diff --git a/src/multithreading/mod.rs b/src/multithreading/mod.rs
index 5c3ed53..71dabb6 100644
--- a/src/multithreading/mod.rs
+++ b/src/multithreading/mod.rs
@@ -4,24 +4,24 @@
 //! threads are available. If so the pool will directly launch a new thread to run the supplied function.
 //! In case no threads are available the job will be stalled for execution until a thread is free to run the first
 //! stalled job.
-//! 
+//!
 //! The pool will also keep track of all the handles that [`std::thread::spawn`] returns. Hence after executing a job
 //! the pool still queries the result of the function which can be retrieved any time after the submission.
 //! After retrieving the result of the function the handle is discarded and cannot be accessed again through the thread pool.
-//! 
+//!
 //! # Threads
 //! The maximum number of threads to be used can be specified when creating a new thread pool.
 //! Alternatively the thread pool can be advised to automatically determine the recommend amount of threads to use.
 //! Note that this has its limitations due to possible side effects of sandboxing, containerization or vms.
 //! For further information see: [`thread::available_parallelism`]
-//! 
+//!
 //! # Memory consumption over time
 //! The pool will store the handle for every thread launched constantly increasing the memory consumption.
 //! It should be noted that the pool won't perform any kind of cleanup of the stored handles, meaning it is recommended to either make regular calls to
 //! `join_all` or `get_finished` in order to clear the vector of handles to avoid endless memory consumption.
 //! Alternatively, you can use the function `with_threads_and_drop_handles` to create a new pool that discard all thread
 //! handles after the threads are finished. This will automatically reduce the memory consumption of the pool over time.
-//! 
+//!
 //! # Portability
 //! This implementation is not fully platform independent. This is due to the usage of [`std::sync::atomic::AtomicUsize`].
 //! This type is used to remove some locks from otherwise used [`std::sync::Mutex`] wrapping a [`usize`].
@@ -36,7 +36,7 @@ use std::{
     collections::VecDeque,
     num::NonZeroUsize,
     sync::{
-        atomic::{AtomicUsize, Ordering, AtomicBool},
+        atomic::{AtomicBool, AtomicUsize, Ordering},
         Arc, Mutex,
     },
     thread::{self, JoinHandle},
@@ -90,13 +90,13 @@ fn get_default_thread_count() -> usize {
 /// Additionally this implementation relies on using the `load` and `store` operations
 /// instead of using more comfortable one like `fetch_add` in order to avoid unnecessary calls
 /// to `unwrap` or `expected` from [`std::sync::MutexGuard`].
-/// 
+///
 /// # Memory consumption over time
 /// The pool will store the handle for every thread launched constantly increasing the memory consumption.
 /// It should be noted that the pool won't perform any kind of cleanup of the stored handles, meaning it is recommended to either make regular calls to
 /// `join_all` or `get_finished` in order to clear the vector of handles to avoid endless memory consumption.
 /// Alternatively, you can use the function `with_threads_and_drop_handles` to create a new pool that discard all thread
-/// handles after the threads are finished. This will automatically reduce the memory consumption of the pool over time. 
+/// handles after the threads are finished. This will automatically reduce the memory consumption of the pool over time.
 #[allow(dead_code)]
 #[derive(Debug)]
 pub struct ThreadPool<F, T>
@@ -132,7 +132,7 @@ where
             // will be initialized to 0
             threads: Arc::new(AtomicUsize::new(0)),
             // do not drop handles by default
-            drop_handles: Arc::new(AtomicBool::new(false))
+            drop_handles: Arc::new(AtomicBool::new(false)),
         }
     }
 }
@@ -173,10 +173,13 @@ where
     /// supplying a number of threads to great may negatively impact performance as the system may not
     /// be able to full fill the required needs
     /// # Memory usage
-    /// if `drop_handles` is set to [`Bool::false`] the pool will continue to store the handles of 
+    /// if `drop_handles` is set to [`Bool::false`] the pool will continue to store the handles of
     /// launched threads. This causes memory consumption to rise over time as more and more
     /// threads are launched.
-    pub fn with_threads_and_drop_handles(max_thread_count: NonZeroUsize, drop_handles: bool) -> Self {
+    pub fn with_threads_and_drop_handles(
+        max_thread_count: NonZeroUsize,
+        drop_handles: bool,
+    ) -> Self {
         Self {
             max_thread_count: max_thread_count.get(),
             drop_handles: Arc::new(AtomicBool::new(drop_handles)),
@@ -318,7 +321,13 @@ fn execute<F, T>(
         let next = queue.lock().unwrap().pop_front();
         if let Some(next_closure) = next {
             // if we have sth. to execute, spawn a new thread
-            execute(queue, handles_copy.clone(), threads, drop.clone(), next_closure);
+            execute(
+                queue,
+                handles_copy.clone(),
+                threads,
+                drop.clone(),
+                next_closure,
+            );
         } else {
             // nothing to execute this thread will run out without any work to do
             // decrement the amount of used threads