A topological sort (sometimes abbreviated topsort or toposort) or topological ordering of a directed graph is a linear ordering of its vertices such that, for every edge uv, u comes before v in the ordering. For instance, the vertices of the graph may represent tasks to be performed, and the edges may represent constraints that one task must be performed before another; in this application, a topological ordering is just a valid sequence for the tasks. A topological ordering is possible if and only if the graph has no directed cycles, that is, if it is a directed acyclic graph (DAG).
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Copy to clipboard1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 | def toposort2(data):
"""Dependencies are expressed as a dictionary whose keys are items
and whose values are a set of dependent items. Output is a list of
sets in topological order. The first set consists of items with no
dependences, each subsequent set consists of items that depend upon
items in the preceeding sets.
>>> print '\\n'.join(repr(sorted(x)) for x in toposort2({
... 2: set([11]),
... 9: set([11,8]),
... 10: set([11,3]),
... 11: set([7,5]),
... 8: set([7,3]),
... }) )
[3, 5, 7]
[8, 11]
[2, 9, 10]
"""
from functools import reduce
# Ignore self dependencies.
for k, v in data.items():
v.discard(k)
# Find all items that don't depend on anything.
extra_items_in_deps = reduce(set.union, data.itervalues()) - set(data.iterkeys())
# Add empty dependences where needed
data.update({item:set() for item in extra_items_in_deps})
while True:
ordered = set(item for item, dep in data.iteritems() if not dep)
if not ordered:
break
yield ordered
data = {item: (dep - ordered)
for item, dep in data.iteritems()
if item not in ordered}
assert not data, "Cyclic dependencies exist among these items:\n%s" % '\n'.join(repr(x) for x in data.iteritems())
|
This is pretty much a duplicate of this, but in a format that is easier to drop into a program. I've moved the example into a doctest and changed the code so that (a) the input data can be any hashable object, not just strings, and (b) no time is wasted sorting the results. I also commented the code a bit and added a doc-string explaining the input and output formats.
If you are doing a lot of sorts, you may want to move the import statement outside the function; I put it inside to not conflict with any other imports you may already have in your program.
