feat: Make SerDe optional

src/algorithm/neighbour/cover_tree.rs

@@ -24,7 +24,7 @@
 //! ```
 use std::fmt::Debug;
 
-use serde::{Deserialize, Serialize};
+#[cfg(feature = "serde")] use serde::{Deserialize, Serialize};
 
 use crate::algorithm::sort::heap_select::HeapSelection;
 use crate::error::{Failed, FailedError};
@@ -32,7 +32,8 @@ use crate::math::distance::Distance;
 use crate::math::num::RealNumber;
 
 /// Implements Cover Tree algorithm
-#[derive(Serialize, Deserialize, Debug)]
+#[cfg_attr(feature = "serde", derive(Serialize, Deserialize))]
+#[derive(Debug)]
 pub struct CoverTree<T, F: RealNumber, D: Distance<T, F>> {
     base: F,
     inv_log_base: F,
@@ -56,7 +57,8 @@ impl<T, F: RealNumber, D: Distance<T, F>> PartialEq for CoverTree<T, F, D> {
     }
 }
 
-#[derive(Debug, Serialize, Deserialize)]
+#[cfg_attr(feature = "serde", derive(Serialize, Deserialize))]
+#[derive(Debug)]
 struct Node<F: RealNumber> {
     idx: usize,
     max_dist: F,
@@ -65,7 +67,7 @@ struct Node<F: RealNumber> {
     scale: i64,
 }
 
-#[derive(Debug, Serialize, Deserialize)]
+#[derive(Debug)]
 struct DistanceSet<F: RealNumber> {
     idx: usize,
     dist: Vec<F>,

src/algorithm/neighbour/linear_search.rs

@@ -22,7 +22,7 @@
 //!
 //! ```
 
-use serde::{Deserialize, Serialize};
+#[cfg(feature = "serde")] use serde::{Deserialize, Serialize};
 use std::cmp::{Ordering, PartialOrd};
 use std::marker::PhantomData;
 
@@ -32,7 +32,8 @@ use crate::math::distance::Distance;
 use crate::math::num::RealNumber;
 
 /// Implements Linear Search algorithm, see [KNN algorithms](../index.html)
-#[derive(Serialize, Deserialize, Debug)]
+#[cfg_attr(feature = "serde", derive(Serialize, Deserialize))]
+#[derive(Debug)]
 pub struct LinearKNNSearch<T, F: RealNumber, D: Distance<T, F>> {
     distance: D,
     data: Vec<T>,

src/algorithm/neighbour/mod.rs

@@ -35,7 +35,7 @@ use crate::algorithm::neighbour::linear_search::LinearKNNSearch;
 use crate::error::Failed;
 use crate::math::distance::Distance;
 use crate::math::num::RealNumber;
-use serde::{Deserialize, Serialize};
+#[cfg(feature = "serde")] use serde::{Deserialize, Serialize};
 
 pub(crate) mod bbd_tree;
 /// tree data structure for fast nearest neighbor search
@@ -45,7 +45,8 @@ pub mod linear_search;
 
 /// Both, KNN classifier and regressor benefits from underlying search algorithms that helps to speed up queries.
 /// `KNNAlgorithmName` maintains a list of supported search algorithms, see [KNN algorithms](../algorithm/neighbour/index.html)
-#[derive(Serialize, Deserialize, Debug, Clone)]
+#[cfg_attr(feature = "serde", derive(Serialize, Deserialize))]
+#[derive(Debug, Clone)]
 pub enum KNNAlgorithmName {
     /// Heap Search algorithm, see [`LinearSearch`](../algorithm/neighbour/linear_search/index.html)
     LinearSearch,
@@ -53,7 +54,8 @@ pub enum KNNAlgorithmName {
     CoverTree,
 }
 
-#[derive(Serialize, Deserialize, Debug)]
+#[cfg_attr(feature = "serde", derive(Serialize, Deserialize))]
+#[derive(Debug)]
 pub(crate) enum KNNAlgorithm<T: RealNumber, D: Distance<Vec<T>, T>> {
     LinearSearch(LinearKNNSearch<Vec<T>, T, D>),
     CoverTree(CoverTree<Vec<T>, T, D>),