EricGustin

"""
This script provides testing Anthropic's tool search functionality across multiple scenarios.

REQUIRED:
- pip install arcadepy
- pip install anthropic
- export ANTHROPIC_API_KEY=<your_anthropic_api_key>
- export ARCADE_API_KEY=<your_arcade_api_key>
"""

EricGustin

@objc func hitEnemy() {
    updateHealthBar()
    UIView.animate(withDuration: 0.25, animations: {
      self.enemy.transform = CGAffineTransform(scaleX: 0.8, y: 0.8)  // Scale the enemy down to 0.8 of its size over 1/4 of a second 
    }) { _ in
      UIView.animate(withDuration: 0.25) {
        self.enemy.transform = .identity  // Once the enemy is done scaling down in size, have it return to its original size over a period of 1/4 of a second 
      }
    }
  }

EricGustin

enemy.addGestureRecognizer(UITapGestureRecognizer(target: self, action: #selector(hitEnemy)))

EricGustin

import UIKit

class ViewController: UIViewController {

  private var healthBar: UIProgressView!
  private var enemy: UIImageView!
  
  override func viewDidLoad() {
    super.viewDidLoad()
    setUpSubviews()

EricGustin

def distributeItems(items: int, n: int):
    itemsPerTurn = []
    j = 0 # current turn
    numOfItems = n*(n+1)//2 # number of items given during turn 0
    while items >= numOfItems:
        items -= numOfItems
        itemsPerTurn.append(numOfItems)
        j += 1
        numOfItems = n**2 * j + n*(n+1)//2 # number of items given during turn j
    return itemsPerTurn

EricGustin

Operation         Example      Big O Time Complexity

Length:          len(s)        O(1)
Add:             s.add(2)      O(1)
Contains:        x in/not in s O(1)
Remove:          s.remove(2)   O(1)
Discard:         s.discard(2)  O(1)
Pop:             s.pop()       O(1)
Clear:           s.clear()     O(1)
Construct:       set(iterable) O(length of iterable)

EricGustin

Operation    Example                        Big O Time Complexity

Index:       dict[k]                        O(1)
Assign:      dict[k] = v                    O(1)
Length:      dict(lst)                      O(1)
Pop:         dict.pop(k)                    O(1)
Pop item:    dict.popitem()                 O(1)
Get a value: dict.get(k)                    O(1)
Get keys:    dict.keys()                    O(1)
Clear:       dict.clear()                   O(1)

EricGustin

Operation         Example                   Big O Time Complexity

Index:            lst[i]                    O(1)
Assign:           lst[i] = 2                O(1)
Length:           len(lst)                  O(1)
Append:           lst.append(i)             O(1)
Pop:              lst.pop()                 O(1)
Clear:            lst.clear()               O(1)
Slice:            lst[start:end]            O(end - start)
Extend:           lst.extend(iterable)      O(length of iterable)

EricGustin

class SortingAlgorithms:
  def quickSort(self, leftIndex, rightIndex, lst) -> int:
      def partition(leftIndex, rightIndex, lst):
        pivotElement = lst[(leftIndex + rightIndex) // 2]
        while leftIndex <= rightIndex:
          # Find element on the left of the partition that is greater than the partitionElement
          while lst[leftIndex] < pivotElement:
            leftIndex += 1
          # Find element on the right of the partition that is less than the partitionElement
          while lst[rightIndex] > pivotElement:

EricGustin

class SortingAlgorithms:
  
  def mergeSort(self, lst):
      if len(lst) > 1:
        # Split part of the algorithm
        middle = len(lst) // 2 # floor division to find middle of the list
        leftList = lst[:middle]
        rightList = lst[middle:]
        self.mergeSort(leftList) # left side of the list
        self.mergeSort(rightList) # right side of the list