batching operations groping method

operations_test.py

#! /user/bin/python3
from collections import defaultdict
from itertools import groupby
import operator

class Operation(object):
    TAPE    = []
    RECORD  = defaultdict(lambda: 0)
    RESULTS = {}
    OPERATIONS = {
        operation : getattr(operator, operation) for operation in ("add", "sub", "mul", "truediv")
    }
    def __init__(self, op, *args):
        self.op         = op
        self.args       = args
        self.evalDependancies(*args)
        self.TAPE.append(self)

    def run(self):
        args = [self.RESULTS.get(v, v) for v in self.args]
        res  = self.OPERATIONS[self.op](*args)
        self.RESULTS[self] = res
        return res

    def evalDependancies(self, *args):
        level               = max(self.RECORD[arg] for arg in args)
        self.RECORD[self]   = level+1

    @classmethod
    def reset(cls):
        cls.TAPE    = []
        cls.RECORD  = defaultdict(lambda: 0)

    @classmethod
    def getOrderedTape(cls):
        return sorted(cls.TAPE, key=lambda x: cls.RECORD[x])

    @classmethod
    def runOrderedTape(cls):
        return (x.run() for x in cls.getOrderedTape())

    @classmethod
    def batchOrderedTape(cls):
        results = []
        for batch, operations in groupby(orderedTape, key=lambda x: Operation.RECORD[x]):
            for op in operations: #here can be parallelized also
                results.append(op.run())
        return results


if __name__ == "__main__":
    a = 5
    b = 10
    op1 = Operation("add", a, b)
    c = 100
    op2 = Operation("sub", c, op1)
    op3 = Operation("mul", a, b)
    op4 = Operation("mul", op2, op3)
    from pprint import pprint
    pprint(Operation.TAPE)
    pprint(Operation.RECORD)
    orderedTape = Operation.getOrderedTape()
    pprint(list(Operation.runOrderedTape()))
    pprint(Operation.batchOrderedTape())