98 lines
2.7 KiB
Python
98 lines
2.7 KiB
Python
|
# util/topological.py
|
||
|
|
# Copyright (C) 2005-2019 the SQLAlchemy authors and contributors
|
||
|
|
# <see AUTHORS file>
|
||
|
|
#
|
||
|
|
# This module is part of SQLAlchemy and is released under
|
||
|
|
# the MIT License: http://www.opensource.org/licenses/mit-license.php
|
||
|
|
|
||
|
|
"""Topological sorting algorithms."""
|
||
|
|
|
||
|
|
from .. import util
|
||
|
|
from ..exc import CircularDependencyError
|
||
|
|
|
||
|
|
|
||
|
|
__all__ = ["sort", "sort_as_subsets", "find_cycles"]
|
||
|
|
|
||
|
|
|
||
|
|
def sort_as_subsets(tuples, allitems, deterministic_order=False):
|
||
|
|
|
||
|
|
edges = util.defaultdict(set)
|
||
|
|
for parent, child in tuples:
|
||
|
|
edges[child].add(parent)
|
||
|
|
|
||
|
|
Set = util.OrderedSet if deterministic_order else set
|
||
|
|
|
||
|
|
todo = Set(allitems)
|
||
|
|
|
||
|
|
while todo:
|
||
|
|
output = Set()
|
||
|
|
for node in todo:
|
||
|
|
if todo.isdisjoint(edges[node]):
|
||
|
|
output.add(node)
|
||
|
|
|
||
|
|
if not output:
|
||
|
|
raise CircularDependencyError(
|
||
|
|
"Circular dependency detected.",
|
||
|
|
find_cycles(tuples, allitems),
|
||
|
|
_gen_edges(edges),
|
||
|
|
)
|
||
|
|
|
||
|
|
todo.difference_update(output)
|
||
|
|
yield output
|
||
|
|
|
||
|
|
|
||
|
|
def sort(tuples, allitems, deterministic_order=False):
|
||
|
|
"""sort the given list of items by dependency.
|
||
|
|
|
||
|
|
'tuples' is a list of tuples representing a partial ordering.
|
||
|
|
'deterministic_order' keeps items within a dependency tier in list order.
|
||
|
|
"""
|
||
|
|
|
||
|
|
for set_ in sort_as_subsets(tuples, allitems, deterministic_order):
|
||
|
|
for s in set_:
|
||
|
|
yield s
|
||
|
|
|
||
|
|
|
||
|
|
def find_cycles(tuples, allitems):
|
||
|
|
# adapted from:
|
||
|
|
# http://neopythonic.blogspot.com/2009/01/detecting-cycles-in-directed-graph.html
|
||
|
|
|
||
|
|
edges = util.defaultdict(set)
|
||
|
|
for parent, child in tuples:
|
||
|
|
edges[parent].add(child)
|
||
|
|
nodes_to_test = set(edges)
|
||
|
|
|
||
|
|
output = set()
|
||
|
|
|
||
|
|
# we'd like to find all nodes that are
|
||
|
|
# involved in cycles, so we do the full
|
||
|
|
# pass through the whole thing for each
|
||
|
|
# node in the original list.
|
||
|
|
|
||
|
|
# we can go just through parent edge nodes.
|
||
|
|
# if a node is only a child and never a parent,
|
||
|
|
# by definition it can't be part of a cycle. same
|
||
|
|
# if it's not in the edges at all.
|
||
|
|
for node in nodes_to_test:
|
||
|
|
stack = [node]
|
||
|
|
todo = nodes_to_test.difference(stack)
|
||
|
|
while stack:
|
||
|
|
top = stack[-1]
|
||
|
|
for node in edges[top]:
|
||
|
|
if node in stack:
|
||
|
|
cyc = stack[stack.index(node) :]
|
||
|
|
todo.difference_update(cyc)
|
||
|
|
output.update(cyc)
|
||
|
|
|
||
|
|
if node in todo:
|
||
|
|
stack.append(node)
|
||
|
|
todo.remove(node)
|
||
|
|
break
|
||
|
|
else:
|
||
|
|
node = stack.pop()
|
||
|
|
return output
|
||
|
|
|
||
|
|
|
||
|
|
def _gen_edges(edges):
|
||
|
|
return set([(right, left) for left in edges for right in edges[left]])
|