67 lines
1.7 KiB
Python
67 lines
1.7 KiB
Python
# report.py
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import csv
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def read_portfolio(filename):
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'''
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Read a stock portfolio file into a list of dictionaries with keys
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name, shares, and price.
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'''
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portfolio = []
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with open(filename) as f:
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rows = csv.reader(f)
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headers = next(rows)
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for row in rows:
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stock = {
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'name' : row[0],
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'shares' : int(row[1]),
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'price' : float(row[2])
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}
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portfolio.append(stock)
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return portfolio
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def read_prices(filename):
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'''
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Read a CSV file of price data into a dict mapping names to prices.
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'''
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prices = {}
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with open(filename) as f:
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rows = csv.reader(f)
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for row in rows:
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try:
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prices[row[0]] = float(row[1])
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except IndexError:
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pass
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return prices
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def make_report_data(portfolio, prices):
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'''
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Make a list of (name, shares, price, change) tuples given a portfolio list
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and prices dictionary.
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'''
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rows = []
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for stock in portfolio:
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current_price = prices[stock['name']]
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change = current_price - stock['price']
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summary = (stock['name'], stock['shares'], current_price, change)
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rows.append(summary)
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return rows
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# Read data files and create the report data
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portfolio = read_portfolio('../../Work/Data/portfolio.csv')
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prices = read_prices('../../Work/Data/prices.csv')
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# Generate the report data
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report = make_report_data(portfolio, prices)
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# Output the report
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headers = ('Name', 'Shares', 'Price', 'Change')
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print('%10s %10s %10s %10s' % headers)
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print(('-' * 10 + ' ') * len(headers))
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for row in report:
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print('%10s %10d %10.2f %10.2f' % row)
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