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+\[ [Index](index.md) | [Exercise 4.4](ex4_4.md) | [Exercise 5.2](ex5_2.md) \]
+
+# Exercise 5.1
+
+*Objectives:*
+
+- Explore a few definitional aspects of functions/methods
+- Making functions more flexible
+- Type hints
+
+In [Exercise 2.6](ex2_6.md) you wrote a `reader.py` module that
+had a function for reading a CSV into a list of dictionaries.  For example:
+
+```python
+>>> import reader
+>>> port = reader.read_csv_as_dicts('Data/portfolio.csv', [str,int,float])
+>>>
+```
+
+We later expanded to that code to work with instances in
+[Exercise 3.3](ex3_3.md): 
+
+```python
+>>> import reader
+>>> from stock import Stock
+>>> port = reader.read_csv_as_instances('Data/portfolio.csv', Stock)
+>>>
+```
+
+Eventually the code was refactored into a collection of classes
+involving inheritance in [Exercise 3.7](ex3_7.md).  However,
+the code has become rather complex and convoluted.
+
+## (a) Back to Basics
+
+Start by reverting the changes related to class definitions.  Rewrite
+the `reader.py` file so that it contains the two basic functions that
+you had before you messed it up with classes:
+
+```python
+# reader.py
+
+import csv
+
+def read_csv_as_dicts(filename, types):
+    '''
+    Read CSV data into a list of dictionaries with optional type conversion
+    '''
+    records = []
+    with open(filename) as file:
+        rows = csv.reader(file)
+        headers = next(rows)
+        for row in rows:
+            record = { name: func(val) 
+                       for name, func, val in zip(headers, types, row) }
+            records.append(record)
+    return records
+
+def read_csv_as_instances(filename, cls):
+    '''
+    Read CSV data into a list of instances
+    '''
+    records = []
+    with open(filename) as file:
+        rows = csv.reader(file)
+        headers = next(rows)
+        for row in rows:
+            record = cls.from_row(row)
+            records.append(record)
+    return records
+```
+
+Make sure the code still works as it did before:
+
+```python
+>>> import reader
+>>> port = reader.read_csv_as_dicts('Data/portfolio.csv', [str, int, float])
+>>> port
+[{'name': 'AA', 'shares': 100, 'price': 32.2}, {'name': 'IBM', 'shares': 50, 'price': 91.1}, 
+ {'name': 'CAT', 'shares': 150, 'price': 83.44}, {'name': 'MSFT', 'shares': 200, 'price': 51.23}, 
+ {'name': 'GE', 'shares': 95, 'price': 40.37}, {'name': 'MSFT', 'shares': 50, 'price': 65.1}, 
+ {'name': 'IBM', 'shares': 100, 'price': 70.44}]
+>>> import stock
+>>> port = reader.read_csv_as_instances('Data/portfolio.csv', stock.Stock)
+>>> port
+[Stock('AA', 100, 32.2), Stock('IBM', 50, 91.1), Stock('CAT', 150, 83.44), 
+ Stock('MSFT', 200, 51.23), Stock('GE', 95, 40.37), Stock('MSFT', 50, 65.1), 
+ Stock('IBM', 100, 70.44)]
+>>>
+```
+
+## (b) Thinking about Flexibility
+
+Right now, the two functions in `reader.py` are hard-wired to work
+with filenames that are passed directly to `open()`.  Refactor the
+code so that it works with any iterable object that produces lines.
+To do this, create two new functions `csv_as_dicts(lines, types)` and
+`csv_as_instances(lines, cls)` that convert any iterable sequence of
+lines.  For example:
+
+```python
+>>> file = open('Data/portfolio.csv')
+>>> port = reader.csv_as_dicts(file, [str, int, float])
+>>> port
+[{'name': 'AA', 'shares': 100, 'price': 32.2}, {'name': 'IBM', 'shares': 50, 'price': 91.1}, 
+ {'name': 'CAT', 'shares': 150, 'price': 83.44}, {'name': 'MSFT', 'shares': 200, 'price': 51.23}, 
+ {'name': 'GE', 'shares': 95, 'price': 40.37}, {'name': 'MSFT', 'shares': 50, 'price': 65.1}, 
+ {'name': 'IBM', 'shares': 100, 'price': 70.44}]
+>>>
+```
+
+The whole point of doing this is to make it possible to work with different
+kinds of input sources.  For example:
+
+```python
+>>> import gzip
+>>> import stock
+>>> file = gzip.open('Data/portfolio.csv.gz')
+>>> port = reader.csv_as_instances(file, stock.Stock)
+>>> port
+[Stock('AA', 100, 32.2), Stock('IBM', 50, 91.1), Stock('CAT', 150, 83.44), 
+ Stock('MSFT', 200, 51.23), Stock('GE', 95, 40.37), Stock('MSFT', 50, 65.1), 
+ Stock('IBM', 100, 70.44)]
+>>>
+```
+
+To maintain backwards compatibility with older code, write functions
+`read_csv_as_dicts()` and `read_csv_as_instances()` that take a
+filename as before.  These functions should call `open()` on the
+supplied filename and use the new `csv_as_dicts()` or
+`csv_as_instances()` functions on the resulting file.
+
+## (c) Design Challenge: CSV Headers
+
+The code assumes that the first line of CSV data always contains
+column headers.  However, this isn't always the case. For example, the
+file `Data/portfolio_noheader.csv` contains data, but no column
+headers.
+
+How would you refactor the code to accommodate missing column headers, having
+them supplied manually by the caller instead?
+
+## (d) API Challenge: Type hints
+
+Functions can have optional type-hints attached to arguments and return values.
+For example:
+
+```python
+def add(x:int, y:int) -> int:
+    return x + y
+```
+
+The `typing` module has additional classes for expressing more complex kinds of
+types including containers.  For example:
+
+```python
+from typing import List
+
+def sum_squares(nums: List[int]) -> int:
+    total = 0
+    for n in nums:
+        total += n*n
+    return total
+```
+
+Your challenge: Modify the code in `reader.py` so that all functions
+have type hints.  Try to make the type-hints as accurate as possible.
+To do this, you may need to consult the documentation for the
+[typing module](https://docs.python.org/3/library/typing.html).
+
+\[ [Solution](soln5_1.md) | [Index](index.md) | [Exercise 4.4](ex4_4.md) | [Exercise 5.2](ex5_2.md) \]
+
+----
+`>>>` Advanced Python Mastery  
+`...` A course by [dabeaz](https://www.dabeaz.com)  
+`...` Copyright 2007-2023  
+
+![](https://i.creativecommons.org/l/by-sa/4.0/88x31.png). This work is licensed under a [Creative Commons Attribution-ShareAlike 4.0 International License](http://creativecommons.org/licenses/by-sa/4.0/)