# Dive Into Python

Python from novice to pro

Find:

## 17.5. `plural.py`, stage 4

Let's factor out the duplication in the code so that defining new rules can be easier.

### Example 17.9. `plural4.py`

    import re

    def buildMatchAndApplyFunctions((pattern, search, replace)):
        matchFunction = lambda word: re.search(pattern, word)
        applyFunction = lambda word: re.sub(search, replace, word)
        return (matchFunction, applyFunction)

`buildMatchAndApplyFunctions` is a function that builds other functions dynamically. It takes `pattern`, `search` and `replace` (actually it takes a tuple, but more on that in a minute), and you can build the match function using the `lambda` syntax to be a function that takes one parameter (`word`) and calls `re.search` with the `pattern` that was passed to the `buildMatchAndApplyFunctions` function, and the `word` that was passed to the match function you're building. Whoa.

Building the apply function works the same way. The apply function is a function that takes one parameter, and calls `re.sub` with the `search` and `replace` parameters that were passed to the `buildMatchAndApplyFunctions` function, and the `word` that was passed to the apply function you're building. This technique of using the values of outside parameters within a dynamic function is called closures. You're essentially defining constants within the apply function you're building: it takes one parameter (`word`), but it then acts on that plus two other values (`search` and `replace`) which were set when you defined the apply function.

| Finally, the `buildMatchAndApplyFunctions` function returns a tuple of two values: the two functions you just created. The constants you defined within those functions (`pattern` within `matchFunction`, and `search` and `replace` within `applyFunction`) stay with those functions, even after you return from `buildMatchAndApplyFunctions`. That's insanely cool.

If this is incredibly confusing (and it should be, this is weird stuff), it may become clearer when you see how to use it.

### Example 17.10. `plural4.py` continued

    patterns = \
      (
        ('[sxz]$', '$', 'es'),
        ('[^aeioudgkprt]h$', '$', 'es'),
        ('(qu|[^aeiou])y$', 'y$', 'ies'),
        ('$', '$', 's')
      )
    rules = map(buildMatchAndApplyFunctions, patterns)

| Our pluralization rules are now defined as a series of strings (not functions). The first string is the regular expression that you would use in `re.search` to see if this rule matches; the second and third are the search and replace expressions you would use in `re.sub` to actually apply the rule to turn a noun into its plural.

This line is magic. It takes the list of strings in `patterns` and turns them into a list of functions. How? By mapping the strings to the `buildMatchAndApplyFunctions` function, which just happens to take three strings as parameters and return a tuple of two functions. This means that `rules` ends up being exactly the same as the previous example: a list of tuples, where each tuple is a pair of functions, where the first function is the match function that calls `re.search`, and the second function is the apply function that calls `re.sub`.

I swear I am not making this up: `rules` ends up with exactly the same list of functions as the previous example. Unroll the `rules` definition, and you'll get this:

### Example 17.11. Unrolling the rules definition

    rules = \
      (
        (
         lambda word: re.search('[sxz]$', word),
         lambda word: re.sub('$', 'es', word)
        ),
        (
         lambda word: re.search('[^aeioudgkprt]h$', word),
         lambda word: re.sub('$', 'es', word)
        ),
        (
         lambda word: re.search('[^aeiou]y$', word),
         lambda word: re.sub('y$', 'ies', word)
        ),
        (
         lambda word: re.search('$', word),
         lambda word: re.sub('$', 's', word)
        )
       )

### Example 17.12. `plural4.py`, finishing up

    def plural(noun):
        for matchesRule, applyRule in rules:
            if matchesRule(noun):
                return applyRule(noun)

Since the `rules` list is the same as the previous example, it should come as no surprise that the `plural` function hasn't changed. Remember, it's completely generic; it takes a list of rule functions and calls them in order. It doesn't care how the rules are defined. In stage 2, they were defined as seperate named functions. In stage 3, they were defined as anonymous `lambda` functions. Now in stage 4, they are built dynamically by mapping the `buildMatchAndApplyFunctions` function onto a list of raw strings. Doesn't matter; the `plural` function still works the same way.

Just in case that wasn't mind-blowing enough, I must confess that there was a subtlety in the definition of `buildMatchAndApplyFunctions` that I skipped over. Let's go back and take another look.

### Example 17.13. Another look at `buildMatchAndApplyFunctions`

    def buildMatchAndApplyFunctions((pattern, search, replace)):

| Notice the double parentheses? This function doesn't actually take three parameters; it actually takes one parameter, a tuple of three elements. But the tuple is expanded when the function is called, and the three elements of the tuple are each assigned to different variables: `pattern`, `search`, and `replace`. Confused yet? Let's see it in action.

### Example 17.14. Expanding tuples when calling functions

    >>> def foo((a, b, c)):
    ...     print c
    ...     print b
    ...     print a
    >>> parameters = ('apple', 'bear', 'catnap')
    >>> foo(parameters)
    catnap
    bear
    apple

| The proper way to call the function `foo` is with a tuple of three elements. When the function is called, the elements are assigned to different local variables within `foo`.

Now let's go back and see why this auto-tuple-expansion trick was necessary. `patterns` was a list of tuples, and each tuple had three elements. When you called `map(buildMatchAndApplyFunctions, patterns)`, that means that `buildMatchAndApplyFunctions` is not getting called with three parameters. Using `map` to map a single list onto a function always calls the function with a single parameter: each element of the list. In the case of `patterns`, each element of the list is a tuple, so `buildMatchAndApplyFunctions` always gets called with the tuple, and you use the auto-tuple-expansion trick in the definition of `buildMatchAndApplyFunctions` to assign the elements of that tuple to named variables that you can work with.