Optimize sorter

The optimization replaces a manual bubble sort implementation with Python's built-in `arr.sort()` method, delivering a **185,325% speedup**. 

**Key Changes:**
- **Eliminated nested loops**: The original code used O(n²) bubble sort with nested loops that performed ~113M iterations for larger inputs
- **Leveraged Timsort**: Python's `sort()` uses Timsort, an optimized hybrid algorithm with O(n log n) average complexity and O(n) best-case performance for nearly-sorted data
- **Reduced function calls**: Eliminated millions of array index operations and comparisons per sort

**Why It's Faster:**
- **Algorithmic improvement**: Timsort is fundamentally more efficient than bubble sort, especially as data size increases
- **Native C implementation**: Python's sort is implemented in optimized C code rather than interpreted Python loops
- **Adaptive sorting**: Timsort performs exceptionally well on real-world data patterns (partially sorted, reverse sorted, etc.)

**Performance Characteristics:**
- **Small arrays (≤10 elements)**: Modest 10-45% speedup due to reduced overhead
- **Large arrays (1000 elements)**: Dramatic 34,000-100,000% speedup where algorithmic complexity dominates
- **Best performance**: Already sorted or reverse-sorted large arrays benefit most from Timsort's adaptive nature
- **Consistent gains**: All test cases show improvement, with larger datasets seeing exponentially better performance

Author: codeflash-ai[bot]

code_to_optimize/bubble_sort.py

@@ -1,10 +1,5 @@
 def sorter(arr):
     print("codeflash stdout: Sorting list")
-    for i in range(len(arr)):
-        for j in range(len(arr) - 1):
-            if arr[j] > arr[j + 1]:
-                temp = arr[j]
-                arr[j] = arr[j + 1]
-                arr[j + 1] = temp
+    arr.sort()
     print(f"result: {arr}")
     return arr