# report.py

import fileparse

def read_portfolio(filename):
    '''
    Read a stock portfolio file into a list of dictionaries with keys
    name, shares, and price.
    '''
    return fileparse.parse_csv(filename, select=['name','shares','price'], types=[str,int,float])

def read_prices(filename):
    '''
    Read a CSV file of price data into a dict mapping names to prices.
    '''
    return dict(fileparse.parse_csv(filename,types=[str,float], has_headers=False))

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')