85 lines
1.9 KiB
Markdown
85 lines
1.9 KiB
Markdown
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# Exercise 3.3 - Solution
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```python
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# stock.py
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class Stock:
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types = (str, int, float)
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def __init__(self, name, shares, price):
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self.name = name
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self.shares = shares
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self.price = price
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def cost(self):
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return self.shares * self.price
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def sell(self, nshares):
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self.shares -= nshares
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@classmethod
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def from_row(cls, row):
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values = [func(val) for func, val in zip(cls.types, row)]
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return cls(*values)
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def read_portfolio(filename):
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'''
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Read a CSV file of stock data into a list of Stocks
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'''
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import csv
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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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record = Stock.from_row(row)
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portfolio.append(record)
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return portfolio
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if __name__ == '__main__':
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import tableformat
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import reader
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portfolio = read_portfolio('Data/portfolio.csv')
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# Generalized version
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# portfolio = reader.read_csv_as_instances('Data/portfolio.csv', Stock)
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tableformat.print_table(portfolio, ['name', 'shares', 'price'])
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```
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The `reader.py` file should now look like this:
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```python
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# reader.py
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import csv
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from collections import defaultdict
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def read_csv_as_dicts(filename, types):
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'''
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Read a CSV file into a list of dicts with column type conversion
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'''
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records = []
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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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record = { name: func(val) for name, func, val in zip(headers, types, row) }
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records.append(record)
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return records
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def read_csv_as_instances(filename, cls):
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'''
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Read a CSV file into a list of instances
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'''
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records = []
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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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records.append(cls.from_row(row))
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return records
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```
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[Back](ex3_3.md)
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