Patch 4

data_structures/hashing/hash_table_with_linked_list.py

@@ -8,7 +8,7 @@ def __init__(self, *args, **kwargs):
         super().__init__(*args, **kwargs)
 
     def _set_value(self, key, data):
-        self.values[key] = deque([]) if self.values[key] is None else self.values[key]
+        self.values[key] = deque() if self.values[key] is None else self.values[key]
         self.values[key].appendleft(data)
         self._keys[key] = self.values[key]
 

machine_learning/linear_discriminant_analysis.py

@@ -252,7 +252,7 @@ def accuracy(actual_y: list, predicted_y: list) -> float:
 num = TypeVar("num")
 
 
-def valid_input(
+def valid_input[num](
     input_type: Callable[[object], num],  # Usually float or int
     input_msg: str,
     err_msg: str,

maths/sign.py

@@ -0,0 +1,40 @@
+"""Sign Function."""
+
+
+def sign(num: float) -> int:
+    """
+    Return the sign of a number: -1 for negative, 0 for zero, 1 for positive.
+
+    >>> sign(-5)
+    -1
+    >>> sign(0)
+    0
+    >>> sign(10)
+    1
+    >>> sign(-0.5)
+    -1
+    """
+    if num > 0:
+        return 1
+    elif num < 0:
+        return -1
+    return 0
+
+
+def test_sign() -> None:
+    """
+    >>> test_sign()
+    """
+    assert sign(-5) == -1
+    assert sign(0) == 0
+    assert sign(10) == 1
+    assert sign(-0.001) == -1
+    assert sign(0.001) == 1
+
+
+if __name__ == "__main__":
+    import doctest
+
+    doctest.testmod()
+    test_sign()
+    print(sign(-5))  # --> -1

searches/jump_search.py

@@ -17,10 +17,7 @@ class Comparable(Protocol):
     def __lt__(self, other: Any, /) -> bool: ...
 
 
-T = TypeVar("T", bound=Comparable)
-
-
-def jump_search(arr: Sequence[T], item: T) -> int:
+def jump_search[T: Comparable](arr: Sequence[T], item: T) -> int:
     """
     Python implementation of the jump search algorithm.
     Return the index if the `item` is found, otherwise return -1.