diff --git a/pyperf/_process_time.py b/pyperf/_process_time.py
index f18dee20..71e03b49 100644
--- a/pyperf/_process_time.py
+++ b/pyperf/_process_time.py
@@ -22,12 +22,13 @@
 import tempfile
 import time
 
+# Try importing resource module for memory usage tracking
 try:
     import resource
 except ImportError:
     resource = None
 
-
+# Function to get maximum RSS (Resident Set Size) memory usage
 def get_max_rss(*, children):
     if resource is not None:
         if children:
@@ -35,13 +36,14 @@ def get_max_rss(*, children):
         else:
             resource_type = resource.RUSAGE_SELF
         usage = resource.getrusage(resource_type)
+        # macOS returns bytes, Linux returns kilobytes
         if sys.platform == 'darwin':
             return usage.ru_maxrss
         return usage.ru_maxrss * 1024
     else:
         return 0
 
-
+# Merge two cProfile profiling statistics files
 def merge_profile_stats_files(src, dst):
     """
     Merging one existing pstats file into another.
@@ -52,16 +54,17 @@ def merge_profile_stats_files(src, dst):
         dst_stats = pstats.Stats(dst)
         dst_stats.add(src_stats)
         dst_stats.dump_stats(dst)
-        os.unlink(src)
+        os.unlink(src)  # Delete source after merging
     else:
-        os.rename(src, dst)
-
+        os.rename(src, dst)  # If no destination exists, just move source
 
+# Benchmark a process by running it multiple times and collecting timing and memory data
 def bench_process(loops, args, kw, profile_filename=None):
     max_rss = 0
     range_it = range(loops)
     start_time = time.perf_counter()
 
+    # If profiling is requested, create a temporary profile output file
     if profile_filename:
         temp_profile_filename = tempfile.mktemp()
         args = [args[0], "-m", "cProfile", "-o", temp_profile_filename] + args[1:]
@@ -69,9 +72,10 @@ def bench_process(loops, args, kw, profile_filename=None):
     for _ in range_it:
         start_rss = get_max_rss(children=True)
 
+        # Start the external process
         proc = subprocess.Popen(args, **kw)
         with proc:
-            proc.wait()
+            proc.wait()  # Wait for the process to complete
 
         exitcode = proc.returncode
         if exitcode != 0:
@@ -81,9 +85,11 @@ def bench_process(loops, args, kw, profile_filename=None):
                 os.unlink(temp_profile_filename)
             sys.exit(exitcode)
 
+        # Update maximum observed memory usage
         rss = get_max_rss(children=True) - start_rss
         max_rss = max(max_rss, rss)
 
+        # Merge profiling results if profiling is enabled
         if profile_filename:
             merge_profile_stats_files(
                 temp_profile_filename, profile_filename
@@ -92,7 +98,7 @@ def bench_process(loops, args, kw, profile_filename=None):
     dt = time.perf_counter() - start_time
     return (dt, max_rss)
 
-
+# Parse optional hook plugins from the command line arguments
 def load_hooks(metadata):
     hook_names = []
     while "--hook" in sys.argv:
@@ -103,7 +109,7 @@ def load_hooks(metadata):
         del sys.argv[hook_idx]
 
     if len(hook_names):
-        # Only import pyperf if we know we have hooks
+        # Import hooks module only if hooks are requested
         import pyperf._hooks
 
         hook_managers = pyperf._hooks.instantiate_selected_hooks(hook_names)
@@ -113,31 +119,32 @@ def load_hooks(metadata):
 
     return hook_managers
 
-
+# Write benchmark results to stdout in a structured format
 def write_data(dt, max_rss, metadata, out=sys.stdout):
-    # Write the data that is communicated back to the main orchestration process.
-    # It is three lines containing:
-    #    - The runtime (in seconds)
-    #    - max_rss (or -1, if not able to compute)
-    #    - The metadata to add to the benchmark entry, as a JSON dictionary
+    # Three lines output:
+    # 1. Runtime (seconds)
+    # 2. Maximum RSS memory (or -1 if unavailable)
+    # 3. Metadata as a JSON dictionary
     print(dt, file=out)
     print(max_rss or -1, file=out)
     json.dump(metadata, fp=out)
     print(file=out)
 
-
+# Main function for script execution
 def main():
-    # Make sure that the pyperf module wasn't imported
+    # Prevent users from wrongly running this internal module via -m option
     if 'pyperf' in sys.modules:
         print("ERROR: don't run %s -m pyperf._process, run the .py script"
               % os.path.basename(sys.executable))
         sys.exit(1)
 
+    # Validate minimal argument count
     if len(sys.argv) < 3:
         print("Usage: %s %s loops program [arg1 arg2 ...] [--profile profile]"
               % (os.path.basename(sys.executable), __file__))
         sys.exit(1)
 
+    # Check if profiling is requested via command line
     if "--profile" in sys.argv:
         profile_idx = sys.argv.index("--profile")
         profile_filename = sys.argv[profile_idx + 1]
@@ -149,10 +156,12 @@ def main():
     metadata = {}
     hook_managers = load_hooks(metadata)
 
+    # Extract the number of loops and the target command arguments
     loops = int(sys.argv[1])
     args = sys.argv[2:]
 
     kw = {}
+    # Redirect stdin, stdout, stderr appropriately
     if hasattr(subprocess, 'DEVNULL'):
         devnull = None
         kw['stdin'] = subprocess.DEVNULL
@@ -163,6 +172,7 @@ def main():
         kw['stdout'] = devnull
     kw['stderr'] = subprocess.STDOUT
 
+    # Handle multiple hooks cleanly using ExitStack
     with contextlib.ExitStack() as stack:
         for hook in hook_managers.values():
             stack.enter_context(hook)
@@ -171,11 +181,12 @@ def main():
     if devnull is not None:
         devnull.close()
 
+    # Call hook teardown methods
     for hook in hook_managers.values():
         hook.teardown(metadata)
 
     write_data(dt, max_rss, metadata)
 
-
+# Entry point check
 if __name__ == "__main__":
     main()