python - reading and writing files for a food processing company -

i working on python project food processing company trying calculate total sales year. python has read text file divided categories split commas. first category type of product, can cereal, chocolate candy etc produced company. second category brand of said product, example, kaptain krunch cereal or coco jam chocolate. third category sales last fiscal year(2014) , last category sales fiscal year(2015). note sales fiscal year 2015 calculated. 2014 has no use in program there. here how text file looks like. name product.txt

cereal,magic balls,2200,2344

cereal,kaptain krunch,3300,3123

cereal,coco bongo,1800,2100

cereal,sugar munch,4355,6500

cereal,oats n barley,3299,5400

sugar candy,pop rocks,546,982

sugar candy,lollipop,1233,1544

sugar candy,gingerbud,2344,2211

sugar candy,respur,1245,2211

chocolate,coco jam,3322,4300

chocolate,larkspur,1600,2200

chocolate,mighty milk,1234,2235

chocolate,almond berry,998,1233

condiments,peanut butter,3500,3902

condiments,hot sauce,1234,1560

condiments,jelly,346,544

condiments,spread,2334,5644

what looking add sales fiscal year 2015 products , total sales in 2015

the output should in written text file

total sales cereal in 2015 : {insert total number here}

total sales sugar candy in 2015 : {insert total number here}

total sales chocolate in 2015 : {insert total number here}

total sales condiments in 2015 : {insert total number here}

---

total sales company in 2015: {insert total products sold in 2015}

along that, should print grand total on python run screen in ide along text file.

total sales company in 2015: {insert total products sold in 2015}

here code. new python , reading , writing files can't if on right track.

product_file = "products.txt" report_file = "report.txt"  def main():     #open file     productfile = open(product_file, "r")     reportfile = open(report_file, "w")      # reading file     prodata = extractdatarecord(productfile)     product = prodata[0]     category = prodata[1]     saleslastyear = prodata[2]     salesthisyear = prodata[3]      #computing     product = 0.0     product = salesthisyear       productfile.close()     reportfile.close()  def extractdatarecord(infile) :    line = infile.readline()    if line == "" :       return []    else :       parts = line.rsplit(",", 1)       parts[1] = int(parts[1])        return parts  # start program. main() 

the short version here you're doing wrong. never roll own parsing code if can it. i'd suggest taking @ the built-in csv module, , trying using "contract out" csv parsing, letting focus on rest of logic.

simple rewrite , completed code csv:

import collections import csv  product_file = "products.txt" report_file = "report.txt"  def main():     # easy way dictionary lookup defaults 0     categorycounts = collections.defaultdict(int)      #open files using statements ensure they're closed     # without need explicit call close, on exceptions     open(product_file, newline='') productfile,\          open(report_file, "w") reportfile:         pcsv = csv.reader(productfile)          # sum sales product type letting csv parse         # filter removes empty rows us; assume other rows complete         category, brand, sales_lastyear, sales_thisyear in filter(none, pcsv):             categorycounts[category] += int(sales_thisyear)          # print categories in sorted order total sales         category, sales in sorted(categorycounts.items()):             print('total sales for', category, 'in 2015:', sales, file=reportfile)          print('-'*80, file=reportfile) # separator line between categories , total          # sum , print total sales both file , screen         totalsales = sum(categorycounts.values())         print("total sales company in 2015:", totalsales, file=reportfile)         print("total sales company in 2015:", totalsales)  if __name__ == '__main__':     main()