numpy refactor

src/customer_cipher.py

@@ -1,13 +1,13 @@
+import numpy as np
 from dataclasses import dataclass
 from typing import ClassVar
 from src.models import KeypadSize
-from src.utils import generate_random_nonrepeating_list
 
 
 @dataclass
 class CustomerCipher:
-    prop_key: list[int]
-    set_key: list[int]
+    prop_key: np.ndarray
+    set_key: np.ndarray
     keypad_size: KeypadSize
     MAX_KEYS: ClassVar[int] = 256
     MAX_PROP_PER_KEY: ClassVar[int] = 256
@@ -24,23 +24,28 @@ class CustomerCipher:
     def create(cls, keypad_size: KeypadSize) -> 'CustomerCipher':
         if keypad_size.numb_of_keys > cls.MAX_KEYS or keypad_size.props_per_key > cls.MAX_PROP_PER_KEY:
             raise ValueError(f"Keys and properties per key must not exceed {cls.MAX_KEYS}")
+
+        # Using numpy to generate non-repeating random integers
+        prop_key = np.random.choice(2 ** 16, size=keypad_size.numb_of_props, replace=False)
+        set_key = np.random.choice(2 ** 16, size=keypad_size.props_per_key, replace=False)
+
         return cls(
-            prop_key=generate_random_nonrepeating_list(keypad_size.numb_of_props),
-            set_key=generate_random_nonrepeating_list(keypad_size.props_per_key),
+            prop_key=prop_key,
+            set_key=set_key,
             keypad_size=keypad_size,
         )
 
     def renew(self):
-        self.prop_key = generate_random_nonrepeating_list(self.keypad_size.numb_of_props)
-        self.set_key = generate_random_nonrepeating_list(self.keypad_size.props_per_key)
+        self.prop_key = np.random.choice(2 ** 16, size=self.keypad_size.numb_of_props, replace=False)
+        self.set_key = np.random.choice(2 ** 16, size=self.keypad_size.props_per_key, replace=False)
 
     def get_prop_set_val(self, prop: int) -> int:
-        assert (prop in self.prop_key)
-        prop_idx = self.prop_key.index(prop)
+        assert np.isin(prop, self.prop_key)
+        prop_idx = np.where(self.prop_key == prop)[0][0]
         set_idx = prop_idx % self.keypad_size.props_per_key
-        return self.set_key[set_idx]
+        return int(self.set_key[set_idx])
 
     def get_set_index(self, set_val: int) -> int:
-        if set_val not in self.set_key:
+        if not np.isin(set_val, self.set_key):
             raise ValueError(f"Set value {set_val} not found in set values")
-        return self.set_key.index(set_val)
+        return int(np.where(self.set_key == set_val)[0][0])