usage.py

import os
import csv
from dateutil.parser import parse

usage={}

def run():
    filenames=get_filenames()
    for filename in filenames:
        process_file(filename)
    print_usage()

def get_filenames():
    filenames=[]
    for file in os.listdir("./usage"):
        if file.endswith(".csv"):
            filenames.append(os.path.join("./usage", file))
    return filenames

def process_file(filename):
    hourly=0
    byol=0
    legacyfree=0
    legacypaid=0

    with open(filename) as csvfile:
        reader = csv.DictReader(csvfile)
        for row in reader:
            process_row(row)

def process_row(row):
    date = parse(row['Usage Start Date'])
    date = str(date.month) + '/1/' + str(date.year)

    if not date in usage:
        usage[date]={}
        usage[date]['hourly']=0
        usage[date]['byol']=0
        usage[date]['legacyfree']=0
        usage[date]['legacypaid']=0

    if 'Hourly Pricing' in row['SKU']:
        usage[date]['hourly']+=float(row['Usage'])
    elif 'BYOL' in row['SKU']:
        usage[date]['byol']+=float(row['Usage'])
    elif 'Paid' in row['SKU Billing Type']:
        usage[date]['legacypaid']+=float(row['Usage'])
    else:
        usage[date]['legacyfree']+=float(row['Usage'])

def print_usage():
    print('Date, Hourly Pricing Usage, BYOL Usage, Legacy Free Usage, Legacy Paid Usage, Total Usage')
    for date in usage:
        total = usage[date]['hourly']+usage[date]['byol']+usage[date]['legacyfree']+usage[date]['legacypaid']
        print(date + ', ' + str(usage[date]['hourly']) + ', ' + str(usage[date]['byol']) + ', ' + str(usage[date]['legacyfree']) + ', ' + str(usage[date]['legacypaid']) + ', ' + str(total))

run()