\[ [Index](index.md) | [Exercise 3.2](ex3_2.md) | [Exercise 3.4](ex3_4.md) \]

# Exercise 3.3

*Objectives:*

- Learn about class variables and class methods

*Files Modified:* `stock.py`, `reader.py`

Instances of the `Stock` class defined in the previous exercise are
normally created as follows:

```python
>>> s = Stock('GOOG', 100, 490.1)
>>>
```

However, the `read_portfolio()` function also creates instances from rows
of data read from files.  For example, code such as the following is used:

```python
>>> import csv
>>> f = open('Data/portfolio.csv')
>>> rows = csv.reader(f)
>>> headers = next(rows)
>>> row = next(rows)
>>> row
['AA', '100', '32.20']
>>> s = Stock(row[0], int(row[1]), float(row[2]))
>>>
```

## (a) Alternate constructors

Perhaps the creation of a `Stock` from a row of raw data is better handled
by an alternate constructor.   Modify the `Stock` class so that it has
a `types` class variable and `from_row()` class method like this:

```python
class Stock:
    types = (str, int, float)
    def __init__(self, name, shares, price):
        self.name = name
        self.shares = shares
        self.price = price

    @classmethod
    def from_row(cls, row):
        values = [func(val) for func, val in zip(cls.types, row)]
        return cls(*values)
    ...
```

Here's how to test it:

```python
>>> row = ['AA', '100', '32.20']
>>> s = Stock.from_row(row)
>>> s.name
'AA'
>>> s.shares
100
>>> s.price
32.2
>>> s.cost()
3220.0000000000005
>>>
```

Carefully observe how the string values in the row have been converted to a proper type.

## (b) Class variables and inheritance

Class variables such as `types` are sometimes used as a customization mechanism
when inheritance is used.  For example, in the `Stock` class, the types can be
easily changed in a subclass.  Try this example which changes the `price` attribute
to a `Decimal` instance (which is often better suited to financial calculations):

```python
>>> from decimal import Decimal
>>> class DStock(Stock):
        types = (str, int, Decimal)

>>> row = ['AA', '100', '32.20']
>>> s = DStock.from_row(row)
>>> s.price
Decimal('32.20')
>>> s.cost()
Decimal('3220.0')
>>>
```

**Design Discussion**

The problem being addressed in this exercise concerns the conversion of data read
from a file.  Would it make sense to perform these conversions in the `__init__()` 
method of the `Stock` class instead?  For example:

```python
class Stock:
    def __init__(self, name, shares, price):
        self.name = str(name)
        self.shares = int(shares)
        self.price = float(price)
```

By doing this, you would convert a row of data as follows:

```python
>>> row = ['AA', '100', '32.20']
>>> s = Stock(*row)
>>> s.name
'AA'
>>> s.shares
100
>>> s.price
32.2
>>>
```

Is this good or bad?  What are your thoughts?  On the whole, I think
it's a questionable design since it mixes two different things
together--the creation of an instance and the conversion of data.
Plus, the implicit conversions in `__init__()` limit flexibility and
might introduce weird bugs if a user isn't paying careful attention.

## (c) Reading Objects

Change the `read_portfolio()` function to use the new `Stock.from_row()`
method that you wrote. 

Point of thought:  Which version of code do you like better?  The
version of `read_portfolio()` that performed the type conversions or
the one that performs conversions in the `Stock.from_row()` method?
Think about data abstraction.

Can you modify `read_portfolio()` to create objects using a class other
than `Stock`?  For example, can the user select the class that they want?  

## (d) Generalizing

A useful feature of class-methods is that you can use them to put a
highly uniform instance creation interface on a wide variety of
classes and write general purpose utility functions that use them.

Earlier, you created a file `reader.py` that had some functions for
reading CSV data.  Add the following `read_csv_as_instances()`
function to the file which accepts a class as input and uses the class
`from_row()` method to create a list of instances:

```python
# reader.py
...

def read_csv_as_instances(filename, cls):
    '''
    Read a CSV file into a list of instances
    '''
    records = []
    with open(filename) as f:
        rows = csv.reader(f)
        headers = next(rows)
        for row in rows:
            records.append(cls.from_row(row))
    return records
```

Get rid of the `read_portfolio()` function--you don't need that anymore.  If you want to
read a list of `Stock` objects, do this:

```python
>>> # Read a portfolio of Stock instances
>>> from reader import read_csv_as_instances
>>> from stock import Stock
>>> portfolio = read_csv_as_instances('Data/portfolio.csv', Stock)
>>> portfolio
[<__main__.Stock object at 0x100674748>, 
<__main__.Stock object at 0x1006746d8>, 
<__main__.Stock object at 0x1006747b8>, 
<__main__.Stock object at 0x100674828>, 
<__main__.Stock object at 0x100674898>, 
<__main__.Stock object at 0x100674908>, 
<__main__.Stock object at 0x100674978>]
>>>
```

Here is another example of how you might use `read_csv_as_instances()` with a completely different class:

```python
>>> class Row:
         def __init__(self, route, date, daytype, numrides):
             self.route = route
             self.date = date
             self.daytype = daytype
             self.numrides = numrides
         @classmethod
         def from_row(cls, row):
             return cls(row[0], row[1], row[2], int(row[3]))

>>> rides = read_csv_as_instances('Data/ctabus.csv', Row)
>>> len(rides)
577563
>>>
```

**Discussion**

This exercise illustrates the two most common uses of class variables
and class methods.  Class variables are often used to hold a global
parameter (e.g., a configuration setting) that is shared across all
instances.  Sometimes subclasses will inherit from the base class and
override the setting to change behavior.

Class methods are most commonly used to implement alternate
constructors as shown.  A common way to spot such class methods is to
look for the word "from" in the name.  For example, here is an example
on built-in dictionaries:

```python
>>> d = dict.fromkeys(['a','b','c'], 0)     # class method
>>> d
{'a': 0, 'c': 0, 'b': 0}
>>>
```

\[ [Solution](soln3_3.md) | [Index](index.md) | [Exercise 3.2](ex3_2.md) | [Exercise 3.4](ex3_4.md) \]

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