def __init__(self,
trace,
content_lens=None,
frame_lens=None,
activity=None):
"""Create from a LoadingTrace (or json of a trace).
Args:
trace: (LoadingTrace/JSON) Loading trace or JSON of a trace.
content_lens: (ContentClassificationLens) Lens used to annotate the
nodes, or None.
frame_lens: (FrameLoadLens) Lens used to augment graph with load nodes.
activity: (ActivityLens) Lens used to augment the edges with the
activity.
"""
if type(trace) == dict:
trace = loading_trace.LoadingTrace.FromJsonDict(trace)
self._trace = trace
self._content_lens = content_lens
self._frame_lens = frame_lens
self._activity_lens = activity
self._BuildDag(trace)
# Sort before splitting children so that we can correctly dectect if a
# reparented child is actually a dependency for a child of its new parent.
try:
for n in dag.TopologicalSort(self._nodes):
self._SplitChildrenByTime(self._node_info[n.Index()])
except AssertionError as exc:
sys.stderr.write('Bad topological sort: %s\n'
'Skipping child split\n' % str(exc))
self._cache_all = False
self._node_filter = lambda _: True
def Cost(self, path_list=None):
"""Compute cost of current model.
Args:
path_list: if not None, gets a list of NodeInfo in the longest path.
Returns:
Cost of the longest path.
"""
costs = [0] * len(self._nodes)
for n in dag.TopologicalSort(self._nodes, self._node_filter):
cost = 0
if n.Predecessors():
cost = max([costs[p.Index()] + self._EdgeCost(p, n)
for p in n.Predecessors()])
if not self._cache_all:
cost += self._NodeCost(n)
costs[n.Index()] = cost
max_cost = max(costs)
assert max_cost > 0 # Otherwise probably the filter went awry.
if path_list is not None:
del path_list[:-1]
n = (i for i in self._nodes if costs[i.Index()] == max_cost).next()
path_list.append(self._node_info[n.Index()])
while n.Predecessors():
n = reduce(lambda costliest, next:
next if (self._node_filter(next) and
cost[next.Index()] > cost[costliest.Index()])
else costliest,
n.Predecessors())
path_list.insert(0, self._node_info[n.Index()])
return max_cost
def MakeGraphviz(self, output, highlight=None):
"""Output a graphviz representation of our DAG.
Args:
output: a file-like output stream which recieves a graphviz dot.
highlight: a list of node items to emphasize. Any resource url which
contains any highlight text will be distinguished in the output.
"""
output.write("""digraph dependencies {
rankdir = LR;
""")
orphans = set()
try:
sorted_nodes = dag.TopologicalSort(self._nodes,
node_filter=self._node_filter)
except AssertionError as exc:
sys.stderr.write('Bad topological sort: %s\n'
'Writing children in order\n' % str(exc))
sorted_nodes = self._nodes
for n in sorted_nodes:
if not n.Successors() and not n.Predecessors():
orphans.add(n)
if orphans:
output.write("""subgraph cluster_orphans {
color=black;
label="Orphans";
""")
for n in orphans:
output.write(self._GraphvizNode(n.Index(), highlight))
output.write('}\n')
output.write("""subgraph cluster_nodes {
color=invis;
""")
for n in sorted_nodes:
if not n.Successors() and not n.Predecessors():
continue
output.write(self._GraphvizNode(n.Index(), highlight))
for n in sorted_nodes:
for s in n.Successors():
style = 'color = orange'
annotations = self._EdgeAnnotation(n, s)
if 'parser' in annotations:
style = 'color = red'
elif 'stack' in annotations:
style = 'color = blue'
elif 'script_inferred' in annotations:
style = 'color = purple'
if 'timing' in annotations:
style += '; style=dashed'
arrow = '[%s; label="%s"]' % (style, self._EdgeCost(n, s))
output.write('%d -> %d %s;\n' % (n.Index(), s.Index(), arrow))
output.write('}\n}\n')
def Nodes(self, sort=False):
"""Return iterable of all nodes via their NodeInfos.
Args:
sort: if true, return nodes in sorted order. This may prune additional
nodes from the unsorted list (eg, non-root, non-ad nodes reachable only
by ad nodes)
Returns:
Iterable of node infos.
"""
if sort:
return (
self._node_info[n.Index()]
for n in dag.TopologicalSort(self._nodes, self._node_filter))
return (n for n in self._node_info if self._node_filter(n.Node()))
def __init__(self, requests):
"""Create from a parsed request set.
Args:
requests: [RequestData, ...] filtered RequestData from loading.log_parser.
"""
self._BuildDag(requests)
self._global_start = min([n.StartTime() for n in self._node_info])
# Sort before splitting children so that we can correctly dectect if a
# reparented child is actually a dependency for a child of its new parent.
try:
for n in dag.TopologicalSort(self._nodes):
self._SplitChildrenByTime(self._node_info[n.Index()])
except AssertionError as exc:
sys.stderr.write('Bad topological sort: %s\n'
'Skipping child split\n' % str(exc))
self._cache_all = False
self._node_filter = lambda _: True
def SortedIndicies(self, graph):
return [n.Index() for n in dag.TopologicalSort(graph._nodes)]
def SortedIndicies(self, graph, node_filter=None): return [n.Index() for n in dag.TopologicalSort(graph, node_filter)]
