An example of using a LazyDist in Python to create a computation graph

gistfile1.py

# the LazyDict implementation, callable values are evaluated before returning them
class LazyDict(dict):
    def __getitem__(self, k):
        val = dict.__getitem__(self, k)
        if callable(val):
            val = val()
            self[k] = val
        return val

# creates lambdas of all the dict entries
def compileGraph(inputs, graph):
    compGraph = LazyDict(inputs)
    for k, (fn, args) in graph.items():
        def constructLambda():
            fn_ = fn
            args_ = args
            compGraph[k] = lambda: fn_(*[compGraph[arg] for arg in args_])
        constructLambda()
    return compGraph


# example usage, args is a dict of input arguments into the graph
def testCalc(args):
    graph = {'windowSize': (windowSize, ('filterWidth')),
             'terrainMask': (calcTerrainMask, ('topo')),
             'composite': (compositeGrid, ('siteGrid', 'siteMask', 'neighbourGrid', 'noDataValue')),
             'diffGrid': (greatestAbsDiffFilter, ('composite', 'windowSize')),
             'thresholdedMask': (calcThresholdMask, ('diffGrid', 'terrainMask', 'thresholds')),
             'aoiMask': (areaOfInterest, ('siteMask', 'otherSiteMasks', 'filterWidth')),
             'borderPercentage': (borderPercentage, ('thresholdedMask', 'aoiMask'))
             }
    computationGraph = compileGraph(args, graph)

    print "Border Percentage:", computationGraph['borderPercentage']

Anything with lazy in the name gets my vote