🚨 Format stray python scripts

Problem:
- Quality build is not clean because some python scripts are not formatted with
  black.

Solution:
- Format them.

Author: elbeno

test/msg/gen_handler_data.py

@@ -1,35 +1,40 @@
 import random
 
 
-big_vals = [int(random.expovariate(10) * (1 << 28)) & 0xffffffff for i in range(0, 100)]
-med_vals = [int(random.expovariate(10) * (1 << 14)) & 0xffff for i in range(0, 50)]
-small_vals = [int(random.expovariate(10) * (1 << 6)) & 0xff for i in range(0, 25)]
+big_vals = [int(random.expovariate(10) * (1 << 28)) & 0xFFFFFFFF for i in range(0, 100)]
+med_vals = [int(random.expovariate(10) * (1 << 14)) & 0xFFFF for i in range(0, 50)]
+small_vals = [int(random.expovariate(10) * (1 << 6)) & 0xFF for i in range(0, 25)]
 
-combos = [(
-    random.choice(big_vals), 
-    random.choice(med_vals), 
-    random.choice(small_vals)
-) for i in range(0, 256)]
+combos = [
+    (random.choice(big_vals), random.choice(med_vals), random.choice(small_vals))
+    for i in range(0, 256)
+]
 
 
-print("""
+print(
+    """
 template<typename T>
 struct test_project {
     constexpr static auto config = cib::config(
         cib::exports<T>, 
-        cib::extend<T>(""")
+        cib::extend<T>("""
+)
 for c in combos:
     print(f"            cb<{c[0]}, {c[1]}, {c[2]}>,")
 print(
-"""        )
+    """        )
     );
 };
-""")
+"""
+)
 
-print("""
-    auto msgs = std::array{""")
+print(
+    """
+    auto msgs = std::array{"""
+)
 for c in combos:
     print(f"        m<{c[0]}, {c[1]}, {c[2]}>,")
 print(
-"""    };
-""")
+    """    };
+"""
+)

tools/benchmark/parse_bench_data.py

@@ -4,24 +4,25 @@
 import csv
 import re
 
+
 def parse_file(file_path):
     data = {}
     current_dataset = None
     current_algorithm = None
     current_size = None
 
-    with open(file_path, 'r') as file:
+    with open(file_path, "r") as file:
         for line in file:
             line = line.strip()
 
-            if line.startswith('dataset:'):
-                current_dataset = line.split(':')[1].strip()
-            elif line.startswith('algorithm:'):
-                current_algorithm = line.split(':')[1].strip()
-            elif line.startswith('size:'):
-                current_size = int(line.split(':')[1].strip())
-            elif line.startswith('|'):
-                fields = line.split('|')[1:]
+            if line.startswith("dataset:"):
+                current_dataset = line.split(":")[1].strip()
+            elif line.startswith("algorithm:"):
+                current_algorithm = line.split(":")[1].strip()
+            elif line.startswith("size:"):
+                current_size = int(line.split(":")[1].strip())
+            elif line.startswith("|"):
+                fields = line.split("|")[1:]
                 if len(fields) >= 5:
                     try:
                         ns_op = float(fields[0].strip())
@@ -34,44 +35,57 @@ def parse_file(file_path):
                         data[current_dataset] = {}
                     if current_algorithm not in data[current_dataset]:
                         data[current_dataset][current_algorithm] = {
-                            'size': current_size
+                            "size": current_size
                         }
 
                     if "chained" in key_gen_type:
-                        data[current_dataset][current_algorithm]['ns_op_chained'] = ns_op
+                        data[current_dataset][current_algorithm][
+                            "ns_op_chained"
+                        ] = ns_op
                     elif "independent" in key_gen_type:
-                        data[current_dataset][current_algorithm]['ns_op_independent'] = ns_op
-
+                        data[current_dataset][current_algorithm][
+                            "ns_op_independent"
+                        ] = ns_op
 
     return data
 
 
 def generate_csv_tables(data, output_prefix):
     datasets = list(data.keys())
-    algorithms = sorted(set(algo for dataset in data.values() for algo in dataset.keys()))
+    algorithms = sorted(
+        set(algo for dataset in data.values() for algo in dataset.keys())
+    )
 
     # Table 1: Chained Algorithm Performance (ns/op) vs Dataset
-    with open(f'{output_prefix}_chained_performance.csv', 'w', newline='') as file:
+    with open(f"{output_prefix}_chained_performance.csv", "w", newline="") as file:
         writer = csv.writer(file)
-        writer.writerow(['Dataset'] + algorithms)
+        writer.writerow(["Dataset"] + algorithms)
         for dataset in datasets:
-            row = [dataset] + [data[dataset].get(algo, {}).get('ns_op_chained', '') for algo in algorithms]
+            row = [dataset] + [
+                data[dataset].get(algo, {}).get("ns_op_chained", "")
+                for algo in algorithms
+            ]
             writer.writerow(row)
 
     # Table 2: Independent Algorithm Performance (ns/op) vs Dataset
-    with open(f'{output_prefix}_independent_performance.csv', 'w', newline='') as file:
+    with open(f"{output_prefix}_independent_performance.csv", "w", newline="") as file:
         writer = csv.writer(file)
-        writer.writerow(['Dataset'] + algorithms)
+        writer.writerow(["Dataset"] + algorithms)
         for dataset in datasets:
-            row = [dataset] + [data[dataset].get(algo, {}).get('ns_op_independent', '') for algo in algorithms]
+            row = [dataset] + [
+                data[dataset].get(algo, {}).get("ns_op_independent", "")
+                for algo in algorithms
+            ]
             writer.writerow(row)
 
     # Table 3: Algorithm Size (bytes) vs Dataset
-    with open(f'{output_prefix}_algorithm_size.csv', 'w', newline='') as file:
+    with open(f"{output_prefix}_algorithm_size.csv", "w", newline="") as file:
         writer = csv.writer(file)
-        writer.writerow(['Dataset'] + algorithms)
+        writer.writerow(["Dataset"] + algorithms)
         for dataset in datasets:
-            row = [dataset] + [data[dataset].get(algo, {}).get('size', '') for algo in algorithms]
+            row = [dataset] + [
+                data[dataset].get(algo, {}).get("size", "") for algo in algorithms
+            ]
             writer.writerow(row)