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<li class="toctree-l1"><a class="reference internal" href="../introduction.html">Introduction</a></li>
<li class="toctree-l1 current active has-children"><a class="current reference internal" href="#">Graph types</a><input checked="" class="toctree-checkbox" id="toctree-checkbox-1" name="toctree-checkbox-1" type="checkbox"/><label class="toctree-toggle" for="toctree-checkbox-1"><i class="fa-solid fa-chevron-down"></i></label><ul>
<li class="toctree-l2"><a class="reference internal" href="graph.html">Graph—Undirected graphs with self loops</a></li>
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<li class="toctree-l2"><a class="reference internal" href="generated/networkx.classes.graphviews.generic_graph_view.html">generic_graph_view</a></li>
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<li class="toctree-l2"><a class="reference internal" href="generated/networkx.classes.coreviews.FilterMultiInner.html">networkx.classes.coreviews.FilterMultiInner</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/networkx.classes.coreviews.FilterMultiAdjacency.html">networkx.classes.coreviews.FilterMultiAdjacency</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/networkx.classes.filters.no_filter.html">no_filter</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/networkx.classes.filters.hide_nodes.html">hide_nodes</a></li>
<li class="toctree-l2"><a class="reference internal" href="generated/networkx.classes.filters.hide_edges.html">hide_edges</a></li>
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<article class="bd-article" role="main">
<section id="graph-types">
<span id="classes"></span><h1>Graph types<a class="headerlink" href="#graph-types" title="Permalink to this heading">#</a></h1>
<p>NetworkX provides data structures and methods for storing graphs.</p>
<p>All NetworkX graph classes allow (hashable) Python objects as nodes
and any Python object can be assigned as an edge attribute.</p>
<p>The choice of graph class depends on the structure of the
graph you want to represent.</p>
<section id="which-graph-class-should-i-use">
<h2>Which graph class should I use?<a class="headerlink" href="#which-graph-class-should-i-use" title="Permalink to this heading">#</a></h2>
<table class="table">
<thead>
<tr class="row-odd"><th class="head"><p>Networkx Class</p></th>
<th class="head"><p>Type</p></th>
<th class="head"><p>Self-loops allowed</p></th>
<th class="head"><p>Parallel edges allowed</p></th>
</tr>
</thead>
<tbody>
<tr class="row-even"><td><p>Graph</p></td>
<td><p>undirected</p></td>
<td><p>Yes</p></td>
<td><p>No</p></td>
</tr>
<tr class="row-odd"><td><p>DiGraph</p></td>
<td><p>directed</p></td>
<td><p>Yes</p></td>
<td><p>No</p></td>
</tr>
<tr class="row-even"><td><p>MultiGraph</p></td>
<td><p>undirected</p></td>
<td><p>Yes</p></td>
<td><p>Yes</p></td>
</tr>
<tr class="row-odd"><td><p>MultiDiGraph</p></td>
<td><p>directed</p></td>
<td><p>Yes</p></td>
<td><p>Yes</p></td>
</tr>
</tbody>
</table>
</section>
<section id="basic-graph-types">
<h2>Basic graph types<a class="headerlink" href="#basic-graph-types" title="Permalink to this heading">#</a></h2>
<div class="toctree-wrapper compound">
<ul>
<li class="toctree-l1"><a class="reference internal" href="graph.html">Graph—Undirected graphs with self loops</a><ul>
<li class="toctree-l2"><a class="reference internal" href="graph.html#overview">Overview</a></li>
<li class="toctree-l2"><a class="reference internal" href="graph.html#methods">Methods</a></li>
</ul>
</li>
<li class="toctree-l1"><a class="reference internal" href="digraph.html">DiGraph—Directed graphs with self loops</a><ul>
<li class="toctree-l2"><a class="reference internal" href="digraph.html#overview">Overview</a></li>
<li class="toctree-l2"><a class="reference internal" href="digraph.html#methods">Methods</a></li>
</ul>
</li>
<li class="toctree-l1"><a class="reference internal" href="multigraph.html">MultiGraph—Undirected graphs with self loops and parallel edges</a><ul>
<li class="toctree-l2"><a class="reference internal" href="multigraph.html#overview">Overview</a></li>
<li class="toctree-l2"><a class="reference internal" href="multigraph.html#methods">Methods</a></li>
</ul>
</li>
<li class="toctree-l1"><a class="reference internal" href="multidigraph.html">MultiDiGraph—Directed graphs with self loops and parallel edges</a><ul>
<li class="toctree-l2"><a class="reference internal" href="multidigraph.html#overview">Overview</a></li>
<li class="toctree-l2"><a class="reference internal" href="multidigraph.html#methods">Methods</a></li>
</ul>
</li>
</ul>
</div>
<div class="admonition note">
<p class="admonition-title">Note</p>
<p>NetworkX uses <code class="xref py py-obj docutils literal notranslate"><span class="pre">dicts</span></code> to store the nodes and neighbors in a graph.
So the reporting of nodes and edges for the base graph classes may not
necessarily be consistent across versions and platforms; however, the reporting
for CPython is consistent across platforms and versions after 3.6.</p>
</div>
</section>
<section id="module-networkx.classes.graphviews">
<span id="graph-views"></span><h2>Graph Views<a class="headerlink" href="#module-networkx.classes.graphviews" title="Permalink to this heading">#</a></h2>
<p>View of Graphs as SubGraph, Reverse, Directed, Undirected.</p>
<p>In some algorithms it is convenient to temporarily morph
a graph to exclude some nodes or edges. It should be better
to do that via a view than to remove and then re-add.
In other algorithms it is convenient to temporarily morph
a graph to reverse directed edges, or treat a directed graph
as undirected, etc. This module provides those graph views.</p>
<p>The resulting views are essentially read-only graphs that
report data from the orignal graph object. We provide an
attribute G._graph which points to the underlying graph object.</p>
<p>Note: Since graphviews look like graphs, one can end up with
view-of-view-of-view chains. Be careful with chains because
they become very slow with about 15 nested views.
For the common simple case of node induced subgraphs created
from the graph class, we short-cut the chain by returning a
subgraph of the original graph directly rather than a subgraph
of a subgraph. We are careful not to disrupt any edge filter in
the middle subgraph. In general, determining how to short-cut
the chain is tricky and much harder with restricted_views than
with induced subgraphs.
Often it is easiest to use .copy() to avoid chains.</p>
<table class="autosummary longtable table autosummary">
<tbody>
<tr class="row-odd"><td><p><a class="reference internal" href="generated/networkx.classes.graphviews.generic_graph_view.html#networkx.classes.graphviews.generic_graph_view" title="networkx.classes.graphviews.generic_graph_view"><code class="xref py py-obj docutils literal notranslate"><span class="pre">generic_graph_view</span></code></a>(G[, create_using])</p></td>
<td><p></p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="generated/networkx.classes.graphviews.subgraph_view.html#networkx.classes.graphviews.subgraph_view" title="networkx.classes.graphviews.subgraph_view"><code class="xref py py-obj docutils literal notranslate"><span class="pre">subgraph_view</span></code></a>(G[, filter_node, filter_edge])</p></td>
<td><p>View of <code class="xref py py-obj docutils literal notranslate"><span class="pre">G</span></code> applying a filter on nodes and edges.</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="generated/networkx.classes.graphviews.reverse_view.html#networkx.classes.graphviews.reverse_view" title="networkx.classes.graphviews.reverse_view"><code class="xref py py-obj docutils literal notranslate"><span class="pre">reverse_view</span></code></a>(G)</p></td>
<td><p>View of <code class="xref py py-obj docutils literal notranslate"><span class="pre">G</span></code> with edge directions reversed</p></td>
</tr>
</tbody>
</table>
</section>
<section id="module-networkx.classes.coreviews">
<span id="core-views"></span><h2>Core Views<a class="headerlink" href="#module-networkx.classes.coreviews" title="Permalink to this heading">#</a></h2>
<p>Views of core data structures such as nested Mappings (e.g. dict-of-dicts).
These <code class="docutils literal notranslate"><span class="pre">Views</span></code> often restrict element access, with either the entire view or
layers of nested mappings being read-only.</p>
<table class="autosummary longtable table autosummary">
<tbody>
<tr class="row-odd"><td><p><a class="reference internal" href="generated/networkx.classes.coreviews.AtlasView.html#networkx.classes.coreviews.AtlasView" title="networkx.classes.coreviews.AtlasView"><code class="xref py py-obj docutils literal notranslate"><span class="pre">AtlasView</span></code></a>(d)</p></td>
<td><p>An AtlasView is a Read-only Mapping of Mappings.</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="generated/networkx.classes.coreviews.AdjacencyView.html#networkx.classes.coreviews.AdjacencyView" title="networkx.classes.coreviews.AdjacencyView"><code class="xref py py-obj docutils literal notranslate"><span class="pre">AdjacencyView</span></code></a>(d)</p></td>
<td><p>An AdjacencyView is a Read-only Map of Maps of Maps.</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="generated/networkx.classes.coreviews.MultiAdjacencyView.html#networkx.classes.coreviews.MultiAdjacencyView" title="networkx.classes.coreviews.MultiAdjacencyView"><code class="xref py py-obj docutils literal notranslate"><span class="pre">MultiAdjacencyView</span></code></a>(d)</p></td>
<td><p>An MultiAdjacencyView is a Read-only Map of Maps of Maps of Maps.</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="generated/networkx.classes.coreviews.UnionAtlas.html#networkx.classes.coreviews.UnionAtlas" title="networkx.classes.coreviews.UnionAtlas"><code class="xref py py-obj docutils literal notranslate"><span class="pre">UnionAtlas</span></code></a>(succ, pred)</p></td>
<td><p>A read-only union of two atlases (dict-of-dict).</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="generated/networkx.classes.coreviews.UnionAdjacency.html#networkx.classes.coreviews.UnionAdjacency" title="networkx.classes.coreviews.UnionAdjacency"><code class="xref py py-obj docutils literal notranslate"><span class="pre">UnionAdjacency</span></code></a>(succ, pred)</p></td>
<td><p>A read-only union of dict Adjacencies as a Map of Maps of Maps.</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="generated/networkx.classes.coreviews.UnionMultiInner.html#networkx.classes.coreviews.UnionMultiInner" title="networkx.classes.coreviews.UnionMultiInner"><code class="xref py py-obj docutils literal notranslate"><span class="pre">UnionMultiInner</span></code></a>(succ, pred)</p></td>
<td><p>A read-only union of two inner dicts of MultiAdjacencies.</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="generated/networkx.classes.coreviews.UnionMultiAdjacency.html#networkx.classes.coreviews.UnionMultiAdjacency" title="networkx.classes.coreviews.UnionMultiAdjacency"><code class="xref py py-obj docutils literal notranslate"><span class="pre">UnionMultiAdjacency</span></code></a>(succ, pred)</p></td>
<td><p>A read-only union of two dict MultiAdjacencies.</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="generated/networkx.classes.coreviews.FilterAtlas.html#networkx.classes.coreviews.FilterAtlas" title="networkx.classes.coreviews.FilterAtlas"><code class="xref py py-obj docutils literal notranslate"><span class="pre">FilterAtlas</span></code></a>(d, NODE_OK)</p></td>
<td><p></p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="generated/networkx.classes.coreviews.FilterAdjacency.html#networkx.classes.coreviews.FilterAdjacency" title="networkx.classes.coreviews.FilterAdjacency"><code class="xref py py-obj docutils literal notranslate"><span class="pre">FilterAdjacency</span></code></a>(d, NODE_OK, EDGE_OK)</p></td>
<td><p></p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="generated/networkx.classes.coreviews.FilterMultiInner.html#networkx.classes.coreviews.FilterMultiInner" title="networkx.classes.coreviews.FilterMultiInner"><code class="xref py py-obj docutils literal notranslate"><span class="pre">FilterMultiInner</span></code></a>(d, NODE_OK, EDGE_OK)</p></td>
<td><p></p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="generated/networkx.classes.coreviews.FilterMultiAdjacency.html#networkx.classes.coreviews.FilterMultiAdjacency" title="networkx.classes.coreviews.FilterMultiAdjacency"><code class="xref py py-obj docutils literal notranslate"><span class="pre">FilterMultiAdjacency</span></code></a>(d, NODE_OK, EDGE_OK)</p></td>
<td><p></p></td>
</tr>
</tbody>
</table>
</section>
<section id="filters">
<h2>Filters<a class="headerlink" href="#filters" title="Permalink to this heading">#</a></h2>
<div class="admonition note">
<p class="admonition-title">Note</p>
<p>Filters can be used with views to restrict the view (or expand it).
They can filter nodes or filter edges. These examples are intended to help
you build new ones. They may instead contain all the filters you ever need.</p>
</div>
<span class="target" id="module-networkx.classes.filters"></span><p>Filter factories to hide or show sets of nodes and edges.</p>
<p>These filters return the function used when creating <code class="xref py py-obj docutils literal notranslate"><span class="pre">SubGraph</span></code>.</p>
<table class="autosummary longtable table autosummary">
<tbody>
<tr class="row-odd"><td><p><a class="reference internal" href="generated/networkx.classes.filters.no_filter.html#networkx.classes.filters.no_filter" title="networkx.classes.filters.no_filter"><code class="xref py py-obj docutils literal notranslate"><span class="pre">no_filter</span></code></a>(*items)</p></td>
<td><p></p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="generated/networkx.classes.filters.hide_nodes.html#networkx.classes.filters.hide_nodes" title="networkx.classes.filters.hide_nodes"><code class="xref py py-obj docutils literal notranslate"><span class="pre">hide_nodes</span></code></a>(nodes)</p></td>
<td><p></p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="generated/networkx.classes.filters.hide_edges.html#networkx.classes.filters.hide_edges" title="networkx.classes.filters.hide_edges"><code class="xref py py-obj docutils literal notranslate"><span class="pre">hide_edges</span></code></a>(edges)</p></td>
<td><p></p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="generated/networkx.classes.filters.hide_diedges.html#networkx.classes.filters.hide_diedges" title="networkx.classes.filters.hide_diedges"><code class="xref py py-obj docutils literal notranslate"><span class="pre">hide_diedges</span></code></a>(edges)</p></td>
<td><p></p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="generated/networkx.classes.filters.hide_multidiedges.html#networkx.classes.filters.hide_multidiedges" title="networkx.classes.filters.hide_multidiedges"><code class="xref py py-obj docutils literal notranslate"><span class="pre">hide_multidiedges</span></code></a>(edges)</p></td>
<td><p></p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="generated/networkx.classes.filters.hide_multiedges.html#networkx.classes.filters.hide_multiedges" title="networkx.classes.filters.hide_multiedges"><code class="xref py py-obj docutils literal notranslate"><span class="pre">hide_multiedges</span></code></a>(edges)</p></td>
<td><p></p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="generated/networkx.classes.filters.show_nodes.html#networkx.classes.filters.show_nodes" title="networkx.classes.filters.show_nodes"><code class="xref py py-obj docutils literal notranslate"><span class="pre">show_nodes</span></code></a>(nodes)</p></td>
<td><p></p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="generated/networkx.classes.filters.show_edges.html#networkx.classes.filters.show_edges" title="networkx.classes.filters.show_edges"><code class="xref py py-obj docutils literal notranslate"><span class="pre">show_edges</span></code></a>(edges)</p></td>
<td><p></p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="generated/networkx.classes.filters.show_diedges.html#networkx.classes.filters.show_diedges" title="networkx.classes.filters.show_diedges"><code class="xref py py-obj docutils literal notranslate"><span class="pre">show_diedges</span></code></a>(edges)</p></td>
<td><p></p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="generated/networkx.classes.filters.show_multidiedges.html#networkx.classes.filters.show_multidiedges" title="networkx.classes.filters.show_multidiedges"><code class="xref py py-obj docutils literal notranslate"><span class="pre">show_multidiedges</span></code></a>(edges)</p></td>
<td><p></p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="generated/networkx.classes.filters.show_multiedges.html#networkx.classes.filters.show_multiedges" title="networkx.classes.filters.show_multiedges"><code class="xref py py-obj docutils literal notranslate"><span class="pre">show_multiedges</span></code></a>(edges)</p></td>
<td><p></p></td>
</tr>
</tbody>
</table>
</section>
<section id="backends">
<h2>Backends<a class="headerlink" href="#backends" title="Permalink to this heading">#</a></h2>
<div class="admonition note">
<p class="admonition-title">Note</p>
<p>This is an experimental feature to dispatch your computations to an
alternate backend like GraphBLAS, instead of using pure Python dictionaries
for computation. Things will change and break in the future!</p>
</div>
<span class="target" id="module-networkx.classes.backends"></span><p>Code to support various backends in a plugin dispatch architecture.</p>
<section id="create-a-dispatcher">
<h3>Create a Dispatcher<a class="headerlink" href="#create-a-dispatcher" title="Permalink to this heading">#</a></h3>
<p>To be a valid plugin, a package must register an entry_point
of <code class="xref py py-obj docutils literal notranslate"><span class="pre">networkx.plugins</span></code> with a key pointing to the handler.</p>
<p>For example,
<code class="docutils literal notranslate"><span class="pre">`</span>
<span class="pre">entry_points={'networkx.plugins':</span> <span class="pre">'sparse</span> <span class="pre">=</span> <span class="pre">networkx_plugin_sparse'}</span>
<span class="pre">`</span></code></p>
<p>The plugin must create a Graph-like object which contains an attribute
<code class="xref py py-obj docutils literal notranslate"><span class="pre">__networkx_plugin__</span></code> with a value of the entry point name.</p>
<p>Continuing the example above:
<a href="#id1"><span class="problematic" id="id2">``</span></a>`
class WrappedSparse:</p>
<blockquote>
<div><p>__networkx_plugin__ = “sparse”
…</p>
</div></blockquote>
<p><a href="#id3"><span class="problematic" id="id4">``</span></a><a href="#id5"><span class="problematic" id="id6">`</span></a></p>
<p>When a dispatchable NetworkX algorithm encounters a Graph-like object
with a <code class="xref py py-obj docutils literal notranslate"><span class="pre">__networkx_plugin__</span></code> attribute, it will look for the associated
dispatch object in the entry_points, load it, and dispatch the work to it.</p>
</section>
<section id="testing">
<h3>Testing<a class="headerlink" href="#testing" title="Permalink to this heading">#</a></h3>
<p>To assist in validating the backend algorithm implementations, if an
environment variable <code class="xref py py-obj docutils literal notranslate"><span class="pre">NETWORKX_GRAPH_CONVERT</span></code> is set to a registered
plugin keys, the dispatch machinery will automatically convert regular
networkx Graphs and DiGraphs to the backend equivalent by calling
<code class="xref py py-obj docutils literal notranslate"><span class="pre"><backend</span> <span class="pre">dispatcher>.convert_from_nx(G,</span> <span class="pre">weight=weight,</span> <span class="pre">name=name)</span></code>.</p>
<p>The converted object is then passed to the backend implementation of
the algorithm. The result is then passed to
<code class="xref py py-obj docutils literal notranslate"><span class="pre"><backend</span> <span class="pre">dispatcher>.convert_to_nx(result,</span> <span class="pre">name=name)</span></code> to convert back
to a form expected by the NetworkX tests.</p>
<p>By defining <code class="xref py py-obj docutils literal notranslate"><span class="pre">convert_from_nx</span></code> and <code class="xref py py-obj docutils literal notranslate"><span class="pre">convert_to_nx</span></code> methods and setting
the environment variable, NetworkX will automatically route tests on
dispatchable algorithms to the backend, allowing the full networkx test
suite to be run against the backend implementation.</p>
<p>Example pytest invocation:
NETWORKX_GRAPH_CONVERT=sparse pytest –pyargs networkx</p>
<p>Dispatchable algorithms which are not implemented by the backend
will cause a <code class="xref py py-obj docutils literal notranslate"><span class="pre">pytest.xfail()</span></code>, giving some indication that not all
tests are working, while avoiding causing an explicit failure.</p>
<p>A special <code class="xref py py-obj docutils literal notranslate"><span class="pre">on_start_tests(items)</span></code> function may be defined by the backend.
It will be called with the list of NetworkX tests discovered. Each item
is a pytest.Node object. If the backend does not support the test, that
test can be marked as xfail.</p>
</section>
<table class="autosummary longtable table autosummary">
<tbody>
<tr class="row-odd"><td><p><a class="reference internal" href="generated/networkx.classes.backends._dispatch.html#networkx.classes.backends._dispatch" title="networkx.classes.backends._dispatch"><code class="xref py py-obj docutils literal notranslate"><span class="pre">_dispatch</span></code></a>([func, name])</p></td>
<td><p>Dispatches to a backend algorithm when the first argument is a backend graph-like object.</p></td>
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