Trigger garbage collection before measuring memory usage.

README.md

@@ -36,7 +36,7 @@ my_function()
 Output: 
 
 ```
-my_function | 312 B | 465.9 ns
+my_function | 432 B | 445.2 ns
 ```
 
 ### 2. Profile only the memory usage of a function
@@ -57,7 +57,7 @@ my_function()
 Output: 
 
 ```
-my_function | 312 B
+my_function | 432 B
 ```
 
 ### 3. Profile only the execution time of a function
@@ -79,7 +79,7 @@ my_function()
 Output: 
 
 ```
-my_function | 432.3 ns
+my_function | 439.3 ns
 ```
 
 ### 4. Change the number of iterations
@@ -106,7 +106,7 @@ pi(100)
 Output:
 
 ```
-pi | 80 B | 6.674 µs
+pi | 168 B | 6.461 µs
 ```
 
 ### 5. Change the time and memory units
@@ -131,7 +131,7 @@ exponential(8, 100)
 Output:
 
 ```
-exponential | 0.08 kB | 0.005581 ms
+exponential | 0.168 kB | 0.005429 ms
 ```
 
 ### 6. Change the time and memory precision
@@ -153,7 +153,7 @@ average([25, 12, 18, 88, 64, 55, 22])
 Output:
 
 ```
-average | 48 B | 172.2024 ns
+average | 120 B | 176.6314 ns
 ```
 
 ### 7. Log the arguments and the result
@@ -174,7 +174,7 @@ greeting_message("John", coins=5)
 Output:
 
 ```
-greeting_message | John, coins=5 | Hello John! You have 5 coins. | 353 B | 332.6 ns
+greeting_message | John, coins=5 | Hello John! You have 5 coins. | 521 B | 350.1 ns
 ```
 
 ### 8. Set a custom name for a function
@@ -198,7 +198,7 @@ factorial(10)
 Output:
 
 ```
-Naive method | 96 B | 420.2 ns
+Naive method | 160 B | 411.3 ns
 ```
 
 ### 9. Compare multiple functions
@@ -225,11 +225,35 @@ my_function_2(10)
 Output:
 
 ```
-List comprehension | 344 B | 619.6 ns
-For loop | 192 B | 664.7 ns
+List comprehension | 464 B | 666.8 ns
+For loop | 312 B | 650.7 ns
 ```
 
-### 10. Enable garbage collection during measurements
+### 10. Profile a recursive function
+
+The decorators work seamlessly with recursive functions.\
+Only one profiling message is logged per function call even if the function is recursive.
+
+```python
+from simple_profile import simple_profile
+
+@simple_profile(print_args=True, print_result=True, iterations=100)
+def fibonacci(n):
+    if n <= 1:
+        return n
+    else:
+        return fibonacci(n - 1) + fibonacci(n - 2)
+
+fibonacci(10)
+```
+
+Output:
+
+```
+fibonacci | 10 | 55 | 1.648 kB | 21.04 µs
+```
+
+### 11. Enable garbage collection during measurements
 
 By default, garbage collection is temporarily turned off to make measurements more comparable, but it is possible to enable it if you prefer.\
 To do this, you can set the `enable_gc` argument of the `simple_profile()` and `time_profile()` decorators to `True`.
@@ -252,7 +276,6 @@ my_function_2()
 Output:
 
 ```
-Without GC | 834 B | 667.3 ns
-With GC | 834 B | 674.6 ns
+Without GC | 954 B | 666.5 ns
+With GC | 954 B | 669.2 ns
 ```
-

simple_profile/utils.py

@@ -1,3 +1,4 @@
+import gc
 import timeit
 import tracemalloc
 from typing import Any, Callable, Optional
@@ -16,6 +17,7 @@ def measure_memory_usage(
     :return: the memory usage of the function call (in bytes) and its result
     """
     tracemalloc.start()
+    gc.collect()
     result = function(*args, **kwargs)
     memory_usage = tracemalloc.get_traced_memory()
     tracemalloc.stop()
@@ -50,10 +52,11 @@ def measure_execution_time(
     :param enable_gc: whether to enable garbage collection during the measurement
     :return: the execution time of all the iterations of the function call (in seconds)
     """
-    setup = "pass"
-    if enable_gc:
-        setup = "gc.enable()"
-    return timeit.timeit(stmt=lambda: function(*args, **kwargs), setup=setup, number=iterations)
+    return timeit.timeit(
+        stmt=lambda: function(*args, **kwargs),
+        setup="gc.enable()" if enable_gc else "pass",
+        number=iterations
+    )
 
 
 def measure_average_execution_time(
@@ -121,9 +124,7 @@ def select_profile_name(name: Optional[str], function: Callable) -> str:
     :param function: the analyzed function
     :return: the profile name
     """
-    if name is not None:
-        return name
-    return function.__name__
+    return name if name is not None else function.__name__
 
 
 def get_function_call_log(