petgraph/
lib.rs

1//! `petgraph` is a graph data structure library.
2//!
3//! Graphs are collections of nodes, and edges between nodes. `petgraph`
4//! provides several [graph types](index.html#graph-types) (each differing in the
5//! tradeoffs taken in their internal representation),
6//! [algorithms](./algo/index.html#functions) on those graphs, and functionality to
7//! [output graphs](./dot/struct.Dot.html) in
8//! [`graphviz`](https://www.graphviz.org/) format. Both nodes and edges
9//! can have arbitrary associated data, and edges may be either directed or undirected.
10//!
11//! # Example
12//!
13//! ```rust
14//! use petgraph::graph::{NodeIndex, UnGraph};
15//! use petgraph::algo::{dijkstra, min_spanning_tree};
16//! use petgraph::data::FromElements;
17//! use petgraph::dot::{Dot, Config};
18//!
19//! // Create an undirected graph with `i32` nodes and edges with `()` associated data.
20//! let g = UnGraph::<i32, ()>::from_edges(&[
21//!     (1, 2), (2, 3), (3, 4),
22//!     (1, 4)]);
23//!
24//! // Find the shortest path from `1` to `4` using `1` as the cost for every edge.
25//! let node_map = dijkstra(&g, 1.into(), Some(4.into()), |_| 1);
26//! assert_eq!(&1i32, node_map.get(&NodeIndex::new(4)).unwrap());
27//!
28//! // Get the minimum spanning tree of the graph as a new graph, and check that
29//! // one edge was trimmed.
30//! let mst = UnGraph::<_, _>::from_elements(min_spanning_tree(&g));
31//! assert_eq!(g.raw_edges().len() - 1, mst.raw_edges().len());
32//!
33//! // Output the tree to `graphviz` `DOT` format
34//! println!("{:?}", Dot::with_config(&mst, &[Config::EdgeNoLabel]));
35//! // graph {
36//! //     0 [label="\"0\""]
37//! //     1 [label="\"0\""]
38//! //     2 [label="\"0\""]
39//! //     3 [label="\"0\""]
40//! //     1 -- 2
41//! //     3 -- 4
42//! //     2 -- 3
43//! // }
44//! ```
45//!
46//! # Graph types
47//!
48//! * [`Graph`](./graph/struct.Graph.html) -
49//!   An adjacency list graph with arbitrary associated data.
50//! * [`StableGraph`](./stable_graph/struct.StableGraph.html) -
51//!   Similar to `Graph`, but it keeps indices stable across removals.
52//! * [`GraphMap`](./graphmap/struct.GraphMap.html) -
53//!   An adjacency list graph backed by a hash table. The node identifiers are the keys
54//!   into the table.
55//! * [`MatrixGraph`](./matrix_graph/struct.MatrixGraph.html) -
56//!   An adjacency matrix graph.
57//! * [`CSR`](./csr/struct.Csr.html) -
58//!   A sparse adjacency matrix graph with arbitrary associated data.
59//!
60//! ### Generic parameters
61//!
62//! Each graph type is generic over a handful of parameters. All graphs share 3 common
63//! parameters, `N`, `E`, and `Ty`. This is a broad overview of what those are. Each
64//! type's documentation will have finer detail on these parameters.
65//!
66//! `N` & `E` are called *weights* in this implementation, and are associated with
67//! nodes and edges respectively. They can generally be of arbitrary type, and don't have to
68//! be what you might conventionally consider weight-like. For example, using `&str` for `N`
69//! will work. Many algorithms that require costs let you provide a cost function that
70//! translates your `N` and `E` weights into costs appropriate to the algorithm. Some graph
71//! types and choices do impose bounds on `N` or `E`.
72//! [`min_spanning_tree`](./algo/fn.min_spanning_tree.html) for example requires edge weights that
73//! implement [`PartialOrd`](https://doc.rust-lang.org/stable/core/cmp/trait.PartialOrd.html).
74//! [`GraphMap`](./graphmap/struct.GraphMap.html) requires node weights that can serve as hash
75//! map keys, since that graph type does not create standalone node indices.
76//!
77//! `Ty` controls whether edges are [`Directed`](./enum.Directed.html) or
78//! [`Undirected`](./enum.Undirected.html).
79//!
80//! `Ix` appears on graph types that use indices. It is exposed so you can control
81//! the size of node and edge indices, and therefore the memory footprint of your graphs.
82//! Allowed values are `u8`, `u16`, `u32`, and `usize`, with `u32` being the default.
83//!
84//! ### Shorthand types
85//!
86//! Each graph type vends a few shorthand type definitions that name some specific
87//! generic choices. For example, [`DiGraph<_, _>`](./graph/type.DiGraph.html) is shorthand
88//! for [`Graph<_, _, Directed>`](graph/struct.Graph.html).
89//! [`UnMatrix<_, _>`](./matrix_graph/type.UnMatrix.html) is shorthand for
90//! [`MatrixGraph<_, _, Undirected>`](./matrix_graph/struct.MatrixGraph.html). Each graph type's
91//! module documentation lists the available shorthand types.
92//!
93//! # Crate features
94//!
95//! * **serde-1** -
96//!   Defaults off. Enables serialization for ``Graph, StableGraph, GraphMap`` using
97//!   [`serde 1.0`](https://crates.io/crates/serde). May require a more recent version
98//!   of Rust than petgraph alone.
99//! * **graphmap** -
100//!   Defaults on. Enables [`GraphMap`](./graphmap/struct.GraphMap.html).
101//! * **stable_graph** -
102//!   Defaults on. Enables [`StableGraph`](./stable_graph/struct.StableGraph.html).
103//! * **matrix_graph** -
104//!   Defaults on. Enables [`MatrixGraph`](./matrix_graph/struct.MatrixGraph.html).
105//!
106#![doc(html_root_url = "https://docs.rs/petgraph/0.4/")]
107
108extern crate fixedbitset;
109#[cfg(feature = "graphmap")]
110extern crate indexmap;
111
112#[cfg(feature = "serde-1")]
113extern crate serde;
114#[cfg(feature = "serde-1")]
115#[macro_use]
116extern crate serde_derive;
117
118#[cfg(all(feature = "serde-1", test))]
119extern crate itertools;
120
121#[doc(no_inline)]
122pub use crate::graph::Graph;
123
124pub use crate::Direction::{Incoming, Outgoing};
125
126#[macro_use]
127mod macros;
128mod scored;
129
130// these modules define trait-implementing macros
131#[macro_use]
132pub mod visit;
133#[macro_use]
134pub mod data;
135
136pub mod acyclic;
137pub mod adj;
138pub mod algo;
139pub mod csr;
140pub mod dot;
141#[cfg(feature = "generate")]
142pub mod generate;
143pub mod graph6;
144mod graph_impl;
145#[cfg(feature = "graphmap")]
146pub mod graphmap;
147mod iter_format;
148mod iter_utils;
149#[cfg(feature = "matrix_graph")]
150pub mod matrix_graph;
151#[cfg(feature = "quickcheck")]
152mod quickcheck;
153#[cfg(feature = "serde-1")]
154mod serde_utils;
155mod traits_graph;
156pub mod unionfind;
157mod util;
158
159pub mod operator;
160pub mod prelude;
161
162/// `Graph<N, E, Ty, Ix>` is a graph datastructure using an adjacency list representation.
163pub mod graph {
164    pub use crate::graph_impl::{
165        edge_index, node_index, DefaultIx, DiGraph, Edge, EdgeIndex, EdgeIndices, EdgeReference,
166        EdgeReferences, EdgeWeightsMut, Edges, EdgesConnecting, Externals, Frozen, Graph,
167        GraphIndex, IndexType, Neighbors, Node, NodeIndex, NodeIndices, NodeReferences,
168        NodeWeightsMut, UnGraph, WalkNeighbors,
169    };
170}
171
172#[cfg(feature = "stable_graph")]
173pub use crate::graph_impl::stable_graph;
174
175// Index into the NodeIndex and EdgeIndex arrays
176/// Edge direction.
177#[derive(Clone, Copy, Debug, PartialEq, PartialOrd, Ord, Eq, Hash)]
178#[repr(usize)]
179#[cfg_attr(
180    feature = "serde-1",
181    derive(serde_derive::Serialize, serde_derive::Deserialize)
182)]
183pub enum Direction {
184    /// An `Outgoing` edge is an outward edge *from* the current node.
185    Outgoing = 0,
186    /// An `Incoming` edge is an inbound edge *to* the current node.
187    Incoming = 1,
188}
189
190impl Direction {
191    /// Return the opposite `Direction`.
192    #[inline]
193    pub fn opposite(self) -> Direction {
194        match self {
195            Outgoing => Incoming,
196            Incoming => Outgoing,
197        }
198    }
199
200    /// Return `0` for `Outgoing` and `1` for `Incoming`.
201    #[inline]
202    pub fn index(self) -> usize {
203        (self as usize) & 0x1
204    }
205}
206
207#[doc(hidden)]
208pub use crate::Direction as EdgeDirection;
209
210/// Marker type for a directed graph.
211#[derive(Clone, Copy, Debug)]
212#[cfg_attr(
213    feature = "serde-1",
214    derive(serde_derive::Serialize, serde_derive::Deserialize)
215)]
216pub enum Directed {}
217
218/// Marker type for an undirected graph.
219#[derive(Clone, Copy, Debug)]
220#[cfg_attr(
221    feature = "serde-1",
222    derive(serde_derive::Serialize, serde_derive::Deserialize)
223)]
224pub enum Undirected {}
225
226/// A graph's edge type determines whether it has directed edges or not.
227pub trait EdgeType {
228    fn is_directed() -> bool;
229}
230
231impl EdgeType for Directed {
232    #[inline]
233    fn is_directed() -> bool {
234        true
235    }
236}
237
238impl EdgeType for Undirected {
239    #[inline]
240    fn is_directed() -> bool {
241        false
242    }
243}
244
245/// Convert an element like `(i, j)` or `(i, j, w)` into
246/// a triple of source, target, edge weight.
247///
248/// For `Graph::from_edges` and `GraphMap::from_edges`.
249pub trait IntoWeightedEdge<E> {
250    type NodeId;
251    fn into_weighted_edge(self) -> (Self::NodeId, Self::NodeId, E);
252}
253
254impl<Ix, E> IntoWeightedEdge<E> for (Ix, Ix)
255where
256    E: Default,
257{
258    type NodeId = Ix;
259
260    fn into_weighted_edge(self) -> (Ix, Ix, E) {
261        let (s, t) = self;
262        (s, t, E::default())
263    }
264}
265
266impl<Ix, E> IntoWeightedEdge<E> for (Ix, Ix, E) {
267    type NodeId = Ix;
268    fn into_weighted_edge(self) -> (Ix, Ix, E) {
269        self
270    }
271}
272
273impl<Ix, E> IntoWeightedEdge<E> for (Ix, Ix, &E)
274where
275    E: Clone,
276{
277    type NodeId = Ix;
278    fn into_weighted_edge(self) -> (Ix, Ix, E) {
279        let (a, b, c) = self;
280        (a, b, c.clone())
281    }
282}
283
284impl<Ix, E> IntoWeightedEdge<E> for &(Ix, Ix)
285where
286    Ix: Copy,
287    E: Default,
288{
289    type NodeId = Ix;
290    fn into_weighted_edge(self) -> (Ix, Ix, E) {
291        let (s, t) = *self;
292        (s, t, E::default())
293    }
294}
295
296impl<Ix, E> IntoWeightedEdge<E> for &(Ix, Ix, E)
297where
298    Ix: Copy,
299    E: Clone,
300{
301    type NodeId = Ix;
302    fn into_weighted_edge(self) -> (Ix, Ix, E) {
303        self.clone()
304    }
305}