--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/planemo/lib/python3.7/site-packages/networkx/readwrite/graphml.py	Fri Jul 31 00:32:28 2020 -0400
@@ -0,0 +1,918 @@
+#    Copyright (C) 2008-2019 by
+#    Aric Hagberg <hagberg@lanl.gov>
+#    Dan Schult <dschult@colgate.edu>
+#    Pieter Swart <swart@lanl.gov>
+#    All rights reserved.
+#    BSD license.
+#
+# Authors: Salim Fadhley
+#          Aric Hagberg (hagberg@lanl.gov)
+"""
+*******
+GraphML
+*******
+Read and write graphs in GraphML format.
+
+This implementation does not support mixed graphs (directed and unidirected
+edges together), hyperedges, nested graphs, or ports.
+
+"GraphML is a comprehensive and easy-to-use file format for graphs. It
+consists of a language core to describe the structural properties of a
+graph and a flexible extension mechanism to add application-specific
+data. Its main features include support of
+
+    * directed, undirected, and mixed graphs,
+    * hypergraphs,
+    * hierarchical graphs,
+    * graphical representations,
+    * references to external data,
+    * application-specific attribute data, and
+    * light-weight parsers.
+
+Unlike many other file formats for graphs, GraphML does not use a
+custom syntax. Instead, it is based on XML and hence ideally suited as
+a common denominator for all kinds of services generating, archiving,
+or processing graphs."
+
+http://graphml.graphdrawing.org/
+
+Format
+------
+GraphML is an XML format.  See
+http://graphml.graphdrawing.org/specification.html for the specification and
+http://graphml.graphdrawing.org/primer/graphml-primer.html
+for examples.
+"""
+import warnings
+from collections import defaultdict
+
+try:
+    from xml.etree.cElementTree import Element, ElementTree
+    from xml.etree.cElementTree import tostring, fromstring
+except ImportError:
+    try:
+        from xml.etree.ElementTree import Element, ElementTree
+        from xml.etree.ElementTree import tostring, fromstring
+    except ImportError:
+        pass
+
+try:
+    import lxml.etree as lxmletree
+except ImportError:
+    lxmletree = None
+
+import networkx as nx
+from networkx.utils import open_file, make_str
+
+__all__ = ['write_graphml', 'read_graphml', 'generate_graphml',
+           'write_graphml_xml', 'write_graphml_lxml',
+           'parse_graphml', 'GraphMLWriter', 'GraphMLReader']
+
+
+@open_file(1, mode='wb')
+def write_graphml_xml(G, path, encoding='utf-8', prettyprint=True,
+                      infer_numeric_types=False):
+    """Write G in GraphML XML format to path
+
+    Parameters
+    ----------
+    G : graph
+       A networkx graph
+    path : file or string
+       File or filename to write.
+       Filenames ending in .gz or .bz2 will be compressed.
+    encoding : string (optional)
+       Encoding for text data.
+    prettyprint : bool (optional)
+       If True use line breaks and indenting in output XML.
+    infer_numeric_types : boolean
+       Determine if numeric types should be generalized.
+       For example, if edges have both int and float 'weight' attributes,
+       we infer in GraphML that both are floats.
+
+    Examples
+    --------
+    >>> G = nx.path_graph(4)
+    >>> nx.write_graphml(G, "test.graphml")
+
+    Notes
+    -----
+    It may be a good idea in Python2 to convert strings to unicode
+    before giving the graph to write_gml. At least the strings with
+    either many characters to escape.
+
+    This implementation does not support mixed graphs (directed
+    and unidirected edges together) hyperedges, nested graphs, or ports.
+    """
+    writer = GraphMLWriter(encoding=encoding, prettyprint=prettyprint,
+                           infer_numeric_types=infer_numeric_types)
+    writer.add_graph_element(G)
+    writer.dump(path)
+
+
+@open_file(1, mode='wb')
+def write_graphml_lxml(G, path, encoding='utf-8', prettyprint=True,
+                       infer_numeric_types=False):
+    """Write G in GraphML XML format to path
+
+    This function uses the LXML framework and should be faster than
+    the version using the xml library.
+
+    Parameters
+    ----------
+    G : graph
+       A networkx graph
+    path : file or string
+       File or filename to write.
+       Filenames ending in .gz or .bz2 will be compressed.
+    encoding : string (optional)
+       Encoding for text data.
+    prettyprint : bool (optional)
+       If True use line breaks and indenting in output XML.
+    infer_numeric_types : boolean
+       Determine if numeric types should be generalized.
+       For example, if edges have both int and float 'weight' attributes,
+       we infer in GraphML that both are floats.
+
+    Examples
+    --------
+    >>> G = nx.path_graph(4)
+    >>> nx.write_graphml_lxml(G, "fourpath.graphml")  # doctest: +SKIP
+
+    Notes
+    -----
+    This implementation does not support mixed graphs (directed
+    and unidirected edges together) hyperedges, nested graphs, or ports.
+    """
+    writer = GraphMLWriterLxml(path, graph=G, encoding=encoding,
+                               prettyprint=prettyprint,
+                               infer_numeric_types=infer_numeric_types)
+    writer.dump()
+
+
+def generate_graphml(G, encoding='utf-8', prettyprint=True):
+    """Generate GraphML lines for G
+
+    Parameters
+    ----------
+    G : graph
+       A networkx graph
+    encoding : string (optional)
+       Encoding for text data.
+    prettyprint : bool (optional)
+       If True use line breaks and indenting in output XML.
+
+    Examples
+    --------
+    >>> G = nx.path_graph(4)
+    >>> linefeed = chr(10)  # linefeed = \n
+    >>> s = linefeed.join(nx.generate_graphml(G))  # doctest: +SKIP
+    >>> for line in nx.generate_graphml(G):  # doctest: +SKIP
+    ...    print(line)
+
+    Notes
+    -----
+    This implementation does not support mixed graphs (directed and unidirected
+    edges together) hyperedges, nested graphs, or ports.
+    """
+    writer = GraphMLWriter(encoding=encoding, prettyprint=prettyprint)
+    writer.add_graph_element(G)
+    for line in str(writer).splitlines():
+        yield line
+
+
+@open_file(0, mode='rb')
+def read_graphml(path, node_type=str, edge_key_type=int):
+    """Read graph in GraphML format from path.
+
+    Parameters
+    ----------
+    path : file or string
+       File or filename to write.
+       Filenames ending in .gz or .bz2 will be compressed.
+
+    node_type: Python type (default: str)
+       Convert node ids to this type
+
+    edge_key_type: Python type (default: int)
+       Convert graphml edge ids to this type as key of multi-edges
+
+
+    Returns
+    -------
+    graph: NetworkX graph
+        If no parallel edges are found a Graph or DiGraph is returned.
+        Otherwise a MultiGraph or MultiDiGraph is returned.
+
+    Notes
+    -----
+    Default node and edge attributes are not propagated to each node and edge.
+    They can be obtained from `G.graph` and applied to node and edge attributes
+    if desired using something like this:
+
+    >>> default_color = G.graph['node_default']['color']  # doctest: +SKIP
+    >>> for node, data in G.nodes(data=True):  # doctest: +SKIP
+    ...     if 'color' not in data:
+    ...         data['color']=default_color
+    >>> default_color = G.graph['edge_default']['color']  # doctest: +SKIP
+    >>> for u, v, data in G.edges(data=True):  # doctest: +SKIP
+    ...     if 'color' not in data:
+    ...         data['color']=default_color
+
+    This implementation does not support mixed graphs (directed and unidirected
+    edges together), hypergraphs, nested graphs, or ports.
+
+    For multigraphs the GraphML edge "id" will be used as the edge
+    key.  If not specified then they "key" attribute will be used.  If
+    there is no "key" attribute a default NetworkX multigraph edge key
+    will be provided.
+
+    Files with the yEd "yfiles" extension will can be read but the graphics
+    information is discarded.
+
+    yEd compressed files ("file.graphmlz" extension) can be read by renaming
+    the file to "file.graphml.gz".
+
+    """
+    reader = GraphMLReader(node_type=node_type, edge_key_type=edge_key_type)
+    # need to check for multiple graphs
+    glist = list(reader(path=path))
+    if len(glist) == 0:
+        # If no graph comes back, try looking for an incomplete header
+        header = b'<graphml xmlns="http://graphml.graphdrawing.org/xmlns">'
+        path.seek(0)
+        old_bytes = path.read()
+        new_bytes = old_bytes.replace(b'<graphml>', header)
+        glist = list(reader(string=new_bytes))
+        if len(glist) == 0:
+            raise nx.NetworkXError('file not successfully read as graphml')
+    return glist[0]
+
+
+def parse_graphml(graphml_string, node_type=str):
+    """Read graph in GraphML format from string.
+
+    Parameters
+    ----------
+    graphml_string : string
+       String containing graphml information
+       (e.g., contents of a graphml file).
+
+    node_type: Python type (default: str)
+       Convert node ids to this type
+
+    Returns
+    -------
+    graph: NetworkX graph
+        If no parallel edges are found a Graph or DiGraph is returned.
+        Otherwise a MultiGraph or MultiDiGraph is returned.
+
+    Examples
+    --------
+    >>> G = nx.path_graph(4)
+    >>> linefeed = chr(10)  # linefeed = \n
+    >>> s = linefeed.join(nx.generate_graphml(G))
+    >>> H = nx.parse_graphml(s)
+
+    Notes
+    -----
+    Default node and edge attributes are not propagated to each node and edge.
+    They can be obtained from `G.graph` and applied to node and edge attributes
+    if desired using something like this:
+
+    >>> default_color = G.graph['node_default']['color']  # doctest: +SKIP
+    >>> for node, data in G.nodes(data=True):  # doctest: +SKIP
+    ...    if 'color' not in data:
+    ...        data['color']=default_color
+    >>> default_color = G.graph['edge_default']['color']  # doctest: +SKIP
+    >>> for u, v, data in G.edges(data=True):  # doctest: +SKIP
+    ...    if 'color' not in data:
+    ...        data['color']=default_color
+
+    This implementation does not support mixed graphs (directed and unidirected
+    edges together), hypergraphs, nested graphs, or ports.
+
+    For multigraphs the GraphML edge "id" will be used as the edge
+    key.  If not specified then they "key" attribute will be used.  If
+    there is no "key" attribute a default NetworkX multigraph edge key
+    will be provided.
+
+    """
+    reader = GraphMLReader(node_type=node_type)
+    # need to check for multiple graphs
+    glist = list(reader(string=graphml_string))
+    if len(glist) == 0:
+        # If no graph comes back, try looking for an incomplete header
+        header = '<graphml xmlns="http://graphml.graphdrawing.org/xmlns">'
+        new_string = graphml_string.replace('<graphml>', header)
+        glist = list(reader(string=new_string))
+        if len(glist) == 0:
+            raise nx.NetworkXError('file not successfully read as graphml')
+    return glist[0]
+
+
+class GraphML(object):
+    NS_GRAPHML = "http://graphml.graphdrawing.org/xmlns"
+    NS_XSI = "http://www.w3.org/2001/XMLSchema-instance"
+    # xmlns:y="http://www.yworks.com/xml/graphml"
+    NS_Y = "http://www.yworks.com/xml/graphml"
+    SCHEMALOCATION = \
+        ' '.join(['http://graphml.graphdrawing.org/xmlns',
+                  'http://graphml.graphdrawing.org/xmlns/1.0/graphml.xsd'])
+
+    try:
+        chr(12345)     # Fails on Py!=3.
+        unicode = str  # Py3k's str is our unicode type
+        long = int     # Py3K's int is our long type
+    except ValueError:
+        # Python 2.x
+        pass
+
+    types = [(int, "integer"),  # for Gephi GraphML bug
+             (str, "yfiles"), (str, "string"), (unicode, "string"),
+             (int, "int"), (long, "long"),
+             (float, "float"), (float, "double"),
+             (bool, "boolean")]
+
+    # These additions to types allow writing numpy types
+    try:
+        import numpy as np
+    except:
+        pass
+    else:
+        # prepend so that python types are created upon read (last entry wins)
+        types = [(np.float64, "float"), (np.float32, "float"),
+                 (np.float16, "float"), (np.float_, "float"),
+                 (np.int, "int"), (np.int8, "int"),
+                 (np.int16, "int"), (np.int32, "int"),
+                 (np.int64, "int"), (np.uint8, "int"),
+                 (np.uint16, "int"), (np.uint32, "int"),
+                 (np.uint64, "int"), (np.int_, "int"),
+                 (np.intc, "int"), (np.intp, "int"),
+                ] + types
+
+    xml_type = dict(types)
+    python_type = dict(reversed(a) for a in types)
+
+    # This page says that data types in GraphML follow Java(TM).
+    #  http://graphml.graphdrawing.org/primer/graphml-primer.html#AttributesDefinition
+    # true and false are the only boolean literals:
+    #  http://en.wikibooks.org/wiki/Java_Programming/Literals#Boolean_Literals
+    convert_bool = {
+        # We use data.lower() in actual use.
+        'true': True, 'false': False,
+        # Include integer strings for convenience.
+        '0': False, 0: False,
+        '1': True, 1: True
+    }
+
+
+class GraphMLWriter(GraphML):
+    def __init__(self, graph=None, encoding="utf-8", prettyprint=True,
+                 infer_numeric_types=False):
+        try:
+            import xml.etree.ElementTree
+        except ImportError:
+            msg = 'GraphML writer requires xml.elementtree.ElementTree'
+            raise ImportError(msg)
+        self.myElement = Element
+
+        self.infer_numeric_types = infer_numeric_types
+        self.prettyprint = prettyprint
+        self.encoding = encoding
+        self.xml = self.myElement("graphml",
+                                  {'xmlns': self.NS_GRAPHML,
+                                   'xmlns:xsi': self.NS_XSI,
+                                   'xsi:schemaLocation': self.SCHEMALOCATION})
+        self.keys = {}
+        self.attributes = defaultdict(list)
+        self.attribute_types = defaultdict(set)
+
+        if graph is not None:
+            self.add_graph_element(graph)
+
+    def __str__(self):
+        if self.prettyprint:
+            self.indent(self.xml)
+        s = tostring(self.xml).decode(self.encoding)
+        return s
+
+    def attr_type(self, name, scope, value):
+        """Infer the attribute type of data named name. Currently this only
+        supports inference of numeric types.
+
+        If self.infer_numeric_types is false, type is used. Otherwise, pick the
+        most general of types found across all values with name and scope. This
+        means edges with data named 'weight' are treated separately from nodes
+        with data named 'weight'.
+        """
+        if self.infer_numeric_types:
+            types = self.attribute_types[(name, scope)]
+
+            try:
+                chr(12345)     # Fails on Py<3.
+                local_long = int     # Py3's int is Py2's long type
+                local_unicode = str  # Py3's str is Py2's unicode type
+            except ValueError:
+                # Python 2.x
+                local_long = long
+                local_unicode = unicode
+
+            if len(types) > 1:
+                if str in types:
+                    return str
+                elif local_unicode in types:
+                    return local_unicode
+                elif float in types:
+                    return float
+                elif local_long in types:
+                    return local_long
+                else:
+                    return int
+            else:
+                return list(types)[0]
+        else:
+            return type(value)
+
+    def get_key(self, name, attr_type, scope, default):
+        keys_key = (name, attr_type, scope)
+        try:
+            return self.keys[keys_key]
+        except KeyError:
+            new_id = "d%i" % len(list(self.keys))
+            self.keys[keys_key] = new_id
+            key_kwargs = {"id": new_id,
+                          "for": scope,
+                          "attr.name": name,
+                          "attr.type": attr_type}
+            key_element = self.myElement("key", **key_kwargs)
+            # add subelement for data default value if present
+            if default is not None:
+                default_element = self.myElement("default")
+                default_element.text = make_str(default)
+                key_element.append(default_element)
+            self.xml.insert(0, key_element)
+        return new_id
+
+    def add_data(self, name, element_type, value,
+                 scope="all",
+                 default=None):
+        """
+        Make a data element for an edge or a node. Keep a log of the
+        type in the keys table.
+        """
+        if element_type not in self.xml_type:
+            msg = 'GraphML writer does not support %s as data values.'
+            raise nx.NetworkXError(msg % element_type)
+        keyid = self.get_key(name, self.xml_type[element_type], scope, default)
+        data_element = self.myElement("data", key=keyid)
+        data_element.text = make_str(value)
+        return data_element
+
+    def add_attributes(self, scope, xml_obj, data, default):
+        """Appends attribute data to edges or nodes, and stores type information
+        to be added later. See add_graph_element.
+        """
+        for k, v in data.items():
+            self.attribute_types[(make_str(k), scope)].add(type(v))
+            self.attributes[xml_obj].append([k, v, scope, default.get(k)])
+
+    def add_nodes(self, G, graph_element):
+        default = G.graph.get('node_default', {})
+        for node, data in G.nodes(data=True):
+            node_element = self.myElement("node", id=make_str(node))
+            self.add_attributes("node", node_element, data, default)
+            graph_element.append(node_element)
+
+    def add_edges(self, G, graph_element):
+        if G.is_multigraph():
+            for u, v, key, data in G.edges(data=True, keys=True):
+                edge_element = self.myElement("edge", source=make_str(u),
+                                              target=make_str(v),
+                                              id=make_str(key))
+                default = G.graph.get('edge_default', {})
+                self.add_attributes("edge", edge_element, data, default)
+                graph_element.append(edge_element)
+        else:
+            for u, v, data in G.edges(data=True):
+                edge_element = self.myElement("edge", source=make_str(u),
+                                              target=make_str(v))
+                default = G.graph.get('edge_default', {})
+                self.add_attributes("edge", edge_element, data, default)
+                graph_element.append(edge_element)
+
+    def add_graph_element(self, G):
+        """
+        Serialize graph G in GraphML to the stream.
+        """
+        if G.is_directed():
+            default_edge_type = 'directed'
+        else:
+            default_edge_type = 'undirected'
+
+        graphid = G.graph.pop('id', None)
+        if graphid is None:
+            graph_element = self.myElement("graph",
+                                           edgedefault=default_edge_type)
+        else:
+            graph_element = self.myElement("graph",
+                                           edgedefault=default_edge_type,
+                                           id=graphid)
+        default = {}
+        data = {k: v for (k, v) in G.graph.items()
+                if k not in ['node_default', 'edge_default']}
+        self.add_attributes("graph", graph_element, data, default)
+        self.add_nodes(G, graph_element)
+        self.add_edges(G, graph_element)
+
+        # self.attributes contains a mapping from XML Objects to a list of
+        # data that needs to be added to them.
+        # We postpone processing in order to do type inference/generalization.
+        # See self.attr_type
+        for (xml_obj, data) in self.attributes.items():
+            for (k, v, scope, default) in data:
+                xml_obj.append(self.add_data(make_str(k),
+                                             self.attr_type(k, scope, v),
+                                             make_str(v), scope, default))
+        self.xml.append(graph_element)
+
+    def add_graphs(self, graph_list):
+        """ Add many graphs to this GraphML document. """
+        for G in graph_list:
+            self.add_graph_element(G)
+
+    def dump(self, stream):
+        if self.prettyprint:
+            self.indent(self.xml)
+        document = ElementTree(self.xml)
+        document.write(stream, encoding=self.encoding, xml_declaration=True)
+
+    def indent(self, elem, level=0):
+        # in-place prettyprint formatter
+        i = "\n" + level * "  "
+        if len(elem):
+            if not elem.text or not elem.text.strip():
+                elem.text = i + "  "
+            if not elem.tail or not elem.tail.strip():
+                elem.tail = i
+            for elem in elem:
+                self.indent(elem, level + 1)
+            if not elem.tail or not elem.tail.strip():
+                elem.tail = i
+        else:
+            if level and (not elem.tail or not elem.tail.strip()):
+                elem.tail = i
+
+
+class IncrementalElement(object):
+    """Wrapper for _IncrementalWriter providing an Element like interface.
+
+    This wrapper does not intend to be a complete implementation but rather to
+    deal with those calls used in GraphMLWriter.
+    """
+
+    def __init__(self, xml, prettyprint):
+        self.xml = xml
+        self.prettyprint = prettyprint
+
+    def append(self, element):
+        self.xml.write(element, pretty_print=self.prettyprint)
+
+
+class GraphMLWriterLxml(GraphMLWriter):
+    def __init__(self, path, graph=None, encoding='utf-8', prettyprint=True,
+                 infer_numeric_types=False):
+        self.myElement = lxmletree.Element
+
+        self._encoding = encoding
+        self._prettyprint = prettyprint
+        self.infer_numeric_types = infer_numeric_types
+
+        self._xml_base = lxmletree.xmlfile(path, encoding=encoding)
+        self._xml = self._xml_base.__enter__()
+        self._xml.write_declaration()
+
+        # We need to have a xml variable that support insertion. This call is
+        # used for adding the keys to the document.
+        # We will store those keys in a plain list, and then after the graph
+        # element is closed we will add them to the main graphml element.
+        self.xml = []
+        self._keys = self.xml
+        self._graphml = self._xml.element(
+            'graphml',
+            {
+                'xmlns': self.NS_GRAPHML,
+                'xmlns:xsi': self.NS_XSI,
+                'xsi:schemaLocation': self.SCHEMALOCATION
+            })
+        self._graphml.__enter__()
+        self.keys = {}
+        self.attribute_types = defaultdict(set)
+
+        if graph is not None:
+            self.add_graph_element(graph)
+
+    def add_graph_element(self, G):
+        """
+        Serialize graph G in GraphML to the stream.
+        """
+        if G.is_directed():
+            default_edge_type = 'directed'
+        else:
+            default_edge_type = 'undirected'
+
+        graphid = G.graph.pop('id', None)
+        if graphid is None:
+            graph_element = self._xml.element('graph',
+                                              edgedefault=default_edge_type)
+        else:
+            graph_element = self._xml.element('graph',
+                                              edgedefault=default_edge_type,
+                                              id=graphid)
+
+        # gather attributes types for the whole graph
+        # to find the most general numeric format needed.
+        # Then pass through attributes to create key_id for each.
+        graphdata = {k: v for k, v in G.graph.items()
+                     if k not in ('node_default', 'edge_default')}
+        node_default = G.graph.get('node_default', {})
+        edge_default = G.graph.get('edge_default', {})
+        # Graph attributes
+        for k, v in graphdata.items():
+            self.attribute_types[(make_str(k), "graph")].add(type(v))
+        for k, v in graphdata.items():
+            element_type = self.xml_type[self.attr_type(k, "graph", v)]
+            self.get_key(make_str(k), element_type, "graph", None)
+        # Nodes and data
+        for node, d in G.nodes(data=True):
+            for k, v in d.items():
+                self.attribute_types[(make_str(k), "node")].add(type(v))
+        for node, d in G.nodes(data=True):
+            for k, v in d.items():
+                T = self.xml_type[self.attr_type(k, "node", v)]
+                self.get_key(make_str(k), T, "node", node_default.get(k))
+        # Edges and data
+        if G.is_multigraph():
+            for u, v, ekey, d in G.edges(keys=True, data=True):
+                for k, v in d.items():
+                    self.attribute_types[(make_str(k), "edge")].add(type(v))
+            for u, v, ekey, d in G.edges(keys=True, data=True):
+                for k, v in d.items():
+                    T = self.xml_type[self.attr_type(k, "edge", v)]
+                    self.get_key(make_str(k), T, "edge", edge_default.get(k))
+        else:
+            for u, v, d in G.edges(data=True):
+                for k, v in d.items():
+                    self.attribute_types[(make_str(k), "edge")].add(type(v))
+            for u, v, d in G.edges(data=True):
+                for k, v in d.items():
+                    T = self.xml_type[self.attr_type(k, "edge", v)]
+                    self.get_key(make_str(k), T, "edge", edge_default.get(k))
+
+        # Now add attribute keys to the xml file
+        for key in self.xml:
+            self._xml.write(key, pretty_print=self._prettyprint)
+
+        # The incremental_writer writes each node/edge as it is created
+        incremental_writer = IncrementalElement(self._xml, self._prettyprint)
+        with graph_element:
+            self.add_attributes('graph', incremental_writer, graphdata, {})
+            self.add_nodes(G, incremental_writer)  # adds attributes too
+            self.add_edges(G, incremental_writer)  # adds attributes too
+
+    def add_attributes(self, scope, xml_obj, data, default):
+        """Appends attribute data."""
+        for k, v in data.items():
+            data_element = self.add_data(make_str(k),
+                                         self.attr_type(make_str(k), scope, v),
+                                         make_str(v), scope, default.get(k))
+            xml_obj.append(data_element)
+
+    def __str__(self):
+        return object.__str__(self)
+
+    def dump(self):
+        self._graphml.__exit__(None, None, None)
+        self._xml_base.__exit__(None, None, None)
+
+
+# Choose a writer function for default
+if lxmletree is None:
+    write_graphml = write_graphml_xml
+else:
+    write_graphml = write_graphml_lxml
+
+
+class GraphMLReader(GraphML):
+    """Read a GraphML document.  Produces NetworkX graph objects."""
+
+    def __init__(self, node_type=str, edge_key_type=int):
+        try:
+            import xml.etree.ElementTree
+        except ImportError:
+            msg = 'GraphML reader requires xml.elementtree.ElementTree'
+            raise ImportError(msg)
+        self.node_type = node_type
+        self.edge_key_type = edge_key_type
+        self.multigraph = False  # assume multigraph and test for multiedges
+        self.edge_ids = {}  # dict mapping (u,v) tuples to id edge attributes
+
+    def __call__(self, path=None, string=None):
+        if path is not None:
+            self.xml = ElementTree(file=path)
+        elif string is not None:
+            self.xml = fromstring(string)
+        else:
+            raise ValueError("Must specify either 'path' or 'string' as kwarg")
+        (keys, defaults) = self.find_graphml_keys(self.xml)
+        for g in self.xml.findall("{%s}graph" % self.NS_GRAPHML):
+            yield self.make_graph(g, keys, defaults)
+
+    def make_graph(self, graph_xml, graphml_keys, defaults, G=None):
+        # set default graph type
+        edgedefault = graph_xml.get("edgedefault", None)
+        if G is None:
+            if edgedefault == 'directed':
+                G = nx.MultiDiGraph()
+            else:
+                G = nx.MultiGraph()
+        # set defaults for graph attributes
+        G.graph['node_default'] = {}
+        G.graph['edge_default'] = {}
+        for key_id, value in defaults.items():
+            key_for = graphml_keys[key_id]['for']
+            name = graphml_keys[key_id]['name']
+            python_type = graphml_keys[key_id]['type']
+            if key_for == 'node':
+                G.graph['node_default'].update({name: python_type(value)})
+            if key_for == 'edge':
+                G.graph['edge_default'].update({name: python_type(value)})
+        # hyperedges are not supported
+        hyperedge = graph_xml.find("{%s}hyperedge" % self.NS_GRAPHML)
+        if hyperedge is not None:
+            raise nx.NetworkXError("GraphML reader doesn't support hyperedges")
+        # add nodes
+        for node_xml in graph_xml.findall("{%s}node" % self.NS_GRAPHML):
+            self.add_node(G, node_xml, graphml_keys, defaults)
+        # add edges
+        for edge_xml in graph_xml.findall("{%s}edge" % self.NS_GRAPHML):
+            self.add_edge(G, edge_xml, graphml_keys)
+        # add graph data
+        data = self.decode_data_elements(graphml_keys, graph_xml)
+        G.graph.update(data)
+
+        # switch to Graph or DiGraph if no parallel edges were found.
+        if not self.multigraph:
+            if G.is_directed():
+                G = nx.DiGraph(G)
+            else:
+                G = nx.Graph(G)
+            nx.set_edge_attributes(G, values=self.edge_ids, name='id')
+
+        return G
+
+    def add_node(self, G, node_xml, graphml_keys, defaults):
+        """Add a node to the graph.
+        """
+        # warn on finding unsupported ports tag
+        ports = node_xml.find("{%s}port" % self.NS_GRAPHML)
+        if ports is not None:
+            warnings.warn("GraphML port tag not supported.")
+        # find the node by id and cast it to the appropriate type
+        node_id = self.node_type(node_xml.get("id"))
+        # get data/attributes for node
+        data = self.decode_data_elements(graphml_keys, node_xml)
+        G.add_node(node_id, **data)
+        # get child nodes
+        if node_xml.attrib.get('yfiles.foldertype') == 'group':
+            graph_xml = node_xml.find("{%s}graph" % self.NS_GRAPHML)
+            self.make_graph(graph_xml, graphml_keys, defaults, G)
+
+    def add_edge(self, G, edge_element, graphml_keys):
+        """Add an edge to the graph.
+        """
+        # warn on finding unsupported ports tag
+        ports = edge_element.find("{%s}port" % self.NS_GRAPHML)
+        if ports is not None:
+            warnings.warn("GraphML port tag not supported.")
+
+        # raise error if we find mixed directed and undirected edges
+        directed = edge_element.get("directed")
+        if G.is_directed() and directed == 'false':
+            msg = "directed=false edge found in directed graph."
+            raise nx.NetworkXError(msg)
+        if (not G.is_directed()) and directed == 'true':
+            msg = "directed=true edge found in undirected graph."
+            raise nx.NetworkXError(msg)
+
+        source = self.node_type(edge_element.get("source"))
+        target = self.node_type(edge_element.get("target"))
+        data = self.decode_data_elements(graphml_keys, edge_element)
+        # GraphML stores edge ids as an attribute
+        # NetworkX uses them as keys in multigraphs too if no key
+        # attribute is specified
+        edge_id = edge_element.get("id")
+        if edge_id:
+            # self.edge_ids is used by `make_graph` method for non-multigraphs
+            self.edge_ids[source, target] = edge_id
+            try:
+                edge_id = self.edge_key_type(edge_id)
+            except ValueError:  # Could not convert.
+                pass
+        else:
+            edge_id = data.get('key')
+
+        if G.has_edge(source, target):
+            # mark this as a multigraph
+            self.multigraph = True
+
+        # Use add_edges_from to avoid error with add_edge when `'key' in data`
+        G.add_edges_from([(source, target, edge_id, data)])
+
+    def decode_data_elements(self, graphml_keys, obj_xml):
+        """Use the key information to decode the data XML if present."""
+        data = {}
+        for data_element in obj_xml.findall("{%s}data" % self.NS_GRAPHML):
+            key = data_element.get("key")
+            try:
+                data_name = graphml_keys[key]['name']
+                data_type = graphml_keys[key]['type']
+            except KeyError:
+                raise nx.NetworkXError("Bad GraphML data: no key %s" % key)
+            text = data_element.text
+            # assume anything with subelements is a yfiles extension
+            if text is not None and len(list(data_element)) == 0:
+                if data_type == bool:
+                    # Ignore cases.
+                    # http://docs.oracle.com/javase/6/docs/api/java/lang/
+                    # Boolean.html#parseBoolean%28java.lang.String%29
+                    data[data_name] = self.convert_bool[text.lower()]
+                else:
+                    data[data_name] = data_type(text)
+            elif len(list(data_element)) > 0:
+                # Assume yfiles as subelements, try to extract node_label
+                node_label = None
+                for node_type in ['ShapeNode', 'SVGNode', 'ImageNode']:
+                    pref = "{%s}%s/{%s}" % (self.NS_Y, node_type, self.NS_Y)
+                    geometry = data_element.find("%sGeometry" % pref)
+                    if geometry is not None:
+                        data['x'] = geometry.get('x')
+                        data['y'] = geometry.get('y')
+                    if node_label is None:
+                        node_label = data_element.find("%sNodeLabel" % pref)
+                if node_label is not None:
+                    data['label'] = node_label.text
+
+                # check all the different types of edges avaivable in yEd.
+                for e in ['PolyLineEdge', 'SplineEdge', 'QuadCurveEdge',
+                          'BezierEdge', 'ArcEdge']:
+                    pref = "{%s}%s/{%s}" % (self.NS_Y, e, self.NS_Y)
+                    edge_label = data_element.find("%sEdgeLabel" % pref)
+                    if edge_label is not None:
+                        break
+
+                if edge_label is not None:
+                    data['label'] = edge_label.text
+        return data
+
+    def find_graphml_keys(self, graph_element):
+        """Extracts all the keys and key defaults from the xml.
+        """
+        graphml_keys = {}
+        graphml_key_defaults = {}
+        for k in graph_element.findall("{%s}key" % self.NS_GRAPHML):
+            attr_id = k.get("id")
+            attr_type = k.get('attr.type')
+            attr_name = k.get("attr.name")
+            yfiles_type = k.get("yfiles.type")
+            if yfiles_type is not None:
+                attr_name = yfiles_type
+                attr_type = 'yfiles'
+            if attr_type is None:
+                attr_type = "string"
+                warnings.warn("No key type for id %s. Using string" % attr_id)
+            if attr_name is None:
+                raise nx.NetworkXError("Unknown key for id %s." % attr_id)
+            graphml_keys[attr_id] = {"name": attr_name,
+                                     "type": self.python_type[attr_type],
+                                     "for": k.get("for")}
+            # check for "default" subelement of key element
+            default = k.find("{%s}default" % self.NS_GRAPHML)
+            if default is not None:
+                graphml_key_defaults[attr_id] = default.text
+        return graphml_keys, graphml_key_defaults
+
+
+# fixture for pytest
+def setup_module(module):
+    import pytest
+    xml.etree.ElementTree = pytest.importorskip('xml.etree.ElementTree')
+
+
+# fixture for pytest
+def teardown_module(module):
+    import os
+    try:
+        os.unlink('test.graphml')
+    except:
+        pass