# stock.py
class Stock:
types = (str, int, float)
def __init__(self, name, shares, price):
self.name = name
self.shares = shares
self.price = price
def cost(self):
return self.shares * self.price
def sell(self, nshares):
self.shares -= nshares
@classmethod
def from_row(cls, row):
values = [func(val) for func, val in zip(cls.types, row)]
return cls(*values)
def read_portfolio(filename):
'''
Read a CSV file of stock data into a list of Stocks
'''
import csv
portfolio = []
with open(filename) as f:
rows = csv.reader(f)
headers = next(rows)
for row in rows:
record = Stock.from_row(row)
portfolio.append(record)
return portfolio
if __name__ == '__main__':
import tableformat
import reader
portfolio = read_portfolio('Data/portfolio.csv')
# Generalized version
# portfolio = reader.read_csv_as_instances('Data/portfolio.csv', Stock)
tableformat.print_table(portfolio, ['name', 'shares', 'price'])
The reader.py
file should now look like this:
# reader.py
import csv
from collections import defaultdict
def read_csv_as_dicts(filename, types):
'''
Read a CSV file into a list of dicts with column type conversion
'''
records = []
with open(filename) as f:
rows = csv.reader(f)
headers = next(rows)
for row in rows:
record = { name: func(val) for name, func, val in zip(headers, types, row) }
records.append(record)
return records
def read_csv_as_instances(filename, cls):
'''
Read a CSV file into a list of instances
'''
records = []
with open(filename) as f:
rows = csv.reader(f)
headers = next(rows)
for row in rows:
records.append(cls.from_row(row))
return records