Shows the order in which "tasks" can be "done".
Groups tasks that can be done simultaneously.
1 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 | def dep(arg):
'''
Dependency resolver
"arg" is a dependency dictionary in which
the values are the dependencies of their respective keys.
'''
d=dict((k, set(arg[k])) for k in arg)
r=[]
while d:
# values not in keys (items without dep)
t=set(i for v in d.values() for i in v)-set(d.keys())
# and keys without value (items without dep)
t.update(k for k, v in d.items() if not v)
# can be done right away
r.append(t)
# and cleaned up
d=dict(((k, v-t) for k, v in d.items() if v))
return r
if __name__=='__main__':
d=dict(
a=('b','c'),
b=('c','d'),
e=(),
f=('c','e'),
g=('h','f'),
i=('f',)
)
print dep(d)
|
Inspired by Recipe 576569
How would you go about extending this <strike>obfuscated</strike> "space efficient" algorithm to deal with pathological cases, specifically circular dependencies?