file di testo

Editor live

Comprimi invariate

Senza a capo

Layout

Livello di dettaglio

Evidenziazione sintassi

Diffchecker Desktop Il modo più sicuro per usare Diffchecker. Ottieni l'app Diffchecker Desktop: i tuoi diff non lasciano mai il tuo computer!Ottieni Desktop

SymbolData.py

Creato 4 anni faIl diff non scade mai

44 rimozioni

Linee
Totale
Rimosso

Caratteri
Totale
Rimosso

Per continuare a utilizzare questa funzione, aggiorna a Diffchecker Pro Visualizza prezzi

140 linee

19 aggiunte

Linee
Totale
Aggiunto

Caratteri
Totale
Aggiunto

Per continuare a utilizzare questa funzione, aggiorna a Diffchecker Pro Visualizza prezzi

132 linee

Charts

Statistics

Code

##################################

# SymbolData Class

##################################

class SymbolData():

## Constructor

## -----------

def __init__(self, theSymbol, algo):

## Algo / Symbol / Price reference

self.algo = algo

self.symbol = theSymbol

self.lastDailyClose = None

self.lastClosePrice = None

## Initialize our Indicators and rolling windows

self.ema = ExponentialMovingAverage(self.algo.dailyEMAPeriod)

self.momentum = MomentumPercent(self.algo.hourlyMomPeriod)

self.lastDailyCloseWindow = RollingWindow[float](2)

self.emaWindow = RollingWindow[float](2)

## These will hold our 'messages' used in our order notes

self.ClosePositionMessage = ""

self.OpenPositionMessage = ""

## Seed Daily indicators with history.

## -----------------------------------

def SeedDailyIndicators(self, dailyHistory):

# Loop over the history data and update our indicators

if dailyHistory.empty or 'close' not in dailyHistory.columns:

# self.algo.Log(f"No Daily history for {self.symbol}")

return

else:

for timeIndex, dailyBar in dailyHistory.loc[self.symbol].iterrows():

if(self.ema is not None):

self.ema.Update(timeIndex, dailyBar['close'])

self.lastDailyClose = dailyBar['close']

self.timeOflastDailyClose = timeIndex

self.lastDailyCloseWindow.Add( dailyBar['close'] )

self.lastDailyCloseWindow.Add(dailyBar['close'])

self.emaWindow.Add( self.ema.Current.Value )

self.emaWindow.Add(self.ema.Current.Value)

## Seed intraday indicators with history

## These indicators might be have eitehr hourly or minute resolution

## -----------------------------------------------------------------

def SeedIntradayIndicators(self, hourlyHistory=None, minuteHistory=None):

# Loop over the history data and update our indicators

if hourlyHistory is not None:

if hourlyHistory.empty or 'close' not in hourlyHistory.columns:

self.algo.Log(f"Missing hourly history for {self.symbol}")

else:

for timeIndex, hourlyBar in hourlyHistory.loc[self.symbol].iterrows():

if(self.momentum is not None):

self.momentum.Update(timeIndex, hourlyBar['close'])

# If you are using minuteHistory, you need to add "someIndicator" to manage it in this class (in __init__())

if minuteHistory is not None:

if minuteHistory.empty or 'close' not in minuteHistory.columns:

self.algo.Log(f"Missing minute history for {self.symbol}")

else:

for timeIndex, hourlyBar in hourlyHistory.loc[self.symbol].iterrows():

for timeIndex, minuteBar in minuteHistory.loc[self.symbol].iterrows():

if(self.someIndicator is not None):

if self.someIndicator is not None:

self.someIndicator.Update(timeIndex, hourlyBar['close'])

self.someIndicator.Update(timeIndex, minuteBar['close'])

return

## Daily screening criteria. Called by the main algorithm.

## Returns true if daily screening conditions are met.

## Replace with your own criteria.

## -------------------------------------------------------

@property

def DailyScreeningCriteriaMet(self):

## Price is above ema.

if(self.lastDailyCloseWindow[0] > self.emaWindow[0]):

if self.lastDailyCloseWindow[0] > self.emaWindow[0]:

return True

return False

## Intraday screening criteria. Called by the main

## algorithm. Returns true if entry conditions are met.

## Replace with your own criteria.

## ----------------------------------------------------

@property

def IntradayScreeningCriteriaMet(self):

## If we have positive momentum

if (self.momentum.Current.Value > 0):

if self.momentum.Current.Value > 0:

## Informative message that will be submitted as order notes

self.OpenPositionMessage = f"OPEN (${round(self.lastDailyCloseWindow[0],3)} > EMA: {round(self.emaWindow[0],3)})"

return True

return False

## Trade Exit criteria. Called by the main algorithm.

## Returns true if exit conditions are met.

## Replace with your own criteria.

## ---------------------------------------------------

@property

def ExitCriteriaMet(self):

## Exit If price is below ema

if( self.lastClosePrice < self.ema.Current.Value ):

if self.lastClosePrice < self.ema.Current.Value:

self.ClosePositionMessage = f"CLOSE (${round(self.lastClosePrice,3)} < EMA: {round(self.ema.Current.Value,3)})"

return True

return False

## Returns true if our daily indicators are ready.

## Called from the main algo

## -----------------------------------------------

@property

def DailyIndicatorsAreReady(self):

return (self.ema.IsReady and self.lastDailyCloseWindow.IsReady)

return self.ema.IsReady and self.lastDailyCloseWindow.IsReady

## Returns true if our intraday indicators are ready.

## Called from the main algo

## --------------------------------------------------

@property

def IntradayIndicatorsAreReady(self):

return (self.momentum.IsReady)

return self.momentum.IsReady

## Called by the main algorithm right after

## a position is opened for this symbol.

## ----------------------------------------

def OnPositionOpened(self):

## Register & warmup the indicators we need to track for exits

self.algo.RegisterIndicator(self.symbol, self.ema, timedelta(1))

self.algo.WarmUpIndicator(self.symbol, self.ema, Resolution.Daily)

## Called by the main algorithm right after

## a position is closed for this symbol.

## ----------------------------------------

def OnPositionClosed(self):

# cleanup

pass

Diff salvati

Testo originale

Apri file

Charts
 Statistics
 Code

##################################
# 
# SymbolData Class
#
##################################
class SymbolData():
    
    ## Constructor
    ## -----------
    def __init__(self, theSymbol, algo):

## Algo / Symbol / Price reference
        self.algo                 = algo
        self.symbol               = theSymbol
        self.lastDailyClose       = None
        self.lastClosePrice       = None
        
        ## Initialize our Indicators and rolling windows
        self.ema                  = ExponentialMovingAverage(self.algo.dailyEMAPeriod)
        self.momentum             = MomentumPercent(self.algo.hourlyMomPeriod)
        self.lastDailyCloseWindow = RollingWindow[float](2)  
        self.emaWindow            = RollingWindow[float](2)  
    
        ## These will hold our 'messages' used in our order notes
        self.ClosePositionMessage = ""
        self.OpenPositionMessage  = ""

## Seed Daily indicators with history.
    ## -----------------------------------
    def SeedDailyIndicators(self, dailyHistory):

# Loop over the history data and update our indicators
        if dailyHistory.empty or 'close' not in dailyHistory.columns:
            # self.algo.Log(f"No Daily history for {self.symbol}")
            return
        
        else:
            for timeIndex, dailyBar in dailyHistory.loc[self.symbol].iterrows():
                if(self.ema is not None): 
                    self.ema.Update(timeIndex, dailyBar['close'])
                    self.lastDailyClose = dailyBar['close']
                    self.timeOflastDailyClose = timeIndex
                    
                    self.lastDailyCloseWindow.Add( dailyBar['close'] )
                    self.emaWindow.Add( self.ema.Current.Value )

## Seed intraday indicators with history
    ## These indicators might be have eitehr hourly or minute resolution
    ## -----------------------------------------------------------------
    def SeedIntradayIndicators(self, hourlyHistory=None, minuteHistory=None):
        
        # Loop over the history data and update our indicators
        if hourlyHistory is not None:    
            if hourlyHistory.empty or 'close' not in hourlyHistory.columns:
                self.algo.Log(f"Missing hourly history for {self.symbol}")
            else:
                for timeIndex, hourlyBar in hourlyHistory.loc[self.symbol].iterrows():
                    if(self.momentum is not None): 
                        self.momentum.Update(timeIndex, hourlyBar['close'])

if minuteHistory is not None:    
            if  minuteHistory.empty or 'close' not in minuteHistory.columns:
                self.algo.Log(f"Missing minute history for {self.symbol}")
            else:
                for timeIndex, hourlyBar in hourlyHistory.loc[self.symbol].iterrows():
                    if(self.someIndicator is not None): 
                        self.someIndicator.Update(timeIndex, hourlyBar['close'])
            return
        
    ## Daily screening criteria. Called by the main algorithm. 
    ## Returns true if daily screening conditions are met. 
    ## Replace with your own criteria.
    ## -------------------------------------------------------
    def DailyScreeningCriteriaMet(self):
    
        ## Price is above ema.
        if(self.lastDailyCloseWindow[0]  > self.emaWindow[0]):
                return True
                
        return False

## If we have positive momentum
        if (self.momentum.Current.Value > 0):

## Informative message that will be submitted as order notes
            self.OpenPositionMessage = f"OPEN (${round(self.lastDailyCloseWindow[0],3)} > EMA: {round(self.emaWindow[0],3)})"
            return True
            
        return False

## Exit If price is below ema
        if( self.lastClosePrice < self.ema.Current.Value ):
            self.ClosePositionMessage = f"CLOSE (${round(self.lastClosePrice,3)} < EMA: {round(self.ema.Current.Value,3)})"
            return True
        return False

## Returns true if our daily indicators are ready.
    ## Called from the main algo
    ## -----------------------------------------------
    def DailyIndicatorsAreReady(self):
        return (self.ema.IsReady and self.lastDailyCloseWindow.IsReady)

## Returns true if our intraday indicators are ready.
    ## Called from the main algo
    ## --------------------------------------------------
    def IntradayIndicatorsAreReady(self):
        return (self.momentum.IsReady)
        
    ## Called by the main algorithm right after 
    ## a position is opened for this symbol.
    ## ----------------------------------------
    def OnPositionOpened(self):
        
        ## Register & warmup the indicators we need to track for exits
        self.algo.RegisterIndicator(self.symbol, self.ema, timedelta(1)) 
        self.algo.WarmUpIndicator(self.symbol, self.ema, Resolution.Daily)
        
    ## Called by the main algorithm right after 
    ## a position is closed for this symbol.
    ## ----------------------------------------
    def OnPositionClosed(self):
        # cleanup
        pass

Testo modificato

Apri file

##################################
# 
# SymbolData Class
#
##################################
class SymbolData():
    
    ## Constructor
    ## -----------
    def __init__(self, theSymbol, algo):
        ## Algo / Symbol / Price reference
        self.algo                 = algo
        self.symbol               = theSymbol
        self.lastDailyClose       = None
        self.lastClosePrice       = None
        
        ## Initialize our Indicators and rolling windows
        self.ema                  = ExponentialMovingAverage(self.algo.dailyEMAPeriod)
        self.momentum             = MomentumPercent(self.algo.hourlyMomPeriod)
        self.lastDailyCloseWindow = RollingWindow[float](2)  
        self.emaWindow            = RollingWindow[float](2)  
    
        ## These will hold our 'messages' used in our order notes
        self.ClosePositionMessage = ""
        self.OpenPositionMessage  = ""

## Seed Daily indicators with history.
    ## -----------------------------------
    def SeedDailyIndicators(self, dailyHistory):
        # Loop over the history data and update our indicators
        if dailyHistory.empty or 'close' not in dailyHistory.columns:
            # self.algo.Log(f"No Daily history for {self.symbol}")
            return
        else:
            for timeIndex, dailyBar in dailyHistory.loc[self.symbol].iterrows():
                self.ema.Update(timeIndex, dailyBar['close'])
                self.lastDailyClose = dailyBar['close']
                self.timeOflastDailyClose = timeIndex
                    
                self.lastDailyCloseWindow.Add(dailyBar['close'])
                self.emaWindow.Add(self.ema.Current.Value)

## Seed intraday indicators with history
    ## These indicators might be have eitehr hourly or minute resolution
    ## -----------------------------------------------------------------
    def SeedIntradayIndicators(self, hourlyHistory=None, minuteHistory=None):
        # Loop over the history data and update our indicators
        if hourlyHistory is not None:    
            if hourlyHistory.empty or 'close' not in hourlyHistory.columns:
                self.algo.Log(f"Missing hourly history for {self.symbol}")
            else:
                for timeIndex, hourlyBar in hourlyHistory.loc[self.symbol].iterrows():
                    self.momentum.Update(timeIndex, hourlyBar['close'])

# If you are using minuteHistory, you need to add "someIndicator" to manage it in this class (in __init__())
        if minuteHistory is not None:    
            if  minuteHistory.empty or 'close' not in minuteHistory.columns:
                self.algo.Log(f"Missing minute history for {self.symbol}")
            else:
                for timeIndex, minuteBar in minuteHistory.loc[self.symbol].iterrows():
                    if self.someIndicator is not None:
                        self.someIndicator.Update(timeIndex, minuteBar['close'])
            return
        
    ## Daily screening criteria. Called by the main algorithm. 
    ## Returns true if daily screening conditions are met. 
    ## Replace with your own criteria.
    ## -------------------------------------------------------
    @property
    def DailyScreeningCriteriaMet(self):
        ## Price is above ema.
        if self.lastDailyCloseWindow[0] > self.emaWindow[0]:
            return True
        
        return False

## Intraday screening criteria. Called by the main 
    ## algorithm. Returns true if entry conditions are met. 
    ## Replace with your own criteria.
    ## ----------------------------------------------------
    @property
    def IntradayScreeningCriteriaMet(self):
        ## If we have positive momentum
        if self.momentum.Current.Value > 0:
            ## Informative message that will be submitted as order notes
            self.OpenPositionMessage = f"OPEN (${round(self.lastDailyCloseWindow[0],3)} > EMA: {round(self.emaWindow[0],3)})"
            return True
            
        return False

## Trade Exit criteria. Called by the main algorithm.
    ## Returns true if exit conditions are met. 
    ## Replace with your own criteria.
    ## ---------------------------------------------------
    @property
    def ExitCriteriaMet(self):
        ## Exit If price is below ema
        if self.lastClosePrice < self.ema.Current.Value:
            self.ClosePositionMessage = f"CLOSE (${round(self.lastClosePrice,3)} < EMA: {round(self.ema.Current.Value,3)})"
            return True

return False

## Returns true if our daily indicators are ready.
    ## Called from the main algo
    ## -----------------------------------------------
    @property
    def DailyIndicatorsAreReady(self):
        return self.ema.IsReady and self.lastDailyCloseWindow.IsReady

## Returns true if our intraday indicators are ready.
    ## Called from the main algo
    ## --------------------------------------------------
    @property
    def IntradayIndicatorsAreReady(self):
        return self.momentum.IsReady
        
    ## Called by the main algorithm right after 
    ## a position is opened for this symbol.
    ## ----------------------------------------
    def OnPositionOpened(self):
        ## Register & warmup the indicators we need to track for exits
        self.algo.RegisterIndicator(self.symbol, self.ema, timedelta(1)) 
        self.algo.WarmUpIndicator(self.symbol, self.ema, Resolution.Daily)
        
    ## Called by the main algorithm right after 
    ## a position is closed for this symbol.
    ## ----------------------------------------
    def OnPositionClosed(self):
        # cleanup
        pass