Calculates the critical path through a network of tasks.
Assumes the given graph is acyclic (has no loops).
A task network is composed of nodes, but it's also organized within a parent node. This allows my node/task model to support recursive nesting of tasks. e.g. An overall "project" node containing multiple tasks can be treated as a single task in itself, and therefore included in more abstract task groupings.
pip install criticalpath
>>> from criticalpath import Node
>>> p = Node('project')
>>> a = p.add(Node('A', duration=3))
>>> b = p.add(Node('B', duration=3, lag=0))
>>> c = p.add(Node('C', duration=4, lag=0))
>>> d = p.add(Node('D', duration=6, lag=0))
>>> e = p.add(Node('E', duration=5, lag=0))
>>> p.link(a, b).link(a, c).link(a, d).link(b, e).link(c, e).link(d, e)
project
>>> p.update_all()
>>> p.get_critical_path()
[A, D, E]
>>> p.duration
14
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