diff --git a/R/simulation_flow_check.R b/R/simulation_flow_check.R
index 4990237..3a61840 100644
--- a/R/simulation_flow_check.R
+++ b/R/simulation_flow_check.R
@@ -1,13 +1,13 @@
 #
 # Example simulation script with data output
 #
+
 # Import dependencies
 source("R/zzz.R")
 initialize_python_env()
 check_python_env()
 
 library(reticulate)
-#library(rEpiabm)
 library(here)
 library(tidyr)
 
@@ -24,7 +24,7 @@ base_dir <- here()
 pe$Parameters$set_file(here("data", "simple_parameters.json"))
 
 # Method to set the seed at the start of the simulation, for reproducibility
-pe$routine$Simulation$set_random_seed(seed=as.integer(42))
+pe$routine$Simulation$set_random_seed(seed = as.integer(42))
 
 # Pop_params are used to configure the population structure being used in this
 # simulation.
@@ -37,7 +37,7 @@ pop_params <- list(
 )
 
 # Create a population based on the parameters given.
-population = pe$routine$ToyPopulationFactory()$make_pop(pop_params)
+population <- pe$routine$ToyPopulationFactory()$make_pop(pop_params)
 
 # sim_params
 sim_params <- list(
@@ -101,10 +101,12 @@ df <- read.csv(filename)
 library(ggplot2)
 
 # Reshape the data from wide to long format using base R
-status_columns <- c("InfectionStatus.Susceptible", 
-                    "InfectionStatus.InfectMild",
-                    "InfectionStatus.Recovered",
-                    "InfectionStatus.Dead")
+status_columns <- c(
+  "InfectionStatus.Susceptible",
+  "InfectionStatus.InfectMild",
+  "InfectionStatus.Recovered",
+  "InfectionStatus.Dead"
+)
 
 df_long <- pivot_longer(
   df,
@@ -112,24 +114,35 @@ df_long <- pivot_longer(
   names_to = "Status",
   values_to = "Count"
 )
-df_long$Status <- factor(df_long$Status,
-                        levels = status_columns,
-                        labels = c("Susceptible", "Infected", "Recovered", "Dead"))
+
+df_long$Status <- factor(
+  df_long$Status,
+  levels = status_columns,
+  labels = c("Susceptible", "Infected", "Recovered", "Dead")
+)
 
 # Create the plot
 p <- ggplot(df_long, aes(x = time, y = Count, color = Status)) +
   geom_line() +
-  scale_color_manual(values = c("Susceptible" = "blue",
-                                "Infected" = "red",
-                                "Recovered" = "green",
-                                "Dead" = "black")) +
+  scale_color_manual(
+    values = c(
+      "Susceptible" = "blue",
+      "Infected" = "red",
+      "Recovered" = "green",
+      "Dead" = "black"
+    )
+  ) +
   theme_minimal() +
-  labs(title = "SIR Model Flow",
-       x = "Time",
-       y = "Count") +
-  theme(legend.position = "right",
-        plot.title = element_text(hjust = 0.5),
-        panel.grid.minor = element_blank())
+  labs(
+    title = "SIR Model Flow",
+    x = "Time",
+    y = "Count"
+  ) +
+  theme(
+    legend.position = "right",
+    plot.title = element_text(hjust = 0.5),
+    panel.grid.minor = element_blank()
+  )
 
 # Display the plot
 print(p)
diff --git a/R/zzz.R b/R/zzz.R
index 4657dce..2f63f42 100644
--- a/R/zzz.R
+++ b/R/zzz.R
@@ -6,12 +6,13 @@ local <- new.env()
 #' @param python_version Character. Python version to use (e.g., "3.8")
 #' @return Logical indicating success
 #' @keywords internal
-create_python_env <- function(env_name = "r-reticulate", python_version = "3.9") {
+create_python_env <- function(
+    env_name = "r-reticulate",
+    python_version = "3.9") {
   tryCatch({
     # Check if virtualenv package is available
     if (!reticulate::virtualenv_exists(env_name)) {
       message(sprintf("Creating new Python virtual environment: %s", env_name))
-      
       # Create virtual environment with system site packages to help with SSL
       reticulate::virtualenv_create(
         envname = env_name,
@@ -20,12 +21,12 @@ create_python_env <- function(env_name = "r-reticulate", python_version = "3.9")
         system_site_packages = TRUE
       )
     }
-    
     # Activate the environment
     reticulate::use_virtualenv(env_name, required = TRUE)
     return(TRUE)
   }, error = function(e) {
-    warning(sprintf("Failed to create/activate Python environment: %s", e$message))
+    warning(sprintf("Failed to create/activate Python environment: %s",
+                    e$message))
     return(FALSE)
   })
 }
@@ -33,24 +34,24 @@ create_python_env <- function(env_name = "r-reticulate", python_version = "3.9")
 .onLoad <- function(libname, pkgname) {
   # Create and activate Python environment
   env_success <- create_python_env()
-  
   if (!env_success) {
-    warning("Failed to set up Python environment. Some functionality may be limited.")
+    warning("Failed to set up Python environment. 
+    Some functionality may be limited.")
     return()
   }
-  
   # Configure reticulate to use the package's environment
   reticulate::configure_environment(pkgname)
-  
   # Install required packages if not present
   ensure_python_dependencies()
-  
   # Import dependencies with error handling
   tryCatch({
     load_python_modules()
   }, error = function(e) {
-    warning(sprintf("Error loading Python dependencies: 
-    %s\nPlease run check_python_env() to diagnose issues.", e$message))
+    warning(sprintf(
+      "Error loading Python dependencies: %s\nPlease 
+      run check_python_env() to diagnose issues.",
+      e$message
+    ))
   })
 }
 
@@ -61,8 +62,8 @@ ensure_python_dependencies <- function() {
   reticulate::py_run_string("
 import sys
 import subprocess
-subprocess.check_call([sys.executable, '-m', 'pip', 'install', 
-'--upgrade', 'pip'])
+subprocess.check_call([sys.executable
+, '-m', 'pip', 'install', '--upgrade', 'pip'])
   ")
   # Install required packages
   reticulate::py_run_string("
@@ -72,9 +73,8 @@ import subprocess
 # Install basic packages
 packages = ['numpy', 'pandas', 'matplotlib']
 for package in packages:
-    subprocess.check_call([sys.executable, '-m', 'pip', 'install',
-     '--upgrade', package])
-
+    subprocess.check_call([sys.executable, '-m', 'pip', 
+    'install', '--upgrade', package])
 # Install pyEpiabm from GitHub
 subprocess.check_call([
     sys.executable, '-m', 'pip', 'install', '--upgrade',
@@ -94,9 +94,9 @@ for package in packages:
         
 print('Missing packages:', missing if missing else 'None')
   ")
-  if (length(result$missing) > 0){
-    stop("Failed to install required packages: ", paste(result$missing,
-    collapse = ", "))
+  if (length(result$missing) > 0) {
+    stop("Failed to install required packages: ",
+         paste(result$missing, collapse = ", "))
   }
   message("All required packages installed successfully")
 }
@@ -132,8 +132,9 @@ check_python_env <- function() {
   # Print Python information
   cat(sprintf("Python version: %s\n", reticulate::py_version()))
   cat(sprintf("Python path: %s\n", python_config$python))
-  cat(sprintf("virtualenv: %s\n", if (is.null(python_config$virtualenv))
-   "None" else python_config$virtualenv))
+  cat(sprintf("virtualenv: %s\n",
+              if (is.null(python_config$virtualenv)) "None"
+              else python_config$virtualenv))
   # Check required packages
   required_packages <- c("numpy", "pandas", "matplotlib", "pyEpiabm")
   cat("\nPackage Status:\n")
@@ -142,8 +143,9 @@ check_python_env <- function() {
     if (reticulate::py_module_available(pkg)) {
       # Try to get version information
       tryCatch({
-        version <- reticulate::py_eval(sprintf("__import__('%s').__version__",
-        pkg))
+        version <- reticulate::py_eval(
+          sprintf("__import__('%s').__version__", pkg)
+        )
         cat(sprintf("✓ %s (version %s)\n", pkg, version))
         pkg_status[[pkg]] <- TRUE
       }, error = function(e) {