Comparar texto

Encontre a diferença entre dois arquivos de texto

Editor live

Recolher inalteradas

Sem quebra de linha

Layout

Nível de detalhe

Realce de sintaxe

Diffchecker Desktop A maneira mais segura de usar o Diffchecker. Obtenha o aplicativo Diffchecker Desktop: seus diffs nunca saem do seu computador!Obter Desktop

SymbolData.py

Criado há 4 anosO diff nunca expira

44 remoções

Linhas
Total
Removido

Caracteres
Total
Removido

Para continuar usando este recurso, atualize para Diffchecker Pro Ver preços

140 linhas

19 adições

Linhas
Total
Adicionado

Caracteres
Total
Adicionado

Para continuar usando este recurso, atualize para Diffchecker Pro Ver preços

132 linhas

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

Diferenças salvas

Texto original

Abrir arquivo

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

Texto alterado

Abrir arquivo

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