Wednesday, July 16, 2008

Groovy Polymorphics with Closures

Let me begin by stating the problem: I need an object that can locate files in a specific folder, parse the selected files, then execute database updates against the parsed results. The twist is that the update process might be inside a grails application using GORM, or, it might be a standalone jdbc process that has it's own data access mechanism. Here is the proposed object:

class Process {
def findFiles() { /* return a list of files */ }
def parseFile(file) { /* parse the file, return the data */ }

// the update function (closure)
def update

// the runner
def run() {
def list = findFiles()
records = []
list.each { records << parseFile( it ) }
update( records )
Forget about the empty methods for now, let's just assume they work. Notice that run() finds the files, parses them, then updates them. Here is how the target object is used:
def process = new Process()
process.update = (isGorm ? gormUpdater : jdbcUpdater)
The first thing you might notice is that 'update' in the Process class has no body--it's simply a tag for the closure name. When the class becomes an object, update is assigned the closure method based on the runtime environment. Here is how a very simple GORM closure would be defined:
myGormUpdater = { records ->
records.each { row ->
Simple. Loop through the records and save each one. The polymorphic magic is implemented with a closure, not a sub class. This eliminates class bloat by using portable stand-alone methods assigned to normal variables of a class--like named function pointers. An added benefit is that the closure can be used on similar classes that require the same functionality.

Real World Scenario: Lets say I have a small group of software engineers. Two of my engineers are data-feed experts, another three are database domain experts. Me, well, I'm the manager.

So, since I have the big picture, I design the base class and create test fixture data. Then, I tell my feed experts to give me methods for parsing a set of files. They don't have to worry about where the files are, just how to parse and create datasets. At the same time I assign the database ops to the database group. They don't have to concern themselves with where the data comes from, just how to convert datasets into database updates for all our target databases.

Even though I'm a manager, I contribute in a real way to the code base. And, to keep my team productive, I create the test data for the parser and database groups. The experts are assigned tasks that they handle best.

Combine this with daily scrum communications and, for the hands-on CTO, this is very Groovalicious!

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