Schema-Aware Path Pruning

The problem

Complex task workflows often waste time and resources by attempting to execute paths that are impossible to complete due to data mismatches. This creates unnecessary overhead in nested systems.

What it does

It looks at a map of tasks and automatically removes any paths that use the wrong data types. It filters out these invalid routes before the system even tries to run them.

Why it matters

It ensures that only logically valid paths are processed, preventing errors and wasted effort in complex workflows.

Validation

It was run in the sandbox and it failed. run produced no meaningful output (empty or near-empty).

$ python3 schema_aware_path_pruning.py
Found 0 valid paths:

No screenshot — there is nothing working to show. This is recorded as an unfinished sketch so the attempt stays visible instead of being quietly dropped.

The code

All of it — 68 lines, one file, standard library only.

# Schema-Aware Path Pruning Implementation

class Node:
    def __init__(self, name, dtype):
        self.name = name
        self.dtype = dtype
        self.children = {}
        self.parent = None
        self.path_weight = 0.0
        self.reachable = False
       
    def add_child(self, edge_type, child):
        self.children[edge_type] = child
        child.parent = self
       

class PathPruner:
    def __init__(self, root_node):
        self.root = root_node
       
    def validate_path(self, path):
        """
        MLIR-like structural constraint checking
        """
        for i in range(1, len(path)):
            current = path[i-1]
            next_node = path[i]
            if current.dtype != next_node.dtype:
                return False
        return True
       
    def recursive_traversal(self, node, current_path, valid_paths):
        current_path.append(node)
       
        # Samyama Graph-inspired reachability scoring
        if node.name == 'target':  # Target node placeholder
            if self.validate_path(current_path):
                valid_paths.append(current_path[:])
       
        for edge_type, child in node.children.items():
            self.recursive_traversal(child, current_path, valid_paths)
       
        current_path.pop()
       
    def prune_paths(self):
        valid_paths = []
        self.recursive_traversal(self.root, [], valid_paths)
        return valid_paths
       

# Example Usage
if __name__ == "__main__":
    # Create sample task graph
    root = Node('root', dtype='string')
    process1 = Node('process1', dtype='int')
    process2 = Node('process2', dtype='bool')
    final_node = Node('target', dtype='string')
       
    root.add_child('edge1', process1)
    process1.add_child('edge2', final_node)
    process1.add_child('invalid_edge', process2)
       
    pruner = PathPruner(root)
    valid_paths = pruner.prune_paths()
       
    print(f"Found {len(valid_paths)} valid paths:\n")
    for i, path in enumerate(valid_paths):
        print(f"Path {i+1}: {' -> '.join([n.name for n in path])}'")