Question

I’m working on parsing a CSV from an export of my company’s database. This is a slimmed down version has around 15 columns, the actual CSV has over 400 columns of data (all necessary). The below works perfectly:

inv = csv.reader(open('inventory_report.txt', 'rU'), dialect='excel', delimiter="\t")

for PART_CODE,MODEL_NUMBER,PRODUCT_NAME,COLOR,TOTAL_ONHAND,TOTAL_ON_ORDER,TOTAL_SALES,\
SALES_YEAR_TO_DATE,SALES_LASTYEAR_TO_DATE,TOTAL_NUMBER_OF_QTYsSOLD,TOTAL_PURCHASES,\
PURCHASES_YEAR_TO_DATE,PURCHASES_LASTYEAR_TO_DATE,TOTAL_NUMBER_OF_QTYpurchased,\
DATE_LAST_SOLD,DATE_FIRST_SOLD in inv:
    print ('%-20s %-90s OnHand: %-10s OnOrder: %-10s') % (MODEL_NUMBER,PRODUCT_NAME,\
    TOTAL_ONHAND,TOTAL_ON_ORDER)

As you can already tell, it will be very painful to read when the ‘for’ loop has 400+ names attached to it for each of item of the row in the CSV. However annoying, it is however very handy for being able to access the output I’m after by this method. I can easily get specific items and perform calculations within the common names we’re already familiar with in our point of sale database.

I’ve been attempting to make this more readable. Trying to figure out a way where I could define a list of all these names in the for loop but still be able to call for them by name when it’s time to do calculations and print the output.

Any thoughts?

Answer 1

you can use csv.DictReader. Elements are read as dict. Assuming u have first line as column name.

inv = csv.DictReader(open('file.csv')):
for i in inv:
  print ('%-20s %-90s OnHand: %-10s OnOrder: %-10s') % (i['MODEL_NUMBER'],i['PRODUCT_NAME'],i['TOTAL_ONHAND'],i['TOTAL_ON_ORDER'])

And if you want the i[MODEL_NUMBER] to come from list. Define a list with all column name. Assuming, l = ['MODEL_NUMBER','PRODUCT_NAME','TOTAL_ONHAND','TOTAL_ON_ORDER']. Then my print statement in above code will be,

print ('%-20s %-90s OnHand: %-10s OnOrder: %-10s') % (i[l[0]],i[l[1]],i[l[2]],i[l[3]])

Code not checked.. 🙂