Loosen trait constraints and simplify structure for longest_path (Qis…

…kit#1195)

In the recently merged Qiskit#1192 a new generic DAG longest_path function was
added to rustworkx-core. However, the trait bounds on the function were
a bit tighter than they needed to be. The traits were forcing NodeId to
be of a NodeIndex type and this wasn't really required. The only
requirement that the NodeId type can be put on a hashmap and do a
partial compare (that implements Hash, Eq, and PartialOrd). Also the
IntoNeighborsDirected wasn't required because it's methods weren't ever
used. This commit loosens the traits bounds to facilitate this. At the
same time this also simplifies the code structure a bit to reduce the
separation of the rust code structure in the rustworkx crate using
longest_path().

rustworkx-core/src/dag_algo.rs

@@ -9,13 +9,15 @@
 // WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the
 // License for the specific language governing permissions and limitations
 // under the License.
+
+use std::cmp::Eq;
+use std::hash::Hash;
+
 use hashbrown::HashMap;
 
 use petgraph::algo;
-use petgraph::graph::NodeIndex;
 use petgraph::visit::{
-    EdgeRef, GraphBase, GraphProp, IntoEdgesDirected, IntoNeighborsDirected, IntoNodeIdentifiers,
-    Visitable,
+    EdgeRef, GraphBase, GraphProp, IntoEdgesDirected, IntoNodeIdentifiers, Visitable,
 };
 use petgraph::Directed;
 
@@ -51,7 +53,6 @@ type LongestPathResult<G, T, E> = Result<Option<(Vec<NodeId<G>>, T)>, E>;
 /// # Example
 /// ```
 /// use petgraph::graph::DiGraph;
-/// use petgraph::graph::NodeIndex;
 /// use petgraph::Directed;
 /// use rustworkx_core::dag_algo::longest_path;
 ///
@@ -69,14 +70,10 @@ type LongestPathResult<G, T, E> = Result<Option<(Vec<NodeId<G>>, T)>, E>;
 /// ```
 pub fn longest_path<G, F, T, E>(graph: G, mut weight_fn: F) -> LongestPathResult<G, T, E>
 where
-    G: GraphProp<EdgeType = Directed>
-        + IntoNodeIdentifiers
-        + IntoNeighborsDirected
-        + IntoEdgesDirected
-        + Visitable
-        + GraphBase<NodeId = NodeIndex>,
+    G: GraphProp<EdgeType = Directed> + IntoNodeIdentifiers + IntoEdgesDirected + Visitable,
     F: FnMut(G::EdgeRef) -> Result<T, E>,
     T: Num + Zero + PartialOrd + Copy,
+    <G as GraphBase>::NodeId: Hash + Eq + PartialOrd,
 {
     let mut path: Vec<NodeId<G>> = Vec::new();
     let nodes = match algo::toposort(graph, None) {
@@ -88,20 +85,20 @@ where
         return Ok(Some((path, T::zero())));
     }
 
-    let mut dist: HashMap<NodeIndex, (T, NodeIndex)> = HashMap::with_capacity(nodes.len()); // Stores the distance and the previous node
+    let mut dist: HashMap<G::NodeId, (T, G::NodeId)> = HashMap::with_capacity(nodes.len()); // Stores the distance and the previous node
 
     // Iterate over nodes in topological order
     for node in nodes {
         let parents = graph.edges_directed(node, petgraph::Direction::Incoming);
-        let mut incoming_path: Vec<(T, NodeIndex)> = Vec::new(); // Stores the distance and the previous node for each parent
+        let mut incoming_path: Vec<(T, G::NodeId)> = Vec::new(); // Stores the distance and the previous node for each parent
         for p_edge in parents {
             let p_node = p_edge.source();
             let weight: T = weight_fn(p_edge)?;
             let length = dist[&p_node].0 + weight;
             incoming_path.push((length, p_node));
         }
         // Determine the maximum distance and corresponding parent node
-        let max_path: (T, NodeIndex) = incoming_path
+        let max_path: (T, G::NodeId) = incoming_path
             .into_iter()
             .max_by(|a, b| a.0.partial_cmp(&b.0).unwrap())
             .unwrap_or((T::zero(), node)); // If there are no incoming edges, the distance is zero
@@ -114,7 +111,7 @@ where
         .max_by(|a, b| a.1.partial_cmp(b.1).unwrap())
         .unwrap();
     let mut v = *first;
-    let mut u: Option<NodeIndex> = None;
+    let mut u: Option<G::NodeId> = None;
     // Backtrack from this node to find the path
     while u.map_or(true, |u| u != v) {
         path.push(v);

src/dag_algo/mod.rs

@@ -10,8 +10,6 @@
 // License for the specific language governing permissions and limitations
 // under the License.
 
-mod longest_path;
-
 use super::DictMap;
 use hashbrown::{HashMap, HashSet};
 use indexmap::IndexSet;
@@ -22,6 +20,7 @@ use std::collections::BinaryHeap;
 use super::iterators::NodeIndices;
 use crate::{digraph, DAGHasCycle, InvalidNode, StablePyGraph};
 
+use rustworkx_core::dag_algo::longest_path as core_longest_path;
 use rustworkx_core::traversal::dfs_edges;
 
 use pyo3::exceptions::PyValueError;
@@ -32,8 +31,54 @@ use pyo3::Python;
 use petgraph::algo;
 use petgraph::graph::NodeIndex;
 use petgraph::prelude::*;
+use petgraph::stable_graph::EdgeReference;
 use petgraph::visit::NodeCount;
 
+use num_traits::{Num, Zero};
+
+/// Calculate the longest path in a directed acyclic graph (DAG).
+///
+/// This function interfaces with the Python `PyDiGraph` object to compute the longest path
+/// using the provided weight function.
+///
+/// # Arguments
+/// * `graph`: Reference to a `PyDiGraph` object.
+/// * `weight_fn`: A callable that takes the source node index, target node index, and the weight
+///   object and returns the weight of the edge as a `PyResult<T>`.
+///
+/// # Type Parameters
+/// * `F`: Type of the weight function.
+/// * `T`: The type of the edge weight. Must implement `Num`, `Zero`, `PartialOrd`, and `Copy`.
+///
+/// # Returns
+/// * `PyResult<(Vec<G::NodeId>, T)>` representing the longest path as a sequence of node indices and its total weight.
+fn longest_path<F, T>(graph: &digraph::PyDiGraph, mut weight_fn: F) -> PyResult<(Vec<usize>, T)>
+where
+    F: FnMut(usize, usize, &PyObject) -> PyResult<T>,
+    T: Num + Zero + PartialOrd + Copy,
+{
+    let dag = &graph.graph;
+
+    // Create a new weight function that matches the required signature
+    let edge_cost = |edge_ref: EdgeReference<'_, PyObject>| -> Result<T, PyErr> {
+        let source = edge_ref.source().index();
+        let target = edge_ref.target().index();
+        let weight = edge_ref.weight();
+        weight_fn(source, target, weight)
+    };
+
+    let (path, path_weight) = match core_longest_path(dag, edge_cost) {
+        Ok(Some((path, path_weight))) => (
+            path.into_iter().map(NodeIndex::index).collect(),
+            path_weight,
+        ),
+        Ok(None) => return Err(DAGHasCycle::new_err("The graph contains a cycle")),
+        Err(e) => return Err(e),
+    };
+
+    Ok((path, path_weight))
+}
+
 /// Return a pair of [`petgraph::Direction`] values corresponding to the "forwards" and "backwards"
 /// direction of graph traversal, based on whether the graph is being traved forwards (following
 /// the edges) or backward (reversing along edges).  The order of returns is (forwards, backwards).
@@ -82,7 +127,7 @@ pub fn dag_longest_path(
             }
         };
     Ok(NodeIndices {
-        nodes: longest_path::longest_path(graph, edge_weight_callable)?.0,
+        nodes: longest_path(graph, edge_weight_callable)?.0,
     })
 }
 
@@ -121,7 +166,7 @@ pub fn dag_longest_path_length(
                 None => Ok(1),
             }
         };
-    let (_, path_weight) = longest_path::longest_path(graph, edge_weight_callable)?;
+    let (_, path_weight) = longest_path(graph, edge_weight_callable)?;
     Ok(path_weight)
 }
 
@@ -163,7 +208,7 @@ pub fn dag_weighted_longest_path(
         Ok(float_res)
     };
     Ok(NodeIndices {
-        nodes: longest_path::longest_path(graph, edge_weight_callable)?.0,
+        nodes: longest_path(graph, edge_weight_callable)?.0,
     })
 }
 
@@ -204,7 +249,7 @@ pub fn dag_weighted_longest_path_length(
         }
         Ok(float_res)
     };
-    let (_, path_weight) = longest_path::longest_path(graph, edge_weight_callable)?;
+    let (_, path_weight) = longest_path(graph, edge_weight_callable)?;
     Ok(path_weight)
 }