def test7(self):
# bad
# /
# /
# /
# root ----------- good1
# \ ----- yields good1, good2 (good1 is seen through good2,
# \ / but is a direct successor of root)
# \ /
# good2
# -----
root = Node(Node.BAD)
bad = Node(Node.BAD)
good1 = Node(Node.GOOD)
good2 = Node(Node.GOOD)
digraph = DirectedGraph(nodes=[root, bad, good1, good2],
edges=[
Edge(root, bad),
Edge(root, good1),
Edge(root, good2),
Edge(good2, good1)
])
self.failUnlessEqual(
set([good1, good2]),
algorithm.nearest_property(digraph=digraph,
entrypoint=root,
property=GoodProperty()))
pass
def test1(self):
# bad1
# / \
# root / good yields good
# \ /----
# \ /
# bad2
root = Node(Node.BAD)
bad1 = Node(Node.BAD)
bad2 = Node(Node.BAD)
good = Node(Node.GOOD)
digraph = DirectedGraph(nodes=[root, bad1, bad2, good],
edges=[
Edge(tail=root, head=bad1),
Edge(tail=root, head=bad2),
Edge(tail=bad1, head=good),
Edge(tail=bad2, head=good)
])
self.failUnlessEqual(
set([good]),
algorithm.nearest_property(digraph=digraph,
entrypoint=root,
property=GoodProperty()))
pass
def test6(self):
# bad
# / \
# / \
# root good2
# \ ----- yields good1, good2
# \
# good1
# -----
root = Node(Node.BAD)
bad = Node(Node.BAD)
good1 = Node(Node.GOOD)
good2 = Node(Node.GOOD)
digraph = DirectedGraph(
nodes=[root, bad, good1, good2],
edges=[Edge(root, bad),
Edge(root, good1),
Edge(bad, good2)])
self.failUnlessEqual(
set([good1, good2]),
algorithm.nearest_property(digraph=digraph,
entrypoint=root,
property=GoodProperty()))
pass
def test3(self):
# good1 --- good3
# / ----- -----
# bad1 /
# / \ yields good1, good2
# root / \ good2
# \ /-----
# \ /
# bad2 /
root = Node(Node.BAD)
bad1 = Node(Node.BAD)
bad2 = Node(Node.BAD)
good1 = Node(Node.GOOD)
good2 = Node(Node.GOOD)
good3 = Node(Node.GOOD)
digraph = DirectedGraph(nodes=[root, bad1, bad2, good1, good2, good3],
edges=[
Edge(root, bad1),
Edge(root, bad2),
Edge(bad1, good1),
Edge(bad1, good2),
Edge(bad2, good2),
Edge(good1, good3)
])
self.failUnlessEqual(
set([good1, good2]),
algorithm.nearest_property(digraph=digraph,
entrypoint=root,
property=GoodProperty()))
pass
def relate(self, node, digraph, topolist):
"""
Builder method. As a service (we do not do anthing meaningful
with the information ourselves), we remember both the
topologically sorted list of the libraries that we depend on,
as well as the libraries that we directly depend on.
"""
Builder.relate(self, node, digraph, topolist)
self.__buildinfo_topo_dependent_native_libs = []
self.__buildinfo_direct_dependent_native_libs = []
nodes_with_library = algorithm.nearest_property(digraph=digraph, entrypoint=node, property=self.HaveLibraryProperty())
for n in nodes_with_library:
for bi in n.iter_buildinfos():
if type(bi) in (BuildInfo_CLibrary_NativeLocal, BuildInfo_CLibrary_NativeInstalled):
self.__buildinfo_direct_dependent_native_libs.append(bi)
pass
pass
pass
for n in topolist:
for bi in n.iter_buildinfos():
if type(bi) in (BuildInfo_CLibrary_NativeLocal, BuildInfo_CLibrary_NativeInstalled):
self.__buildinfo_topo_dependent_native_libs.insert(0, bi)
pass
pass
pass
pass
def test0(self):
# root ---- bad yields []
root = Node(Node.BAD)
bad = Node(Node.BAD)
digraph = DirectedGraph(nodes=[root, bad], edges=[Edge(root, bad)])
self.failUnlessEqual(
set(),
algorithm.nearest_property(digraph=digraph,
entrypoint=root,
property=GoodProperty()))
pass
def test8(self):
# root --- good1 --- good2 yields good1
root = Node(Node.BAD)
good1 = Node(Node.GOOD)
good2 = Node(Node.GOOD)
digraph = DirectedGraph(nodes=[root, good1, good2],
edges=[Edge(root, good1),
Edge(good1, good2)])
self.failUnlessEqual(
set([good1]),
algorithm.nearest_property(digraph=digraph,
entrypoint=root,
property=GoodProperty()))
pass
def test2(self):
# bad
# / \
# root /______\ good yields good
# ----
root = Node(Node.BAD)
bad = Node(Node.BAD)
good = Node(Node.GOOD)
digraph = DirectedGraph(
nodes=[root, bad, good],
edges=[Edge(root, bad),
Edge(root, good),
Edge(bad, good)])
self.failUnlessEqual(
set([good]),
algorithm.nearest_property(digraph=digraph,
entrypoint=root,
property=GoodProperty()))
pass