161 lines
3.8 KiB
Markdown
161 lines
3.8 KiB
Markdown
# 7.2 Anonymous Functions and Lambda
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### List Sorting Revisited
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Lists can be sorted *in-place*. Using the `sort` method.
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```python
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s = [10,1,7,3]
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s.sort() # s = [1,3,7,10]
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```
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You can sort in reverse order.
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```python
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s = [10,1,7,3]
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s.sort(reverse=True) # s = [10,7,3,1]
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```
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It seems simple enough. However, how do we sort a list of dicts?
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```python
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[{'name': 'AA', 'price': 32.2, 'shares': 100},
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{'name': 'IBM', 'price': 91.1, 'shares': 50},
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{'name': 'CAT', 'price': 83.44, 'shares': 150},
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{'name': 'MSFT', 'price': 51.23, 'shares': 200},
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{'name': 'GE', 'price': 40.37, 'shares': 95},
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{'name': 'MSFT', 'price': 65.1, 'shares': 50},
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{'name': 'IBM', 'price': 70.44, 'shares': 100}]
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```
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By what criteria?
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You can guide the sorting by using a *key function*. The *key function* is a function that receives the dictionary and returns the value in a specific key.
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```python
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def stock_name(s):
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return s['name']
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portfolio.sort(key=stock_name)
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```
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The value returned by the *key function* determines the sorting.
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```python
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# Check how the dictionaries are sorted by the `name` key
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[
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{'name': 'AA', 'price': 32.2, 'shares': 100},
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{'name': 'CAT', 'price': 83.44, 'shares': 150},
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{'name': 'GE', 'price': 40.37, 'shares': 95},
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{'name': 'IBM', 'price': 91.1, 'shares': 50},
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{'name': 'IBM', 'price': 70.44, 'shares': 100},
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{'name': 'MSFT', 'price': 51.23, 'shares': 200},
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{'name': 'MSFT', 'price': 65.1, 'shares': 50}
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]
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```
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### Callback Functions
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Callback functions are often short one-line functions that are only used for that one operation. For example of previous sorting example.
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Programmers often ask for a short-cut, so is there a shorter way to specify custom processing for `sort()`?
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### Lambda: Anonymous Functions
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Use a lambda instead of creating the function.
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In our previous sorting example.
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```python
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portfolio.sort(key=lambda s: s['name'])
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```
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This creates an *unnamed* function that evaluates a *single* expression.
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The above code is much shorter than the initial code.
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```python
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def stock_name(s):
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return s['name']
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portfolio.sort(key=stock_name)
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# vs lambda
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portfolio.sort(key=lambda s: s['name'])
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```
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### Using lambda
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* lambda is highly restricted.
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* Only a single expression is allowed.
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* No statements like `if`, `while`, etc.
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* Most common use is with functions like `sort()`.
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## Exercises
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Read some stock portfolio data and convert it into a list:
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```python
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>>> import report
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>>> portfolio = list(report.read_portfolio('Data/portfolio.csv'))
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>>> for s in portfolio:
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print(s)
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Stock('AA', 100, 32.2)
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Stock('IBM', 50, 91.1)
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Stock('CAT', 150, 83.44)
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Stock('MSFT', 200, 51.23)
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Stock('GE', 95, 40.37)
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Stock('MSFT', 50, 65.1)
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Stock('IBM', 100, 70.44)
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>>>
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```
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### (a) Sorting on a field
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Try the following statements which sort the portfolio data
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alphabetically by stock name.
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```python
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>>> def stock_name(s):
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return s.name
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>>> portfolio.sort(key=stock_name)
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>>> for s in portfolio:
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print(s)
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... inspect the result ...
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>>>
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```
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In this part, the `stock_name()` function extracts the name of a stock from
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a single entry in the `portfolio` list. `sort()` uses the result of
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this function to do the comparison.
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### (b) Sorting on a field with lambda
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Try sorting the portfolio according the number of shares using a
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`lambda` expression:
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```python
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>>> portfolio.sort(key=lambda s: s.shares)
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>>> for s in portfolio:
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print(s)
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... inspect the result ...
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>>>
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```
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Try sorting the portfolio according to the price of each stock
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```python
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>>> portfolio.sort(key=lambda s: s.price)
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>>> for s in portfolio:
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print(s)
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... inspect the result ...
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>>>
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```
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Note: `lambda` is a useful shortcut because it allows you to
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define a special processing function directly in the call to `sort()` as
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opposed to having to define a separate function first (as in part a).
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[Next](03_Returning_functions) |