Exemple #1
0
    def get_data_by_date_range(name, startMonth, startYear, endMonth, endYear):
        caseSensitiveName = DataManager.idToName[DataManager.nameToId[
            name.lower()]]

        rtn = []

        #iterate through month by month, year by year from the start to the
        #end and add any nonzero datapoints to the list of data
        currYear = startYear
        currMonth = startMonth
        while (currYear <= endYear):

            #if the current year is before the end year, then we just
            #iterate through all months
            if (currYear < endYear):
                while (currMonth <= 12):
                    monthData = PriceReader.read_month_data(
                        currMonth, currYear, caseSensitiveName)
                    for day in range(1, len(monthData.data)):
                        prices = monthData.get(day)

                        #we only add nonzero prices becauase prices of 0
                        #means that there was no price data for that given date
                        if (prices[0] != 0 and prices[1] != 0):
                            rtn.append((currYear, currMonth, day, prices[0],
                                        prices[1]))
                    currMonth = currMonth + 1

                #have to reset the month back to 1 after we've gone through
                #all 12 months in the current year
                currMonth = 1

            #if the current year is the end year, then we can only iterate
            #up to the end month
            elif (currYear == endYear):
                while (currMonth <= endMonth):
                    monthData = PriceReader.read_month_data(
                        currMonth, currYear, name)
                    for day in range(1, len(monthData.data)):
                        prices = monthData.get(day)
                        if (prices[0] != 0 and prices[1] != 0):
                            rtn.append((currYear, currMonth, day, prices[0],
                                        prices[1]))
                    currMonth = currMonth + 1

            #move on to the next year
            currYear = currYear + 1

        return rtn
 def get_data_by_date_range( name , startMonth , startYear , endMonth , endYear ):
     caseSensitiveName = DataManager.idToName[ DataManager.nameToId[ name.lower() ] ]
     
     rtn = []
     
     #iterate through month by month, year by year from the start to the
     #end and add any nonzero datapoints to the list of data
     currYear = startYear
     currMonth = startMonth
     while( currYear <= endYear ):
         
         #if the current year is before the end year, then we just
         #iterate through all months
         if ( currYear < endYear ):
             while( currMonth <= 12 ):
                 monthData = PriceReader.read_month_data( currMonth , currYear , caseSensitiveName )
                 for day in range( 1 , len( monthData.data ) ):
                     prices = monthData.get( day )
                     
                     #we only add nonzero prices becauase prices of 0
                     #means that there was no price data for that given date
                     if ( prices[ 0 ] != 0 and prices[ 1 ] != 0 ):
                         rtn.append( (currYear , currMonth , day , prices[ 0 ] , prices[ 1 ] ) )
                 currMonth = currMonth + 1
                 
             #have to reset the month back to 1 after we've gone through
             #all 12 months in the current year
             currMonth = 1
             
         #if the current year is the end year, then we can only iterate
         #up to the end month
         elif ( currYear == endYear ):
             while( currMonth <= endMonth ):
                 monthData = PriceReader.read_month_data( currMonth , currYear , name )
                 for day in range( 1 , len( monthData.data ) ):
                     prices = monthData.get( day )
                     if ( prices[ 0 ] != 0 and prices[ 1 ] != 0 ):
                         rtn.append( (currYear , currMonth , day , prices[ 0 ] , prices[ 1 ] ) )
                 currMonth = currMonth + 1
             
         #move on to the next year
         currYear = currYear + 1
     
     return rtn
 def get_profitability_rankings( totalFunds , duration ):
     f = open( "price_data/item_ids" , 'r' )
     rankings = []
     for line in f.readlines():
         commodityId = int(line.split( "," )[ 1 ])
         data = PriceReader.get_price_data_from_csv( commodityId )
         rankings.append( (data , ProfitabilityRanker.get_item_profitability( data , totalFunds , duration ) ) )
         
     rankings.sort( key=lambda x: -1*x[1] )
     return rankings
Exemple #4
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    def get_profitability_rankings(totalFunds, duration):
        f = open("price_data/item_ids", 'r')
        rankings = []
        for line in f.readlines():
            commodityId = int(line.split(",")[1])
            data = PriceReader.get_price_data_from_csv(commodityId)
            rankings.append((data,
                             ProfitabilityRanker.get_item_profitability(
                                 data, totalFunds, duration)))

        rankings.sort(key=lambda x: -1 * x[1])
        return rankings
Exemple #5
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 def get_data_by_id(id):
     return PriceReader.get_price_data_from_csv(id)
Exemple #6
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 def get_data_by_name(name):
     id = DataManager.nameToId[name.lower()]
     return PriceReader.get_price_data_from_csv(id)
 def get_data_by_id( id ):
     return PriceReader.get_price_data_from_csv( id )
 def get_data_by_name( name ):
     id = DataManager.nameToId[ name.lower() ]
     return PriceReader.get_price_data_from_csv( id )
def get_data_by_id( commodityId ):
    from price_data_io import PriceReader
    return PriceReader.get_price_data_from_csv( commodityId )
Exemple #10
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def get_data_by_id(commodityId):
    from price_data_io import PriceReader
    return PriceReader.get_price_data_from_csv(commodityId)