diff --git a/src/examples/performance_tips.ipynb b/src/examples/performance_tips.ipynb
index a048b8ea6..69227c04e 100644
--- a/src/examples/performance_tips.ipynb
+++ b/src/examples/performance_tips.ipynb
@@ -49,19 +49,21 @@
     "import time\n",
     "from typing import Any\n",
     "\n",
-    "\n",
     "class DummyTask(Task):\n",
     "    def do_run(self, input: Any, task_span: TaskSpan) -> Any:\n",
     "        time.sleep(2)\n",
     "        print(\"Task1 complete\")\n",
     "        return input\n",
+    "\n",
     "tracer = NoOpTracer()\n",
     "\n",
     "task_input = [\"A\", \"B\", \"C\", \"D\"]\n",
     "task = DummyTask()\n",
     "\n",
     "\n",
-    "result = task.run_concurrently(task_input, tracer) # this finishes in 2 seconds instead of 8\n",
+    "result = task.run_concurrently(\n",
+    "    task_input, tracer\n",
+    ")  # this finishes in 2 seconds instead of 8\n",
     "result"
    ]
   },
@@ -88,13 +90,14 @@
     "        time.sleep(2)\n",
     "        print(\"Task2 complete\")\n",
     "        return input\n",
-    "    \n",
+    "\n",
+    "\n",
     "# initialize all tasks and inputs\n",
     "task_1 = DummyTask()\n",
     "task_2 = DummyTask2()\n",
     "\n",
     "task_input_1 = list(range(10))\n",
-    "task_input_2 = list(range(10,20))"
+    "task_input_2 = list(range(10, 20))"
    ]
   },
   {
@@ -146,9 +149,11 @@
     "jobs = list(zip(repeat(task_1), task_input_1)) + list(zip(repeat(task_2), task_input_2))\n",
     "\n",
     "with ThreadPoolExecutor(max_workers=20) as executor:\n",
-    "    result = list(executor.map(lambda task_input: task_input[0].run(task_input[1], tracer), jobs))\n",
-    "    print(\"Task 1 result:\", result[:len(task_input_1)])\n",
-    "    print(\"Task 2 result:\", result[len(task_input_1):]) "
+    "    result = list(\n",
+    "        executor.map(lambda job: job[0].run(job[1], tracer), jobs)\n",
+    "    )\n",
+    "    print(\"Task 1 result:\", result[: len(task_input_1)])\n",
+    "    print(\"Task 2 result:\", result[len(task_input_1) :])"
    ]
   },
   {
@@ -167,9 +172,14 @@
    "outputs": [],
    "source": [
     "with ThreadPoolExecutor(max_workers=2) as executor:\n",
-    "    results = list(executor.map(lambda task_input: task_input[0].run_concurrently(task_input[1], tracer), [(task_1, task_input_1), (task_2, task_input_2)]))\n",
-    "    print(\"Task 1 result:\", result[:len(task_input_1)])\n",
-    "    print(\"Task 2 result:\", result[len(task_input_1):])"
+    "    results = list(\n",
+    "        executor.map(\n",
+    "            lambda job: job[0].run_concurrently(job[1], tracer),\n",
+    "            [(task_1, task_input_1), (task_2, task_input_2)],\n",
+    "        )\n",
+    "    )\n",
+    "    print(\"Task 1 result:\", result[: len(task_input_1)])\n",
+    "    print(\"Task 2 result:\", result[len(task_input_1) :])"
    ]
   },
   {
@@ -183,12 +193,6 @@
     "\n",
     "If tasks are CPU bound, the abovementioned code will not help. In that case, replace the `ThreadPoolExecutor` with a `ProcessPoolExecutor`."
    ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "f946ac08",
-   "metadata": {},
-   "source": []
   }
  ],
  "metadata": {