diff --git a/data_structures/arrays/dutch_national_flag.py b/data_structures/arrays/dutch_national_flag.py
new file mode 100644
index 000000000000..77193a7963dd
--- /dev/null
+++ b/data_structures/arrays/dutch_national_flag.py
@@ -0,0 +1,39 @@
+def dutch_national_flag(arr: list[int]) -> list[int]:
+    """
+    Sorts an array containing only 0s, 1s and 2s
+
+    Args:
+        arr(list[int]): The input array (containing only 0s, 1s and 2s)
+
+    Returns:
+        list[int]: Sorted array
+
+    Examples:
+        >>> dutch_national_flag([2, 0, 2, 1, 2, 0, 1])
+        [0, 0, 1, 1, 2, 2, 2]
+        >>> dutch_national_flag([0, 1, 2, 0, 1, 2])
+        [0, 0, 1, 1, 2, 2]
+        >>> dutch_national_flag([1, 1, 1])
+        [1, 1, 1]
+        >>> dutch_national_flag([])
+        []
+    """
+
+    low, mid, high = 0, 0, len(arr) - 1
+
+    while mid <= high:
+        if arr[mid] == 0:
+            arr[low], arr[mid] = arr[mid], arr[low]
+            low += 1
+            mid += 1
+        elif arr[mid] == 1:
+            mid += 1
+        else:
+            arr[mid], arr[high] = arr[high], arr[mid]
+            high -= 1
+    return arr
+
+
+if __name__ == "__main__":
+    arr = [2, 0, 2, 1, 2, 0, 1]
+    print("Sorted array: ", dutch_national_flag(arr))
diff --git a/greedy_methods/fractional_knapsack.py b/greedy_methods/fractional_knapsack.py
index d52b56f23569..f7455a9c9fce 100644
--- a/greedy_methods/fractional_knapsack.py
+++ b/greedy_methods/fractional_knapsack.py
@@ -39,9 +39,11 @@ def frac_knapsack(vl, wt, w, n):
     return (
         0
         if k == 0
-        else sum(vl[:k]) + (w - acc[k - 1]) * (vl[k]) / (wt[k])
-        if k != n
-        else sum(vl[:k])
+        else (
+            sum(vl[:k]) + (w - acc[k - 1]) * (vl[k]) / (wt[k])
+            if k != n
+            else sum(vl[:k])
+        )
     )
 
 
diff --git a/matrix/matrix_class.py b/matrix/matrix_class.py
index dee9247282f9..5efe0b0e09f3 100644
--- a/matrix/matrix_class.py
+++ b/matrix/matrix_class.py
@@ -204,9 +204,11 @@ def cofactors(self) -> Matrix:
         return Matrix(
             [
                 [
-                    self.minors().rows[row][column]
-                    if (row + column) % 2 == 0
-                    else self.minors().rows[row][column] * -1
+                    (
+                        self.minors().rows[row][column]
+                        if (row + column) % 2 == 0
+                        else self.minors().rows[row][column] * -1
+                    )
                     for column in range(self.minors().num_columns)
                 ]
                 for row in range(self.minors().num_rows)