mirror of
https://github.com/aykhans/AzSuicideDataVisualization.git
synced 2025-04-21 18:23:35 +00:00
351 lines
12 KiB
Python
351 lines
12 KiB
Python
"""
|
|
This module exposes utilities to illustrate objects and their references as
|
|
(directed) graphs. The current implementation requires 'graphviz' to be
|
|
installed.
|
|
"""
|
|
|
|
from pympler.asizeof import Asizer, named_refs
|
|
from pympler.util.stringutils import safe_repr, trunc
|
|
from gc import get_referents
|
|
from subprocess import Popen, PIPE
|
|
from copy import copy
|
|
from sys import platform
|
|
|
|
__all__ = ['ReferenceGraph']
|
|
|
|
|
|
# Popen might lead to deadlocks when file descriptors are leaked to
|
|
# sub-processes on Linux. On Windows, however, close_fds=True leads to
|
|
# ValueError if stdin/stdout/stderr is piped:
|
|
# http://code.google.com/p/pympler/issues/detail?id=28#c1
|
|
popen_flags = {}
|
|
if platform not in ['win32']: # pragma: no branch
|
|
popen_flags['close_fds'] = True
|
|
|
|
|
|
class _MetaObject(object):
|
|
"""
|
|
The _MetaObject stores meta-information, like a string representation,
|
|
corresponding to each object passed to a ReferenceGraph.
|
|
"""
|
|
__slots__ = ('size', 'id', 'type', 'str', 'group', 'cycle')
|
|
|
|
def __init__(self):
|
|
self.cycle = False
|
|
|
|
|
|
class _Edge(object):
|
|
"""
|
|
Describes a reference from one object `src` to another object `dst`.
|
|
"""
|
|
__slots__ = ('src', 'dst', 'label', 'group')
|
|
|
|
def __init__(self, src, dst, label):
|
|
self.src = src
|
|
self.dst = dst
|
|
self.label = label
|
|
self.group = None
|
|
|
|
def __repr__(self):
|
|
return "<%08x => %08x, '%s', %s>" % (self.src, self.dst, self.label,
|
|
self.group)
|
|
|
|
def __hash__(self):
|
|
return (self.src, self.dst, self.label).__hash__()
|
|
|
|
def __eq__(self, other):
|
|
return self.__hash__() == other.__hash__()
|
|
|
|
|
|
class ReferenceGraph(object):
|
|
"""
|
|
The ReferenceGraph illustrates the references between a collection of
|
|
objects by rendering a directed graph. That requires that 'graphviz' is
|
|
installed.
|
|
|
|
>>> from pympler.refgraph import ReferenceGraph
|
|
>>> a = 42
|
|
>>> b = 'spam'
|
|
>>> c = {a: b}
|
|
>>> gb = ReferenceGraph([a,b,c])
|
|
>>> gb.render('spam.eps')
|
|
True
|
|
"""
|
|
def __init__(self, objects, reduce=False):
|
|
"""
|
|
Initialize the ReferenceGraph with a collection of `objects`.
|
|
"""
|
|
self.objects = list(objects)
|
|
self.count = len(self.objects)
|
|
self.num_in_cycles = 'N/A'
|
|
self.edges = None
|
|
|
|
if reduce:
|
|
self.num_in_cycles = self._reduce_to_cycles()
|
|
self._reduced = self # TODO: weakref?
|
|
else:
|
|
self._reduced = None
|
|
|
|
self._get_edges()
|
|
self._annotate_objects()
|
|
|
|
def _eliminate_leafs(self, graph):
|
|
"""
|
|
Eliminate leaf objects - that are objects not referencing any other
|
|
objects in the list `graph`. Returns the list of objects without the
|
|
objects identified as leafs.
|
|
"""
|
|
result = []
|
|
idset = set([id(x) for x in graph])
|
|
for n in graph:
|
|
refset = set([id(x) for x in get_referents(n)])
|
|
if refset.intersection(idset):
|
|
result.append(n)
|
|
return result
|
|
|
|
def _reduce_to_cycles(self):
|
|
"""
|
|
Iteratively eliminate leafs to reduce the set of objects to only those
|
|
that build cycles. Return the number of objects involved in reference
|
|
cycles. If there are no cycles, `self.objects` will be an empty list
|
|
and this method returns 0.
|
|
"""
|
|
cycles = self.objects[:]
|
|
cnt = 0
|
|
while cnt != len(cycles):
|
|
cnt = len(cycles)
|
|
cycles = self._eliminate_leafs(cycles)
|
|
self.objects = cycles
|
|
return len(self.objects)
|
|
|
|
def reduce_to_cycles(self):
|
|
"""
|
|
Iteratively eliminate leafs to reduce the set of objects to only those
|
|
that build cycles. Return the reduced graph. If there are no cycles,
|
|
None is returned.
|
|
"""
|
|
if not self._reduced:
|
|
reduced = copy(self)
|
|
reduced.objects = self.objects[:]
|
|
reduced.metadata = []
|
|
reduced.edges = []
|
|
self.num_in_cycles = reduced._reduce_to_cycles()
|
|
reduced.num_in_cycles = self.num_in_cycles
|
|
if self.num_in_cycles:
|
|
reduced._get_edges()
|
|
reduced._annotate_objects()
|
|
for meta in reduced.metadata:
|
|
meta.cycle = True
|
|
else:
|
|
reduced = None
|
|
self._reduced = reduced
|
|
return self._reduced
|
|
|
|
def _get_edges(self):
|
|
"""
|
|
Compute the edges for the reference graph.
|
|
The function returns a set of tuples (id(a), id(b), ref) if a
|
|
references b with the referent 'ref'.
|
|
"""
|
|
idset = set([id(x) for x in self.objects])
|
|
self.edges = set([])
|
|
for n in self.objects:
|
|
refset = set([id(x) for x in get_referents(n)])
|
|
for ref in refset.intersection(idset):
|
|
label = ''
|
|
members = None
|
|
if isinstance(n, dict):
|
|
members = n.items()
|
|
if not members:
|
|
members = named_refs(n)
|
|
for (k, v) in members:
|
|
if id(v) == ref:
|
|
label = k
|
|
break
|
|
self.edges.add(_Edge(id(n), ref, label))
|
|
|
|
def _annotate_groups(self):
|
|
"""
|
|
Annotate the objects belonging to separate (non-connected) graphs with
|
|
individual indices.
|
|
"""
|
|
g = {}
|
|
for x in self.metadata:
|
|
g[x.id] = x
|
|
|
|
idx = 0
|
|
for x in self.metadata:
|
|
if not hasattr(x, 'group'):
|
|
x.group = idx
|
|
idx += 1
|
|
neighbors = set()
|
|
for e in self.edges:
|
|
if e.src == x.id:
|
|
neighbors.add(e.dst)
|
|
if e.dst == x.id:
|
|
neighbors.add(e.src)
|
|
for nb in neighbors:
|
|
g[nb].group = min(x.group, getattr(g[nb], 'group', idx))
|
|
|
|
# Assign the edges to the respective groups. Both "ends" of the edge
|
|
# should share the same group so just use the first object's group.
|
|
for e in self.edges:
|
|
e.group = g[e.src].group
|
|
|
|
self._max_group = idx
|
|
|
|
def _filter_group(self, group):
|
|
"""
|
|
Eliminate all objects but those which belong to `group`.
|
|
``self.objects``, ``self.metadata`` and ``self.edges`` are modified.
|
|
Returns `True` if the group is non-empty. Otherwise returns `False`.
|
|
"""
|
|
self.metadata = [x for x in self.metadata if x.group == group]
|
|
group_set = set([x.id for x in self.metadata])
|
|
self.objects = [obj for obj in self.objects if id(obj) in group_set]
|
|
self.count = len(self.metadata)
|
|
if self.metadata == []:
|
|
return False
|
|
|
|
self.edges = [e for e in self.edges if e.group == group]
|
|
|
|
del self._max_group
|
|
|
|
return True
|
|
|
|
def split(self):
|
|
"""
|
|
Split the graph into sub-graphs. Only connected objects belong to the
|
|
same graph. `split` yields copies of the Graph object. Shallow copies
|
|
are used that only replicate the meta-information, but share the same
|
|
object list ``self.objects``.
|
|
|
|
>>> from pympler.refgraph import ReferenceGraph
|
|
>>> a = 42
|
|
>>> b = 'spam'
|
|
>>> c = {a: b}
|
|
>>> t = (1,2,3)
|
|
>>> rg = ReferenceGraph([a,b,c,t])
|
|
>>> for subgraph in rg.split():
|
|
... print (subgraph.index)
|
|
0
|
|
1
|
|
"""
|
|
self._annotate_groups()
|
|
index = 0
|
|
|
|
for group in range(self._max_group):
|
|
subgraph = copy(self)
|
|
subgraph.metadata = self.metadata[:]
|
|
subgraph.edges = self.edges.copy()
|
|
|
|
if subgraph._filter_group(group):
|
|
subgraph.total_size = sum([x.size for x in subgraph.metadata])
|
|
subgraph.index = index
|
|
index += 1
|
|
yield subgraph
|
|
|
|
def split_and_sort(self):
|
|
"""
|
|
Split the graphs into sub graphs and return a list of all graphs sorted
|
|
by the number of nodes. The graph with most nodes is returned first.
|
|
"""
|
|
graphs = list(self.split())
|
|
graphs.sort(key=lambda x: -len(x.metadata))
|
|
for index, graph in enumerate(graphs):
|
|
graph.index = index
|
|
return graphs
|
|
|
|
def _annotate_objects(self):
|
|
"""
|
|
Extract meta-data describing the stored objects.
|
|
"""
|
|
self.metadata = []
|
|
sizer = Asizer()
|
|
sizes = sizer.asizesof(*self.objects)
|
|
self.total_size = sizer.total
|
|
for obj, sz in zip(self.objects, sizes):
|
|
md = _MetaObject()
|
|
md.size = sz
|
|
md.id = id(obj)
|
|
try:
|
|
md.type = obj.__class__.__name__
|
|
except (AttributeError, ReferenceError): # pragma: no cover
|
|
md.type = type(obj).__name__
|
|
md.str = safe_repr(obj, clip=128)
|
|
self.metadata.append(md)
|
|
|
|
def _get_graphviz_data(self):
|
|
"""
|
|
Emit a graph representing the connections between the objects described
|
|
within the metadata list. The text representation can be transformed to
|
|
a graph with graphviz. Returns a string.
|
|
"""
|
|
s = []
|
|
header = '// Process this file with graphviz\n'
|
|
s.append(header)
|
|
s.append('digraph G {\n')
|
|
s.append(' node [shape=box];\n')
|
|
for md in self.metadata:
|
|
label = trunc(md.str, 48).replace('"', "'")
|
|
extra = ''
|
|
if md.type == 'instancemethod':
|
|
extra = ', color=red'
|
|
elif md.type == 'frame':
|
|
extra = ', color=orange'
|
|
s.append(' "X%s" [ label = "%s\\n%s" %s ];\n' %
|
|
(hex(md.id)[1:], label, md.type, extra))
|
|
for e in self.edges:
|
|
extra = ''
|
|
if e.label == '__dict__':
|
|
extra = ',weight=100'
|
|
s.append(' X%s -> X%s [label="%s"%s];\n' %
|
|
(hex(e.src)[1:], hex(e.dst)[1:], e.label, extra))
|
|
|
|
s.append('}\n')
|
|
return "".join(s)
|
|
|
|
def render(self, filename, cmd='dot', format='ps', unflatten=False):
|
|
"""
|
|
Render the graph to `filename` using graphviz. The graphviz invocation
|
|
command may be overridden by specifying `cmd`. The `format` may be any
|
|
specifier recognized by the graph renderer ('-Txxx' command). The
|
|
graph can be preprocessed by the *unflatten* tool if the `unflatten`
|
|
parameter is True. If there are no objects to illustrate, the method
|
|
does not invoke graphviz and returns False. If the renderer returns
|
|
successfully (return code 0), True is returned.
|
|
|
|
An `OSError` is raised if the graphviz tool cannot be found.
|
|
"""
|
|
if self.objects == []:
|
|
return False
|
|
|
|
data = self._get_graphviz_data()
|
|
|
|
options = ('-Nfontsize=10',
|
|
'-Efontsize=10',
|
|
'-Nstyle=filled',
|
|
'-Nfillcolor=#E5EDB8',
|
|
'-Ncolor=#CCCCCC')
|
|
cmdline = (cmd, '-T%s' % format, '-o', filename) + options
|
|
|
|
if unflatten:
|
|
p1 = Popen(('unflatten', '-l7'), stdin=PIPE, stdout=PIPE,
|
|
**popen_flags)
|
|
p2 = Popen(cmdline, stdin=p1.stdout, **popen_flags)
|
|
p1.communicate(data.encode())
|
|
p2.communicate()
|
|
return p2.returncode == 0
|
|
else:
|
|
p = Popen(cmdline, stdin=PIPE, **popen_flags)
|
|
p.communicate(data.encode())
|
|
return p.returncode == 0
|
|
|
|
def write_graph(self, filename):
|
|
"""
|
|
Write raw graph data which can be post-processed using graphviz.
|
|
"""
|
|
f = open(filename, 'w')
|
|
f.write(self._get_graphviz_data())
|
|
f.close()
|