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question:def evaluate_expression(expression: str) -> float: Evaluates an arithmetic expression containing +, -, *, / while ignoring arbitrary whitespace. >>> evaluate_expression("3 + 5") 8.0 >>> evaluate_expression("10 + 2 * 6") 22.0 >>> evaluate_expression("100 * 2 + 12") 212.0 >>> evaluate_expression("100 * ( 2 + 12 )") 1400.0 >>> evaluate_expression("100 * ( 2 + 12 ) / 14") 100.0 >>> evaluate_expression("3.5 + 2.5 * 2") 8.5
answer:def evaluate_expression(expression: str) -> float: Evaluates an arithmetic expression containing +, -, *, / while ignoring arbitrary whitespace. # Remove any whitespace characters expression = expression.replace(" ", "") # Evaluate the expression, catch division by zero error if it occurs try: result = float(eval(expression)) except ZeroDivisionError: raise ZeroDivisionError("division by zero is not allowed") return result
question:class CircularDeque: def __init__(self, k: int) -> None: Initialize an empty circular deque with a specified capacity. def insertFront(self, value: int) -> bool: Insert an element to the front of the deque. Returns True if the operation is successful, otherwise returns False. def insertLast(self, value: int) -> bool: Insert an element to the rear of the deque. Returns True if the operation is successful, otherwise returns False. def deleteFront(self) -> bool: Delete an element from the front of the deque. Returns True if the operation is successful, otherwise returns False. def deleteLast(self) -> bool: Delete an element from the rear of the deque. Returns True if the operation is successful, otherwise returns False. def getFront(self) -> int: Get the front element of the deque. Returns -1 if the deque is empty. def getRear(self) -> int: Get the rear element of the deque. Returns -1 if the deque is empty. def isEmpty(self) -> bool: Check if the deque is empty. Returns True if empty, otherwise False. def isFull(self) -> bool: Check if the deque is full. Returns True if full, otherwise False. def display(self) -> list: Display the current state of the deque's elements in a list format.
answer:class CircularDeque: def __init__(self, k: int) -> None: self.k = k self.queue = [None] * k self.front = -1 self.rear = -1 self.size = 0 def insertFront(self, value: int) -> bool: if self.isFull(): return False if self.isEmpty(): self.front = self.rear = 0 else: self.front = (self.front - 1) % self.k self.queue[self.front] = value self.size += 1 return True def insertLast(self, value: int) -> bool: if self.isFull(): return False if self.isEmpty(): self.front = self.rear = 0 else: self.rear = (self.rear + 1) % self.k self.queue[self.rear] = value self.size += 1 return True def deleteFront(self) -> bool: if self.isEmpty(): return False if self.front == self.rear: self.front = self.rear = -1 else: self.front = (self.front + 1) % self.k self.size -= 1 return True def deleteLast(self) -> bool: if self.isEmpty(): return False if self.front == self.rear: self.front = self.rear = -1 else: self.rear = (self.rear - 1) % self.k self.size -= 1 return True def getFront(self) -> int: if self.isEmpty(): return -1 return self.queue[self.front] def getRear(self) -> int: if self.isEmpty(): return -1 return self.queue[self.rear] def isEmpty(self) -> bool: return self.size == 0 def isFull(self) -> bool: return self.size == self.k def display(self) -> list: if self.isEmpty(): return [] result = [] i = self.front while True: result.append(self.queue[i]) if i == self.rear: break i = (i + 1) % self.k return result
question:from typing import Optional, Tuple def sieve_of_eratosthenes(max_num: int) -> list: Generate a list indicating prime numbers up to max_num using the Sieve of Eratosthenes algorithm. is_prime = [True] * (max_num + 1) is_prime[0] = is_prime[1] = False for num in range(2, int(math.isqrt(max_num)) + 1): if is_prime[num]: for multiple in range(num * num, max_num + 1, num): is_prime[multiple] = False return is_prime def find_prime_pair(n: int) -> Optional[Tuple[int, int]]: Return a tuple of two primes that sum up to n, or None if no such pair exists. >>> find_prime_pair(10) in [(3, 7), (5, 5)] True >>> find_prime_pair(26) in [(3, 23), (13, 13)] True >>> find_prime_pair(44) in [(3, 41), (17, 27)] True >>> find_prime_pair(17) is None True pass # Implement the function here
answer:from typing import Optional, Tuple import math def sieve_of_eratosthenes(max_num: int) -> list: is_prime = [True] * (max_num + 1) is_prime[0] = is_prime[1] = False for num in range(2, int(math.isqrt(max_num)) + 1): if is_prime[num]: for multiple in range(num * num, max_num + 1, num): is_prime[multiple] = False return is_prime def find_prime_pair(n: int) -> Optional[Tuple[int, int]]: if n <= 2: return None is_prime = sieve_of_eratosthenes(n) for i in range(2, n): if is_prime[i] and is_prime[n - i] and i != (n - i): return (i, n - i) return None
question:from typing import List def detect_anomalies(data: List[float], threshold: float) -> List[int]: Identifies and returns the indices of anomalies in the data based on the specified Z-Score threshold. Parameters: - data (List[float]): A list of numerical values representing the data set. - threshold (float): The Z-Score threshold for determining anomalies. A data point is considered an anomaly if its absolute Z-Score is greater than this threshold. Returns: - List[int]: The list of indices of anomalies. >>> detect_anomalies([10.0, 12.0, 15.0, 18.0, 9.0, 50.0, 11.0], 2.0) [5] >>> detect_anomalies([5.0, 6.0, 7.0, 8.0, 10.0, 50.0, 7.5], 1.5) [5] >>> detect_anomalies([1.0, 2.0, 2.5, 3.0, 2.0, 100.0, 2.0, 2.1], 3.0) [5] >>> detect_anomalies([10.0, 11.0, 9.0, 10.5, 10.3], 3.0) [] >>> detect_anomalies([5.0, 5.0, 5.0, 5.0, 5.0], 2.0) [] >>> detect_anomalies([1.0], 2.0) Traceback (most recent call last): ValueError: Data should contain at least two numerical values.
answer:from typing import List import numpy as np def detect_anomalies(data: List[float], threshold: float) -> List[int]: Identifies and returns the indices of anomalies in the data based on the specified Z-Score threshold. Parameters: - data (List[float]): The data set. - threshold (float): The Z-Score threshold for determining anomalies. Returns: - List[int]: The list of indices of anomalies. if len(data) < 2: raise ValueError("Data should contain at least two numerical values.") mean = np.mean(data) std_dev = np.std(data) anomalies = [] for index, value in enumerate(data): z_score = (value - mean) / std_dev if std_dev else 0 if abs(z_score) > threshold: anomalies.append(index) return anomalies