# report.py
import csv
def read_portfolio(filename):
'''
Read a stock portfolio file into a list of dictionaries with keys
name, shares, and price.
'''
portfolio = []
with open(filename) as f:
rows = csv.reader(f)
headers = next(rows)
for row in rows:
record = dict(zip(headers, row))
stock = {
'name' : record['name'],
'shares' : int(record['shares']),
'price' : float(record['price'])
}
portfolio.append(stock)
return portfolio
def read_prices(filename):
'''
Read a CSV file of price data into a dict mapping names to prices.
'''
prices = {}
with open(filename) as f:
rows = csv.reader(f)
for row in rows:
try:
prices[row[0]] = float(row[1])
except IndexError:
pass
return prices
def make_report_data(portfolio,prices):
'''
Make a list of (name, shares, price, change) tuples given a portfolio list
and prices dictionary.
'''
rows = []
for stock in portfolio:
current_price = prices[stock['name']]
change = current_price - stock['price']
summary = (stock['name'], stock['shares'], current_price, change)
rows.append(summary)
return rows
def print_report(reportdata):
'''
Print a nicely formated table from a list of (name, shares, price, change) tuples.
'''
headers = ('Name','Shares','Price','Change')
print('%10s %10s %10s %10s' % headers)
print(('-'*10 + ' ')*len(headers))
for row in reportdata:
print('%10s %10d %10.2f %10.2f' % row)
def portfolio_report(portfoliofile,pricefile):
'''
Make a stock report given portfolio and price data files.
'''
# Read data files
portfolio = read_portfolio(portfoliofile)
prices = read_prices(pricefile)
# Create the report data
report = make_report_data(portfolio,prices)
# Print it out
print_report(report)
portfolio_report('../../Work/Data/portfolio.csv',
'../../Work/Data/prices.csv')