Bump the edition to 2021

8 files changed, 1 insertions, 16 deletions

diff --git a/Cargo.toml b/Cargo.toml
index b7743a1..2132b69 100644
--- a/Cargo.toml
+++ b/Cargo.toml
@@ -2,7 +2,7 @@
 name = "acap"
 version = "0.2.0"
 authors = ["Tavian Barnes <tavianator@tavianator.com>"]
-edition = "2018"
+edition = "2021"
 description = "As Close As Possible — nearest neighbor search in Rust."
 readme = "README.md"
 repository = "https://github.com/tavianator/acap"
diff --git a/benches/benches.rs b/benches/benches.rs
index 07d21b3..e0001ac 100644
--- a/benches/benches.rs
+++ b/benches/benches.rs
@@ -8,8 +8,6 @@ use acap::vp::{FlatVpTree, VpTree};
 
 use criterion::{black_box, criterion_group, criterion_main, BatchSize, Criterion};
 
-use std::iter::FromIterator;
-
 type Point = Euclidean<[f32; 3]>;
 
 /// Generates a spiral used as the benchmark data set.
diff --git a/src/cos.rs b/src/cos.rs
index a3a4f6c..1520c41 100644
--- a/src/cos.rs
+++ b/src/cos.rs
@@ -7,7 +7,6 @@ use num_traits::real::Real;
 use num_traits::{one, zero};
 
 use std::cmp::Ordering;
-use std::convert::TryFrom;
 
 /// Compute the [cosine *similarity*] between two points.
 ///
@@ -398,7 +397,6 @@ where
 ///
 ///     # use acap::distance::Distance;
 ///     # use acap::cos::AngularDistance;
-///     # use std::convert::TryFrom;
 ///     let zero = AngularDistance::from_cos(1.0);
 ///     let pi_2 = AngularDistance::from_cos(0.0);
 ///     let pi = AngularDistance::from_cos(-1.0);
diff --git a/src/euclid.rs b/src/euclid.rs
index 3ec0af9..e1ee3c9 100644
--- a/src/euclid.rs
+++ b/src/euclid.rs
@@ -7,7 +7,6 @@ use crate::lp::Minkowski;
 use num_traits::zero;
 
 use std::cmp::Ordering;
-use std::convert::TryFrom;
 
 /// A point in Euclidean space.
 ///
@@ -155,7 +154,6 @@ where
 ///
 ///     # use acap::distance::Distance;
 ///     # use acap::euclid::EuclideanDistance;
-///     # use std::convert::TryFrom;
 ///     let a = EuclideanDistance::try_from(3).unwrap();
 ///     let b = EuclideanDistance::try_from(4).unwrap();
 ///     let c = EuclideanDistance::from_squared(a.squared_value() + b.squared_value());
diff --git a/src/exhaustive.rs b/src/exhaustive.rs
index 3f42876..7b63ef7 100644
--- a/src/exhaustive.rs
+++ b/src/exhaustive.rs
@@ -3,8 +3,6 @@
 use crate::distance::Proximity;
 use crate::knn::{ExactNeighbors, NearestNeighbors, Neighborhood};
 
-use std::iter::FromIterator;
-
 /// A [`NearestNeighbors`] implementation that does exhaustive search.
 #[derive(Clone, Debug)]
 pub struct ExhaustiveSearch<T>(Vec<T>);
diff --git a/src/kd.rs b/src/kd.rs
index 3c3699a..d9bed6a 100644
--- a/src/kd.rs
+++ b/src/kd.rs
@@ -8,8 +8,6 @@ use crate::util::Ordered;
 
 use num_traits::Signed;
 
-use std::iter::FromIterator;
-
 /// A node in a k-d tree.
 #[derive(Debug)]
 struct KdNode<T> {
diff --git a/src/knn.rs b/src/knn.rs
index 1cc1f39..444c9a7 100644
--- a/src/knn.rs
+++ b/src/knn.rs
@@ -2,8 +2,6 @@
 
 use crate::distance::{Distance, Proximity};
 
-use std::convert::TryInto;
-
 /// A nearest neighbor.
 #[derive(Clone, Copy, Debug)]
 pub struct Neighbor<V, D> {
@@ -353,8 +351,6 @@ pub mod tests {
 
     use rand::prelude::*;
 
-    use std::iter::FromIterator;
-
     type Point = Euclidean<[f32; 3]>;
 
     /// Test an [ExactNeighbors] implementation.
diff --git a/src/vp.rs b/src/vp.rs
index 4417b6b..a761cbf 100644
--- a/src/vp.rs
+++ b/src/vp.rs
@@ -7,7 +7,6 @@ use crate::util::Ordered;
 use num_traits::zero;
 
 use std::fmt::{self, Debug, Formatter};
-use std::iter::{Extend, FromIterator};
 
 /// A node in a VP tree.
 #[derive(Debug)]