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How to Build a DAG Execution Stage Calculator in Python
Computes the execution stages of a directed acyclic graph (DAG) by grouping nodes that become ready simultaneously using topological sorting with Kahn's algorithm.
from collections import defaultdict, deque
def get_stages(edges):
"""Return list of stages, where each stage is a list of nodes
that become ready at the same time in a DAG."""
graph = defaultdict(list)
in_degree = defaultdict(int)
nodes = set()
for src, dst in edges:
graph[src].appen…How to Stage ML Model Workflows with Python Classes
Defines a Stage class to model ML pipeline stages with variants and mocks, printing grammar for Model, Staging, and Production stages.
class Stage:
def __init__(self, name):
self.name = name
self.mocks = []
self.variants = []
def add_mock(self, mock_name):
self.mocks.append(mock_name)
def add_variant(self, variant_name, productions=()):
self.variants.append((variant_name, list(productions)))
…Training Pipeline Orchestration Mock DAG in Python
Build a mock DAG orchestrator that runs ML pipeline stages in dependency order using topological sorting (Kahn's algorithm).
from collections import deque
from dataclasses import dataclass, field
@dataclass
class DAGNode:
name: str
task: callable
dependencies: list[str] = field(default_factory=list)
class MockDAG:
def __init__(self, nodes: list[DAGNode]):
self.nodes = {n.name: n for n in nodes}
self.execu…Browse by section
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