def ticker(filename, logfilename, fmt):
inventory = read_inventory(filename)
rows = parse_product_data(follow(logfilename))
# rows = filter_names(rows, inventory)
rows = (row for row in rows if row['name'] in inventory)
formatter = create_formatter(fmt)
formatter.headings(['Name', 'prices', 'Change'])
for row in rows:
name = row['name']
price = row['price']
change = row['change']
rowdata = [name, f'{price:0.2f}', f'{change:0.2f}']
formatter.row(rowdata)
def inventory_cost(filename):
#ive = read_inventory(filename)
inventory = read_inventory(filename)
return inventory.total_cost
yield [row[idx] for idx in indices]
def parse_product_data(lines):
rows = csv.reader(lines)
rows = select_columns(rows, [0, 1, 4])
# Equivalent Generator expression below select_columns.
#rows = ( [row[idx] for idx in [0,1,4]] for row in rows )
rows = convert_types(rows, [str, float, float])
# Equivalent Generator expression below for convert_types
#rows = ( [ func(val) for func, val in zip([str,float,float],row) ] for row in rows )
headers = ['name', 'price', 'change']
#rows = make_dicts(rows,headers)
rows = (dict(zip(headers, row)) for row in rows)
return rows
if __name__ == '__main__':
inventory = read_inventory('Data/inventory.csv')
lines = follow('Data/marketlog.csv')
rows = parse_product_data(lines)
#rows = filter_names(rows,inventory)
rows = (row for row in rows if row['name'] in inventory)
for row in rows:
print(row)
def inventory_cost(file_name):
inventory = read_inventory(file_name)
return inventory.total_cost