use alloc::collections::BinaryHeap;
use core::hash::Hash;

use hashbrown::hash_map::{
    Entry::{Occupied, Vacant},
    HashMap,
};

use crate::algo::Measure;
use crate::scored::MinScored;
use crate::visit::{EdgeRef, IntoEdges, VisitMap, Visitable};

/// \[Generic\] Dijkstra's shortest path algorithm.
///
/// Compute the length of the shortest path from `start` to every reachable
/// node.
///
/// The graph should be `Visitable` and implement `IntoEdges`. The function
/// `edge_cost` should return the cost for a particular edge, which is used
/// to compute path costs. Edge costs must be non-negative.
///
/// If `goal` is not `None`, then the algorithm terminates once the `goal` node's
/// cost is calculated.
///
/// Returns a `HashMap` that maps `NodeId` to path cost.
/// # Example
/// ```rust
/// use petgraph::Graph;
/// use petgraph::algo::dijkstra;
/// use petgraph::prelude::*;
/// use hashbrown::HashMap;
///
/// let mut graph: Graph<(), (), Directed> = Graph::new();
/// let a = graph.add_node(()); // node with no weight
/// let b = graph.add_node(());
/// let c = graph.add_node(());
/// let d = graph.add_node(());
/// let e = graph.add_node(());
/// let f = graph.add_node(());
/// let g = graph.add_node(());
/// let h = graph.add_node(());
/// // z will be in another connected component
/// let z = graph.add_node(());
///
/// graph.extend_with_edges(&[
///     (a, b),
///     (b, c),
///     (c, d),
///     (d, a),
///     (e, f),
///     (b, e),
///     (f, g),
///     (g, h),
///     (h, e),
/// ]);
/// // a ----> b ----> e ----> f
/// // ^       |       ^       |
/// // |       v       |       v
/// // d <---- c       h <---- g
///
/// let expected_res: HashMap<NodeIndex, usize> = [
///     (a, 3),
///     (b, 0),
///     (c, 1),
///     (d, 2),
///     (e, 1),
///     (f, 2),
///     (g, 3),
///     (h, 4),
/// ].iter().cloned().collect();
/// let res = dijkstra(&graph, b, None, |_| 1);
/// assert_eq!(res, expected_res);
/// // z is not inside res because there is not path from b to z.
/// ```
pub fn dijkstra<G, F, K>(
    graph: G,
    start: G::NodeId,
    goal: Option<G::NodeId>,
    mut edge_cost: F,
) -> HashMap<G::NodeId, K>
where
    G: IntoEdges + Visitable,
    G::NodeId: Eq + Hash,
    F: FnMut(G::EdgeRef) -> K,
    K: Measure + Copy,
{
    let mut visited = graph.visit_map();
    let mut scores = HashMap::new();
    //let mut predecessor = HashMap::new();
    let mut visit_next = BinaryHeap::new();
    let zero_score = K::default();
    scores.insert(start, zero_score);
    visit_next.push(MinScored(zero_score, start));
    while let Some(MinScored(node_score, node)) = visit_next.pop() {
        if visited.is_visited(&node) {
            continue;
        }
        if goal.as_ref() == Some(&node) {
            break;
        }
        for edge in graph.edges(node) {
            let next = edge.target();
            if visited.is_visited(&next) {
                continue;
            }
            let next_score = node_score + edge_cost(edge);
            match scores.entry(next) {
                Occupied(ent) => {
                    if next_score < *ent.get() {
                        *ent.into_mut() = next_score;
                        visit_next.push(MinScored(next_score, next));
                        //predecessor.insert(next.clone(), node.clone());
                    }
                }
                Vacant(ent) => {
                    ent.insert(next_score);
                    visit_next.push(MinScored(next_score, next));
                    //predecessor.insert(next.clone(), node.clone());
                }
            }
        }
        visited.visit(node);
    }
    scores
}
