def processForecastCSV()

in forecastMetrics/forecastMetrics.py [0:0]

• 28 lines of code
• 10 McCabe index (conditional complexity)

def processForecastCSV(csvPath):
    inputFile=open(csvPath,'r')
    readerObj=csv.reader(inputFile)
    # get start and end date, get Rawdata Map
    cur_startDate=date.today()
    cur_endDate=None
    colNameList=[]
    for row in readerObj:
       # header
       if(row[0]=="item_id"):
          if (len(vars.forecastPList)==0):
             for i in range(2,len(row)):
                 vars.forecastPList.append(row[i])
          continue
       tmp_date_string=row[1][:10]
       tmp_date=getDateFromString(tmp_date_string)
       tmp_item_string=row[0]
       if (not tmp_item_string in vars.ItemList):
           vars.ItemList.append(tmp_item_string)
       if (not tmp_date_string in vars.ForcastData):
           vars.ForcastData[tmp_date_string]={}
       if (not tmp_item_string in vars.ForcastData[tmp_date_string]):
           vars.ForcastData[tmp_date_string][tmp_item_string]={}
       tmp_object={}
       i=2
       for p in vars.forecastPList:
          tmp_object[p]=row[i]
          i=i+1
       vars.ForcastData[tmp_date_string][tmp_item_string]=tmp_object
    inputFile.close()