Update rust toolchain and fix clippy warnings

.github/workflows/coverage.yaml

@@ -26,7 +26,7 @@ jobs:
       - name: Run cargo-tarpaulin
         uses: actions-rs/[email protected]
         with:
-          version: '0.19.1'
+          version: '0.31.0'
           args: '--exclude-files *_test.rs *tests* *experiments*'
 
       - name: Upload to codecov.io

CHANGELOG.md

@@ -8,6 +8,10 @@ are already published. So, I stick to it for now.
 
 ## [Unreleased]
 
+### Changed
+
+* update rust version
+
 
 ## [1.24.0] 2024-07-13
 

Dockerfile

@@ -1,4 +1,4 @@
-FROM rust:1.79-alpine AS Builder
+FROM rust:1.80-alpine AS Builder
 
 LABEL maintainer="Ilya Builuk <[email protected]>" \
       org.opencontainers.image.title="A Vehicle Routing Problem solver CLI" \

rosomaxa/src/algorithms/math/remedian.rs

@@ -11,9 +11,9 @@ pub type RemedianUsize = Remedian<usize, fn(&usize, &usize) -> Ordering>;
 ///
 /// References:
 /// - P.J. Rousseeuw, G.W. Bassett Jr., "The remedian: A robust averaging method for large data sets",
-/// Journal of the American Statistical  Association, vol. 85 (1990), pp. 97-104
+///   Journal of the American Statistical  Association, vol. 85 (1990), pp. 97-104
 /// - Domenico Cantone, Micha Hofri, "Further analysis of the remedian algorithm", Theoretical Computer
-/// Science, vol. 495 (2013), pp. 1-16
+///   Science, vol. 495 (2013), pp. 1-16
 pub struct Remedian<T, F>
 where
     T: Clone,

vrp-cli/Cargo.toml

@@ -33,7 +33,7 @@ serde_json.workspace = true
 csv = { version = "1.3.0", optional = true }
 
 [target.'cfg(not(target_arch = "wasm32"))'.dependencies]
-clap = "4.5.9"
+clap = "4.5.11"
 ctrlc = { version = "3.4.4", features = ["termination"] }
 num_cpus = "1.16.0"
 

vrp-cli/src/lib.rs

@@ -338,7 +338,7 @@ mod c_interop {
 }
 
 #[cfg(feature = "py_bindings")]
-#[cfg(all(not(target_arch = "wasm32"), not(tarpaulin)))]
+#[cfg(not(target_arch = "wasm32"))]
 mod py_interop {
     use super::*;
     use crate::extensions::solve::config::read_config;

vrp-core/src/construction/heuristics/insertions.rs

@@ -255,14 +255,12 @@ impl InsertionHeuristic {
     /// Runs common insertion heuristic algorithm using given selector specializations.
     pub fn process(
         &self,
-        insertion_ctx: InsertionContext,
+        mut insertion_ctx: InsertionContext,
         job_selector: &(dyn JobSelector + Send + Sync),
         route_selector: &(dyn RouteSelector + Send + Sync),
         leg_selection: &LegSelection,
         result_selector: &(dyn ResultSelector + Send + Sync),
     ) -> InsertionContext {
-        let mut insertion_ctx = insertion_ctx;
-
         prepare_insertion_ctx(&mut insertion_ctx);
 
         while !insertion_ctx.solution.required.is_empty()

vrp-core/src/models/goal.rs

@@ -243,14 +243,14 @@ impl GoalBuilder {
 /// job values, etc. Each feature consists of three optional parts (but at least one should be defined):
 ///
 /// * **constraint**: an invariant which should be hold to have a feasible VRP solution in the end.
-/// A good examples are hard constraints such as capacity, time, travel limits, etc.
+///   A good examples are hard constraints such as capacity, time, travel limits, etc.
 ///
 /// * **objective**: an objective of the optimization such as minimization of unassigned jobs or tours.
-///  All objectives form together a hierarchy which describes a goal of optimization, including
-///  various soft constraints: assignment of preferred jobs, optional breaks, etc. This helps to
-///  guide the search on the global objective level (e.g. comparison of various solutions in order to
-///  find out which one is "better") and local objective level (e.g. which job should be inserted next
-///  into specific solution).
+///   All objectives form together a hierarchy which describes a goal of optimization, including
+///   various soft constraints: assignment of preferred jobs, optional breaks, etc. This helps to
+///   guide the search on the global objective level (e.g. comparison of various solutions in order to
+///   find out which one is "better") and local objective level (e.g. which job should be inserted next
+///   into specific solution).
 ///
 /// * **state**: the corresponding cached data of constraint/objective to speed up/control their evaluations.
 ///
@@ -260,7 +260,7 @@ impl GoalBuilder {
 /// * hard constraint can be defined without objective as this is an invariant
 /// * state should be used to avoid expensive calculations during insertion evaluation phase.
 ///   `FeatureObjective::estimate` and `FeatureConstraint::evaluate` methods are called during this phase.
-///  Additionally, it can be used to do some solution modifications at `FeatureState::accept_solution_state`.
+///   Additionally, it can be used to do some solution modifications at `FeatureState::accept_solution_state`.
 #[derive(Clone, Default)]
 pub struct Feature {
     /// An unique id of the feature.