# 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 = []
    f = open(filename)
    f_csv = csv.reader(f)
    headers = next(f_csv)

    for row in f_csv:
        record = dict(zip(headers, row))
        stock = {
            'name' : record['name'],
            'shares' : int(record['shares']),
            'price' : float(record['price'])
        }
        portfolio.append(stock)
    f.close()
    return portfolio

def read_prices(filename):
    '''
    Read a CSV file of price data into a dict mapping names to prices.
    '''
    prices = {}
    f = open(filename)
    f_csv = csv.reader(f)
    for row in f_csv:
        try:
            prices[row[0]] = float(row[1])
        except IndexError:
            pass
    f.close()
    return prices

def make_report(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

# ---- ADDED
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 ' * len(headers)) % headers
    print ('-'*10 + ' ')*len(headers)
    for row in reportdata:
        print '%10s %10d %10.2f %10.2f' % row

# ---- END

# Read data files
portfolio = read_portfolio('Data/portfolio.csv')
prices    = read_prices('Data/prices.csv')

# Create the report data
report    = make_report(portfolio,prices)

# ---- ADDED
# Print it out
print_report(report)
# ---- END

# 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 = []
    f = open(filename)
    f_csv = csv.reader(f)
    headers = next(f_csv)

    for row in f_csv:
        record = dict(zip(headers, row))
        stock = {
            'name' : record['name'],
            'shares' : int(record['shares']),
            'price' : float(record['price'])
        }
        portfolio.append(stock)
    f.close()
    return portfolio

def read_prices(filename):
    '''
    Read a CSV file of price data into a dict mapping names to prices.
    '''
    prices = {}
    f = open(filename)
    f_csv = csv.reader(f)
    for row in f_csv:
        try:
            prices[row[0]] = float(row[1])
        except IndexError:
            pass
    f.close()
    return prices

def make_report(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 ' * len(headers)) % headers
    print ('-'*10 + ' ')*len(headers)
    for row in reportdata:
        print '%10s %10d %10.2f %10.2f' % row

# ---- ADDED
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(portfolio,prices)

    # Print it out
    print_report(report)

portfolio_report('Data/portfolio.csv',
                 'Data/prices.csv')
# ---- END