15950659371

Committed 29 Jun 2025 02:17AM UTC coverage: 94.575% (-0.6%) from 95.201%

Build # 15950659371

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push

github

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web-flow

Commit Message

Adding quickcheck for complete graph (#1471)

* Adding quickcheck for complete graph

To verify the structural integrity of complete graph, we check the number of nodes, edges and whether all expected edges exist.

* Add ignore for files temporarily

* Address lint in test target as well

---------

Co-authored-by: Ivan Carvalho <ivancarvalho@gatech.edu>

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98.12

/src/digraph.rs

// Licensed under the Apache License, Version 2.0 (the "License"); you may
// not use this file except in compliance with the License. You may obtain
// a copy of the License at
//
//     http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS, WITHOUT
// WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the
// License for the specific language governing permissions and limitations
// under the License.

#![allow(clippy::borrow_as_ptr, clippy::redundant_closure)]

use std::cmp;
use std::cmp::Ordering;
use std::collections::BTreeMap;

use std::fs::File;
use std::io::prelude::*;
use std::io::{BufReader, BufWriter};
use std::str;

use hashbrown::hash_set::Entry;
use hashbrown::{HashMap, HashSet};

use rustworkx_core::dictmap::*;
use rustworkx_core::graph_ext::*;

use smallvec::SmallVec;

use pyo3::exceptions::PyIndexError;
use pyo3::gc::PyVisit;
use pyo3::prelude::*;
use pyo3::types::{IntoPyDict, PyBool, PyDict, PyGenericAlias, PyList, PyString, PyTuple, PyType};
use pyo3::IntoPyObjectExt;
use pyo3::PyTraverseError;
use pyo3::Python;

use ndarray::prelude::*;
use num_traits::Zero;
use numpy::Complex64;
use numpy::PyReadonlyArray2;
use petgraph::algo;
use petgraph::graph::{EdgeIndex, NodeIndex};
use petgraph::prelude::*;
use rustworkx_core::graph_ext::contraction::can_contract;

use crate::RxPyResult;
use petgraph::visit::{
    EdgeIndexable, GraphBase, IntoEdgeReferences, IntoNodeReferences, NodeCount, NodeFiltered,
    NodeIndexable, Visitable,
};

use super::dot_utils::build_dot;
use super::iterators::{
    EdgeIndexMap, EdgeIndices, EdgeList, NodeIndices, NodeMap, WeightedEdgeList,
};
use super::{
    find_node_by_weight, weight_callable, DAGHasCycle, DAGWouldCycle, IsNan, NoEdgeBetweenNodes,
    NoSuitableNeighbors, NodesRemoved, StablePyGraph,
};
use foldhash::fast::RandomState;
use indexmap::IndexSet;

use super::dag_algo::is_directed_acyclic_graph;

/// A class for creating directed graphs
///
/// The ``PyDiGraph`` class is used to create a directed graph. It can be a
/// multigraph (have multiple edges between nodes). Each node and edge
/// (although rarely used for edges) is indexed by an integer id. These ids
/// are stable for the lifetime of the graph object and on node or edge
/// deletions you can have holes in the list of indices for the graph.
/// Node indices will be reused on additions after removal. For example:
///
/// .. jupyter-execute::
///
///        import rustworkx as rx
///
///        graph = rx.PyDiGraph()
///        graph.add_nodes_from(list(range(5)))
///        graph.add_nodes_from(list(range(2)))
///        graph.remove_node(2)
///        print("After deletion:", graph.node_indices())
///        res_manual = graph.add_parent(6, None, None)
///        print("After adding a new node:", graph.node_indices())
///
/// Additionally, each node and edge contains an arbitrary Python object as a
/// weight/data payload. You can use the index for access to the data payload
/// as in the following example:
///
/// .. jupyter-execute::
///
///     import rustworkx as rx
///
///     graph = rx.PyDiGraph()
///     data_payload = "An arbitrary Python object"
///     node_index = graph.add_node(data_payload)
///     print("Node Index: %s" % node_index)
///     print(graph[node_index])
///
/// The PyDiGraph implements the Python mapping protocol for nodes so in
/// addition to access you can also update the data payload with:
///
/// .. jupyter-execute::
///
///     import rustworkx as rx
///
///     graph = rx.PyDiGraph()
///     data_payload = "An arbitrary Python object"
///     node_index = graph.add_node(data_payload)
///     graph[node_index] = "New Payload"
///     print("Node Index: %s" % node_index)
///     print(graph[node_index])
///
/// The PyDiGraph class has an option for real time cycle checking which can
/// be used to ensure any edges added to the graph does not introduce a cycle.
/// By default the real time cycle checking feature is disabled for performance,
/// however you can enable it by setting the ``check_cycle`` attribute to True.
/// For example::
///
///     import rustworkx as rx
///     dag = rx.PyDiGraph()
///     dag.check_cycle = True
///
/// or at object creation::
///
///     import rustworkx as rx
///     dag = rx.PyDiGraph(check_cycle=True)
///
/// With check_cycle set to true any calls to :meth:`PyDiGraph.add_edge` will
/// ensure that no cycles are added, ensuring that the PyDiGraph class truly
/// represents a directed acyclic graph. Do note that this cycle checking on
/// :meth:`~PyDiGraph.add_edge`, :meth:`~PyDiGraph.add_edges_from`,
/// :meth:`~PyDiGraph.add_edges_from_no_data`,
/// :meth:`~PyDiGraph.extend_from_edge_list`,  and
/// :meth:`~PyDiGraph.extend_from_weighted_edge_list` comes with a performance
/// penalty that grows as the graph does. If you're adding a node and edge at
/// the same time leveraging :meth:`PyDiGraph.add_child` or
/// :meth:`PyDiGraph.add_parent` will avoid this overhead.
///
/// By default a ``PyDiGraph`` is a multigraph (meaning there can be parallel
/// edges between nodes) however this can be disabled by setting the
/// ``multigraph`` kwarg to ``False`` when calling the ``PyDiGraph``
/// constructor. For example::
///
///     import rustworkx as rx
///     graph = rx.PyDiGraph(multigraph=False)
///
/// This can only be set at ``PyDiGraph`` initialization and not adjusted after
/// creation. When :attr:`~rustworkx.PyDiGraph.multigraph` is set to ``False``
/// if a method call is made that would add a parallel edge it will instead
/// update the existing edge's weight/data payload.
///
/// Each ``PyDiGraph`` object has an :attr:`~.PyDiGraph.attrs` attribute which is
/// used to contain additional attributes/metadata of the graph instance. By
/// default this is set to ``None`` but can optionally be specified by using the
/// ``attrs`` keyword argument when constructing a new graph::
///
///     graph = rustworkx.PyDiGraph(attrs=dict(source_path='/tmp/graph.csv'))
///
/// This attribute can be set to any Python object. Additionally, you can access
/// and modify this attribute after creating an object. For example::
///
///     source_path = graph.attrs
///     graph.attrs = {'new_path': '/tmp/new.csv', 'old_path': source_path}
///
/// The maximum number of nodes and edges allowed on a ``PyGraph`` object is
/// :math:`2^{32} - 1` (4,294,967,294) each. Attempting to add more nodes or
/// edges than this will result in an exception being raised.
///
/// :param bool check_cycle: When this is set to ``True`` the created
///     ``PyDiGraph`` has runtime cycle detection enabled.
/// :param bool multigraph: When this is set to ``False`` the created
///     ``PyDiGraph`` object will not be a multigraph. When ``False`` if a
///     method call is made that would add parallel edges the weight/weight
///     from that method call will be used to update the existing edge in place.
/// :param attrs: An optional attributes payload to assign to the
///     :attr:`~.PyDiGraph.attrs` attribute. This can be any Python object. If
///     it is not specified :attr:`~.PyDiGraph.attrs` will be set to ``None``.
/// :param int node_count_hint: An optional hint that will allocate with enough capacity to store this
///     many nodes before needing to grow.  This does not prepopulate any nodes with data, it is
///     only a potential performance optimization if the complete size of the graph is known in
///     advance.
/// :param int edge_count_hint: An optional hint that will allocate enough capacity to store this
///     many edges before needing to grow.  This does not prepopulate any edges with data, it is
///     only a potential performance optimization if the complete size of the graph is known in
///     advance.
#[pyclass(mapping, module = "rustworkx", subclass)]
#[derive(Clone)]
pub struct PyDiGraph {
    pub graph: StablePyGraph<Directed>,
    pub cycle_state: algo::DfsSpace<NodeIndex, <StablePyGraph<Directed> as Visitable>::Map>,
    pub check_cycle: bool,
    pub node_removed: bool,
    pub multigraph: bool,
    #[pyo3(get, set)]
    pub attrs: PyObject,
}

impl GraphBase for PyDiGraph {
    type NodeId = NodeIndex;
    type EdgeId = EdgeIndex;
}

impl NodesRemoved for &PyDiGraph {
    fn nodes_removed(&self) -> bool {
        self.node_removed
    }
}

impl NodeCount for PyDiGraph {
    fn node_count(&self) -> usize {
        self.graph.node_count()
    }
}

// Rust side only PyDiGraph methods
impl PyDiGraph {
    fn add_edge_no_cycle_check(
        &mut self,
        p_index: NodeIndex,
        c_index: NodeIndex,
        edge: PyObject,
    ) -> usize {
        if !self.multigraph {
            let exists = self.graph.find_edge(p_index, c_index);
            if let Some(index) = exists {
                let edge_weight = self.graph.edge_weight_mut(index).unwrap();
                *edge_weight = edge;
                return index.index();
            }
        }
        let edge = self.graph.add_edge(p_index, c_index, edge);
        edge.index()
    }

    fn _add_edge(
        &mut self,
        p_index: NodeIndex,
        c_index: NodeIndex,
        edge: PyObject,
    ) -> PyResult<usize> {
        // Only check for cycles if instance attribute is set to true
        if self.check_cycle {
            // Only check for a cycle (by running has_path_connecting) if
            // the new edge could potentially add a cycle
            let cycle_check_required = is_cycle_check_required(self, p_index, c_index);
            let state = Some(&mut self.cycle_state);
            if cycle_check_required
                && algo::has_path_connecting(&self.graph, c_index, p_index, state)
            {
                return Err(DAGWouldCycle::new_err("Adding an edge would cycle"));
            }
        }
        Ok(self.add_edge_no_cycle_check(p_index, c_index, edge))
    }

    fn insert_between(
        &mut self,
        py: Python,
        node: usize,
        node_between: usize,
        direction: bool,
    ) -> PyResult<()> {
        let dir = if direction {
            petgraph::Direction::Outgoing
        } else {
            petgraph::Direction::Incoming
        };
        let index = NodeIndex::new(node);
        let node_between_index = NodeIndex::new(node_between);
        let edges: Vec<(NodeIndex, EdgeIndex, PyObject)> = self
            .graph
            .edges_directed(node_between_index, dir)
            .map(|edge| {
                if direction {
                    (edge.target(), edge.id(), edge.weight().clone_ref(py))
                } else {
                    (edge.source(), edge.id(), edge.weight().clone_ref(py))
                }
            })
            .collect::<Vec<(NodeIndex, EdgeIndex, PyObject)>>();
        for (other_index, edge_index, weight) in edges {
            if direction {
                self._add_edge(node_between_index, index, weight.clone_ref(py))?;
                self._add_edge(index, other_index, weight.clone_ref(py))?;
            } else {
                self._add_edge(other_index, index, weight.clone_ref(py))?;
                self._add_edge(index, node_between_index, weight.clone_ref(py))?;
            }
            self.graph.remove_edge(edge_index);
        }
        Ok(())
    }
}

#[pymethods]
impl PyDiGraph {
    #[new]
    #[pyo3(signature=(/, check_cycle=false, multigraph=true, attrs=None, *, node_count_hint=None, edge_count_hint=None))]
    fn new(
        py: Python,
        check_cycle: bool,
        multigraph: bool,
        attrs: Option<PyObject>,
        node_count_hint: Option<usize>,
        edge_count_hint: Option<usize>,
    ) -> Self {
        PyDiGraph {
            graph: StablePyGraph::<Directed>::with_capacity(
                node_count_hint.unwrap_or_default(),
                edge_count_hint.unwrap_or_default(),
            ),
            cycle_state: algo::DfsSpace::default(),
            check_cycle,
            node_removed: false,
            multigraph,
            attrs: attrs.unwrap_or_else(|| py.None()),
        }
    }

    fn __getnewargs_ex__<'py>(
        &self,
        py: Python<'py>,
    ) -> PyResult<(Bound<'py, PyTuple>, Bound<'py, PyDict>)> {
        Ok((
            (self.check_cycle, self.multigraph, self.attrs.clone_ref(py)).into_pyobject(py)?,
            [
                ("node_count_hint", self.graph.node_bound()),
                ("edge_count_hint", self.graph.edge_bound()),
            ]
            .into_py_dict(py)?,
        ))
    }

    fn __getstate__(&self, py: Python) -> PyResult<PyObject> {
        let mut nodes: Vec<PyObject> = Vec::with_capacity(self.graph.node_bound());
        let mut edges: Vec<PyObject> = Vec::with_capacity(self.graph.edge_bound());

        // save nodes to a list along with its index
        for node_idx in self.graph.node_indices() {
            let node_data = self.graph.node_weight(node_idx).unwrap();
            nodes.push((node_idx.index(), node_data).into_py_any(py)?);
        }

        // edges are saved with none (deleted edges) instead of their index to save space
        for i in 0..self.graph.edge_bound() {
            let idx = EdgeIndex::new(i);
            let edge = match self.graph.edge_weight(idx) {
                Some(edge_w) => {
                    let endpoints = self.graph.edge_endpoints(idx).unwrap();
                    (endpoints.0.index(), endpoints.1.index(), edge_w).into_py_any(py)?
                }
                None => py.None(),
            };
            edges.push(edge);
        }
        let out_dict = PyDict::new(py);
        let nodes_lst = PyList::new(py, nodes)?;
        let edges_lst = PyList::new(py, edges)?;
        out_dict.set_item("nodes", nodes_lst)?;
        out_dict.set_item("edges", edges_lst)?;
        out_dict.set_item("nodes_removed", self.node_removed)?;
        Ok(out_dict.into())
    }

    fn __setstate__(&mut self, py: Python, state: PyObject) -> PyResult<()> {
        let dict_state = state.downcast_bound::<PyDict>(py)?;
        let binding = dict_state.get_item("nodes")?.unwrap();
        let nodes_lst = binding.downcast::<PyList>()?;
        let binding = dict_state.get_item("edges")?.unwrap();
        let edges_lst = binding.downcast::<PyList>()?;
        self.graph = StablePyGraph::<Directed>::new();
        let dict_state = state.downcast_bound::<PyDict>(py)?;
        self.node_removed = dict_state
            .get_item("nodes_removed")?
            .unwrap()
            .downcast::<PyBool>()?
            .extract()?;

        // graph is empty, stop early
        if nodes_lst.is_empty() {
            return Ok(());
        }

        if !self.node_removed {
            for item in nodes_lst.iter() {
                let node_w = item
                    .downcast::<PyTuple>()
                    .unwrap()
                    .get_item(1)
                    .unwrap()
                    .extract()
                    .unwrap();
                self.graph.add_node(node_w);
            }
        } else if nodes_lst.len() == 1 {
            // graph has only one node, handle logic here to save one if in the loop later
            let binding = nodes_lst.get_item(0).unwrap();
            let item = binding.downcast::<PyTuple>().unwrap();
            let node_idx: usize = item.get_item(0).unwrap().extract().unwrap();
            let node_w = item.get_item(1).unwrap().extract().unwrap();

            for _i in 0..node_idx {
                self.graph.add_node(py.None());
            }
            self.graph.add_node(node_w);
            for i in 0..node_idx {
                self.graph.remove_node(NodeIndex::new(i));
            }
        } else {
            let binding = nodes_lst.get_item(nodes_lst.len() - 1).unwrap();
            let last_item = binding.downcast::<PyTuple>().unwrap();

            // list of temporary nodes that will be removed later to re-create holes
            let node_bound_1: usize = last_item.get_item(0).unwrap().extract().unwrap();
            let mut tmp_nodes: Vec<NodeIndex> =
                Vec::with_capacity(node_bound_1 + 1 - nodes_lst.len());

            for item in nodes_lst {
                let item = item.downcast::<PyTuple>().unwrap();
                let next_index: usize = item.get_item(0).unwrap().extract().unwrap();
                let weight: PyObject = item.get_item(1).unwrap().extract().unwrap();
                while next_index > self.graph.node_bound() {
                    // node does not exist
                    let tmp_node = self.graph.add_node(py.None());
                    tmp_nodes.push(tmp_node);
                }
                // add node to the graph, and update the next available node index
                self.graph.add_node(weight);
            }
            // Remove any temporary nodes we added
            for tmp_node in tmp_nodes {
                self.graph.remove_node(tmp_node);
            }
        }

        // to ensure O(1) on edge deletion, use a temporary node to store missing edges
        let tmp_node = self.graph.add_node(py.None());

        for item in edges_lst {
            if item.is_none() {
                // add a temporary edge that will be deleted later to re-create the hole
                self.graph.add_edge(tmp_node, tmp_node, py.None());
            } else {
                let triple = item.downcast::<PyTuple>().unwrap();
                let edge_p: usize = triple.get_item(0).unwrap().extract().unwrap();
                let edge_c: usize = triple.get_item(1).unwrap().extract().unwrap();
                let edge_w = triple.get_item(2).unwrap().extract().unwrap();
                self.graph
                    .add_edge(NodeIndex::new(edge_p), NodeIndex::new(edge_c), edge_w);
            }
        }

        // remove the temporary node will remove all deleted edges in bulk,
        // the cost is equal to the number of edges
        self.graph.remove_node(tmp_node);

        Ok(())
    }

    /// Whether cycle checking is enabled for the DiGraph/DAG.
    ///
    /// If set to ``True`` adding new edges that would introduce a cycle
    /// will raise a :class:`DAGWouldCycle` exception.
    #[getter]
    fn get_check_cycle(&self) -> bool {
        self.check_cycle
    }

    #[setter]
    fn set_check_cycle(&mut self, value: bool) -> PyResult<()> {
        if !self.check_cycle && value && !is_directed_acyclic_graph(self) {
            return Err(DAGHasCycle::new_err("PyDiGraph object has a cycle"));
        }
        self.check_cycle = value;
        Ok(())
    }

    /// Whether the graph is a multigraph (allows multiple edges between
    /// nodes) or not
    ///
    /// If set to ``False`` multiple edges between nodes are not allowed and
    /// calls that would add a parallel edge will instead update the existing
    /// edge
    #[getter]
    fn multigraph(&self) -> bool {
        self.multigraph
    }

    /// Detect if the graph has parallel edges or not
    ///
    /// :returns: ``True`` if the graph has parallel edges, otherwise ``False``
    /// :rtype: bool
    #[pyo3(text_signature = "(self)")]
    fn has_parallel_edges(&self) -> bool {
        if !self.multigraph {
            return false;
        }
        self.graph.has_parallel_edges()
    }

    /// Clear all nodes and edges
    #[pyo3(text_signature = "(self)")]
    pub fn clear(&mut self) {
        self.graph.clear();
        self.node_removed = true;
    }

    /// Clears all edges, leaves nodes intact
    #[pyo3(text_signature = "(self)")]
    pub fn clear_edges(&mut self) {
        self.graph.clear_edges();
    }

    /// Return the number of nodes in the graph
    #[pyo3(text_signature = "(self)")]
    pub fn num_nodes(&self) -> usize {
        self.graph.node_count()
    }

    /// Return the number of edges in the graph
    #[pyo3(text_signature = "(self)")]
    pub fn num_edges(&self) -> usize {
        self.graph.edge_count()
    }

    /// Return a list of all edge data.
    ///
    /// :returns: A list of all the edge data objects in the graph
    /// :rtype: list[T]
    #[pyo3(text_signature = "(self)")]
    pub fn edges(&self) -> Vec<&PyObject> {
        self.graph
            .edge_indices()
            .map(|edge| self.graph.edge_weight(edge).unwrap())
            .collect()
    }

    /// Return a list of all edge indices.
    ///
    /// :returns: A list of all the edge indices in the graph
    /// :rtype: EdgeIndices
    #[pyo3(text_signature = "(self)")]
    pub fn edge_indices(&self) -> EdgeIndices {
        EdgeIndices {
            edges: self.graph.edge_indices().map(|edge| edge.index()).collect(),
        }
    }

    /// Return a list of indices of all directed edges between specified nodes
    ///
    /// :param int node_a: The index of the first node
    /// :param int node_b: The index of the second node
    ///
    /// :returns: A list of all the edge indices connecting the specified start and end node
    /// :rtype: EdgeIndices
    pub fn edge_indices_from_endpoints(&self, node_a: usize, node_b: usize) -> EdgeIndices {
        let node_a_index = NodeIndex::new(node_a);
        let node_b_index = NodeIndex::new(node_b);

        EdgeIndices {
            edges: self
                .graph
                .edges_directed(node_a_index, petgraph::Direction::Outgoing)
                .filter(|edge| edge.target() == node_b_index)
                .map(|edge| edge.id().index())
                .collect(),
        }
    }

    /// Return a list of all node data.
    ///
    /// :returns: A list of all the node data objects in the graph
    /// :rtype: list[S]
    #[pyo3(text_signature = "(self)")]
    pub fn nodes(&self) -> Vec<&PyObject> {
        self.graph
            .node_indices()
            .map(|node| self.graph.node_weight(node).unwrap())
            .collect()
    }

    /// Return a list of all node indices.
    ///
    /// :returns: A list of all the node indices in the graph
    /// :rtype: NodeIndices
    #[pyo3(text_signature = "(self)")]
    pub fn node_indices(&self) -> NodeIndices {
        NodeIndices {
            nodes: self.graph.node_indices().map(|node| node.index()).collect(),
        }
    }

    /// Return a list of all node indices.
    ///
    /// .. note::
    ///
    ///     This is identical to :meth:`.node_indices()`, which is the
    ///     preferred method to get the node indices in the graph. This
    ///     exists for backwards compatibility with earlier releases.
    ///
    /// :returns: A list of all the node indices in the graph
    /// :rtype: NodeIndices
    #[pyo3(text_signature = "(self)")]
    pub fn node_indexes(&self) -> NodeIndices {
        self.node_indices()
    }

    /// Check if the node exists in the graph.
    ///
    /// :param int node: The node index to check
    ///
    /// :returns: ``True`` if the node exists, ``False`` otherwise
    /// :rtype: bool
    #[pyo3(text_signature = "(self, node, /)")]
    pub fn has_node(&self, node: usize) -> bool {
        let index = NodeIndex::new(node);
        self.graph.contains_node(index)
    }

    /// Check if there is a directed edge from ``node_a`` to ``node_b``.
    ///
    /// :param int node_a: The index of the source node
    /// :param int node_b: The index of the destination node
    ///
    /// :returns: ``True`` if the edge exists, ``False`` otherwise
    /// :rtype: bool
    #[pyo3(text_signature = "(self, node_a, node_b, /)")]
    pub fn has_edge(&self, node_a: usize, node_b: usize) -> bool {
        let index_a = NodeIndex::new(node_a);
        let index_b = NodeIndex::new(node_b);
        self.graph.find_edge(index_a, index_b).is_some()
    }

    /// Return a list of data of all node successors in a directed graph
    ///
    /// A successor is defined as a node that has a directed edge pointing
    /// from the specified node. In a multigraph, where two nodes can be connected
    /// by multiple edges, each successor node is returned only once.
    ///
    ///     >>> G = rx.PyDiGraph()
    ///     >>> G.add_nodes_from(["A", "B", "C", "D", "E"])
    ///     NodeIndices[0, 1, 2, 3, 4]
    ///     >>> G.extend_from_edge_list([(0, 1), (1, 2), (1, 3), (1, 4)])
    ///     >>> G.successors(1)  # successors of the 'B' node
    ///     ['E', 'D', 'C']
    ///     >>> G.successors(10) # successors of an non-existing node
    ///     []
    ///
    /// .. seealso ::
    ///   To filter the successors by the attributes of the connecting edge,
    ///   see :func:`~find_successors_by_edge`.
    ///
    ///   See also :func:`~predecessors` and :func:`~neighbors`.
    ///
    ///   For undirected graphs, see :func:`~PyGraph.neighbors`.
    ///
    ///   To go beyond the nearest successors, see :func:`~rustworkx.descendants`.
    ///
    /// :param int node: The index of the node to get the predecessors for
    ///
    /// :returns: A list of the node data of all node's predecessors
    /// :rtype: list[S]
    #[pyo3(text_signature = "(self, node, /)")]
    pub fn successors(&self, node: usize) -> Vec<&PyObject> {
        let index = NodeIndex::new(node);
        let children = self
            .graph
            .neighbors_directed(index, petgraph::Direction::Outgoing);
        let mut successors: Vec<&PyObject> = Vec::new();
        let mut used_indices: HashSet<NodeIndex> = HashSet::new();
        for succ in children {
            match used_indices.entry(succ) {
                Entry::Vacant(used_indices_entry) => {
                    used_indices_entry.insert();
                    successors.push(self.graph.node_weight(succ).unwrap());
                }
                Entry::Occupied(_) => {}
            }
        }
        successors
    }

    /// Return a list of data of all node predecessors in a directed graph
    ///
    /// A predecessor is defined as a node that has a directed edge pointing
    /// to the specified node. In a multigraph, where two nodes can be connected
    /// by multiple edges, each predecessor node is returned only once.
    ///
    ///     >>> G = rx.PyDiGraph()
    ///     >>> G.add_nodes_from(["A", "B", "C", "D", "E"])
    ///     NodeIndices[0, 1, 2, 3, 4]
    ///     >>> G.extend_from_edge_list([(0, 3), (1, 3), (2, 3), (3, 4)])
    ///     >>> G.predecessors(3)  # predecessors of the 'D' node
    ///     ['C', 'B', 'A']
    ///     >>> G.predecessors(10) # predecessors of an non-existing node
    ///     []
    ///
    /// .. seealso ::
    ///   To filter the predecessors by the attributes of the connecting edge,
    ///   see :func:`~find_predecessors_by_edge`.
    ///
    ///   See also :func:`~successors`.
    ///
    ///   For undirected graphs, see :func:`~PyGraph.neighbors`.
    ///
    ///   To get beyond the nearest predecessors, see :func:`~rustworkx.ancestors`.
    ///
    /// :param int node: The index of the node to get the predecessors for
    ///
    /// :returns: A list of the node data of all node's predecessors
    /// :rtype: list[S]
    #[pyo3(text_signature = "(self, node, /)")]
    pub fn predecessors(&self, node: usize) -> Vec<&PyObject> {
        let index = NodeIndex::new(node);
        let parents = self
            .graph
            .neighbors_directed(index, petgraph::Direction::Incoming);
        let mut predec: Vec<&PyObject> = Vec::new();
        let mut used_indices: HashSet<NodeIndex> = HashSet::new();
        for pred in parents {
            match used_indices.entry(pred) {
                Entry::Vacant(used_indices_entry) => {
                    used_indices_entry.insert();
                    predec.push(self.graph.node_weight(pred).unwrap());
                }
                Entry::Occupied(_) => {}
            }
        }
        predec
    }

    /// Return a list of data associated with the successors of the given node,
    /// where the edges connecting to those nodes satisfy the provided
    /// filter function.
    ///
    /// A predecessor is defined as a node that has a directed edge pointing
    /// to the specified node. This method returns all nodes where the edges
    /// match the condition.
    ///
    ///     >>> G = rx.PyDiGraph()
    ///     >>> G.add_nodes_from(["A", "B", "C", "D", "E"])
    ///     NodeIndices[0, 1, 2, 3, 4]
    ///     >>> G.extend_from_weighted_edge_list([(0, 1, 10), (1, 2, 10), (1, 3, 20), (1, 4, 30)])
    ///     >>> G.find_successors_by_edge(1, lambda x: x < 25)
    ///     ['D', 'C']
    ///
    /// To get one node only, see :func:`~find_successor_node_by_edge`.
    ///
    /// See also :func:`~find_predecessors_by_edge`.
    ///
    /// :param int node: The index of the node to get the successors for
    ///
    /// :param filter_fn: The filter function to apply on edges. It takes
    ///     in one argument, the edge data payload/weight object, and returns a
    ///     boolean whether the edge matches the conditions or not.
    ///     If any edge returns ``True``, the node will be included.
    ///
    /// :returns: A list of the node data for all the successor nodes
    ///           where at least one edge leading to it matches the filter
    /// :rtype: list[S]
    #[pyo3(text_signature = "(self, node, filter_fn, /)")]
    pub fn find_successors_by_edge(
        &self,
        py: Python,
        node: usize,
        filter_fn: PyObject,
    ) -> PyResult<Vec<&PyObject>> {
        let index = NodeIndex::new(node);
        let mut successors: Vec<&PyObject> = Vec::new();
        let mut used_indices: HashSet<NodeIndex> = HashSet::new();

        let filter_edge = |edge: &PyObject| -> PyResult<bool> {
            let res = filter_fn.call1(py, (edge,))?;
            res.extract(py)
        };

        let raw_edges = self
            .graph
            .edges_directed(index, petgraph::Direction::Outgoing);

        for edge in raw_edges {
            let succ = edge.target();
            match used_indices.entry(succ) {
                Entry::Vacant(used_indices_entry) => {
                    let edge_weight = edge.weight();
                    if filter_edge(edge_weight)? {
                        used_indices_entry.insert();
                        successors.push(self.graph.node_weight(succ).unwrap());
                    }
                }
                Entry::Occupied(_) => {}
            }
        }
        Ok(successors)
    }

    /// Return a list of data associated with the predecessors of the given node,
    /// where the edges connecting from those nodes satisfy the provided
    /// filter function.
    ///
    /// A predecessor is defined as a node that has a directed edge pointing
    /// to the specified node. This method returns all nodes where the edges
    /// match the condition.
    ///
    ///     >>> G = rx.PyDiGraph()
    ///     >>> G.add_nodes_from(["A", "B", "C", "D", "E"])
    ///     NodeIndices[0, 1, 2, 3, 4]
    ///     >>> G.extend_from_weighted_edge_list([(0, 3, 10), (1, 3, 20), (2, 3, 30), (3, 4, 10)])
    ///     >>> G.find_predecessors_by_edge(3, lambda x: x < 25)
    ///     ['B', 'A']
    ///
    /// To get one node only, see :func:`~find_predecessor_node_by_edge`.
    ///
    /// :param int node: The index of the node to get the predecessors for
    /// :param Callable filter_fn: The filter function to apply on edges. It takes
    ///     in one argument, the edge data payload/weight object, and returns a
    ///     boolean whether the edge matches the conditions or not.
    ///     If any edge returns ``True``, the node will be included.
    ///
    /// :returns: A list of the node data for all the predecessor nodes
    ///           where at least one edge leading from it matches the filter
    /// :rtype: list[S]
    #[pyo3(text_signature = "(self, node, filter_fn, /)")]
    pub fn find_predecessors_by_edge(
        &self,
        py: Python,
        node: usize,
        filter_fn: PyObject,
    ) -> PyResult<Vec<&PyObject>> {
        let index = NodeIndex::new(node);
        let mut predec: Vec<&PyObject> = Vec::new();
        let mut used_indices: HashSet<NodeIndex> = HashSet::new();

        let filter_edge = |edge: &PyObject| -> PyResult<bool> {
            let res = filter_fn.call1(py, (edge,))?;
            res.extract(py)
        };

        let raw_edges = self
            .graph
            .edges_directed(index, petgraph::Direction::Incoming);

        for edge in raw_edges {
            let pred = edge.source();
            match used_indices.entry(pred) {
                Entry::Vacant(used_indices_entry) => {
                    let edge_weight = edge.weight();
                    if filter_edge(edge_weight)? {
                        used_indices_entry.insert();
                        predec.push(self.graph.node_weight(pred).unwrap());
                    }
                }
                Entry::Occupied(_) => {}
            }
        }
        Ok(predec)
    }

    /// Return the edge data for an edge between 2 nodes.
    ///
    /// :param int node_a: The index of the first node
    /// :param int node_b: The index of the second node
    ///
    /// :returns: The data object set for the edge
    /// :rtype: S
    /// :raises NoEdgeBetweenNodes: When there is no edge between the nodes
    #[pyo3(text_signature = "(self, node_a, node_b, /)")]
    pub fn get_edge_data(&self, node_a: usize, node_b: usize) -> PyResult<&PyObject> {
        let index_a = NodeIndex::new(node_a);
        let index_b = NodeIndex::new(node_b);
        let edge_index = match self.graph.find_edge(index_a, index_b) {
            Some(edge_index) => edge_index,
            None => return Err(NoEdgeBetweenNodes::new_err("No edge found between nodes")),
        };

        let data = self.graph.edge_weight(edge_index).unwrap();
        Ok(data)
    }

    /// Return the edge data for the edge by its given index
    ///
    /// :param int edge_index: The edge index to get the data for
    ///
    /// :returns: The data object for the edge
    /// :rtype: T
    /// :raises IndexError: when there is no edge present with the provided
    ///     index
    #[pyo3(text_signature = "(self, edge_index, /)")]
    pub fn get_edge_data_by_index(&self, edge_index: usize) -> PyResult<&PyObject> {
        let data = match self.graph.edge_weight(EdgeIndex::new(edge_index)) {
            Some(data) => data,
            None => {
                return Err(PyIndexError::new_err(format!(
                    "Provided edge index {} is not present in the graph",
                    edge_index
                )));
            }
        };
        Ok(data)
    }

    /// Return the edge endpoints for the edge by its given index
    ///
    /// :param int edge_index: The edge index to get the endpoints for
    ///
    /// :returns: The endpoint tuple for the edge
    /// :rtype: tuple[int, int]
    /// :raises IndexError: when there is no edge present with the provided
    ///     index
    #[pyo3(text_signature = "(self, edge_index, /)")]
    pub fn get_edge_endpoints_by_index(&self, edge_index: usize) -> PyResult<(usize, usize)> {
        let endpoints = match self.graph.edge_endpoints(EdgeIndex::new(edge_index)) {
            Some(endpoints) => (endpoints.0.index(), endpoints.1.index()),
            None => {
                return Err(PyIndexError::new_err(format!(
                    "Provided edge index {} is not present in the graph",
                    edge_index
                )));
            }
        };
        Ok(endpoints)
    }

    /// Update an edge's weight/payload in place
    ///
    /// If there are parallel edges in the graph only one edge will be updated.
    /// if you need to update a specific edge or need to ensure all parallel
    /// edges get updated you should use
    /// :meth:`~rustworkx.PyDiGraph.update_edge_by_index` instead.
    ///
    /// :param int source: The index of the first node
    /// :param int target: The index of the second node
    ///
    /// :raises NoEdgeBetweenNodes: When there is no edge between nodes
    #[pyo3(text_signature = "(self, source, target, edge, /)")]
    pub fn update_edge(&mut self, source: usize, target: usize, edge: PyObject) -> PyResult<()> {
        let index_a = NodeIndex::new(source);
        let index_b = NodeIndex::new(target);
        let edge_index = match self.graph.find_edge(index_a, index_b) {
            Some(edge_index) => edge_index,
            None => return Err(NoEdgeBetweenNodes::new_err("No edge found between nodes")),
        };
        let data = self.graph.edge_weight_mut(edge_index).unwrap();
        *data = edge;
        Ok(())
    }

    /// Update an edge's weight/data payload in place by the edge index
    ///
    /// :param int edge_index: The index of the edge
    /// :param T edge: The python object to attach to the edge
    ///
    /// :raises IndexError: when there is no edge present with the provided
    ///     index
    #[pyo3(text_signature = "(self, edge_index, edge, /)")]
    pub fn update_edge_by_index(&mut self, edge_index: usize, edge: PyObject) -> PyResult<()> {
        match self.graph.edge_weight_mut(EdgeIndex::new(edge_index)) {
            Some(data) => *data = edge,
            None => return Err(PyIndexError::new_err("No edge found for index")),
        };
        Ok(())
    }

    /// Return the node data for a given node index
    ///
    /// :param int node: The index of the node
    ///
    /// :returns: The data object set for that node
    /// :rtype: S
    /// :raises IndexError: when an invalid node index is provided
    #[pyo3(text_signature = "(self, node, /)")]
    pub fn get_node_data(&self, node: usize) -> PyResult<&PyObject> {
        let index = NodeIndex::new(node);
        let node = match self.graph.node_weight(index) {
            Some(node) => node,
            None => return Err(PyIndexError::new_err("No node found for index")),
        };
        Ok(node)
    }

    /// Return the edge data for all the edges between 2 nodes.
    ///
    /// :param int node_a: The index of the first node
    /// :param int node_b: The index of the second node
    ///
    /// :returns: A list with all the data objects for the edges between nodes
    /// :rtype: list[T]
    /// :raises NoEdgeBetweenNodes: When there is no edge between nodes
    #[pyo3(text_signature = "(self, node_a, node_b, /)")]
    pub fn get_all_edge_data(&self, node_a: usize, node_b: usize) -> PyResult<Vec<&PyObject>> {
        let index_a = NodeIndex::new(node_a);
        let index_b = NodeIndex::new(node_b);
        let raw_edges = self
            .graph
            .edges_directed(index_a, petgraph::Direction::Outgoing);
        let out: Vec<&PyObject> = raw_edges
            .filter(|x| x.target() == index_b)
            .map(|edge| edge.weight())
            .collect();
        if out.is_empty() {
            Err(NoEdgeBetweenNodes::new_err("No edge found between nodes"))
        } else {
            Ok(out)
        }
    }

    /// Get edge list
    ///
    /// Returns a list of tuples of the form ``(source, target)`` where
    /// ``source`` and ``target`` are the node indices.
    ///
    /// :returns: An edge list without weights
    /// :rtype: EdgeList
    pub fn edge_list(&self) -> EdgeList {
        EdgeList {
            edges: self
                .graph
                .edge_references()
                .map(|edge| (edge.source().index(), edge.target().index()))
                .collect(),
        }
    }

    /// Get edge list with weights
    ///
    /// Returns a list of tuples of the form ``(source, target, weight)`` where
    /// ``source`` and ``target`` are the node indices and ``weight`` is the
    /// payload of the edge.
    ///
    /// :returns: An edge list with weights
    /// :rtype: WeightedEdgeList
    pub fn weighted_edge_list(&self, py: Python) -> WeightedEdgeList {
        WeightedEdgeList {
            edges: self
                .graph
                .edge_references()
                .map(|edge| {
                    (
                        edge.source().index(),
                        edge.target().index(),
                        edge.weight().clone_ref(py),
                    )
                })
                .collect(),
        }
    }

    /// Get an edge index map
    ///
    /// Returns a read only mapping from edge indices to the weighted edge
    /// tuple in the form: ``{0: (0, 1, "weight"), 1: (2, 3, 2.3)}``
    ///
    /// :returns: An edge index map
    /// :rtype: EdgeIndexMap
    #[pyo3(text_signature = "(self)")]
    pub fn edge_index_map(&self, py: Python) -> EdgeIndexMap {
        EdgeIndexMap {
            edge_map: self
                .graph
                .edge_references()
                .map(|edge| {
                    (
                        edge.id().index(),
                        (
                            edge.source().index(),
                            edge.target().index(),
                            edge.weight().clone_ref(py),
                        ),
                    )
                })
                .collect(),
        }
    }

    /// Remove a node from the graph.
    ///
    /// :param int node: The index of the node to remove. If the index is not
    ///     present in the graph it will be ignored and this function will have
    ///     no effect.
    #[pyo3(text_signature = "(self, node, /)")]
    pub fn remove_node(&mut self, node: usize) -> PyResult<()> {
        let index = NodeIndex::new(node);
        self.graph.remove_node(index);
        self.node_removed = true;
        Ok(())
    }

    /// Remove a node from the graph and add edges from all predecessors to all
    /// successors
    ///
    /// By default the data/weight on edges into the removed node will be used
    /// for the retained edges.
    ///
    /// This function has a minimum time complexity of :math:`\mathcal O(e_i e_o)`, where
    /// :math:`e_i` and :math:`e_o` are the numbers of incoming and outgoing edges respectively.
    /// If your ``condition`` can be cast as an equality between two hashable quantities, consider
    /// using :meth:`remove_node_retain_edges_by_key` instead, or if your ``condition`` is
    /// referential object identity of the edge weights, consider
    /// :meth:`remove_node_retain_edges_by_id`.
    ///
    /// :param int node: The index of the node to remove. If the index is not
    ///     present in the graph it will be ignored and this function will have
    ///     no effect.
    /// :param bool use_outgoing: If set to ``True`` the weight/data from the
    ///     edge outgoing from ``node`` will be used in the retained edge
    ///     instead of the default weight/data from the incoming edge.
    /// :param Callable condition: A callable that will be passed 2 edge weight/data
    ///     objects, one from the incoming edge to ``node`` the other for the
    ///     outgoing edge, and will return a ``bool`` on whether an edge should
    ///     be retained. For example setting this kwarg to::
    ///
    ///         lambda in_edge, out_edge: in_edge == out_edge
    ///
    ///     would only retain edges if the input edge to ``node`` had the same
    ///     data payload as the outgoing edge.
    #[pyo3(text_signature = "(self, node, /, use_outgoing=False, condition=None)")]
    #[pyo3(signature=(node, use_outgoing=false, condition=None))]
    pub fn remove_node_retain_edges(
        &mut self,
        py: Python,
        node: usize,
        use_outgoing: bool,
        condition: Option<PyObject>,
    ) -> PyResult<()> {
        let index = NodeIndex::new(node);
        let mut edge_list: Vec<(NodeIndex, NodeIndex, PyObject)> = Vec::new();

        fn check_condition(
            py: Python,
            condition: &Option<PyObject>,
            in_weight: &PyObject,
            out_weight: &PyObject,
        ) -> PyResult<bool> {
            match condition {
                Some(condition) => {
                    let res = condition.call1(py, (in_weight, out_weight))?;
                    Ok(res.extract(py)?)
                }
                None => Ok(true),
            }
        }

        for (source, in_weight) in self
            .graph
            .edges_directed(index, petgraph::Direction::Incoming)
            .map(|x| (x.source(), x.weight()))
        {
            for (target, out_weight) in self
                .graph
                .edges_directed(index, petgraph::Direction::Outgoing)
                .map(|x| (x.target(), x.weight()))
            {
                let weight = if use_outgoing { out_weight } else { in_weight };
                if check_condition(py, &condition, in_weight, out_weight)? {
                    edge_list.push((source, target, weight.clone_ref(py)));
                }
            }
        }
        for (source, target, weight) in edge_list {
            self._add_edge(source, target, weight)?;
        }
        self.node_removed = self.graph.remove_node(index).is_some();
        Ok(())
    }

    /// Remove a node from the graph and add edges from predecessors to successors in cases where
    /// an incoming and outgoing edge have the same weight by Python object identity.
    ///
    /// This function has a minimum time complexity of :math:`\mathcal O(e_i + e_o)`, where
    /// :math:`e_i` is the number of incoming edges and :math:`e_o` the number of outgoing edges
    /// (the full complexity depends on the number of new edges to be created).
    ///
    /// Edges will be added between all pairs of predecessor and successor nodes that have the same
    /// weight.  As a consequence, any weight which appears only on predecessor edges will not
    /// appear in the output, as there are no successors to pair it with.
    ///
    /// :param int node: The index of the node to remove. If the index is not present in the graph
    ///     it will be ignored and this function will have no effect.
    #[pyo3(signature=(node, /))]
    pub fn remove_node_retain_edges_by_id(&mut self, py: Python, node: usize) -> PyResult<()> {
        // As many indices as will fit inline within the minimum inline size of a `SmallVec`.  Many
        // use cases of this likely only have one inbound and outbound edge with each id anyway.
        const INLINE_SIZE: usize =
            2 * ::std::mem::size_of::<usize>() / ::std::mem::size_of::<NodeIndex>();
        let new_node_list = || SmallVec::<[NodeIndex; INLINE_SIZE]>::new();
        let node_index = NodeIndex::new(node);
        let in_edges = {
            let mut in_edges = HashMap::new();
            for edge in self
                .graph
                .edges_directed(node_index, petgraph::Direction::Incoming)
            {
                in_edges
                    .entry(PyAnyId(edge.weight().clone_ref(py)))
                    .or_insert_with(new_node_list)
                    .push(edge.source());
            }
            in_edges
        };
        let mut out_edges = {
            let mut out_edges = HashMap::new();
            for edge in self
                .graph
                .edges_directed(node_index, petgraph::Direction::Outgoing)
            {
                out_edges
                    .entry(PyAnyId(edge.weight().clone_ref(py)))
                    .or_insert_with(new_node_list)
                    .push(edge.target());
            }
            out_edges
        };

        for (weight, in_edges_subset) in in_edges {
            let out_edges_subset = match out_edges.remove(&weight) {
                Some(out_edges_key) => out_edges_key,
                None => continue,
            };
            for source in in_edges_subset {
                for target in out_edges_subset.iter() {
                    self._add_edge(source, *target, weight.clone_ref(py))?;
                }
            }
        }
        self.node_removed = self.graph.remove_node(node_index).is_some();
        Ok(())
    }

    /// Remove a node from the graph and add edges from predecessors to successors in cases where
    /// an incoming and outgoing edge have the same weight by Python object equality.
    ///
    /// This function has a minimum time complexity of :math:`\mathcal O(e_i + e_o)`, where
    /// :math:`e_i` is the number of incoming edges and :math:`e_o` the number of outgoing edges
    /// (the full complexity depends on the number of new edges to be created).
    ///
    /// Edges will be added between all pairs of predecessor and successor nodes that have equal
    /// weights.  As a consequence, any weight which appears only on predecessor edges will not
    /// appear in the output, as there are no successors to pair it with.
    ///
    /// If there are multiple edges with the same weight, the exact Python object used on the new
    /// edges is an implementation detail and may change.  The only guarantees are that it will be
    /// deterministic for a given graph, and that it will be drawn from the incoming edges if
    /// ``use_outgoing=False`` (the default) or from the outgoing edges if ``use_outgoing=True``.
    ///
    /// :param int node: The index of the node to remove. If the index is not present in the graph
    ///     it will be ignored and this function will have no effect.
    /// :param Callable key: A callable Python object that is called once for each connected edge, to
    ///     generate the "key" for that weight.  It is passed exactly one argument positionally
    ///     (the weight of the edge), and should return a Python object that is hashable and
    ///     implements equality checking with all other relevant keys.  If not given, the edge
    ///     weights will be used directly.
    /// :param bool use_outgoing: If ``False`` (default), the new edges will use the weight from
    ///     one of the incoming edges.  If ``True``, they will instead use a weight from one of the
    ///     outgoing edges.
    #[pyo3(signature=(node, /, key=None, *, use_outgoing=false))]
    pub fn remove_node_retain_edges_by_key(
        &mut self,
        py: Python,
        node: usize,
        key: Option<Py<PyAny>>,
        use_outgoing: bool,
    ) -> PyResult<()> {
        let node_index = NodeIndex::new(node);
        let in_edges = {
            let in_edges = PyDict::new(py);
            for edge in self
                .graph
                .edges_directed(node_index, petgraph::Direction::Incoming)
            {
                let key_value = if let Some(key_fn) = &key {
                    key_fn.call1(py, (edge.weight(),))?
                } else {
                    edge.weight().clone_ref(py)
                };
                if let Some(edge_data) = in_edges.get_item(key_value.bind(py))? {
                    let edge_data = edge_data.downcast::<RemoveNodeEdgeValue>()?;
                    edge_data.borrow_mut().nodes.push(edge.source());
                } else {
                    in_edges.set_item(
                        key_value,
                        RemoveNodeEdgeValue {
                            weight: edge.weight().clone_ref(py),
                            nodes: vec![edge.source()],
                        }
                        .into_pyobject(py)?,
                    )?
                }
            }
            in_edges
        };
        let out_edges = {
            let out_edges = PyDict::new(py);
            for edge in self
                .graph
                .edges_directed(node_index, petgraph::Direction::Outgoing)
            {
                let key_value = if let Some(key_fn) = &key {
                    key_fn.call1(py, (edge.weight(),))?
                } else {
                    edge.weight().clone_ref(py)
                };
                if let Some(edge_data) = out_edges.get_item(key_value.bind(py))? {
                    let edge_data = edge_data.downcast::<RemoveNodeEdgeValue>()?;
                    edge_data.borrow_mut().nodes.push(edge.target());
                } else {
                    out_edges.set_item(
                        key_value,
                        RemoveNodeEdgeValue {
                            weight: edge.weight().clone_ref(py),
                            nodes: vec![edge.target()],
                        }
                        .into_pyobject(py)?,
                    )?
                }
            }
            out_edges
        };

        for (in_key, in_edge_data) in in_edges {
            let in_edge_data = in_edge_data.downcast::<RemoveNodeEdgeValue>()?.borrow();
            let out_edge_data = match out_edges.get_item(in_key)? {
                Some(out_edge_data) => out_edge_data.downcast::<RemoveNodeEdgeValue>()?.borrow(),
                None => continue,
            };
            for source in in_edge_data.nodes.iter() {
                for target in out_edge_data.nodes.iter() {
                    let weight = if use_outgoing {
                        out_edge_data.weight.clone_ref(py)
                    } else {
                        in_edge_data.weight.clone_ref(py)
                    };
                    self._add_edge(*source, *target, weight)?;
                }
            }
        }
        self.node_removed = self.graph.remove_node(node_index).is_some();
        Ok(())
    }

    /// Add an edge between 2 nodes.
    ///
    /// Use add_child() or add_parent() to create a node with an edge at the
    /// same time as an edge for better performance. Using this method
    /// allows for adding duplicate edges between nodes if the ``multigraph``
    /// attribute is set to ``True``.
    ///
    /// :param int parent: The index of the parent node
    /// :param int child: The index of the child node
    /// :param T edge: The Python object to attach to the edge.
    ///
    /// :returns: The index of the newly created edge
    /// :rtype: int
    ///
    /// :raises: PyIndexError: When the new edge would create a cycle
    #[pyo3(text_signature = "(self, parent, child, edge, /)")]
    pub fn add_edge(&mut self, parent: usize, child: usize, edge: PyObject) -> PyResult<usize> {
        let p_index = NodeIndex::new(parent);
        let c_index = NodeIndex::new(child);
        if !self.graph.contains_node(p_index) || !self.graph.contains_node(c_index) {
            return Err(PyIndexError::new_err(
                "One of the endpoints of the edge does not exist in graph",
            ));
        }
        let out_index = self._add_edge(p_index, c_index, edge)?;
        Ok(out_index)
    }

    /// Add new edges to the graph.
    ///
    /// :param iterable[tuple[int, int, T]] obj_list: An iterable of tuples of the form
    ///     ``(parent, child, obj)`` to attach to the graph. ``parent`` and
    ///     ``child`` are integer indices describing where an edge should be
    ///     added, and obj is the python object for the edge data.
    ///
    /// :returns: A list of indices of the newly created edges
    /// :rtype: EdgeIndices
    #[pyo3(text_signature = "(self, obj_list, /)")]
    pub fn add_edges_from(&mut self, obj_list: Bound<'_, PyAny>) -> PyResult<Vec<usize>> {
        let mut out_list = Vec::new();
        for py_obj in obj_list.try_iter()? {
            let obj = py_obj?.extract::<(usize, usize, PyObject)>()?;
            let edge = self.add_edge(obj.0, obj.1, obj.2)?;
            out_list.push(edge);
        }
        Ok(out_list)
    }

    /// Add new edges to the graph without python data.
    ///
    /// :param iterable[tuple[int, int]] obj_list: An iterable of tuples of the form
    ///     ``(parent, child)`` to attach to the graph. ``parent`` and
    ///     ``child`` are integer indices describing where an edge should be
    ///     added. Unlike :meth:`add_edges_from` there is no data payload and
    ///     when the edge is created None will be used.
    ///
    /// :returns: A list of indices of the newly created edges
    /// :rtype: EdgeIndices
    #[pyo3(text_signature = "(self, obj_list, /)")]
    pub fn add_edges_from_no_data(
        &mut self,
        py: Python,
        obj_list: Bound<'_, PyAny>,
    ) -> PyResult<Vec<usize>> {
        let mut out_list = Vec::new();
        for py_obj in obj_list.try_iter()? {
            let obj = py_obj?.extract::<(usize, usize)>()?;
            let edge = self.add_edge(obj.0, obj.1, py.None())?;
            out_list.push(edge);
        }
        Ok(out_list)
    }

    /// Extend graph from an edge list
    ///
    /// This method differs from :meth:`add_edges_from_no_data` in that it will
    /// add nodes if a node index is not present in the edge list.
    ///
    /// :param iterable[tuple[int, int]] edge_list: An iterable of tuples
    ///     in the form ``(source, target)`` where ``source`` and ``target``
    ///     are integer node indices. If the node index
    ///     is not present in the graph, nodes will be added (with a node
    ///     weight of ``None``) to that index.
    #[pyo3(text_signature = "(self, edge_list, /)")]
    pub fn extend_from_edge_list(
        &mut self,
        py: Python,
        edge_list: Bound<'_, PyAny>,
    ) -> PyResult<()> {
        for py_obj in edge_list.try_iter()? {
            let (source, target) = py_obj?.extract::<(usize, usize)>()?;
            let max_index = cmp::max(source, target);
            while max_index >= self.node_count() {
                self.graph.add_node(py.None());
            }
            self._add_edge(NodeIndex::new(source), NodeIndex::new(target), py.None())?;
        }
        Ok(())
    }

    /// Extend graph from a weighted edge list
    ///
    /// This method differs from :meth:`add_edges_from` in that it will
    /// add nodes if a node index is not present in the edge list.
    ///
    /// :param iterable[tuple[int, int, T]] edge_list: An iterable of tuples
    ///     in the form ``(source, target, weight)`` where ``source`` and ``target``
    ///     are integer node indices. If the node index is not present in the graph
    ///     nodes will be added (with a node weight of ``None``) to that index.
    #[pyo3(text_signature = "(self, edge_list, /)")]
    pub fn extend_from_weighted_edge_list(
        &mut self,
        py: Python,
        edge_list: Bound<'_, PyAny>,
    ) -> PyResult<()> {
        for py_obj in edge_list.try_iter()? {
            let (source, target, weight) = py_obj?.extract::<(usize, usize, PyObject)>()?;
            let max_index = cmp::max(source, target);
            while max_index >= self.node_count() {
                self.graph.add_node(py.None());
            }
            self._add_edge(NodeIndex::new(source), NodeIndex::new(target), weight)?;
        }
        Ok(())
    }

    /// Insert a node between a list of reference nodes and all their predecessors
    ///
    /// This essentially iterates over all edges leading into the reference nodes
    /// specified in the ``ref_nodes`` parameter, removes those edges and then
    /// adds 2 edges, one from the predecessor of ``ref_node`` to ``node``
    /// and the other one from ``node`` to ``ref_node``. The edge payloads of
    /// the two newly created edges are copied by reference from the original
    /// edge that gets removed.
    ///
    /// :param int node: The index of the node to insert
    /// :param list[int] ref_nodes: The list of indices of reference nodes
    ///      to be prepended by ``node``
    #[pyo3(text_signature = "(self, node, ref_nodes, /)")]
    pub fn insert_node_on_in_edges_multiple(
        &mut self,
        py: Python,
        node: usize,
        ref_nodes: Vec<usize>,
    ) -> PyResult<()> {
        for ref_node in ref_nodes {
            self.insert_between(py, node, ref_node, false)?;
        }
        Ok(())
    }

    /// Insert a node between a list of reference nodes and all their successors
    ///
    /// This essentially iterates over all edges leading out of the reference nodes
    /// specified in the ``ref_nodes`` parameter, removes those edges and then
    /// adds 2 edges, one from ``ref_node`` to ``node`` and the other one from
    /// ``node`` to the successor of ``ref_node``. The edge payloads of the two
    /// newly created edges are copied by reference from the original edge that
    /// gets removed.
    ///
    /// :param int node: The index of the node to insert
    /// :param list[int] ref_nodes: The list of indices of reference nodes
    ///     to be appended by ``node``
    #[pyo3(text_signature = "(self, node, ref_nodes, /)")]
    pub fn insert_node_on_out_edges_multiple(
        &mut self,
        py: Python,
        node: usize,
        ref_nodes: Vec<usize>,
    ) -> PyResult<()> {
        for ref_node in ref_nodes {
            self.insert_between(py, node, ref_node, true)?;
        }
        Ok(())
    }

    /// Insert a node between a reference node and all its predecessor nodes
    ///
    /// This essentially iterates over all edges leading into the reference node
    /// specified in the ``ref_node`` parameter, removes those edges and then
    /// adds 2 edges, one from the predecessor of ``ref_node`` to ``node`` and
    /// the other one from ``node`` to ``ref_node``. The edge payloads of the two
    /// newly created edges are copied by reference from the original edge that
    /// gets removed.
    ///
    /// :param int node: The index of the node to insert
    /// :param int ref_node: The index of the reference node to be prepended by ``node``
    #[pyo3(text_signature = "(self, node, ref_node, /)")]
    pub fn insert_node_on_in_edges(
        &mut self,
        py: Python,
        node: usize,
        ref_node: usize,
    ) -> PyResult<()> {
        self.insert_between(py, node, ref_node, false)?;
        Ok(())
    }

    /// Insert a node between a reference node and all its successor nodes
    ///
    /// This essentially iterates over all edges leading out of the reference node
    /// specified in the ``ref_node`` parameter, removes those edges and then
    /// adds 2 edges, one from ``ref_node`` to ``node`` and the other one from
    /// ``node`` to the successor of ``ref_node``. The edge payloads of the two
    /// newly created edges are copied by reference from the original edge
    /// that gets removed.
    ///
    /// :param int node: The index of the node to insert
    /// :param int ref_node: The index of the reference node to be appended by ``node``
    #[pyo3(text_signature = "(self, node, ref_node, /)")]
    pub fn insert_node_on_out_edges(
        &mut self,
        py: Python,
        node: usize,
        ref_node: usize,
    ) -> PyResult<()> {
        self.insert_between(py, node, ref_node, true)?;
        Ok(())
    }

    /// Remove an edge between 2 nodes.
    ///
    /// Note if there are multiple edges between the specified nodes only one
    /// will be removed.
    ///
    /// :param int parent: The index of the parent node
    /// :param int child: The index of the child node
    ///
    /// :raises NoEdgeBetweenNodes: If there is no edge between the nodes
    ///     specified
    #[pyo3(text_signature = "(self, parent, child, /)")]
    pub fn remove_edge(&mut self, parent: usize, child: usize) -> PyResult<()> {
        let p_index = NodeIndex::new(parent);
        let c_index = NodeIndex::new(child);
        let edge_index = match self.graph.find_edge(p_index, c_index) {
            Some(edge_index) => edge_index,
            None => return Err(NoEdgeBetweenNodes::new_err("No edge found between nodes")),
        };
        self.graph.remove_edge(edge_index);
        Ok(())
    }

    /// Remove an edge identified by the provided index
    ///
    /// :param int edge: The index of the edge to remove
    #[pyo3(text_signature = "(self, edge, /)")]
    pub fn remove_edge_from_index(&mut self, edge: usize) -> PyResult<()> {
        let edge_index = EdgeIndex::new(edge);
        self.graph.remove_edge(edge_index);
        Ok(())
    }

    /// Remove edges from the graph.
    ///
    /// Note if there are multiple edges between the specified nodes only one
    /// will be removed.
    ///
    /// :param iterable[tuple[int, int]] index_list: An iterable of node index pairs
    ///     to remove from the graph
    ///
    /// :raises NoEdgeBetweenNodes: If there are no edges between a specified
    ///     pair of nodes.
    #[pyo3(text_signature = "(self, index_list, /)")]
    pub fn remove_edges_from(&mut self, index_list: Bound<'_, PyAny>) -> PyResult<()> {
        for py_obj in index_list.try_iter()? {
            let (x, y) = py_obj?.extract::<(usize, usize)>()?;
            let (p_index, c_index) = (NodeIndex::new(x), NodeIndex::new(y));
            let edge_index = match self.graph.find_edge(p_index, c_index) {
                Some(edge_index) => edge_index,
                None => return Err(NoEdgeBetweenNodes::new_err("No edge found between nodes")),
            };
            self.graph.remove_edge(edge_index);
        }
        Ok(())
    }

    /// Add a new node to the graph.
    ///
    /// :param S obj: The Python object to attach to the node
    ///
    /// :returns: The index of the newly created node
    /// :rtype: int
    #[pyo3(text_signature = "(self, obj, /)")]
    pub fn add_node(&mut self, obj: PyObject) -> PyResult<usize> {
        let index = self.graph.add_node(obj);
        Ok(index.index())
    }

    /// Find node within this graph given a specific weight
    ///
    /// This algorithm has a worst case of O(n) since it searches the node
    /// indices in order. If there is more than one node in the graph with the
    /// same weight only the first match (by node index) will be returned.
    ///
    /// :param T obj: The weight to look for in the graph.
    ///
    /// :returns: the index of the first node in the graph that is equal to the
    ///     weight. If no match is found ``None`` will be returned.
    /// :rtype: int
    #[pyo3(text_signature = "(self, obj, /)")]
    pub fn find_node_by_weight(&self, py: Python, obj: PyObject) -> PyResult<Option<usize>> {
        find_node_by_weight(py, &self.graph, &obj).map(|node| node.map(|x| x.index()))
    }

    /// Merge two nodes in the graph.
    ///
    /// If the nodes have equal weight objects then all the edges
    /// leading into and out of `u` will be redirected
    /// to `v` and `u` will be removed from the graph. If the nodes don't have equal weight
    /// objects then no changes will be made and no error will be raised
    ///
    /// :param int u: The index of the source node that is going to be merged
    /// :param int v: The index of the target node that is going to persist
    #[pyo3(text_signature = "(self, u, v, /)")]
    pub fn merge_nodes(&mut self, py: Python, u: usize, v: usize) -> PyResult<()> {
        let source_node = NodeIndex::new(u);
        let target_node = NodeIndex::new(v);

        let source_weight = match self.graph.node_weight(source_node) {
            Some(weight) => weight,
            None => return Err(PyIndexError::new_err("No node found for index")),
        };

        let target_weight = match self.graph.node_weight(target_node) {
            Some(weight) => weight,
            None => return Err(PyIndexError::new_err("No node found for index")),
        };

        let have_same_weights =
            source_weight.bind(py).compare(target_weight.bind(py))? == Ordering::Equal;

        if have_same_weights {
            const DIRECTIONS: [petgraph::Direction; 2] =
                [petgraph::Direction::Outgoing, petgraph::Direction::Incoming];

            let mut edges_to_add: Vec<(usize, usize, PyObject)> = Vec::new();
            for dir in &DIRECTIONS {
                for edge in self.graph.edges_directed(NodeIndex::new(u), *dir) {
                    let s = edge.source();
                    let d = edge.target();

                    if s.index() == u {
                        edges_to_add.push((v, d.index(), edge.weight().clone_ref(py)));
                    } else {
                        edges_to_add.push((s.index(), v, edge.weight().clone_ref(py)));
                    }
                }
            }
            self.remove_node(u)?;
            for edge in edges_to_add {
                self.add_edge(edge.0, edge.1, edge.2)?;
            }
        }

        Ok(())
    }

    /// Add a new child node to the graph.
    ///
    /// This will create a new node on the graph and add an edge leading
    /// from an existing parent to that new node.
    ///
    /// :param int parent: The index of the parent node
    /// :param S obj: The Python object to attach to the new node
    /// :param edge: The python object to attach to the edge
    ///
    /// :returns: The index of the newly created child node
    /// :rtype: int
    #[pyo3(text_signature = "(self, parent, obj, edge, /)")]
    pub fn add_child(&mut self, parent: usize, obj: PyObject, edge: PyObject) -> PyResult<usize> {
        let index = NodeIndex::new(parent);
        let child_node = self.graph.add_node(obj);
        self.graph.add_edge(index, child_node, edge);
        Ok(child_node.index())
    }

    /// Add a new parent node to the graph.
    ///
    /// This will create a new node on the graph and add an edge leading
    /// from that new node to an existing child.
    ///
    /// :param int child: The index of the child node
    /// :param obj: The Python object to attach to the new node
    /// :param edge: The python object to attach to the edge
    ///
    /// :returns index: The index of the newly created parent node
    /// :rtype: int
    #[pyo3(text_signature = "(self, child, obj, edge, /)")]
    pub fn add_parent(&mut self, child: usize, obj: PyObject, edge: PyObject) -> PyResult<usize> {
        let index = NodeIndex::new(child);
        let parent_node = self.graph.add_node(obj);
        self.graph.add_edge(parent_node, index, edge);
        Ok(parent_node.index())
    }

    /// Get the index and data for the neighbors of a node.
    ///
    /// This will return a dictionary where the keys are the node indices of
    /// the adjacent nodes (inbound or outbound) and the value is the edge data
    /// objects between that adjacent node and the provided node. Note in
    /// the case of a multigraph only one edge will be used, not all of the
    /// edges between two node.
    ///
    ///     >>> G = rx.PyDiGraph()
    ///     >>> G.add_nodes_from(["A", "B", "C", "D", "E"])
    ///     >>> NodeIndices[0, 1, 2, 3, 4]
    ///     >>> G.extend_from_weighted_edge_list([(0, 2, "A->C"), (1, 2, "B->C"), (2, 3, "C->D"), (3, 4, "D->E")])
    ///     >>> G.adj(2)  # neighbors of the node "C"
    ///     {1: 'B->C', 0: 'A->C', 3: 'C->D'}
    ///
    /// For direction-aware neighbors, see :func:`~adj_direction`.
    ///
    /// :param int node: The index of the node to get the neighbors of
    ///
    /// :returns: A dictionary where the keys are the node indices and the values
    ///     are the edge data objects for all nodes that share an edge with the
    ///     specified node.
    /// :rtype: dict[int, T]
    #[pyo3(text_signature = "(self, node, /)")]
    pub fn adj(&mut self, node: usize) -> DictMap<usize, &PyObject> {
        let index = NodeIndex::new(node);
        self.graph
            .edges_directed(index, petgraph::Direction::Incoming)
            .map(|edge| (edge.source().index(), edge.weight()))
            .chain(
                self.graph
                    .edges_directed(index, petgraph::Direction::Outgoing)
                    .map(|edge| (edge.target().index(), edge.weight())),
            )
            .collect()
    }

    /// Get the index and data for either the parents or children of a node.
    ///
    /// This will return a dictionary where the keys are the node indices of
    /// the adjacent nodes (inbound or outbound as specified) and the value
    /// is the edge data objects for the edges between that adjacent node
    /// and the provided node. Note in the case of a multigraph only one edge
    /// one edge will be used, not all of the edges between two node.
    ///
    ///     >>> G = rx.PyDiGraph()
    ///     >>> G.add_nodes_from(["A", "B", "C", "D", "E"])
    ///     >>> NodeIndices[0, 1, 2, 3, 4]
    ///     >>> G.extend_from_weighted_edge_list([(0, 2, "A->C"), (1, 2, "B->C"), (2, 3, "C->D"), (3, 4, "D->E")])
    ///     >>> G.adj_direction(2, True)
    ///     {1: 'B->C', 0: 'A->C'}
    ///     >>> G.adj_direction(2, False)
    ///     {3: 'C->D'}
    ///
    /// For direction-naive neighbors, see :func:`~adj`.
    ///
    /// :param int node: The index of the node to get the neighbors of
    /// :param bool direction: The direction to use for finding nodes,
    ///     ``True`` means inbound edges and ``False`` means outbound edges.
    ///
    /// :returns: A dictionary where the keys are node indices and
    ///     the value is the edge data object for all nodes that share an
    ///     edge with the specified node.
    /// :rtype: dict[int, T]
    #[pyo3(text_signature = "(self, node, direction, /)")]
    pub fn adj_direction(&mut self, node: usize, direction: bool) -> DictMap<usize, &PyObject> {
        let index = NodeIndex::new(node);
        if direction {
            self.graph
                .edges_directed(index, petgraph::Direction::Incoming)
                .map(|edge| (edge.source().index(), edge.weight()))
                .collect()
        } else {
            self.graph
                .edges_directed(index, petgraph::Direction::Outgoing)
                .map(|edge| (edge.target().index(), edge.weight()))
                .collect()
        }
    }

    /// Return a list of node indices of neighbors (i.e. successors) in a directed graph
    ///
    /// A successor is defined as a node that has a directed edge pointing
    /// from the specified node. In a multigraph, where two nodes can be connected
    /// by multiple edges, each successor node index is returned only once.
    ///
    /// This function is equivalent to :meth:`successor_indices`.
    ///
    ///     >>> G = rx.PyDiGraph()
    ///     >>> G.add_nodes_from(["A", "B", "C", "D", "E"])
    ///     NodeIndices[0, 1, 2, 3, 4]
    ///     >>> G.extend_from_edge_list([(0, 1), (1, 2), (1, 3), (1, 4)])
    ///     >>> G.neighbors(1)  # neighbors of the 'B' node
    ///     NodeIndices[4, 3, 2]
    ///
    /// To get the data of these nodes, see :func:`~successors`.
    ///
    /// To filter the successors by the attributes of the connecting edge,
    /// see :func:`~find_successors_by_edge`.
    ///
    /// See also :func:`~predecessor_indices`.
    ///
    /// For undirected graphs, see :func:`~PyGraph.neighbors`.
    ///
    /// :param int node: The index of the node to get the neighbors of
    ///
    /// :returns: A list of the neighboring node indices
    /// :rtype: NodeIndices
    #[pyo3(text_signature = "(self, node, /)")]
    pub fn neighbors(&self, node: usize) -> NodeIndices {
        NodeIndices {
            nodes: self
                .graph
                .neighbors(NodeIndex::new(node))
                .map(|node| node.index())
                .collect::<HashSet<usize>>()
                .drain()
                .collect(),
        }
    }

    /// Get the direction-agnostic neighbors (i.e. successors and predecessors) of a node.
    ///
    /// This is functionally equivalent to converting the directed graph to an undirected
    /// graph, and calling ``neighbors`` thereon.
    ///
    ///     >>> G = rx.PyDiGraph()
    ///     >>> G.extend_from_edge_list([(0, 1), (1, 2), (2, 3), (3, 4)])
    ///     >>> node = 2
    ///     >>> G.neighbors_undirected(node)
    ///     NodeIndices[3, 1]
    ///     >>> G.to_undirected().neighbors(node)
    ///     NodeIndices[1, 3]
    ///
    /// For direction-aware neighbors, see :func:`~predecessors` and :func:`~successors`.
    ///
    /// :param int node: The index of the node to get the neighbors of
    ///
    /// :returns: A list of the neighboring node indices
    /// :rtype: NodeIndices
    #[pyo3(text_signature = "(self, node, /)")]
    pub fn neighbors_undirected(&self, node: usize) -> NodeIndices {
        NodeIndices {
            nodes: self
                .graph
                .neighbors_undirected(NodeIndex::new(node))
                .map(|node| node.index())
                .collect::<HashSet<usize>>()
                .drain()
                .collect(),
        }
    }

    /// Return a list of successor node indices in a directed graph
    ///
    /// A successor is defined as a node that has a directed edge pointing
    /// from the specified node. In a multigraph, where two nodes can be connected
    /// by multiple edges, each successor node index is returned only once.
    ///
    ///     >>> G = rx.PyDiGraph()
    ///     >>> G.add_nodes_from(["A", "B", "C", "D", "E"])
    ///     NodeIndices[0, 1, 2, 3, 4]
    ///     >>> G.extend_from_edge_list([(0, 1), (1, 2), (1, 3), (1, 4)])
    ///     >>> G.successor_indices(1)  # successors of the 'B' node
    ///     NodeIndices[4, 3, 2]
    ///
    /// To get the data of these nodes, see :func:`~successors`.`
    ///
    /// To filter the successors by the attributes of the connecting edge,
    /// see :func:`~find_successors_by_edge`.
    ///
    /// See also :func:`~predecessor_indices` and :func:`~neighbors`.
    ///
    /// For undirected graphs, see :func:`~PyGraph.neighbors`.
    ///
    /// :param int node: The index of the node to get the successors for
    ///
    /// :returns: A list of the node indices of all node's successors
    /// :rtype: NodeIndices
    #[pyo3(text_signature = "(self, node, /)")]
    pub fn successor_indices(&self, node: usize) -> NodeIndices {
        NodeIndices {
            nodes: self
                .graph
                .neighbors_directed(NodeIndex::new(node), petgraph::Direction::Outgoing)
                .map(|node| node.index())
                .collect(),
        }
    }

    /// Return a list of predecessor node indices in a directed graph
    ///
    /// A predecessor is defined as a node that has a directed edge pointing
    /// to the specified node. In a multigraph, where two nodes can be connected
    /// by multiple edges, each predecessor node index is returned only once.
    ///
    ///     >>> G = rx.PyDiGraph()
    ///     >>> G.add_nodes_from(["A", "B", "C", "D", "E"])
    ///     NodeIndices[0, 1, 2, 3, 4]
    ///     >>> G.extend_from_edge_list([(0, 3), (1, 3), (2, 3), (3, 4)])
    ///     >>> G.predecessor_indices(3)  # predecessors of the 'D' node
    ///     NodeIndices[2, 1, 0]
    ///
    /// To get the data of these nodes, see [predecessors]
    ///
    /// To filter the predecessors by the attributes of the connecting edge,
    /// see :func:`~find_predecessors_by_edge`.
    ///
    /// See also :func:`~successor_indices`.
    ///
    /// For undirected graphs, see :func:`~PyGraph.neighbors`.
    ///
    /// :param int node: The index of the node to get the predecessors for
    ///
    /// :returns: A list of the node indices of all node's predecessors
    /// :rtype: NodeIndices
    #[pyo3(text_signature = "(self, node, /)")]
    pub fn predecessor_indices(&self, node: usize) -> NodeIndices {
        NodeIndices {
            nodes: self
                .graph
                .neighbors_directed(NodeIndex::new(node), petgraph::Direction::Incoming)
                .map(|node| node.index())
                .collect(),
        }
    }

    /// Return the list of edge indices incident to a provided node
    ///
    /// You can later retrieve the data payload of this edge with
    /// :meth:`~rustworkx.PyDiGraph.get_edge_data_by_index` or its
    /// endpoints with :meth:`~rustworkx.PyDiGraph.get_edge_endpoints_by_index`.
    ///
    /// By default this method will only return the outgoing edges of
    /// the provided ``node``. If you would like to access both the
    /// incoming and outgoing edges you can set the ``all_edges``
    /// kwarg to ``True``.
    ///
    /// :param int node: The node index to get incident edges from. If
    ///     this node index is not present in the graph this method will
    ///     return an empty list and not raise an error.
    /// :param bool all_edges: If set to ``True`` both incoming and outgoing
    ///     edges to ``node`` will be returned.
    ///
    /// :returns: A list of the edge indices incident to a node in the graph
    /// :rtype: EdgeIndices
    #[pyo3(text_signature = "(self, node, /, all_edges=False)")]
    #[pyo3(signature=(node, all_edges=false))]
    pub fn incident_edges(&self, node: usize, all_edges: bool) -> EdgeIndices {
        let node_index = NodeIndex::new(node);
        if all_edges {
            EdgeIndices {
                edges: self
                    .graph
                    .edges_directed(node_index, petgraph::Direction::Outgoing)
                    .chain(
                        self.graph
                            .edges_directed(node_index, petgraph::Direction::Incoming),
                    )
                    .map(|e| e.id().index())
                    .collect(),
            }
        } else {
            EdgeIndices {
                edges: self
                    .graph
                    .edges(node_index)
                    .map(|e| e.id().index())
                    .collect(),
            }
        }
    }

    /// Return the list of incoming edge indices to a provided node
    ///
    /// This method will return the incoming edges of the provided
    /// ``node``.
    ///
    /// :param int node: The node index to get incoming edges from. If
    ///     this node index is not present in the graph this method will
    ///     return an empty list and not raise an error.
    ///
    /// :returns: A list of the incoming edge indices to a node in the graph
    /// :rtype: EdgeIndices
    #[pyo3(text_signature = "(self, node, /)")]
    pub fn in_edge_indices(&self, node: usize) -> EdgeIndices {
        let node_index = NodeIndex::new(node);
        let dir = petgraph::Direction::Incoming;
        EdgeIndices {
            edges: self
                .graph
                .edges_directed(node_index, dir)
                .map(|e| e.id().index())
                .collect(),
        }
    }

    /// Return the list of outgoing edge indices from a provided node
    ///
    /// This method will return the outgoing edges of the provided
    /// ``node``.
    ///
    /// :param int node: The node index to get outgoing edges from. If
    ///     this node index is not present in the graph this method will
    ///     return an empty list and not raise an error.
    ///
    /// :returns: A list of the outgoing edge indices from a node in the graph
    /// :rtype: EdgeIndices
    #[pyo3(text_signature = "(self, node, /)")]
    pub fn out_edge_indices(&self, node: usize) -> EdgeIndices {
        let node_index = NodeIndex::new(node);
        let dir = petgraph::Direction::Outgoing;
        EdgeIndices {
            edges: self
                .graph
                .edges_directed(node_index, dir)
                .map(|e| e.id().index())
                .collect(),
        }
    }

    /// Return the index map of edges incident to a provided node
    ///
    /// By default this method will only return the outgoing edges of
    /// the provided ``node``. If you would like to access both the
    /// incoming and outgoing edges you can set the ``all_edges``
    /// kwarg to ``True``.
    ///
    /// :param int node: The node index to get incident edges from. If
    ///     this node index is not present in the graph this method will
    ///     return an empty list and not error.
    /// :param bool all_edges: If set to ``True`` both incoming and outgoing
    ///     edges to ``node`` will be returned. If set to ``False``, only outgoing ones.
    ///
    /// :returns: A mapping of incident edge indices to the tuple
    ///     ``(source, target, data)``
    /// :rtype: EdgeIndexMap
    #[pyo3(text_signature = "(self, node, /, all_edges=False)")]
    #[pyo3(signature=(node, all_edges=false))]
    pub fn incident_edge_index_map(
        &self,
        py: Python,
        node: usize,
        all_edges: bool,
    ) -> EdgeIndexMap {
        let node_index = NodeIndex::new(node);
        if all_edges {
            EdgeIndexMap {
                edge_map: self
                    .graph
                    .edges_directed(node_index, petgraph::Direction::Outgoing)
                    .chain(
                        self.graph
                            .edges_directed(node_index, petgraph::Direction::Incoming),
                    )
                    .map(|edge| {
                        (
                            edge.id().index(),
                            (
                                edge.source().index(),
                                edge.target().index(),
                                edge.weight().clone_ref(py),
                            ),
                        )
                    })
                    .collect(),
            }
        } else {
            EdgeIndexMap {
                edge_map: self
                    .graph
                    .edges(node_index)
                    .map(|edge| {
                        (
                            edge.id().index(),
                            (
                                edge.source().index(),
                                edge.target().index(),
                                edge.weight().clone_ref(py),
                            ),
                        )
                    })
                    .collect(),
            }
        }
    }

    /// Get the index and edge data for all parents of a node.
    ///
    /// This will return a list of tuples with the parent index, the node (itself) index,
    /// and the edge data. This can be used to recreate add_edge() calls.
    ///
    /// :param int node: The index of the node to get the edges for
    ///
    /// :returns: A list of tuples in the form:
    ///     ``(parent_index, node_index, edge_data)```
    /// :rtype: WeightedEdgeList
    #[pyo3(text_signature = "(self, node, /)")]
    pub fn in_edges(&self, py: Python, node: usize) -> WeightedEdgeList {
        let index = NodeIndex::new(node);
        let dir = petgraph::Direction::Incoming;
        let raw_edges = self.graph.edges_directed(index, dir);
        let out_list: Vec<(usize, usize, PyObject)> = raw_edges
            .map(|x| (x.source().index(), node, x.weight().clone_ref(py)))
            .collect();
        WeightedEdgeList { edges: out_list }
    }

    /// Get the index and edge data for all children of a node.
    ///
    /// This will return a list of tuples with the child index, the node (itself) index,
    /// and the edge data. This can be used to recreate add_edge() calls.
    ///
    /// :param int node: The index of the node to get the edges for
    ///
    /// :returns out_edges: A list of tuples of the form:
    ///     ```(node_index, child_index, edge_data)```
    /// :rtype: WeightedEdgeList
    #[pyo3(text_signature = "(self, node, /)")]
    pub fn out_edges(&self, py: Python, node: usize) -> WeightedEdgeList {
        let index = NodeIndex::new(node);
        let dir = petgraph::Direction::Outgoing;
        let raw_edges = self.graph.edges_directed(index, dir);
        let out_list: Vec<(usize, usize, PyObject)> = raw_edges
            .map(|x| (node, x.target().index(), x.weight().clone_ref(py)))
            .collect();
        WeightedEdgeList { edges: out_list }
    }

    /// Add new nodes to the graph.
    ///
    /// :param iterable[S] obj_list: An iterable of Python objects to attach to the new nodes
    ///
    /// :returns: A list of indices of the newly created nodes
    /// :rtype: NodeIndices
    #[pyo3(text_signature = "(self, obj_list, /)")]
    pub fn add_nodes_from(&mut self, obj_list: Bound<'_, PyAny>) -> PyResult<NodeIndices> {
        let mut out_list = Vec::new();
        for py_obj in obj_list.try_iter()? {
            let obj = py_obj?.extract::<PyObject>()?;
            out_list.push(self.graph.add_node(obj).index());
        }
        Ok(NodeIndices { nodes: out_list })
    }

    /// Remove nodes from the graph.
    ///
    /// If a node index in the list is not present in the graph, it will be
    /// ignored.
    ///
    /// :param iterable[int] index_list: An iterable of node indices to remove from the
    ///     graph.
    #[pyo3(text_signature = "(self, index_list, /)")]
    pub fn remove_nodes_from(&mut self, index_list: Bound<'_, PyAny>) -> PyResult<()> {
        for py_obj in index_list.try_iter()? {
            let node = py_obj?.extract::<usize>()?;
            self.remove_node(node)?;
        }
        Ok(())
    }

    /// Get the degree of a node for inbound edges.
    ///
    /// :param int node: The index of the node to find the inbound degree of
    ///
    /// :returns: The inbound degree for the specified node (i.e. number of inbound edges)
    /// :rtype: int
    #[pyo3(text_signature = "(self, node, /)")]
    pub fn in_degree(&self, node: usize) -> usize {
        let index = NodeIndex::new(node);
        let dir = petgraph::Direction::Incoming;
        let neighbors = self.graph.edges_directed(index, dir);
        neighbors.count()
    }

    /// Get the degree of a node for outbound edges.
    ///
    /// :param int node: The index of the node to find the outbound degree of
    ///
    /// :returns: The outbound degree for the specified node (i.e. number of outbound endges)
    /// :rtype: int
    #[pyo3(text_signature = "(self, node, /)")]
    pub fn out_degree(&self, node: usize) -> usize {
        let index = NodeIndex::new(node);
        let dir = petgraph::Direction::Outgoing;
        let neighbors = self.graph.edges_directed(index, dir);
        neighbors.count()
    }

    /// Find any adjacent (successor) node connected with an edge that matches the condition
    ///
    /// This method is used to find a target node that is a adjacent to a given
    /// node as a successor given an edge condition. This method returns one
    /// arbitrary node where the edge matches the condition.
    ///
    ///     >>> G = rx.PyDiGraph()
    ///     >>> G.add_nodes_from(["A", "B", "C", "D", "E"])
    ///     NodeIndices[0, 1, 2, 3, 4]
    ///     >>> G.extend_from_weighted_edge_list([(0, 1, 10), (1, 2, 10), (1, 3, 20), (1, 4, 30)])
    ///     >>> G.find_adjacent_node_by_edge(1, lambda x: x < 25)
    ///     'D'
    ///
    /// :param int node: The index of the node to use as the source of the search
    /// :param Callable predicate: A Python callable that will take a single
    ///     parameter, the edge object, and will return a boolean if the
    ///     edge matches or not
    ///
    /// :returns: The node object that is connected by an edge to the given node
    ///     as a successor which matches the provided condition
    /// :rtype: S
    /// :raises: NoSuitableNeighbors: If there are no suitable nodes
    #[pyo3(text_signature = "(self, node, predicate, /)")]
    pub fn find_adjacent_node_by_edge(
        &self,
        py: Python,
        node: usize,
        predicate: PyObject,
    ) -> PyResult<&PyObject> {
        let predicate_callable = |a: &PyObject| -> PyResult<PyObject> {
            let res = predicate.call1(py, (a,))?;
            res.into_py_any(py)
        };
        let index = NodeIndex::new(node);
        let dir = petgraph::Direction::Outgoing;
        let edges = self.graph.edges_directed(index, dir);
        for edge in edges {
            let edge_predicate_raw = predicate_callable(edge.weight())?;
            let edge_predicate: bool = edge_predicate_raw.extract(py)?;
            if edge_predicate {
                return Ok(self.graph.node_weight(edge.target()).unwrap());
            }
        }
        Err(NoSuitableNeighbors::new_err("No suitable neighbor"))
    }

    /// Find any predecessor node connected with an edge that matches the condition
    ///
    /// A predecessor is defined as a node that has a directed edge pointing
    /// to the specified node. This method returns one arbitrary node where the edge
    /// matches the condition.
    ///
    ///     >>> G = rx.PyDiGraph()
    ///     >>> G.add_nodes_from(["A", "B", "C", "D", "E"])
    ///     NodeIndices[0, 1, 2, 3, 4]
    ///     >>> G.extend_from_weighted_edge_list([(0, 3, 10), (1, 3, 20), (2, 3, 30), (3, 4, 10)])
    ///     >>> G.find_predecessor_node_by_edge(3, lambda x: x < 25)
    ///     'B'
    ///
    /// To get all such nodes, see :func:`~find_predecessors_by_edge`.
    ///
    /// :param int node: The node to use as the source of the search
    /// :param Callable predicate: A Python callable that will take a single
    ///     parameter, the edge object, and will return a boolean if the
    ///     edge matches or not
    ///
    /// :returns: The node object that is connected as a predecessor
    ///     by an edge to the given node which matches the provided condition
    /// :rtype: S
    /// :raises: NoSuitableNeighbors: If there are no suitable nodes
    #[pyo3(text_signature = "(self, node, predicate, /)")]
    pub fn find_predecessor_node_by_edge(
        &self,
        py: Python,
        node: usize,
        predicate: PyObject,
    ) -> PyResult<&PyObject> {
        let predicate_callable = |a: &PyObject| -> PyResult<PyObject> {
            let res = predicate.call1(py, (a,))?;
            res.into_py_any(py)
        };
        let index = NodeIndex::new(node);
        let dir = petgraph::Direction::Incoming;
        let edges = self.graph.edges_directed(index, dir);
        for edge in edges {
            let edge_predicate_raw = predicate_callable(edge.weight())?;
            let edge_predicate: bool = edge_predicate_raw.extract(py)?;
            if edge_predicate {
                return Ok(self.graph.node_weight(edge.source()).unwrap());
            }
        }
        Err(NoSuitableNeighbors::new_err("No suitable neighbor"))
    }

    /// Find any successor node connected with an edge that matches the condition
    ///
    /// A successor is defined as a node that has a directed edge pointing
    /// from the specified node. This method returns one arbitrary node where the edge
    /// matches the condition.
    ///
    ///     >>> G = rx.PyDiGraph()
    ///     >>> G.add_nodes_from(["A", "B", "C", "D", "E"])
    ///     NodeIndices[0, 1, 2, 3, 4]
    ///     >>> G.extend_from_weighted_edge_list([(0, 1, 10), (1, 2, 10), (1, 3, 20), (1, 4, 30)])
    ///     >>> G.find_successor_node_by_edge(1, lambda x: x < 25)
    ///     'D'
    ///
    /// To get all such nodes, see :func:`~find_successors_by_edge`.
    ///
    /// :param int node: The node to use as the source of the search
    /// :param Callable predicate: A Python callable that will take a single
    ///     parameter, the edge object, and will return a boolean if the
    ///     edge matches or not
    ///
    /// :returns: The node object that is connected as a successor
    ///     by an edge to the given node which matches the provided condition
    /// :rtype: S
    /// :raises: NoSuitableNeighbors: If there are no suitable nodes
    #[pyo3(text_signature = "(self, node, predicate, /)")]
    pub fn find_successor_node_by_edge(
        &self,
        py: Python,
        node: usize,
        predicate: PyObject,
    ) -> PyResult<&PyObject> {
        let predicate_callable = |a: &PyObject| -> PyResult<PyObject> {
            let res = predicate.call1(py, (a,))?;
            res.into_py_any(py)
        };
        let index = NodeIndex::new(node);
        let dir = petgraph::Direction::Outgoing;
        let edges = self.graph.edges_directed(index, dir);
        for edge in edges {
            let edge_predicate_raw = predicate_callable(edge.weight())?;
            let edge_predicate: bool = edge_predicate_raw.extract(py)?;
            if edge_predicate {
                return Ok(self.graph.node_weight(edge.source()).unwrap());
            }
        }
        Err(NoSuitableNeighbors::new_err("No suitable neighbor"))
    }

    /// Generate a dot file from the graph
    ///
    /// :param node_attr: A callable that will take in a node data object
    ///     and return a dictionary of attributes to be associated with the
    ///     node in the dot file. The key and value of this dictionary **must**
    ///     be strings. If they're not strings rustworkx will raise TypeError
    ///     (unfortunately without an error message because of current
    ///     limitations in the PyO3 type checking)
    /// :param edge_attr: A callable that will take in an edge data object
    ///     and return a dictionary of attributes to be associated with the
    ///     node in the dot file. The key and value of this dictionary **must**
    ///     be a string. If they're not strings rustworkx will raise TypeError
    ///     (unfortunately without an error message because of current
    ///     limitations in the PyO3 type checking)
    /// :param dict graph_attr: An optional dictionary that specifies any graph
    ///     attributes for the output dot file. The key and value of this
    ///     dictionary **must** be a string. If they're not strings rustworkx
    ///     will raise TypeError (unfortunately without an error message
    ///     because of current limitations in the PyO3 type checking)
    /// :param str filename: An optional path to write the dot file to
    ///     if specified there is no return from the function
    ///
    /// :returns: A string with the dot file contents if filename is not
    ///     specified.
    /// :rtype: str
    ///
    /// Using this method enables you to leverage graphviz to visualize a
    /// :class:`rustworkx.PyDiGraph` object. For example:
    ///
    /// .. jupyter-execute::
    ///
    ///   import os
    ///   import tempfile
    ///
    ///   import pydot
    ///   from PIL import Image
    ///
    ///   import rustworkx as rx
    ///
    ///   graph = rx.directed_gnp_random_graph(15, .25)
    ///   dot_str = graph.to_dot(
    ///       lambda node: dict(
    ///           color='black', fillcolor='lightblue', style='filled'))
    ///   dot = pydot.graph_from_dot_data(dot_str)[0]
    ///
    ///   with tempfile.TemporaryDirectory() as tmpdirname:
    ///       tmp_path = os.path.join(tmpdirname, 'dag.png')
    ///       dot.write_png(tmp_path)
    ///       image = Image.open(tmp_path)
    ///       os.remove(tmp_path)
    ///   image
    ///
    #[pyo3(
        text_signature = "(self, /, node_attr=None, edge_attr=None, graph_attr=None, filename=None)",
        signature = (node_attr=None, edge_attr=None, graph_attr=None, filename=None)
    )]
    pub fn to_dot<'py>(
        &self,
        py: Python<'py>,
        node_attr: Option<PyObject>,
        edge_attr: Option<PyObject>,
        graph_attr: Option<BTreeMap<String, String>>,
        filename: Option<String>,
    ) -> PyResult<Option<Bound<'py, PyString>>> {
        match filename {
            Some(filename) => {
                let mut file = File::create(filename)?;
                build_dot(py, &self.graph, &mut file, graph_attr, node_attr, edge_attr)?;
                Ok(None)
            }
            None => {
                let mut file = Vec::<u8>::new();
                build_dot(py, &self.graph, &mut file, graph_attr, node_attr, edge_attr)?;
                Ok(Some(PyString::new(py, str::from_utf8(&file)?)))
            }
        }
    }

    /// Read an edge list file and create a new PyDiGraph object from the
    /// contents
    ///
    /// The expected format for the edge list file is a line separated list
    /// of delimited node ids. If there are more than 3 elements on
    /// a line the 3rd on will be treated as a string weight for the edge
    ///
    /// :param str path: The path of the file to open
    /// :param str comment: Optional character to use as a comment by default
    ///     there are no comment characters
    /// :param str deliminator: Optional character to use as a deliminator by
    ///     default any whitespace will be used
    /// :param bool labels: If set to ``True`` the first two separated fields
    ///     will be treated as string labels uniquely identifying a node
    ///     instead of node indices.
    ///
    /// For example:
    ///
    /// .. jupyter-execute::
    ///
    ///   import tempfile
    ///
    ///   import rustworkx as rx
    ///   from rustworkx.visualization import mpl_draw
    ///
    ///   with tempfile.NamedTemporaryFile('wt') as fd:
    ///       path = fd.name
    ///       fd.write('0 1\n')
    ///       fd.write('0 2\n')
    ///       fd.write('0 3\n')
    ///       fd.write('1 2\n')
    ///       fd.write('2 3\n')
    ///       fd.flush()
    ///       graph = rx.PyDiGraph.read_edge_list(path)
    ///   mpl_draw(graph)
    ///
    #[staticmethod]
    #[pyo3(signature=(path, comment=None, deliminator=None, labels=false))]
    #[pyo3(text_signature = "(path, /, comment=None, deliminator=None, labels=False)")]
    pub fn read_edge_list(
        py: Python,
        path: &str,
        comment: Option<String>,
        deliminator: Option<String>,
        labels: bool,
    ) -> PyResult<PyDiGraph> {
        let file = File::open(path)?;
        let buf_reader = BufReader::new(file);
        let mut out_graph = StablePyGraph::<Directed>::new();
        let mut label_map: HashMap<String, usize> = HashMap::new();
        for line_raw in buf_reader.lines() {
            let line = line_raw?;
            let skip = match &comment {
                Some(comm) => line.trim().starts_with(comm),
                None => line.trim().is_empty(),
            };
            if skip {
                continue;
            }
            let line_no_comments = match &comment {
                Some(comm) => line
                    .find(comm)
                    .map(|idx| &line[..idx])
                    .unwrap_or(&line)
                    .trim()
                    .to_string(),
                None => line,
            };
            let pieces: Vec<&str> = match &deliminator {
                Some(del) => line_no_comments.split(del).collect(),
                None => line_no_comments.split_whitespace().collect(),
            };
            let src: usize;
            let target: usize;
            if labels {
                let src_str = pieces[0];
                let target_str = pieces[1];
                src = match label_map.get(src_str) {
                    Some(index) => *index,
                    None => {
                        let index = out_graph.add_node(src_str.into_py_any(py)?).index();
                        label_map.insert(src_str.to_string(), index);
                        index
                    }
                };
                target = match label_map.get(target_str) {
                    Some(index) => *index,
                    None => {
                        let index = out_graph.add_node(target_str.into_py_any(py)?).index();
                        label_map.insert(target_str.to_string(), index);
                        index
                    }
                };
            } else {
                src = pieces[0].parse::<usize>()?;
                target = pieces[1].parse::<usize>()?;
                let max_index = cmp::max(src, target);
                // Add nodes to graph
                while max_index >= out_graph.node_count() {
                    out_graph.add_node(py.None());
                }
            }
            // Add edges to graph
            let weight = if pieces.len() > 2 {
                let weight_str = match &deliminator {
                    Some(del) => pieces[2..].join(del),
                    None => pieces[2..].join(&' '.to_string()),
                };
                PyString::new(py, &weight_str).into()
            } else {
                py.None()
            };
            out_graph.add_edge(NodeIndex::new(src), NodeIndex::new(target), weight);
        }
        Ok(PyDiGraph {
            graph: out_graph,
            cycle_state: algo::DfsSpace::default(),
            check_cycle: false,
            node_removed: false,
            multigraph: true,
            attrs: py.None(),
        })
    }

    /// Write an edge list file from the PyDiGraph object
    ///
    /// :param str path: The path to write the output file to
    /// :param str deliminator: The optional character to use as a deliminator
    ///     if not specified ``" "`` is used.
    /// :param callable weight_fn: An optional callback function that will be
    ///     passed an edge's data payload/weight object and is expected to
    ///     return a string (a ``TypeError`` will be raised if it doesn't
    ///     return a string). If specified the weight in the output file
    ///     for each edge will be set to the returned string.
    ///
    ///  For example:
    ///
    ///  .. jupyter-execute::
    ///
    ///     import os
    ///     import tempfile
    ///
    ///     import rustworkx as rx
    ///
    ///     graph = rx.generators.directed_path_graph(5)
    ///     path = os.path.join(tempfile.gettempdir(), "edge_list")
    ///     graph.write_edge_list(path, deliminator=',')
    ///     # Print file contents
    ///     with open(path, 'rt') as edge_file:
    ///         print(edge_file.read())
    ///
    #[pyo3(text_signature = "(self, path, /, deliminator=None, weight_fn=None)", signature = (path, deliminator=None, weight_fn=None))]
    pub fn write_edge_list(
        &self,
        py: Python,
        path: &str,
        deliminator: Option<char>,
        weight_fn: Option<PyObject>,
    ) -> PyResult<()> {
        let file = File::create(path)?;
        let mut buf_writer = BufWriter::new(file);
        let delim = match deliminator {
            Some(delim) => delim.to_string(),
            None => " ".to_string(),
        };

        for edge in self.graph.edge_references() {
            buf_writer.write_all(
                format!(
                    "{}{}{}",
                    edge.source().index(),
                    delim,
                    edge.target().index()
                )
                .as_bytes(),
            )?;
            match weight_callable(py, &weight_fn, edge.weight(), None as Option<String>)? {
                Some(weight) => buf_writer.write_all(format!("{}{}\n", delim, weight).as_bytes()),
                None => buf_writer.write_all(b"\n"),
            }?;
        }
        buf_writer.flush()?;
        Ok(())
    }

    /// Create a new :class:`~rustworkx.PyDiGraph` object from an adjacency matrix
    /// with matrix elements of type ``float``
    ///
    /// This method can be used to construct a new :class:`~rustworkx.PyDiGraph`
    /// object from an input adjacency matrix. The node weights will be the
    /// index from the matrix. The edge weights will be a float value of the
    /// value from the matrix.
    ///
    /// This differs from the
    /// :meth:`~rustworkx.PyDiGraph.from_complex_adjacency_matrix` in that the
    /// type of the elements of input matrix must be a ``float`` (specifically
    /// a ``numpy.float64``) and the output graph edge weights will be ``float``
    /// too. While in :meth:`~rustworkx.PyDiGraph.from_complex_adjacency_matrix`
    /// the matrix elements are of type ``complex`` (specifically
    /// ``numpy.complex128``) and the edge weights in the output graph will be
    /// ``complex`` too.
    ///
    /// :param ndarray matrix: The input numpy array adjacency matrix to create
    ///     a new :class:`~rustworkx.PyDiGraph` object from. It must be a 2
    ///     dimensional array and be a ``float``/``np.float64`` data type.
    /// :param float null_value: An optional float that will treated as a null
    ///     value. If any element in the input matrix is this value it will be
    ///     treated as not an edge. By default this is ``0.0``
    ///
    /// :returns: A new graph object generated from the adjacency matrix
    /// :rtype: PyDiGraph
    #[staticmethod]
    #[pyo3(signature=(matrix, null_value=0.0), text_signature = "(matrix, /, null_value=0.0)")]
    pub fn from_adjacency_matrix<'p>(
        py: Python<'p>,
        matrix: PyReadonlyArray2<'p, f64>,
        null_value: f64,
    ) -> PyResult<PyDiGraph> {
        _from_adjacency_matrix(py, matrix, null_value)
    }

    /// Create a new :class:`~rustworkx.PyDiGraph` object from an adjacency matrix
    /// with matrix elements of type ``complex``
    ///
    /// This method can be used to construct a new :class:`~rustworkx.PyDiGraph`
    /// object from an input adjacency matrix. The node weights will be the
    /// index from the matrix. The edge weights will be a complex value of the
    /// value from the matrix.
    ///
    /// This differs from the
    /// :meth:`~rustworkx.PyDiGraph.from_adjacency_matrix` in that the type of
    /// the elements of the input matrix in this method must be a ``complex``
    /// (specifically a ``numpy.complex128``) and the output graph edge weights
    /// will be ``complex`` too. While in
    /// :meth:`~rustworkx.PyDiGraph.from_adjacency_matrix` the matrix elements
    /// are of type ``float`` (specifically ``numpy.float64``) and the edge
    /// weights in the output graph will be ``float`` too.
    ///
    /// :param ndarray matrix: The input numpy array adjacency matrix to create
    ///     a new :class:`~rustworkx.PyDiGraph` object from. It must be a 2
    ///     dimensional array and be a ``complex``/``np.complex128`` data type.
    /// :param complex null_value: An optional complex that will treated as a
    ///     null value. If any element in the input matrix is this value it
    ///     will be treated as not an edge. By default this is ``0.0+0.0j``
    ///
    /// :returns: A new graph object generated from the adjacency matrix
    /// :rtype: PyDiGraph
    #[staticmethod]
    #[pyo3(signature=(matrix, null_value=Complex64::zero()), text_signature = "(matrix, /, null_value=0.0+0.0j)")]
    pub fn from_complex_adjacency_matrix<'p>(
        py: Python<'p>,
        matrix: PyReadonlyArray2<'p, Complex64>,
        null_value: Complex64,
    ) -> PyResult<PyDiGraph> {
        _from_adjacency_matrix(py, matrix, null_value)
    }

    /// Add another PyDiGraph object into this PyDiGraph
    ///
    /// :param PyDiGraph other: The other PyDiGraph object to add onto this
    ///     graph.
    /// :param dict[int, tuple[int, tuple[int, T]]] node_map: A dictionary
    ///     mapping node indices from this
    ///     PyDiGraph object to node indices in the other PyDiGraph object.
    ///     The key is a node index in this graph and the value is a tuple
    ///     of the node index in the other graph to add an edge to and the
    ///     weight of that edge. For example::
    ///
    ///         {
    ///             1: (2, "weight"),
    ///             2: (4, "weight2")
    ///         }
    ///
    /// :param Callable node_map_func: An optional Python callable that will take in a
    ///     single node weight/data object and return a new node weight/data
    ///     object that will be used when adding an node from other onto this
    ///     graph.
    /// :param Callable edge_map_func: An optional Python callable that will take in a
    ///     single edge weight/data object and return a new edge weight/data
    ///     object that will be used when adding an edge from other onto this
    ///     graph.
    ///
    /// :returns: new_node_ids: A dictionary mapping node index from the other
    ///     PyDiGraph to the corresponding node index in this PyDAG after they've been
    ///     combined
    /// :rtype: dict[int, int]
    ///
    /// For example, start by building a graph:
    ///
    /// .. jupyter-execute::
    ///
    ///   import rustworkx as rx
    ///   from rustworkx.visualization import mpl_draw
    ///
    ///   # Build first graph and visualize:
    ///   graph = rx.PyDiGraph()
    ///   node_a = graph.add_node('A')
    ///   node_b = graph.add_child(node_a, 'B', 'A to B')
    ///   node_c = graph.add_child(node_b, 'C', 'B to C')
    ///   mpl_draw(graph, with_labels=True, labels=str, edge_labels=str)
    ///
    /// Then build a second one:
    ///
    /// .. jupyter-execute::
    ///
    ///   # Build second graph and visualize:
    ///   other_graph = rx.PyDiGraph()
    ///   node_d = other_graph.add_node('D')
    ///   other_graph.add_child(node_d, 'E', 'D to E')
    ///   mpl_draw(other_graph, with_labels=True, labels=str, edge_labels=str)
    ///
    /// Finally compose the ``other_graph`` onto ``graph``
    ///
    /// .. jupyter-execute::
    ///
    ///   node_map = {node_b: (node_d, 'B to D')}
    ///   graph.compose(other_graph, node_map)
    ///   mpl_draw(graph, with_labels=True, labels=str, edge_labels=str)
    ///
    #[pyo3(text_signature = "(self, other, node_map, /, node_map_func=None, edge_map_func=None)", signature = (other, node_map, node_map_func=None, edge_map_func=None))]
    pub fn compose(
        &mut self,
        py: Python,
        other: &PyDiGraph,
        node_map: HashMap<usize, (usize, PyObject)>,
        node_map_func: Option<PyObject>,
        edge_map_func: Option<PyObject>,
    ) -> PyResult<PyObject> {
        let mut new_node_map: DictMap<NodeIndex, NodeIndex> =
            DictMap::with_capacity(other.node_count());

        // TODO: Reimplement this without looping over the graphs
        // Loop over other nodes add to self graph
        for node in other.graph.node_indices() {
            let new_index = self.graph.add_node(weight_transform_callable(
                py,
                &node_map_func,
                &other.graph[node],
            )?);
            new_node_map.insert(node, new_index);
        }

        // loop over other edges and add to self graph
        for edge in other.graph.edge_references() {
            let new_p_index = new_node_map.get(&edge.source()).unwrap();
            let new_c_index = new_node_map.get(&edge.target()).unwrap();
            let weight = weight_transform_callable(py, &edge_map_func, edge.weight())?;
            self._add_edge(*new_p_index, *new_c_index, weight)?;
        }
        // Add edges from map
        for (this_index, (index, weight)) in node_map.iter() {
            let new_index = new_node_map.get(&NodeIndex::new(*index)).unwrap();
            self._add_edge(
                NodeIndex::new(*this_index),
                *new_index,
                weight.clone_ref(py),
            )?;
        }
        let out_dict = PyDict::new(py);
        for (orig_node, new_node) in new_node_map.iter() {
            out_dict.set_item(orig_node.index(), new_node.index())?;
        }
        Ok(out_dict.into())
    }

    /// Substitute a node with a PyDigraph object
    ///
    /// :param int node: The index of the node to be replaced with the PyDiGraph object
    /// :param PyDiGraph other: The other graph to replace ``node`` with
    /// :param Callable edge_map_fn: A callable object that will take 3 position
    ///     parameters, ``(source, target, weight)`` to represent an edge either to
    ///     or from ``node`` in this graph. The expected return value from this
    ///     callable is the node index of the node in ``other`` that an edge should
    ///     be to/from. If None is returned, that edge will be skipped and not
    ///     be copied.
    /// :param Callable node_filter: An optional callable object that when used
    ///     will receive a node's payload object from ``other`` and return
    ///     ``True`` if that node is to be included in the graph or not.
    /// :param Callable edge_weight_map: An optional callable object that when
    ///     used will receive an edge's weight/data payload from ``other`` and
    ///     will return an object to use as the weight for a newly created edge
    ///     after the edge is mapped from ``other``. If not specified the weight
    ///     from the edge in ``other`` will be copied by reference and used.
    ///
    /// :returns: A mapping of node indices in ``other`` to the equivalent node
    ///     in this graph.
    /// :rtype: NodeMap
    ///
    /// .. note::
    ///
    ///    The return type is a :class:`rustworkx.NodeMap` which is an unordered
    ///    type. So it does not provide a deterministic ordering between objects
    ///    when iterated over (although the same object will have a consistent
    ///    order when iterated over multiple times).
    ///
    #[pyo3(
        text_signature = "(self, node, other, edge_map_fn, /, node_filter=None, edge_weight_map=None)",
        signature = (node, other, edge_map_fn, node_filter=None, edge_weight_map=None)
    )]
    fn substitute_node_with_subgraph(
        &mut self,
        py: Python,
        node: usize,
        other: &PyDiGraph,
        edge_map_fn: PyObject,
        node_filter: Option<PyObject>,
        edge_weight_map: Option<PyObject>,
    ) -> PyResult<NodeMap> {
        let weight_map_fn = |obj: &PyObject, weight_fn: &Option<PyObject>| -> PyResult<PyObject> {
            match weight_fn {
                Some(weight_fn) => weight_fn.call1(py, (obj,)),
                None => Ok(obj.clone_ref(py)),
            }
        };
        let map_fn = |source: usize, target: usize, weight: &PyObject| -> PyResult<Option<usize>> {
            let res = edge_map_fn.call1(py, (source, target, weight))?;
            res.extract(py)
        };
        let filter_fn = |obj: &PyObject, filter_fn: &Option<PyObject>| -> PyResult<bool> {
            match filter_fn {
                Some(filter) => {
                    let res = filter.call1(py, (obj,))?;
                    res.extract(py)
                }
                None => Ok(true),
            }
        };
        let node_index: NodeIndex = NodeIndex::new(node);
        if self.graph.node_weight(node_index).is_none() {
            return Err(PyIndexError::new_err(format!(
                "Specified node {} is not in this graph",
                node
            )));
        }
        // Copy nodes from other to self
        let mut out_map: DictMap<usize, usize> = DictMap::with_capacity(other.node_count());
        for node in other.graph.node_indices() {
            let node_weight = other.graph[node].clone_ref(py);
            if !filter_fn(&node_weight, &node_filter)? {
                continue;
            }
            let new_index = self.graph.add_node(node_weight);
            out_map.insert(node.index(), new_index.index());
        }
        // If no nodes are copied bail here since there is nothing left
        // to do.
        if out_map.is_empty() {
            self.remove_node(node_index.index())?;
            // Return a new empty map to clear allocation from out_map
            return Ok(NodeMap {
                node_map: DictMap::new(),
            });
        }
        // Copy edges from other to self
        for edge in other.graph.edge_references().filter(|edge| {
            out_map.contains_key(&edge.target().index())
                && out_map.contains_key(&edge.source().index())
        }) {
            self._add_edge(
                NodeIndex::new(out_map[&edge.source().index()]),
                NodeIndex::new(out_map[&edge.target().index()]),
                weight_map_fn(edge.weight(), &edge_weight_map)?,
            )?;
        }
        // Add edges to/from node to nodes in other
        let in_edges: Vec<(NodeIndex, NodeIndex, PyObject)> = self
            .graph
            .edges_directed(node_index, petgraph::Direction::Incoming)
            .map(|edge| (edge.source(), edge.target(), edge.weight().clone_ref(py)))
            .collect();
        let out_edges: Vec<(NodeIndex, NodeIndex, PyObject)> = self
            .graph
            .edges_directed(node_index, petgraph::Direction::Outgoing)
            .map(|edge| (edge.source(), edge.target(), edge.weight().clone_ref(py)))
            .collect();
        for (source, target, weight) in in_edges {
            let old_index = map_fn(source.index(), target.index(), &weight)?;
            let target_out = match old_index {
                Some(old_index) => match out_map.get(&old_index) {
                    Some(new_index) => NodeIndex::new(*new_index),
                    None => {
                        return Err(PyIndexError::new_err(format!(
                            "No mapped index {} found",
                            old_index
                        )))
                    }
                },
                None => continue,
            };
            self._add_edge(source, target_out, weight)?;
        }
        for (source, target, weight) in out_edges {
            let old_index = map_fn(source.index(), target.index(), &weight)?;
            let source_out = match old_index {
                Some(old_index) => match out_map.get(&old_index) {
                    Some(new_index) => NodeIndex::new(*new_index),
                    None => {
                        return Err(PyIndexError::new_err(format!(
                            "No mapped index {} found",
                            old_index
                        )))
                    }
                },
                None => continue,
            };
            self._add_edge(source_out, target, weight)?;
        }
        // Remove node
        self.remove_node(node_index.index())?;
        Ok(NodeMap { node_map: out_map })
    }

    /// Substitute a set of nodes with a single new node.
    ///
    /// :param list[int] nodes: A set of nodes to be removed and replaced
    ///     by the new node. Any nodes not in the graph are ignored.
    ///     If empty, this method behaves like :meth:`~PyDiGraph.add_node`
    ///     (but slower).
    /// :param S obj: The data/weight to associate with the new node.
    /// :param bool check_cycle: If set to ``True``, validates
    ///     that the contraction will not introduce cycles before
    ///     modifying the graph. If set to ``False``, validation is
    ///     skipped. If not provided, inherits the value
    ///     of ``check_cycle`` from this instance of
    ///     :class:`~rustworkx.PyDiGraph`.
    /// :param Callable weight_combo_fn: An optional Python callable that, when
    ///     specified, is used to merge parallel edges introduced by the
    ///     contraction, which will occur when multiple nodes in
    ///     ``nodes`` have an incoming edge
    ///     from the same source node or when multiple nodes in
    ///     ``nodes`` have an outgoing edge to the same target node.
    ///     If this instance of :class:`~rustworkx.PyDiGraph` is a multigraph,
    ///     leave this unspecified to preserve parallel edges. If unspecified
    ///     when not a multigraph, parallel edges and their weights will be
    ///     combined by choosing one of the edge's weights arbitrarily based
    ///     on an internal iteration order, subject to change.
    /// :returns: The index of the newly created node
    /// :rtype: int
    /// :raises DAGWouldCycle: The cycle check is enabled and the
    ///     contraction would introduce cycle(s).
    #[pyo3(text_signature = "(self, nodes, obj, /, check_cycle=None, weight_combo_fn=None)", signature = (nodes, obj, check_cycle=None, weight_combo_fn=None))]
    pub fn contract_nodes(
        &mut self,
        py: Python,
        nodes: Vec<usize>,
        obj: PyObject,
        check_cycle: Option<bool>,
        weight_combo_fn: Option<PyObject>,
    ) -> RxPyResult<usize> {
        let nodes = nodes.into_iter().map(|i| NodeIndex::new(i));
        let check_cycle = check_cycle.unwrap_or(self.check_cycle);
        let res = match (weight_combo_fn, &self.multigraph) {
            (Some(user_callback), _) => {
                self.graph
                    .contract_nodes_simple(nodes, obj, check_cycle, |w1, w2| {
                        user_callback.call1(py, (w1, w2))
                    })?
            }
            (None, false) => {
                // By default, just take first edge.
                self.graph
                    .contract_nodes_simple(nodes, obj, check_cycle, move |w1, _| {
                        Ok::<_, PyErr>(w1.clone_ref(py))
                    })?
            }
            (None, true) => self.graph.contract_nodes(nodes, obj, check_cycle)?,
        };
        Ok(res.index())
    }

    /// Check if contracting the specified nodes can occur without introducing cycles.
    ///
    /// :param list[int] nodes: A set of node indices to check for contraction.
    /// :returns: `True` if contraction can proceed without creating cycles, `False` otherwise.
    #[pyo3(text_signature = "(self, nodes, /)",signature = (nodes))]
    pub fn can_contract_without_cycle(&self, nodes: Vec<usize>) -> bool {
        let index_set: IndexSet<NodeIndex, RandomState> =
            nodes.into_iter().map(NodeIndex::new).collect();
        can_contract(&self.graph, &index_set)
    }

    /// Return a new PyDiGraph object for a subgraph of this graph and a NodeMap
    /// object that maps the nodes of the subgraph to the nodes of the original graph.
    ///
    /// .. note::
    ///     This method is identical to :meth:`.subgraph()` but includes a
    ///     NodeMap object that maps the nodes of the subgraph to the nodes of
    ///     the original graph.
    ///
    /// :param list[int] nodes: A list of node indices to generate the subgraph
    ///     from. If a node index is included that is not present in the graph
    ///     it will silently be ignored.
    /// :param bool preserve_attrs: If set to ``True`` the attributes of the PyDiGraph
    ///     will be copied by reference to be the attributes of the output
    ///     subgraph. By default this is set to ``False`` and the :attr:`~.PyDiGraph.attrs`
    ///     attribute will be ``None`` in the subgraph.
    ///
    /// :returns: A tuple containing a new PyDiGraph object representing a subgraph of this graph
    ///     and a NodeMap object that maps the nodes of the subgraph to the nodes of the original graph.
    ///     It is worth noting that node and edge weight/data payloads are
    ///     passed by reference so if you update (not replace) an object used
    ///     as the weight in graph or the subgraph it will also be updated in
    ///     the other.
    /// :rtype: tuple[PyDiGraph, NodeMap]
    ///
    #[pyo3(signature=(nodes, preserve_attrs=false), text_signature = "(self, nodes, /, preserve_attrs=False)")]
    pub fn subgraph_with_nodemap(
        &self,
        py: Python,
        nodes: Vec<usize>,
        preserve_attrs: bool,
    ) -> (PyDiGraph, NodeMap) {
        let node_set: HashSet<usize> = nodes.iter().cloned().collect();
        // mapping from original node index to new node index
        let mut node_map: HashMap<NodeIndex, NodeIndex> = HashMap::with_capacity(nodes.len());
        // mapping from new node index to original node index
        let mut node_dict: DictMap<usize, usize> = DictMap::with_capacity(nodes.len());
        let node_filter = |node: NodeIndex| -> bool { node_set.contains(&node.index()) };
        let mut out_graph = StablePyGraph::<Directed>::new();
        let filtered = NodeFiltered(&self.graph, node_filter);
        for node in filtered.node_references() {
            let new_node = out_graph.add_node(node.1.clone_ref(py));
            node_map.insert(node.0, new_node);
            node_dict.insert(new_node.index(), node.0.index());
        }
        for edge in filtered.edge_references() {
            let new_source = *node_map.get(&edge.source()).unwrap();
            let new_target = *node_map.get(&edge.target()).unwrap();
            out_graph.add_edge(new_source, new_target, edge.weight().clone_ref(py));
        }
        let attrs = if preserve_attrs {
            self.attrs.clone_ref(py)
        } else {
            py.None()
        };
        let node_map = NodeMap {
            node_map: node_dict,
        };
        let subgraph = PyDiGraph {
            graph: out_graph,
            node_removed: false,
            cycle_state: algo::DfsSpace::default(),
            check_cycle: self.check_cycle,
            multigraph: self.multigraph,
            attrs,
        };
        (subgraph, node_map)
    }

    /// Return a new PyDiGraph object for a subgraph of this graph.
    ///
    /// .. note::
    ///     To return a NodeMap object that maps the nodes of the subgraph to
    ///     the nodes of the original graph, use :meth:`.subgraph_with_nodemap()`.
    ///
    /// :param list[int] nodes: A list of node indices to generate the subgraph
    ///     from. If a node index is included that is not present in the graph
    ///     it will silently be ignored.
    /// :param bool preserve_attrs: If set to the True the attributes of the PyDiGraph
    ///     will be copied by reference to be the attributes of the output
    ///     subgraph. By default this is set to False and the :attr:`~.PyDiGraph.attrs`
    ///     attribute will be ``None`` in the subgraph.
    ///
    /// :returns: A new PyDiGraph object representing a subgraph of this graph.
    ///     It is worth noting that node and edge weight/data payloads are
    ///     passed by reference so if you update (not replace) an object used
    ///     as the weight in graph or the subgraph it will also be updated in
    ///     the other.
    /// :rtype: PyDiGraph
    ///
    #[pyo3(signature=(nodes, preserve_attrs=false), text_signature = "(self, nodes, /, preserve_attrs=False)")]
    pub fn subgraph(&self, py: Python, nodes: Vec<usize>, preserve_attrs: bool) -> PyDiGraph {
        let (subgraph, _) = self.subgraph_with_nodemap(py, nodes, preserve_attrs);
        subgraph
    }

    /// Return a new PyDiGraph object for an edge induced subgraph of this graph
    ///
    /// The induced subgraph contains each edge in `edge_list` and each node
    /// incident to any of those edges.
    ///
    /// :param list[tuple[int, int]] edge_list: A list of edge tuples
    ///     (2-tuples with the source and
    ///     target node) to generate the subgraph from. In cases of parallel
    ///     edges for a multigraph all edges between the specified node. In case
    ///     of an edge specified that doesn't exist in the graph it will be
    ///     silently ignored.
    ///
    /// :returns: The edge subgraph
    /// :rtype: PyDiGraph
    ///
    #[pyo3(text_signature = "(self, edge_list, /)")]
    pub fn edge_subgraph(&self, edge_list: Vec<[usize; 2]>) -> PyDiGraph {
        // Filter non-existent edges
        let edges: Vec<[usize; 2]> = edge_list
            .into_iter()
            .filter(|x| {
                let source = NodeIndex::new(x[0]);
                let target = NodeIndex::new(x[1]);
                self.graph.find_edge(source, target).is_some()
            })
            .collect();

        let nodes: HashSet<NodeIndex> = edges
            .iter()
            .flat_map(|x| x.iter())
            .copied()
            .map(NodeIndex::new)
            .collect();
        let mut edge_set: HashSet<[NodeIndex; 2]> = HashSet::with_capacity(edges.len());
        for edge in edges {
            let source_index = NodeIndex::new(edge[0]);
            let target_index = NodeIndex::new(edge[1]);
            edge_set.insert([source_index, target_index]);
        }
        let mut out_graph = self.clone();
        for node in self
            .graph
            .node_indices()
            .filter(|node| !nodes.contains(node))
        {
            out_graph.graph.remove_node(node);
            out_graph.node_removed = true;
        }
        for edge in self
            .graph
            .edge_references()
            .filter(|edge| !edge_set.contains(&[edge.source(), edge.target()]))
        {
            out_graph.graph.remove_edge(edge.id());
        }
        out_graph
    }

    /// Check if the graph is symmetric
    ///
    /// :returns: True if the graph is symmetric
    /// :rtype: bool
    #[pyo3(text_signature = "(self)")]
    pub fn is_symmetric(&self) -> bool {
        let mut edges: HashSet<(NodeIndex, NodeIndex)> = HashSet::new();
        for (source, target) in self
            .graph
            .edge_references()
            .map(|edge| (edge.source(), edge.target()))
        {
            let edge = (source, target);
            let reversed = (target, source);
            if edges.contains(&reversed) {
                edges.remove(&reversed);
            } else {
                edges.insert(edge);
            }
        }
        edges.is_empty()
    }

    /// Make edges in graph symmetric
    ///
    /// This function iterates over all the edges in the graph, adding for each
    /// edge the reversed edge, unless one is already present. Note the edge insertion
    /// is not fixed and the edge indices are not guaranteed to be consistent
    /// between executions of this method on identical graphs.
    ///
    /// :param Callable edge_payload: This optional argument takes in a callable which will
    ///     be passed a single positional argument the data payload for an edge that will
    ///     have a reverse copied in the graph. The returned value from this callable will
    ///     be used as the data payload for the new edge created. If this is not specified
    ///     then by default the data payload will be copied when the reverse edge is added.
    ///     If there are parallel edges, then one of the edges (typically the one with the lower
    ///     index, but this is not a guarantee) will be copied.
    #[pyo3(signature = (edge_payload_fn=None))]
    pub fn make_symmetric(
        &mut self,
        py: Python,
        edge_payload_fn: Option<PyObject>,
    ) -> PyResult<()> {
        let edges: HashMap<[NodeIndex; 2], EdgeIndex> = self
            .graph
            .edge_references()
            .map(|edge| ([edge.source(), edge.target()], edge.id()))
            .collect();
        for ([edge_source, edge_target], edge_index) in edges.iter() {
            if !edges.contains_key(&[*edge_target, *edge_source]) {
                let forward_weight = self.graph.edge_weight(*edge_index).unwrap();
                let weight: PyObject = match edge_payload_fn.as_ref() {
                    Some(callback) => callback.call1(py, (forward_weight,))?,
                    None => forward_weight.clone_ref(py),
                };
                self._add_edge(*edge_target, *edge_source, weight)?;
            }
        }
        Ok(())
    }

    /// Generate a new PyGraph object from this graph
    ///
    /// This will create a new :class:`~rustworkx.PyGraph` object from this
    /// graph. All edges in this graph will be created as undirected edges in
    /// the new graph object. For directed graphs with bidirectional edges, you
    /// can set `multigraph=False` to condense them into a single edge and specify
    /// a function to combine the weights/data of the edges.
    /// Do note that the node and edge weights/data payloads will be passed
    /// by reference to the new :class:`~rustworkx.PyGraph` object.
    ///
    /// .. note::
    ///
    ///     The node indices in the output :class:`~rustworkx.PyGraph` may
    ///     differ if nodes have been removed.
    ///
    /// :param bool multigraph: If set to `False` the output graph will not
    ///     allow parallel edges. Instead parallel edges will be condensed
    ///     into a single edge and their data will be combined using
    ///     `weight_combo_fn`. If `weight_combo_fn` is not provided, the data
    ///     of the edge with the largest index will be kept. Default: `True`.
    /// :param Callable weight_combo_fn: An optional python callable that will take in a
    ///     two edge weight/data object and return a new edge weight/data
    ///     object that will be used when adding an edge between two nodes
    ///     connected by multiple edges (of either direction) in the original
    ///     directed graph.
    ///
    /// :returns: A new PyGraph object with an undirected edge for every
    ///     directed edge in this graph
    /// :rtype: PyGraph
    #[pyo3(signature=(multigraph=true, weight_combo_fn=None), text_signature = "(self, /, multigraph=True, weight_combo_fn=None)")]
    pub fn to_undirected(
        &self,
        py: Python,
        multigraph: bool,
        weight_combo_fn: Option<PyObject>,
    ) -> PyResult<crate::graph::PyGraph> {
        let node_count = self.node_count();
        let mut new_graph = if multigraph {
            StablePyGraph::<Undirected>::with_capacity(node_count, self.graph.edge_count())
        } else {
            // If multigraph is false edge count is difficult to predict
            // without counting parallel edges. So, just stick with 0 and
            // reallocate dynamically
            StablePyGraph::<Undirected>::with_capacity(node_count, 0)
        };

        let mut node_map: HashMap<NodeIndex, NodeIndex> = HashMap::with_capacity(node_count);

        let combine = |a: &PyObject,
                       b: &PyObject,
                       combo_fn: &Option<PyObject>|
         -> PyResult<Option<PyObject>> {
            match combo_fn {
                Some(combo_fn) => {
                    let res = combo_fn.call1(py, (a, b))?;
                    Ok(Some(res))
                }
                None => Ok(None),
            }
        };

        for node_index in self.graph.node_indices() {
            let node = self.graph[node_index].clone_ref(py);
            let new_index = new_graph.add_node(node);
            node_map.insert(node_index, new_index);
        }
        for edge in self.graph.edge_references() {
            let &source = node_map.get(&edge.source()).unwrap();
            let &target = node_map.get(&edge.target()).unwrap();
            let weight = edge.weight().clone_ref(py);
            if multigraph {
                new_graph.add_edge(source, target, weight);
            } else {
                let exists = new_graph.find_edge(source, target);
                match exists {
                    Some(index) => {
                        let old_weight = new_graph.edge_weight_mut(index).unwrap();
                        match combine(old_weight, edge.weight(), &weight_combo_fn)? {
                            Some(value) => {
                                *old_weight = value;
                            }
                            None => {
                                *old_weight = weight;
                            }
                        }
                    }
                    None => {
                        new_graph.add_edge(source, target, weight);
                    }
                }
            }
        }
        Ok(crate::graph::PyGraph {
            graph: new_graph,
            node_removed: false,
            multigraph,
            attrs: py.None(),
        })
    }

    /// Return a shallow copy of the graph
    ///
    /// All node and edge weight/data payloads in the copy will have a
    /// shared reference to the original graph.
    #[pyo3(text_signature = "(self)")]
    pub fn copy(&self) -> PyDiGraph {
        self.clone()
    }

    /// Reverse the direction of all edges in the graph, in place.
    ///
    /// This method modifies the graph instance to reverse the direction of all edges.
    /// It does so by iterating over all edges in the graph and removing each edge,
    /// then adding a new edge in the opposite direction with the same weight.
    ///
    /// For Example::
    ///
    ///     import rustworkx as rx
    ///
    ///     graph = rx.PyDiGraph()
    ///
    ///     # Generate a path directed path graph with weights
    ///     graph.extend_from_weighted_edge_list([
    ///         (0, 1, 3),
    ///         (1, 2, 5),
    ///         (2, 3, 2),
    ///     ])
    ///     # Reverse edges
    ///     graph.reverse()
    ///
    ///     assert graph.weighted_edge_list() == [(3, 2, 2), (2, 1, 5), (1, 0, 3)];
    #[pyo3(text_signature = "(self)")]
    pub fn reverse(&mut self, py: Python) {
        let indices = self.graph.edge_indices().collect::<Vec<EdgeIndex>>();
        for idx in indices {
            let (source_node, dest_node) = self.graph.edge_endpoints(idx).unwrap();
            let weight = self.graph.edge_weight(idx).unwrap().clone_ref(py);
            self.graph.remove_edge(idx);
            self.graph.add_edge(dest_node, source_node, weight);
        }
    }

    /// Filters a graph's nodes by some criteria conditioned on a node's data payload and returns those nodes' indices.
    ///
    /// This function takes in a function as an argument. This filter function will be passed in a node's data payload and is
    /// required to return a boolean value stating whether the node's data payload fits some criteria.
    ///
    /// For example::
    ///
    ///     from rustworkx import PyDiGraph
    ///
    ///     graph = PyDiGraph()
    ///     graph.add_nodes_from(list(range(5)))
    ///
    ///     def my_filter_function(node):
    ///         return node > 2
    ///
    ///     indices = graph.filter_nodes(my_filter_function)
    ///     assert indices == [3, 4]
    ///
    /// :param Callable filter_function: Function with which to filter nodes
    ///
    /// :returns: The node indices that match the filter
    /// :rtype: NodeIndices
    #[pyo3(text_signature = "(self, filter_function)")]
    pub fn filter_nodes(&self, py: Python, filter_function: PyObject) -> PyResult<NodeIndices> {
        let filter = |nindex: NodeIndex| -> PyResult<bool> {
            let res = filter_function.call1(py, (&self.graph[nindex],))?;
            res.extract(py)
        };

        let mut n = Vec::with_capacity(self.graph.node_count());
        for node_index in self.graph.node_indices() {
            if filter(node_index)? {
                n.push(node_index.index())
            };
        }
        Ok(NodeIndices { nodes: n })
    }

    /// Filters a graph's edges by some criteria conditioned on a edge's data payload and returns those edges' indices.
    ///
    /// This function takes in a function as an argument. This filter function will be passed in an edge's data payload and is
    /// required to return a boolean value stating whether the edge's data payload fits some criteria.
    ///
    /// For example::
    ///
    ///     from rustworkx import PyGraph
    ///     from rustworkx.generators import complete_graph
    ///
    ///     graph = PyGraph()
    ///     graph.add_nodes_from(range(3))
    ///     graph.add_edges_from([(0, 1, 'A'), (0, 1, 'B'), (1, 2, 'C')])
    ///
    ///     def my_filter_function(edge):
    ///         if edge:
    ///             return edge == 'B'
    ///         return False
    ///
    ///     indices = graph.filter_edges(my_filter_function)
    ///     assert indices == [1]
    ///
    /// :param Callable filter_function: Function with which to filter edges
    ///
    /// :returns: The edge indices that match the filter
    /// :rtype: EdgeIndices
    #[pyo3(text_signature = "(self, filter_function)")]
    pub fn filter_edges(&self, py: Python, filter_function: PyObject) -> PyResult<EdgeIndices> {
        let filter = |eindex: EdgeIndex| -> PyResult<bool> {
            let res = filter_function.call1(py, (&self.graph[eindex],))?;
            res.extract(py)
        };

        let mut e = Vec::with_capacity(self.graph.edge_count());
        for edge_index in self.graph.edge_indices() {
            if filter(edge_index)? {
                e.push(edge_index.index())
            };
        }
        Ok(EdgeIndices { edges: e })
    }

    /// Return the number of nodes in the graph
    fn __len__(&self) -> PyResult<usize> {
        Ok(self.graph.node_count())
    }

    fn __getitem__(&self, idx: usize) -> PyResult<&PyObject> {
        match self.graph.node_weight(NodeIndex::new(idx)) {
            Some(data) => Ok(data),
            None => Err(PyIndexError::new_err("No node found for index")),
        }
    }

    fn __setitem__(&mut self, idx: usize, value: PyObject) -> PyResult<()> {
        let data = match self.graph.node_weight_mut(NodeIndex::new(idx)) {
            Some(node_data) => node_data,
            None => return Err(PyIndexError::new_err("No node found for index")),
        };
        *data = value;
        Ok(())
    }

    fn __delitem__(&mut self, idx: usize) -> PyResult<()> {
        match self.graph.remove_node(NodeIndex::new(idx)) {
            Some(_) => {
                self.node_removed = true;
                Ok(())
            }
            None => Err(PyIndexError::new_err("No node found for index")),
        }
    }

    #[classmethod]
    #[pyo3(signature = (key, /))]
    pub fn __class_getitem__(
        cls: &Bound<'_, PyType>,
        key: &Bound<'_, PyAny>,
    ) -> PyResult<PyObject> {
        let alias = PyGenericAlias::new(cls.py(), cls.as_any(), key)?;
        Ok(alias.into())
    }

    // Functions to enable Python Garbage Collection

    // Function for PyTypeObject.tp_traverse [1][2] used to tell Python what
    // objects the PyDiGraph has strong references to.
    //
    // [1] https://docs.python.org/3/c-api/typeobj.html#c.PyTypeObject.tp_traverse
    // [2] https://pyo3.rs/v0.12.4/class/protocols.html#garbage-collector-integration
    fn __traverse__(&self, visit: PyVisit) -> Result<(), PyTraverseError> {
        for node in self
            .graph
            .node_indices()
            .map(|node| self.graph.node_weight(node).unwrap())
        {
            visit.call(node)?;
        }
        for edge in self
            .graph
            .edge_indices()
            .map(|edge| self.graph.edge_weight(edge).unwrap())
        {
            visit.call(edge)?;
        }
        visit.call(&self.attrs)?;
        Ok(())
    }

    // Function for PyTypeObject.tp_clear [1][2] used to tell Python's GC how
    // to drop all references held by a PyDiGraph object when the GC needs to
    // break reference cycles.
    //
    // ]1] https://docs.python.org/3/c-api/typeobj.html#c.PyTypeObject.tp_clear
    // [2] https://pyo3.rs/v0.12.4/class/protocols.html#garbage-collector-integration
    fn __clear__(&mut self, py: Python) {
        self.graph = StablePyGraph::<Directed>::new();
        self.node_removed = false;
        self.attrs = py.None();
    }
}

fn is_cycle_check_required(dag: &PyDiGraph, a: NodeIndex, b: NodeIndex) -> bool {
    let mut parents_a = dag
        .graph
        .neighbors_directed(a, petgraph::Direction::Incoming);
    let mut children_b = dag
        .graph
        .neighbors_directed(b, petgraph::Direction::Outgoing);
    parents_a.next().is_some() && children_b.next().is_some() && dag.graph.find_edge(a, b).is_none()
}

fn weight_transform_callable(
    py: Python,
    map_fn: &Option<PyObject>,
    value: &PyObject,
) -> PyResult<PyObject> {
    match map_fn {
        Some(map_fn) => {
            let res = map_fn.call1(py, (value,))?;
            res.into_py_any(py)
        }
        None => Ok(value.clone_ref(py)),
    }
}

fn _from_adjacency_matrix<'p, T>(
    py: Python<'p>,
    matrix: PyReadonlyArray2<'p, T>,
    null_value: T,
) -> PyResult<PyDiGraph>
where
    T: Copy + std::cmp::PartialEq + numpy::Element + pyo3::IntoPyObject<'p> + IsNan,
{
    let array = matrix.as_array();
    let shape = array.shape();
    let mut out_graph = StablePyGraph::<Directed>::new();
    let _node_indices: Vec<NodeIndex> = (0..shape[0])
        .map(|node| Ok(out_graph.add_node(node.into_py_any(py)?)))
        .collect::<PyResult<Vec<NodeIndex>>>()?;
    for (index, row) in array.axis_iter(Axis(0)).enumerate() {
        let source_index = NodeIndex::new(index);
        for (target_index, elem) in row.iter().enumerate() {
            if null_value.is_nan() {
                if !elem.is_nan() {
                    out_graph.add_edge(
                        source_index,
                        NodeIndex::new(target_index),
                        elem.into_py_any(py)?,
                    );
                }
            } else if *elem != null_value {
                out_graph.add_edge(
                    source_index,
                    NodeIndex::new(target_index),
                    elem.into_py_any(py)?,
                );
            }
        }
    }
    Ok(PyDiGraph {
        graph: out_graph,
        cycle_state: algo::DfsSpace::default(),
        check_cycle: false,
        node_removed: false,
        multigraph: true,
        attrs: py.None(),
    })
}

/// Simple wrapper newtype that lets us use `Py` pointers as hash keys with the equality defined by
/// the pointer address.  This is equivalent to using Python's `is` operator for comparisons.
/// Using a newtype rather than casting the pointer to `usize` inline lets us retrieve a copy of
/// the reference from the key entry.
struct PyAnyId(Py<PyAny>);
impl PyAnyId {
    fn clone_ref(&self, py: Python) -> Py<PyAny> {
        self.0.clone_ref(py)
    }
}
impl ::std::hash::Hash for PyAnyId {
    fn hash<H: ::std::hash::Hasher>(&self, state: &mut H) {
        (self.0.as_ptr() as usize).hash(state)
    }
}
impl PartialEq for PyAnyId {
    fn eq(&self, other: &Self) -> bool {
        self.0.as_ptr() == other.0.as_ptr()
    }
}
impl Eq for PyAnyId {}

/// Internal-only helper class used by `remove_node_retain_edges_by_key` to store its data as a
/// typed object in a Python dictionary.
#[pyclass]
struct RemoveNodeEdgeValue {
    weight: Py<PyAny>,
    nodes: Vec<NodeIndex>,
}

Qiskit / rustworkx / 15950659371

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