address review comments

pyperformance/data-files/benchmarks/bm_deepcopy/run_benchmark.py

@@ -10,30 +10,61 @@
 import pyperf
 from dataclasses import dataclass
 
+
 @dataclass
 class A:
-    string : str
-    lst : list
-    boolean : bool
-
+    string: str
+    lst: list
+    boolean: bool
+
+
+def benchmark_reduce(n):
+    class C(object):
+        def __init__(self):
+            self.a = 1
+            self.b = 2
+
+        def __reduce__(self):
+            return (C, (), self.__dict__)
+
+        def __setstate__(self, state):
+            self.__dict__.update(state)
+    c = C()
+
+    t0 = pyperf.perf_counter()
+    for ii in range(n):
+        _ = copy.deepcopy(c)
+    dt = pyperf.perf_counter() - t0
+    return dt
+
 
 def benchmark(n):
-    a = {'list': [1,2,3,43], 't': (1,2,3), 'str': 'hello', 'subdict': {'a': True}}
-    dc = A('hello', [1,2,3], True)
+    a = {
+        'list': [1, 2, 3, 43],
+        't': (1 ,2, 3),
+        'str': 'hello',
+        'subdict': {'a': True}
+    }
+    dc = A('hello', [1, 2, 3], True)
+
+    t0 = pyperf.perf_counter()
     for ii in range(n):
-        for jj in range(60):
+        for jj in range(30):
             _ = copy.deepcopy(a)
         for s in ['red', 'blue', 'green']:
             dc.string = s
-            for kk in range(10):
+            for kk in range(5):
                 dc.lst[0] = kk
                 for b in [True, False]:
                     dc.boolean = b
                     _ = copy.deepcopy(dc)
-
+    dt = pyperf.perf_counter() - t0
+    return dt
+
 
 if __name__ == "__main__":
     runner = pyperf.Runner()
     runner.metadata['description'] = "deepcopy benchmark"
 
-    runner.bench_func('deepcopy', benchmark, 200)
+    runner.bench_time_func('deepcopy', benchmark)
+    runner.bench_time_func('deepcopy_reduce', benchmark)