Contents | Previous (7.1 Variable Arguments) | Next (7.3 Returning Functions)

7.2 Anonymous Functions and Lambda

List Sorting Revisited

Lists can be sorted in-place. Using the sort method.

s = [10,1,7,3]
s.sort() # s = [1,3,7,10]

You can sort in reverse order.

s = [10,1,7,3]
s.sort(reverse=True) # s = [10,7,3,1]

It seems simple enough. However, how do we sort a list of dicts?

[{'name': 'AA', 'price': 32.2, 'shares': 100},
{'name': 'IBM', 'price': 91.1, 'shares': 50},
{'name': 'CAT', 'price': 83.44, 'shares': 150},
{'name': 'MSFT', 'price': 51.23, 'shares': 200},
{'name': 'GE', 'price': 40.37, 'shares': 95},
{'name': 'MSFT', 'price': 65.1, 'shares': 50},
{'name': 'IBM', 'price': 70.44, 'shares': 100}]

By what criteria?

You can guide the sorting by using a key function. The key function is a function that receives the dictionary and returns the value of interest for sorting.

def stock_name(s):
    return s['name']

portfolio.sort(key=stock_name)

Here’s the result.

# Check how the dictionaries are sorted by the `name` key
[
  {'name': 'AA', 'price': 32.2, 'shares': 100},
  {'name': 'CAT', 'price': 83.44, 'shares': 150},
  {'name': 'GE', 'price': 40.37, 'shares': 95},
  {'name': 'IBM', 'price': 91.1, 'shares': 50},
  {'name': 'IBM', 'price': 70.44, 'shares': 100},
  {'name': 'MSFT', 'price': 51.23, 'shares': 200},
  {'name': 'MSFT', 'price': 65.1, 'shares': 50}
]

Callback Functions

In the above example, the key function is an example of a callback function. The sort() method “calls back” to a function you supply. Callback functions are often short one-line functions that are only used for that one operation. Programmers often ask for a short-cut for specifying this extra processing.

Lambda: Anonymous Functions

Use a lambda instead of creating the function. In our previous sorting example.

portfolio.sort(key=lambda s: s['name'])

This creates an unnamed function that evaluates a single expression. The above code is much shorter than the initial code.

def stock_name(s):
    return s['name']

portfolio.sort(key=stock_name)

# vs lambda
portfolio.sort(key=lambda s: s['name'])

Using lambda

lambda is highly restricted.
Only a single expression is allowed.
No statements like if, while, etc.
Most common use is with functions like sort().

Exercises

Read some stock portfolio data and convert it into a list:

>>> import report
>>> portfolio = list(report.read_portfolio('Data/portfolio.csv'))
>>> for s in portfolio:
        print(s)

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)
>>>

Exercise 7.5: Sorting on a field

Try the following statements which sort the portfolio data alphabetically by stock name.

>>> def stock_name(s):
       return s.name

>>> portfolio.sort(key=stock_name)
>>> for s in portfolio:
           print(s)

... inspect the result ...
>>>

In this part, the stock_name() function extracts the name of a stock from a single entry in the portfolio list. sort() uses the result of this function to do the comparison.

Exercise 7.6: Sorting on a field with lambda

Try sorting the portfolio according the number of shares using a lambda expression:

>>> portfolio.sort(key=lambda s: s.shares)
>>> for s in portfolio:
        print(s)

... inspect the result ...
>>>

Try sorting the portfolio according to the price of each stock

>>> portfolio.sort(key=lambda s: s.price)
>>> for s in portfolio:
        print(s)

... inspect the result ...
>>>

Note: lambda is a useful shortcut because it allows you to define a special processing function directly in the call to sort() as opposed to having to define a separate function first.