"""
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()