We are currently solving the following issue within our repository. Here is the issue text:
--- BEGIN ISSUE ---
sorts/random_normal_distribution_quicksort.py has no tests
### Repository commit

3

### Python version (python --version)

Python 3.11.5

### Dependencies version (pip freeze)

Numpy

### Expected behavior

Tests.

### Actual behavior

No tests.

--- END ISSUE ---

Below are some code segments, each from a relevant file. One or more of these files may contain bugs.
--- BEGIN FILES ---
Path: `sorts/random_normal_distribution_quicksort.py`
Content:
```
1 from random import randint
2 from tempfile import TemporaryFile
3 
4 import numpy as np
5 
6 
7 def _in_place_quick_sort(a, start, end):
8     count = 0
9     if start < end:
10         pivot = randint(start, end)
11         temp = a[end]
12         a[end] = a[pivot]
13         a[pivot] = temp
14 
15         p, count = _in_place_partition(a, start, end)
16         count += _in_place_quick_sort(a, start, p - 1)
17         count += _in_place_quick_sort(a, p + 1, end)
18     return count
19 
20 
21 def _in_place_partition(a, start, end):
22     count = 0
23     pivot = randint(start, end)
24     temp = a[end]
25     a[end] = a[pivot]
26     a[pivot] = temp
27     new_pivot_index = start - 1
28     for index in range(start, end):
29         count += 1
30         if a[index] < a[end]:  # check if current val is less than pivot value
31             new_pivot_index = new_pivot_index + 1
32             temp = a[new_pivot_index]
33             a[new_pivot_index] = a[index]
34             a[index] = temp
35 
36     temp = a[new_pivot_index + 1]
37     a[new_pivot_index + 1] = a[end]
38     a[end] = temp
39     return new_pivot_index + 1, count
40 
41 
42 outfile = TemporaryFile()
43 p = 100  # 1000 elements are to be sorted
44 
45 
46 mu, sigma = 0, 1  # mean and standard deviation
47 X = np.random.normal(mu, sigma, p)
48 np.save(outfile, X)
49 print("The array is")
50 print(X)
51 
52 
53 outfile.seek(0)  # using the same array
54 M = np.load(outfile)
55 r = len(M) - 1
56 z = _in_place_quick_sort(M, 0, r)
57 
58 print(
59     "No of Comparisons for 100 elements selected from a standard normal distribution"
60     "is :"
61 )
62 print(z)
63
```
--- END FILES ---

Please first localize the bug based on the issue statement, and then generate a patch according to the `git diff` format fenced by three backticks.

Here is an example:

```diff
diff --git a/examples/server_async.py b/examples/server_async.py
--- a/examples/server_async.py
+++ b/examples/server_async.py
@@ -313,4 +313,4 @@
 
 
 if __name__ == "__main__":
-    asyncio.run(run_async_server("."), debug=True)
+    asyncio.run(run_async_server(), debug=True)
diff --git a/examples/server_sync.py b/examples/server_sync.py
--- a/examples/server_sync.py
+++ b/examples/server_sync.py
@@ -313,5 +313,5 @@
 
 
 if __name__ == "__main__":
-    server = run_sync_server(".")
+    server = run_sync_server()
     server.shutdown()

```

diff --git a/sorts/random_normal_distribution_quicksort.py b/sorts/random_normal_distribution_quicksort.py
deleted file mode 100644
--- a/sorts/random_normal_distribution_quicksort.py
+++ /dev/null
@@ -1,62 +0,0 @@
-from random import randint
-from tempfile import TemporaryFile
-
-import numpy as np
-
-
-def _in_place_quick_sort(a, start, end):
-    count = 0
-    if start < end:
-        pivot = randint(start, end)
-        temp = a[end]
-        a[end] = a[pivot]
-        a[pivot] = temp
-
-        p, count = _in_place_partition(a, start, end)
-        count += _in_place_quick_sort(a, start, p - 1)
-        count += _in_place_quick_sort(a, p + 1, end)
-    return count
-
-
-def _in_place_partition(a, start, end):
-    count = 0
-    pivot = randint(start, end)
-    temp = a[end]
-    a[end] = a[pivot]
-    a[pivot] = temp
-    new_pivot_index = start - 1
-    for index in range(start, end):
-        count += 1
-        if a[index] < a[end]:  # check if current val is less than pivot value
-            new_pivot_index = new_pivot_index + 1
-            temp = a[new_pivot_index]
-            a[new_pivot_index] = a[index]
-            a[index] = temp
-
-    temp = a[new_pivot_index + 1]
-    a[new_pivot_index + 1] = a[end]
-    a[end] = temp
-    return new_pivot_index + 1, count
-
-
-outfile = TemporaryFile()
-p = 100  # 1000 elements are to be sorted
-
-
-mu, sigma = 0, 1  # mean and standard deviation
-X = np.random.normal(mu, sigma, p)
-np.save(outfile, X)
-print("The array is")
-print(X)
-
-
-outfile.seek(0)  # using the same array
-M = np.load(outfile)
-r = len(M) - 1
-z = _in_place_quick_sort(M, 0, r)
-
-print(
-    "No of Comparisons for 100 elements selected from a standard normal distribution"
-    "is :"
-)
-print(z)

{"golden_diff": "diff --git a/sorts/random_normal_distribution_quicksort.py b/sorts/random_normal_distribution_quicksort.py\ndeleted file mode 100644\n--- a/sorts/random_normal_distribution_quicksort.py\n+++ /dev/null\n@@ -1,62 +0,0 @@\n-from random import randint\n-from tempfile import TemporaryFile\n-\n-import numpy as np\n-\n-\n-def _in_place_quick_sort(a, start, end):\n-    count = 0\n-    if start < end:\n-        pivot = randint(start, end)\n-        temp = a[end]\n-        a[end] = a[pivot]\n-        a[pivot] = temp\n-\n-        p, count = _in_place_partition(a, start, end)\n-        count += _in_place_quick_sort(a, start, p - 1)\n-        count += _in_place_quick_sort(a, p + 1, end)\n-    return count\n-\n-\n-def _in_place_partition(a, start, end):\n-    count = 0\n-    pivot = randint(start, end)\n-    temp = a[end]\n-    a[end] = a[pivot]\n-    a[pivot] = temp\n-    new_pivot_index = start - 1\n-    for index in range(start, end):\n-        count += 1\n-        if a[index] < a[end]:  # check if current val is less than pivot value\n-            new_pivot_index = new_pivot_index + 1\n-            temp = a[new_pivot_index]\n-            a[new_pivot_index] = a[index]\n-            a[index] = temp\n-\n-    temp = a[new_pivot_index + 1]\n-    a[new_pivot_index + 1] = a[end]\n-    a[end] = temp\n-    return new_pivot_index + 1, count\n-\n-\n-outfile = TemporaryFile()\n-p = 100  # 1000 elements are to be sorted\n-\n-\n-mu, sigma = 0, 1  # mean and standard deviation\n-X = np.random.normal(mu, sigma, p)\n-np.save(outfile, X)\n-print(\"The array is\")\n-print(X)\n-\n-\n-outfile.seek(0)  # using the same array\n-M = np.load(outfile)\n-r = len(M) - 1\n-z = _in_place_quick_sort(M, 0, r)\n-\n-print(\n-    \"No of Comparisons for 100 elements selected from a standard normal distribution\"\n-    \"is :\"\n-)\n-print(z)\n", "issue": "sorts/random_normal_distribution_quicksort.py has no tests\n### Repository commit\n\n3\n\n### Python version (python --version)\n\nPython 3.11.5\n\n### Dependencies version (pip freeze)\n\nNumpy\n\n### Expected behavior\n\nTests.\n\n### Actual behavior\n\nNo tests.\n", "before_files": [{"content": "from random import randint\nfrom tempfile import TemporaryFile\n\nimport numpy as np\n\n\ndef _in_place_quick_sort(a, start, end):\n    count = 0\n    if start < end:\n        pivot = randint(start, end)\n        temp = a[end]\n        a[end] = a[pivot]\n        a[pivot] = temp\n\n        p, count = _in_place_partition(a, start, end)\n        count += _in_place_quick_sort(a, start, p - 1)\n        count += _in_place_quick_sort(a, p + 1, end)\n    return count\n\n\ndef _in_place_partition(a, start, end):\n    count = 0\n    pivot = randint(start, end)\n    temp = a[end]\n    a[end] = a[pivot]\n    a[pivot] = temp\n    new_pivot_index = start - 1\n    for index in range(start, end):\n        count += 1\n        if a[index] < a[end]:  # check if current val is less than pivot value\n            new_pivot_index = new_pivot_index + 1\n            temp = a[new_pivot_index]\n            a[new_pivot_index] = a[index]\n            a[index] = temp\n\n    temp = a[new_pivot_index + 1]\n    a[new_pivot_index + 1] = a[end]\n    a[end] = temp\n    return new_pivot_index + 1, count\n\n\noutfile = TemporaryFile()\np = 100  # 1000 elements are to be sorted\n\n\nmu, sigma = 0, 1  # mean and standard deviation\nX = np.random.normal(mu, sigma, p)\nnp.save(outfile, X)\nprint(\"The array is\")\nprint(X)\n\n\noutfile.seek(0)  # using the same array\nM = np.load(outfile)\nr = len(M) - 1\nz = _in_place_quick_sort(M, 0, r)\n\nprint(\n    \"No of Comparisons for 100 elements selected from a standard normal distribution\"\n    \"is :\"\n)\nprint(z)\n", "path": "sorts/random_normal_distribution_quicksort.py"}], "after_files": [{"content": null, "path": "sorts/random_normal_distribution_quicksort.py"}]}