⚡️ Speed up function sorter by 104,077%

The optimization replaces a manual bubble sort implementation with Python's built-in `arr.sort()` method, delivering a massive **104,077% speedup**.

**What changed:**
- Removed the nested loops that implement bubble sort (O(n²) complexity)
- Replaced with a single call to `arr.sort()` which uses Timsort (O(n log n) complexity)

**Why this is dramatically faster:**
The original bubble sort performs ~62 million comparisons and ~27 million swaps for larger datasets, as shown in the line profiler. Each comparison (`arr[j] > arr[j + 1]`) and swap operation takes significant time when repeated millions of times. Python's built-in `sort()` uses Timsort, a highly optimized hybrid stable sorting algorithm that:
- Has O(n log n) time complexity vs O(n²) for bubble sort
- Is implemented in C, making individual operations much faster
- Uses adaptive techniques that perform better on partially sorted data

**Performance gains by test case type:**
- **Small lists (≤10 elements)**: 15-40% faster - modest gains since overhead dominates
- **Medium lists (~100 elements)**: 1,000-2,000% faster - algorithm efficiency starts showing
- **Large lists (1000+ elements)**: 10,000-90,000% faster - massive gains where O(n²) vs O(n log n) difference is most pronounced
- **Best case scenarios**: Already sorted or reverse sorted large lists show the highest speedups (55,000-92,000%) due to Timsort's adaptive nature

The optimization maintains identical behavior including in-place sorting and all print statements.

Author: codeflash-ai[bot]

codeflash/bubble_sort.py

@@ -0,0 +1,5 @@
+def sorter(arr):
+    print("codeflash stdout: Sorting list")
+    arr.sort()
+    print(f"result: {arr}")
+    return arr