Technical Problem Solving and Learning Agility Questions

from typing import Iterable, Sequence, Optional

def accuracy(preds: Iterable, labels: Iterable, allow_empty: bool = False) -> Optional[float]:
    """
    Compute accuracy = (# equal pairs) / (number of labels).
    - preds, labels: any iterables; elements need only support equality (==), not hashing.
    - allow_empty: if True, return 0.0 for empty inputs; if False, raise ValueError for empty labels.
    Returns float in [0.0, 1.0] or None if allow_empty True and both empty (caller can choose behavior).
    """
    if preds is None or labels is None:
        raise TypeError("preds and labels must be provided, not None")

    # Materialize to sequences to compute length and support single-pass iterables
    try:
        preds_seq = list(preds)
        labels_seq = list(labels)
    except TypeError:
        raise TypeError("preds and labels must be iterable")

    if len(labels_seq) == 0:
        if allow_empty:
            return 0.0  # or return None if you prefer signaling "undefined"
        raise ValueError("labels is empty; accuracy undefined")

    if len(preds_seq) != len(labels_seq):
        raise ValueError(f"Length mismatch: preds={len(preds_seq)}, labels={len(labels_seq)}")

    matches = 0
    for p, l in zip(preds_seq, labels_seq):
        try:
            if p == l:
                matches += 1
        except Exception as e:
            raise TypeError(f"Equality check failed for elements {p!r} and {l!r}: {e}")

    return matches / len(labels_seq)

class Node:
    def __init__(self, key, val):
        self.key = key
        self.val = val
        self.prev = None
        self.next = None

class LRUCache:
    def __init__(self, capacity: int):
        self.capacity = capacity
        self.map = {}  # key -> Node
        # dummy head/tail to avoid edge checks
        self.head = Node(None, None)
        self.tail = Node(None, None)
        self.head.next = self.tail
        self.tail.prev = self.head
        self.size = 0

    def _add_to_head(self, node):
        node.next = self.head.next
        node.prev = self.head
        self.head.next.prev = node
        self.head.next = node

    def _remove_node(self, node):
        node.prev.next = node.next
        node.next.prev = node.prev

    def _move_to_head(self, node):
        self._remove_node(node)
        self._add_to_head(node)

    def _pop_tail(self):
        if self.tail.prev is self.head:
            return None
        node = self.tail.prev
        self._remove_node(node)
        return node

    def get(self, key: int) -> int:
        node = self.map.get(key)
        if not node:
            return -1
        self._move_to_head(node)
        return node.val

    def put(self, key: int, value: int) -> None:
        node = self.map.get(key)
        if node:
            node.val = value
            self._move_to_head(node)
            return
        new_node = Node(key, value)
        self.map[key] = new_node
        self._add_to_head(new_node)
        self.size += 1
        if self.size > self.capacity:
            tail = self._pop_tail()
            if tail:
                del self.map[tail.key]
                self.size -= 1