day23_turtle crossing game_240725.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "553f2d4f-ec92-416f-83ea-0aa84f77a058",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/jpeg": 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",
      "text/plain": [
       "<PIL.JpegImagePlugin.JpegImageFile image mode=RGB size=604x637>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# turtle crossing game\n",
    "# Playing scence of the game\n",
    "from PIL import Image\n",
    "from IPython.display import display\n",
    "img = Image.open('turtle_crossing_game.jpg')\n",
    "display(img)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "e76aebc7-8bae-4a10-9fd8-973e024cba56",
   "metadata": {},
   "outputs": [],
   "source": [
    "# My own sloution\n",
    "# main.py\n",
    "import time\n",
    "from turtle import Screen\n",
    "from player import Player, FINISH_LINE_Y\n",
    "from car_manager import CarManager\n",
    "from scoreboard import Scoreboard\n",
    "\n",
    "screen = Screen()\n",
    "screen.setup(width=600, height=600)\n",
    "screen.title(\"Turtle Crossing Game\")\n",
    "screen.tracer(0)\n",
    "\n",
    "\n",
    "player = Player()\n",
    "score = Scoreboard()\n",
    "car_manager = CarManager()\n",
    "\n",
    "screen.listen()\n",
    "screen.onkey(player.move, \"Up\")\n",
    "\n",
    "a = 1\n",
    "game_is_on = True\n",
    "while game_is_on:\n",
    "    time.sleep(0.1)\n",
    "    screen.update()\n",
    "    if a > 0:\n",
    "        car_manager.car_generating()\n",
    "    a *= -1\n",
    "    car_manager.passing()\n",
    "\n",
    "    if player.ycor() == FINISH_LINE_Y:\n",
    "        # clear the cars\n",
    "        car_manager.reset_cars()\n",
    "        car_manager.speed_up()\n",
    "        # player position update\n",
    "        player.next_level_starting_position()\n",
    "        # plyer score update\n",
    "        score.score_up()\n",
    "\n",
    "    for a_car in car_manager.cars:\n",
    "        if player.ycor() == a_car.ycor() and (player.xcor() >= a_car.xcor()-30) and player.xcor() <= a_car.xcor():\n",
    "            game_is_on = False\n",
    "            score.game_over()\n",
    "\n",
    "\n",
    "screen.exitonclick()\n",
    "\n",
    "# reflection\n",
    "# 1) I used variable 'a' to control the amount of the car, teacher used random_chance for it. teacher solution is better as it can set the probability to create a car\n",
    "# 2) I call FINISH_LINE_Y from player.py. I could make a function in the Player class like is_at_finish_line. Then I don't need to call the FINISH_LINE_L variable.\n",
    "# 3) My code to detect collision with car was same with teacher's code using for loop. Well doen.\n",
    "# 4) Overall codes are similar. Well done to build and call classes and objects properly."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "e64c93c6-eb04-4471-baf8-24dfb53a7e33",
   "metadata": {},
   "outputs": [],
   "source": [
    "# player.py\n",
    "from turtle import Turtle\n",
    "\n",
    "STARTING_POSITION = (0, -280)\n",
    "MOVE_DISTANCE = 20\n",
    "FINISH_LINE_Y = 280\n",
    "\n",
    "\n",
    "class Player(Turtle):\n",
    "    def __init__(self):\n",
    "        super().__init__()\n",
    "        self.shape(\"turtle\")\n",
    "        self.penup()\n",
    "        self.setheading(90)\n",
    "        self.goto(STARTING_POSITION)\n",
    "\n",
    "    def move(self):\n",
    "        self.fd(MOVE_DISTANCE)\n",
    "\n",
    "    def next_level_starting_position(self):\n",
    "        self.goto(STARTING_POSITION)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "029d16e3-80c7-4f7d-bbf5-ac859c3dbb5a",
   "metadata": {},
   "outputs": [],
   "source": [
    "# car_manager.py\n",
    "from turtle import Turtle\n",
    "import random\n",
    "\n",
    "COLORS = [\"red\", \"orange\", \"yellow\", \"green\", \"blue\", \"purple\"]\n",
    "STARTING_MOVE_DISTANCE = 5\n",
    "MOVE_INCREMENT = 10\n",
    "STARTING_LINE_X = 320\n",
    "\n",
    "\n",
    "class CarManager:\n",
    "    def __init__(self):\n",
    "        self.cars = []\n",
    "\n",
    "    def car_generating(self):\n",
    "        a_car = Turtle(\"square\")\n",
    "        a_car.setheading(180)\n",
    "        a_car.color(random.choice(COLORS))\n",
    "        a_car.shapesize(stretch_wid=1, stretch_len=3)\n",
    "        a_car.penup()\n",
    "        a_car.goto(STARTING_LINE_X, random.randrange(-260,260, 20))\n",
    "        self.cars.append(a_car)\n",
    "    def passing(self):\n",
    "        for car_num in range(len(self.cars)):\n",
    "            new_x = self.cars[car_num].xcor() - STARTING_MOVE_DISTANCE\n",
    "            self.cars[car_num].goto(new_x, self.cars[car_num].ycor())\n",
    "\n",
    "    def reset_cars(self):\n",
    "        for car_num in range(len(self.cars)):\n",
    "            self.cars[car_num].hideturtle()\n",
    "        self.cars = []\n",
    "\n",
    "    def speed_up(self):\n",
    "        global STARTING_MOVE_DISTANCE\n",
    "        STARTING_MOVE_DISTANCE +=  MOVE_INCREMENT\n",
    "\n",
    "\n",
    "class Car(Turtle):\n",
    "    def __init__(self):\n",
    "        super().__init__()\n",
    "        self.setheading(180)\n",
    "        self.shape(\"square\")\n",
    "        self.color(random.choice(COLORS))\n",
    "        self.shapesize(stretch_wid=1, stretch_len=3)\n",
    "        self.penup()\n",
    "        self.goto(STARTING_LINE_X, random.randint(-580,580))\n",
    "\n",
    "    def passing(self):\n",
    "        self.fd(STARTING_MOVE_DISTANCE)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "fe8257b5-1421-459d-9576-b8fe0a04c659",
   "metadata": {},
   "outputs": [],
   "source": [
    "# scoreboard.py\n",
    "from turtle import Turtle\n",
    "FONT = (\"Courier\", 24, \"normal\")\n",
    "\n",
    "class Scoreboard(Turtle):\n",
    "    def __init__(self):\n",
    "        super().__init__()\n",
    "        self.color(\"black\")\n",
    "        self.penup()\n",
    "        self.hideturtle()\n",
    "        self.score = 0\n",
    "        self.update_scoreboard()\n",
    "\n",
    "    def update_scoreboard(self):\n",
    "        self.clear()\n",
    "        self.goto(-220, 250)\n",
    "        self.write(\"Level: \", align=\"center\", font=FONT)\n",
    "        self.goto(-150,250)\n",
    "        self.write(self.score, align=\"center\", font=FONT)\n",
    "\n",
    "    def score_up(self):\n",
    "        self.score +=1\n",
    "        self.update_scoreboard()\n",
    "\n",
    "    def game_over(self):\n",
    "        self.goto(0, 0)\n",
    "        self.write(\"GAME OVER\", align=\"center\", font=FONT)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "331b4268-a7e9-47fa-97e4-459fd81055ad",
   "metadata": {},
   "outputs": [],
   "source": [
    "# teacher solution\n",
    "# main.py\n",
    "import time\n",
    "from turtle import Screen\n",
    "from player import Player\n",
    "from car_manager import CarManager\n",
    "from scoreboard import Scoreboard\n",
    "\n",
    "screen = Screen()\n",
    "screen.setup(width=600, height=600)\n",
    "screen.tracer(0)\n",
    "\n",
    "player = Player()\n",
    "car_manager = CarManager()\n",
    "scoreboard = Scoreboard()\n",
    "\n",
    "screen.listen()\n",
    "screen.onkey(player.go_up, \"Up\")\n",
    "\n",
    "game_is_on = True\n",
    "while game_is_on:\n",
    "    time.sleep(0.1)\n",
    "    screen.update()\n",
    "\n",
    "    car_manager.create_car()\n",
    "    car_manager.move_cars()\n",
    "\n",
    "    # Detect collision with car\n",
    "    for car in car_manager.all_cars:\n",
    "        if car.distance(player) < 20:\n",
    "            game_is_on = False\n",
    "            scoreboard.game_over()\n",
    "\n",
    "    # Detect successful crossing\n",
    "    if player.is_at_finish_line():\n",
    "        player.go_to_start()\n",
    "        car_manager.level_up()\n",
    "        scoreboard.increase_level()\n",
    "\n",
    "screen.exitonclick()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "a09b052b-dddb-457c-bb26-2f50634044b2",
   "metadata": {},
   "outputs": [],
   "source": [
    "# player.py\n",
    "from turtle import Turtle\n",
    "\n",
    "STARTING_POSITION = (0, -280)\n",
    "MOVE_DISTANCE = 10\n",
    "FINISH_LINE_Y = 280\n",
    "\n",
    "class Player(Turtle):\n",
    "\n",
    "    def __init__(self):\n",
    "        super().__init__()\n",
    "        self.shape(\"turtle\")\n",
    "        self.penup()\n",
    "        self.go_to_start()\n",
    "        self.setheading(90)\n",
    "\n",
    "    def go_up(self):\n",
    "        self.fd(MOVE_DISTANCE)\n",
    "\n",
    "    def go_to_start(self):\n",
    "        self.goto(STARTING_POSITION)\n",
    "\n",
    "    def is_at_finish_line(self):\n",
    "        if self.ycor() > FINISH_LINE_Y:\n",
    "            return True\n",
    "        else:\n",
    "            return False"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "257a9ec3-61d0-4512-a233-ff615ea573d5",
   "metadata": {},
   "outputs": [],
   "source": [
    "# car_manager.py\n",
    "from turtle import Turtle\n",
    "import random\n",
    "\n",
    "COLORS = [\"red\", \"orange\", \"yellow\", \"green\", \"blue\", \"purple\"]\n",
    "STARTING_MOVE_DISTANCE = 5\n",
    "MOVE_INCREMENT = 10\n",
    "\n",
    "\n",
    "class CarManager:\n",
    "\n",
    "    def __init__(self):\n",
    "        self.all_cars=[]\n",
    "        self.car_speed = STARTING_MOVE_DISTANCE\n",
    "\n",
    "    def create_car(self):\n",
    "        random_chance = random.randint(1,6)\n",
    "        if random_chance ==1:\n",
    "            new_car = Turtle(\"square\")\n",
    "            new_car.shapesize(stretch_wid=1, stretch_len=2)\n",
    "            new_car.penup()\n",
    "            new_car.color(random.choice(COLORS))\n",
    "            random_y = random.randint(-250, 250)\n",
    "            new_car.goto(300, random_y)\n",
    "            self.all_cars.append(new_car)\n",
    "\n",
    "    def move_cars(self):\n",
    "        for car in self.all_cars:\n",
    "            car.backward(self.car_speed)\n",
    "\n",
    "    def level_up(self):\n",
    "        self.car_speed += MOVE_INCREMENT"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "6a8b3243-b2f3-4f6c-8577-45cc2a0040ec",
   "metadata": {},
   "outputs": [],
   "source": [
    "# scoreboard.py\n",
    "from turtle import Turtle\n",
    "FONT = (\"Courier\", 24, \"normal\")\n",
    "\n",
    "\n",
    "class Scoreboard(Turtle):\n",
    "\n",
    "    def __init__(self):\n",
    "        super().__init__()\n",
    "        self.level = 1\n",
    "        self.hideturtle()\n",
    "        self.penup()\n",
    "        self.goto(-280, 250)\n",
    "        self.update_scoreboard()\n",
    "\n",
    "    def update_scoreboard(self):\n",
    "        self.clear()\n",
    "        self.write(f\"Level: {self.level}\", align=\"left\", font=FONT)\n",
    "\n",
    "    def increase_level(self):\n",
    "        self.level +=1\n",
    "        self.update_scoreboard()\n",
    "\n",
    "    def game_over(self):\n",
    "        self.goto(0,0)\n",
    "        self.write(f\"GAME OVER\", align=\"center\", font=FONT)"
   ]
  }
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