diff --git a/.DS_Store b/.DS_Store new file mode 100644 index 00000000..5d3cf54e Binary files /dev/null and b/.DS_Store differ diff --git a/your-code/.DS_Store b/your-code/.DS_Store new file mode 100644 index 00000000..e50100af Binary files /dev/null and b/your-code/.DS_Store differ diff --git a/your-code/.ipynb_checkpoints/Dacha_Escape_Room-checkpoint.ipynb b/your-code/.ipynb_checkpoints/Dacha_Escape_Room-checkpoint.ipynb new file mode 100644 index 00000000..f1d3f0a9 --- /dev/null +++ b/your-code/.ipynb_checkpoints/Dacha_Escape_Room-checkpoint.ipynb @@ -0,0 +1,1104 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 4, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 85 + }, + "id": "uRjaA6neUGcr", + "outputId": "26d6a096-bc21-4165-819d-f4277543cab4" + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Requirement already satisfied: soundfile in c:\\users\\eloi pc\\appdata\\local\\programs\\python\\python38-32\\lib\\site-packages (0.10.3.post1)\n", + "Requirement already satisfied: cffi>=1.0 in c:\\users\\eloi pc\\appdata\\local\\programs\\python\\python38-32\\lib\\site-packages (from soundfile) (1.14.2)\n", + "Requirement already satisfied: pycparser in c:\\users\\eloi pc\\appdata\\local\\programs\\python\\python38-32\\lib\\site-packages (from cffi>=1.0->soundfile) (2.20)\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING: You are using pip version 20.1.1; however, version 20.2.4 is available.\n", + "You should consider upgrading via the 'c:\\users\\eloi pc\\appdata\\local\\programs\\python\\python38-32\\python.exe -m pip install --upgrade pip' command.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Requirement already satisfied: playsound in c:\\users\\eloi pc\\appdata\\local\\programs\\python\\python38-32\\lib\\site-packages (1.2.2)\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING: You are using pip version 20.1.1; however, version 20.2.4 is available.\n", + "You should consider upgrading via the 'c:\\users\\eloi pc\\appdata\\local\\programs\\python\\python38-32\\python.exe -m pip install --upgrade pip' command.\n" + ] + } + ], + "source": [ + "# Here we should import all packages and define other things such as classes\n", + "import time\n", + "import numpy as np\n", + "import pandas as pd\n", + "from IPython.display import Audio\n", + "from IPython.display import Image\n", + "from IPython.display import display\n", + "\n", + "import multiprocessing\n", + "!pip install soundfile\n", + "import soundfile as sf\n", + "!pip install playsound\n", + "from playsound import playsound\n", + "\n", + "class color:\n", + " ### How to use:\n", + " ### print(color.BOLD + 'Hello World !' + color.END)\n", + " ### print(color.DARKCYAN + color.BOLD + 'Hello World !' + color.END)\n", + " PURPLE = '\\033[95m'\n", + " CYAN = '\\033[96m'\n", + " DARKCYAN = '\\033[36m'\n", + " BLUE = '\\033[94m'\n", + " GREEN = '\\033[92m'\n", + " YELLOW = '\\033[93m'\n", + " RED = '\\033[91m'\n", + " BOLD = '\\033[1m'\n", + " UNDERLINE = '\\033[4m'\n", + " END = '\\033[0m'\n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": 71, + "metadata": { + "id": "IHF3ccywR3zo" + }, + "outputs": [], + "source": [ + "# Object declaration/initialization.\n", + "\n", + "# RUI: Library of Images and sounds\n", + "# [RUI: to be done, now dummy data just to test // sounds will not run properly on colaborative]\n", + "map_game_room = Image(filename=\"sounds_and_images\\map_game_room.png\")\n", + "map_corridor = Image(filename=\"sounds_and_images\\map_corridor.png\")\n", + "map_bathroom = Image(filename=\"sounds_and_images\\map_bathroom.png\")\n", + "map_kitchen = Image(filename=\"sounds_and_images\\map_kitchen.png\")\n", + "map_living_room = Image(filename=\"sounds_and_images\\map_living_room.png\")\n", + "\n", + "#[Rui, these soun]\n", + "sound_bathtub = \"sounds_and_images\\clogged_bathtub.wav\"\n", + "sound_old_lady = \"sounds_and_images\\gulping_bottle.wav\"\n", + "sound_cutlery_drawer = \"sounds_and_images\\smashing_wood.wav\"\n", + "\n", + "# [RUI: This one could be called maybe when we write \"congratulations\".]\n", + "sound_victory = \"sounds_and_images\\win.wav\"\n", + "# [RUI: This one can be called maybe when we call the function to get the next room.]\n", + "sound_door_creaking = \"sounds_and_images\\door_creaking.wav\"\n", + "\n", + "# Definition of ROOMS:\n", + "game_room = {\n", + " \"name\": \"game room\",\n", + " \"type\": \"room\",\n", + " \"map\": map_game_room}\n", + "corridor = {\n", + " \"name\": \"corridor\",\n", + " \"type\": \"room\",\n", + " \"map\": map_corridor}\n", + "bathroom = {\n", + " \"name\": \"bathroom\",\n", + " \"type\": \"room\",\n", + " \"map\": map_bathroom}\n", + "kitchen = {\n", + " \"name\": \"kitchen\",\n", + " \"type\": \"room\",\n", + " \"map\": map_kitchen}\n", + "living_room = {\n", + " \"name\": \"living room\",\n", + " \"type\": \"room\",\n", + " \"map\": map_living_room}\n", + "\n", + "# Definition of DOORS\n", + "door_gameroom = {\n", + " \"name\": \"game room door\",\n", + " \"type\": \"door\",}\n", + "door_bathroom = {\n", + " \"name\": \"bathroom door\",\n", + " \"type\": \"door\",}\n", + "door_kitchen = {\n", + " \"name\": \"kitchen door\",\n", + " \"type\": \"door\",}\n", + "door_livingroom = {\n", + " \"name\": \"living room door\",\n", + " \"type\": \"door\",}\n", + "door_other = {\n", + " \"name\": \"other door\",\n", + " \"type\": \"door\",}\n", + "\n", + "# FURNITURE AND PEOPLE\n", + "\n", + "# GAME ROOM\n", + "side_table = {\n", + " \"name\": \"side table\",\n", + " \"type\": \"furniture\",\n", + " \"useful\": False,\n", + " #flavour_text of side table is set at start with the start game function.\n", + " \"flavour_text\": \"\"}\n", + "couch = {\n", + " \"name\": \"couch\",\n", + " \"type\": \"furniture\",\n", + " \"useful\": False,\n", + " \"flavour_text\": \"Potato.\",\n", + "}\n", + "piano = {\n", + " \"name\": \"piano\",\n", + " \"type\": \"furniture\",\n", + " \"useful\": True,\n", + " \"status\": \"closed\",\n", + " \"code\": \"9857\",\n", + " \"flavour_text\": \"You would be surprised if it was working.\",\n", + "}\n", + "chairs = {\n", + " \"name\": \"chairs\",\n", + " \"type\": \"furniture\",\n", + " \"useful\": False,\n", + " \"flavour_text\": \"Previously owned by a dictator.\",\n", + "}\n", + "bookshelf = {\n", + " \"name\": \"bookshelf\",\n", + " \"type\": \"furniture\",\n", + " \"useful\": True,\n", + " \"books_in_russian\": [\"Преступление и наказание\",\"Маленькие женщины\",\"Большие надежды\",\"Война и мир\",\"Les Misérables\",\"Записки из метро\", \"Белые ночи\", \"Сон о смехотворном человеке\",\"Идиот\",\"Женщина в белом\",\"Отцы и сыновья\",\"Лунный камень\",\"Сайлас Марнер\",\"Путешествие к центру Земли\",\"Мельница на зубной нити\",\"Русско-английский словарь/English–Russian Dictionary\",\"книга джунглей\"],\n", + " \"books_in_english\": [\"Crime and Punishment\",\"Little Women\",\"Great Expectations\",\"War and Peace\",\"Les Misérables\", \"Notes from Underground\",\"White Nights\",\"Dreams of a ridiculous man\",\"The Idiot\",\"The Woman in White\",\"Fathers and Sons\",\"The Moonstone\",\"Silas Marner\",\"Journey to the Center of the Earth\",\"The Mill on the Floss\",\"Russian-English Dictionary/English–Russian Dictionary\",\"The Jungle Book\"],\n", + " \"flavour_text\": \"Packed!\",\n", + " # Bookshelf will have another property key \"play\" with a function attributed as value.\n", + "}\n", + "wall_clock = {\n", + " \"name\": \"wall clock\",\n", + " \"type\": \"furniture\",\n", + " \"useful\": False,\n", + " \"flavour_text\": color.BOLD + \"Antique! \" + color.END + \"Would be worth millions if it was not broken, cracked nor the home of a million of bugs.\",\n", + "}\n", + "piano = {\n", + " \"name\": \"piano\",\n", + " \"type\": \"furniture\",\n", + " \"useful\": True,\n", + " \"password\": \"9857\",\n", + " \"flavour_text\": \"Cords and... bones. Even not creepy pianos have bones\",\n", + "}\n", + "\n", + "# CORRIDOR\n", + "vault = {\n", + " \"name\": \"vault\",\n", + " \"type\": \"furniture\",\n", + " \"password\": \"volga\",\n", + " \"useful\": True,\n", + " \"flavour_text\": \"The lock has a message: \\\"For the sake of the future of this family, the answer is kept secret in the very heart of this great surname.\\\" <>\",\n", + "}\n", + "old_picture = {\n", + " \"name\": \"old picture\",\n", + " \"type\": \"furniture\",\n", + " \"useful\": False,\n", + " \"flavour_text\": \"2.8 - Oglav family at their Dacha close by a famous river.\",\n", + "}\n", + "# BATHROOM\n", + "bathtub = {\n", + " \"name\": \"bathtub\",\n", + " \"type\": \"furniture\",\n", + " \"useful\": True,\n", + " \"counter\": 0,\n", + " \"flavour_text\": \"The bathtub is filled with rain from the gap on the ceiling\",\n", + " \"sound\": sound_bathtub}\n", + "toilet = {\n", + " \"name\": \"toilet\",\n", + " \"type\": \"furniture\",\n", + " \"useful\": True,\n", + " \"flavour_text\": \"There's no time for number 1's or 2's, you have to leave this dacha!\",}\n", + "sink = {\n", + " \"name\": \"sink\",\n", + " \"type\": \"furniture\",\n", + " \"useful\": True,\n", + " \"flavour_text\": \"You feel bad for breaking the sink but you ain't no plumer\",}\n", + "cabinet = {\n", + " \"name\": \"toilet\",\n", + " \"type\": \"furniture\",\n", + " \"useful\": False,\n", + " \"flavour_text\": \"There is a shatered mirror and a small medicine box that says аспирин 3,5 миллиграмма\",}\n", + "rug = {\n", + " \"name\": \"rug\",\n", + " \"type\": \"furniture\",\n", + " \"useful\": True,\n", + " \"flavour_text\": \"Who the hell has a rug on a bathroom? I’ll keep looking somewhere else, maybe on the bathtub?\",}\n", + "\n", + "# KITCHEN\n", + "plate_cabinet = {\n", + " \"name\": \"plate cabinet\",\n", + " \"type\": \"furniture\",\n", + " \"useful\": False,\n", + " \"flavour_text\": \"Just some old fancy plates.\"\n", + "}\n", + "cutlery_drawer = {\n", + " \"name\": \"cutlery drawer\",\n", + " \"type\": \"furniture\",\n", + " \"useful\": True,\n", + " \"flavour_text\": \"It is full of stuff and things, nothing useful though.\",\n", + " \"sound\": sound_cutlery_drawer\n", + "}\n", + "table_with_chairs = {\n", + " \"name\": \"old table with chairs\",\n", + " \"type\": \"furniture\",\n", + " \"useful\": False,\n", + " \"flavour_text\": \"There are some cutlery and an old tsarist newspaper that says: \\\"Правда - 22 апреля 1912 года\\\". \\n It seems that reading a dictionary doesn't make you that fluent after all!\"\n", + "}\n", + "pantry = {\n", + " \"name\": \"pantry\",\n", + " \"type\": \"furniture\",\n", + " \"useful\": True,\n", + " \"object\": [\"wine\" , \"food can\"],\n", + " \"flavour_text\": \"It's full of food cans and wine bottles from another era, the tags barely visible.\"\n", + "}\n", + "stove_oven = {\n", + " \"name\": \"oven\",\n", + " \"type\": \"furniture\",\n", + " \"useful\": True,\n", + " \"password\": \"1890\",\n", + " \"flavour_text\": \"It is an old stove, the wood fueled kind. It is very scratched... life took a toll on it. \\n There is a small lock to open it, with 4 rotating numerical pieces.\",\n", + "}\n", + "# LIVING ROOM\n", + "old_lady = {\n", + " \"name\": \"old lady\",\n", + " \"type\": \"furniture\",\n", + " \"status\": \"sleeping\",\n", + " \"useful\": True,\n", + " \"flavour_text\": \"All dressed in black, no teeth and sitted on a wooden chair. You doubt she is still alive\",\n", + " \"sound\": sound_old_lady\n", + "}\n", + "pendulum = {\n", + " \"name\": \"pendulum\",\n", + " \"type\": \"furniture\",\n", + " \"useful\": True,\n", + " \"status\": \"closed\",\n", + " \"code\": \"0915\",\n", + " \"flavour_text\": \"What a gorgeous clock this must have been.\",\n", + "}\n", + "crib = {\n", + " \"name\": \"crib\",\n", + " \"type\": \"furniture\",\n", + " \"useful\": True,\n", + " \"flavour_text\": \"Do you really felt like checking this twice?\",\n", + "}\n", + "\n", + "# KNOWLEDGE\n", + "\n", + "russian = {\n", + "#Learn from bookshelf interaction\n", + " \"name\": \"russian\",\n", + " \"type\": \"knowledge\",\n", + " \"target\": side_table,\n", + "}\n", + "\n", + "wrench = {\n", + " \"name\": \"wrench\",\n", + " \"type\": \"knowledge\",\n", + " \"target\": sink,}\n", + "lever = {\n", + " \"name\": \"lever\",\n", + " \"type\": \"knowledge\",\n", + " \"target\": toilet,}\n", + "wine = {\n", + " \"name\": \"open wine\",\n", + " \"type\": \"knowledge\",\n", + " \"target\": old_lady}\n", + "wine_opener = {\n", + " \"name\": \"wine opener\",\n", + " \"type\": \"knowledge\",\n", + " \"target\": wine}\n", + "keys_pendulum = {\n", + " \"name\": \"keys pendulum\",\n", + " \"type\": \"knowledge\",\n", + " \"target\": pendulum, }\n", + "hammer = {\n", + " \"name\": \"hammer\",\n", + " \"type\": \"knowledge\",\n", + " \"target\": cutlery_drawer}\n", + "\n", + "\n", + "#KEYS\n", + "key_gameroom = {\n", + " \"name\": \"key for game room\",\n", + " \"type\": \"key\",\n", + " \"target\": door_gameroom,}\n", + "key_bathroom = {\n", + " \"name\": \"key for bathroom\",\n", + " \"type\": \"key\",\n", + " \"target\": door_bathroom,}\n", + "key_kitchen = {\n", + " \"name\": \"key for kitchen\",\n", + " \"type\": \"key\",\n", + " \"target\": door_kitchen,}\n", + "key_livingroom = {\n", + " \"name\": \"key for living room\",\n", + " \"type\": \"key\",\n", + " \"target\": door_livingroom,}\n", + "key_outside = {\n", + " \"name\": \"key for outside\",\n", + " \"type\": \"key\",\n", + " \"target\": door_other,}\n", + "\n", + "\n", + "# OUTSIDE\n", + "outside = {\n", + " \"name\": \"outside\"}\n", + "\n", + "# ALL\n", + "all_rooms = [game_room, corridor, bathroom, kitchen, living_room, outside]\n", + "all_doors = [door_gameroom, door_bathroom, door_livingroom, door_kitchen, door_other]\n", + "all_knowledge = [bookshelf, wrench, lever, wine_opener, wine, hammer]\n", + "# Here we should define all object relations\n", + " # At least these should be: \n", + " # For rooms: which objects (furnitures and doors - probably not knowledge) it contains.\n", + " # For furniture/people: which items(keys) it contains.\n", + " # For doors: which rooms they connect.\n", + " \n", + "object_relations = {\n", + " \"game room\": [couch, chairs, bookshelf, piano, side_table, wall_clock, door_gameroom],\n", + " \"bathroom\":[toilet, bathtub, sink, cabinet, rug, door_bathroom],\n", + " \"corridor\": [old_picture, vault, door_gameroom, door_bathroom, door_kitchen, door_livingroom],\n", + " \"kitchen\": [plate_cabinet, cutlery_drawer, stove_oven, table_with_chairs, pantry, door_kitchen],\n", + " \"living room\": [old_lady, pendulum, crib, door_livingroom, door_other],\n", + "\n", + " \"book shelf\": [key_gameroom],\n", + " \"vault\": [key_bathroom],\n", + "\n", + " #### RUI: Would making this Rug lower case (rug) make any difference ? It is lower case everywhere else.\n", + " \"Rug\": [key_kitchen],\n", + " \"oven\": [key_livingroom],\n", + " \"piano\": [key_outside],\n", + " \n", + "\n", + " \"bathtub\": [lever],\n", + " \"toilet\": [wrench],\n", + "\n", + " \"game room door\": [game_room, corridor],\n", + " \"living room door\": [corridor, living_room],\n", + " \"kitchen door\": [corridor, kitchen],\n", + " \"bathroom door\": [corridor, bathroom],\n", + " \"other door\": [living_room, outside],\n", + "\n", + " \"outside\": [door_other],\n", + "\n", + "}\n", + "# Here we need to define the original/starting state of the game.\n", + "# We need to say which is the starting room.\n", + "# We need to make empty lists for our keys_collected or for our knowledge.\n", + "# We need to establish the target (which is outside.) \n", + "\n", + "INIT_GAME_STATE = {\n", + " \"current_room\": game_room,\n", + " \"keys_collected\": [],\n", + " \"knowledge_collected\": [],\n", + " \"map_collected\": [game_room],\n", + " \"target_room\": outside\n", + "}" + ] + }, + { + "cell_type": "code", + "execution_count": 72, + "metadata": { + "id": "pVI6VLkaS-lN" + }, + "outputs": [], + "source": [ + "# Here we should try to put all new functions of general use we make\n", + "def linebreak():\n", + " \"\"\"\n", + " Print a line break\n", + " \"\"\"\n", + " print(\"\\n\")\n", + "\n", + "def play_my_sound(audio_string):\n", + " f = sf.SoundFile(audio_string)\n", + " lengh_audio = len(f) / f.samplerate\n", + " p = multiprocessing.Process(target=playsound, args=(audio_string,))\n", + " p.start()\n", + " time.sleep(lengh_audio)\n", + " p.terminate()\n", + "\n", + "def keys_in_pocket():\n", + " \"\"\"\n", + " List all keys currently obtained.\n", + " \"\"\"\n", + " #The for-loop gets all key_names. \n", + " #It looks inside the game_state dictonary for the value corresponding to the \"keys_collected\" key.\n", + " #It prints a message if no keys have been collected and another message if keys have been collected.\n", + " #The difference between the print in the elif and else is just to make sure \n", + " #that the last two keys are separated by a word \"and\" instead of a comma.\n", + " \n", + " myList = []\n", + " for i in range(len(game_state[\"keys_collected\"])):\n", + " myList.append(game_state[\"keys_collected\"][i].get(\"name\"))\n", + " \n", + " if len(myList)==0:\n", + " print('You have nothing on your pocket.')\n", + " elif len(myList)==1:\n", + " print('In your pocked you find: ' + ''.join(myList) + '.')\n", + " else:\n", + " print('In your pocked you find: ' + \" and \".join([\", \".join(myList[:-1]),myList[-1]]) + '.')\n", + "\n", + "def are_words_similar(s1,s2):\n", + " \"\"\"\n", + " Compares the lower case version of two words.\n", + " Allows for words to have one typo.\n", + " \"\"\"\n", + " s1 = s1.strip().lower()\n", + " s2 = s2.strip().lower()\n", + " if len(s1) > len(s2):\n", + " s1,s2 = s2,s1\n", + " s = sum([s1[i] != s2[i] for i in range(len(s1))])\n", + " if s == 1:\n", + " return True\n", + " else:\n", + " return False\n", + "\n", + "def show_map():\n", + " if game_room in game_state[\"map_collected\"] and corridor not in game_state[\"map_collected\"]:\n", + " display(game_room[\"map\"])\n", + " time.sleep(0.1)\n", + " return\n", + " elif corridor in game_state[\"map_collected\"] and bathroom not in game_state[\"map_collected\"]:\n", + " display(corridor[\"map\"])\n", + " time.sleep(0.1)\n", + " return\n", + " elif bathroom in game_state[\"map_collected\"] and kitchen not in game_state[\"map_collected\"]:\n", + " display(bathroom[\"map\"])\n", + " time.sleep(0.1)\n", + " return\n", + " elif kitchen in game_state[\"map_collected\"] and living_room not in game_state[\"map_collected\"]:\n", + " display(kitchen[\"map\"])\n", + " time.sleep(0.1)\n", + " return\n", + " elif living_room in game_state[\"map_collected\"]:\n", + " display(living_room[\"map\"])\n", + " time.sleep(0.1)\n", + " return" + ] + }, + { + "cell_type": "code", + "execution_count": 73, + "metadata": { + "id": "55EMPCGHDvIO" + }, + "outputs": [], + "source": [ + "# Game Room.\n", + "# Bookshelf Interactions (Function)\n", + "\n", + "def consult_books(knows_russian):\n", + " if knows_russian == False:\n", + " print(\"You look at the bookshelf. You find the following books:\")\n", + " for book in (bookshelf.get(\"books_in_russian\")):\n", + " print(str(bookshelf.get(\"books_in_russian\").index(book)) + str(\" - \" + book))\n", + " elif knows_russian == True:\n", + " print(\"You go to the bookshelf, you find many books in russian. Their tittles in English are:\")\n", + " for book in (bookshelf.get(\"books_in_english\")):\n", + " print(str(bookshelf.get(\"books_in_english\").index(book)) + str(\" - \" + book))\n", + "\n", + "def take_book(): \n", + " print('Do you want to take a book? Write: ' + color.DARKCYAN + color.BOLD + \"Yes\" + color.END + \" or \"+ color.DARKCYAN + color.BOLD + \"No\" + color.END)\n", + " take_book_yes_no = input('').lower().strip()\n", + " if take_book_yes_no == \"no\":\n", + " return \"no\"\n", + " elif take_book_yes_no == \"yes\":\n", + " return \"yes\" \n", + "\n", + "def choose_book(knows_russian):\n", + " print('Which book do you want to take? Write the number which identifies the book')\n", + " book_chosen = input('').lower().strip()\n", + " if knows_russian == False:\n", + " if book_chosen == str(15):\n", + " print('A dictionary! It helps reading russian. ' + color.UNDERLINE + 'You feel like you learnt something today.' + color.END)\n", + " game_state[\"knowledge_collected\"].append(russian)\n", + " side_table[\"flavour_text\"] = \"A table with a picture of an old lady reading a book on top of it. She is devouring the book called \" + color.BOLD + \"The Jungle Book.\" + color.END\n", + " return str(book_chosen)\n", + " elif book_chosen == str(4):\n", + " print('You do not speak baguette. You wonder why do French always copy English words... croissant comes to mind.')\n", + " print('You put back the book.')\n", + " return str(book_chosen)\n", + " elif book_chosen in str([0, 1, 2, 3, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 16]) or book_chosen in [\"zero\", \"one\", \"two\", \"three\", \"five\", \"six\", \"seven\", \"eight\", \"nine\", \"ten\", \"eleven\", \"twelve\", \"thirteen\", \"fourteen\", \"sixteen\"]:\n", + " print('These characters are somewhat familiar, but you have no idea how to prounounce anything.')\n", + " print('You put back the book.')\n", + " return str(book_chosen)\n", + " else:\n", + " print('Input unclear.')\n", + " choose_book(knows_russian)\n", + " return\n", + " elif knows_russian == True:\n", + " if book_chosen == str(15):\n", + " print('A dictionary! It helps reading russian... which you already know!')\n", + " print('You put back the book.')\n", + " return str(book_chosen)\n", + " elif book_chosen == str(16):\n", + " if key_gameroom in game_state[\"keys_collected\"]:\n", + " print('Classic literature... boring.')\n", + " return str(book_chosen)\n", + " else:\n", + " print('You open The Jungle. You find a key inside! ' + color.UNDERLINE + 'You take it with you!' + color.END)\n", + " game_state[\"keys_collected\"].append(key_gameroom)\n", + " return str(book_chosen)\n", + " elif book_chosen in str([0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14]) or book_chosen in [\"zero\", \"one\", \"two\", \"three\", \"four\", \"five\", \"six\", \"seven\", \"eight\", \"nine\", \"ten\", \"eleven\", \"twelve\", \"thirteen\", \"fourteen\"]:\n", + " print('Classic literature... boring.')\n", + " print('You put back the book.')\n", + " return str(book_chosen)\n", + " else:\n", + " print('Input unclear.')\n", + " choose_book(knows_russian)\n", + " return\n", + "\n", + "def play_bookshelf():\n", + " consult_books(russian in game_state[\"knowledge_collected\"])\n", + " if take_book() == \"yes\":\n", + " cycle_break = False\n", + " while not(cycle_break):\n", + " if choose_book(russian in game_state[\"knowledge_collected\"]) == \"15\" and not (russian in game_state[\"knowledge_collected\"]):\n", + " cycle_break = True\n", + " elif (russian in game_state[\"knowledge_collected\"]):\n", + " cycle_break = True\n", + " else:\n", + " return\n", + " \n", + "#The statement below adds the function above to the bookshelf dictionary/object.\n", + "bookshelf[\"play\"] = play_bookshelf" + ] + }, + { + "cell_type": "code", + "execution_count": 74, + "metadata": { + "id": "0mt-b6f_4d8S" + }, + "outputs": [], + "source": [ + "#Bathroom Functions, one per interactable furniture.\n", + "\n", + "def bathtub_check():\n", + " furniture = bathtub\n", + " have_tool = False\n", + " if (bathtub[\"counter\"] == 0):\n", + " play_my_sound(bathtub[\"sound\"])\n", + " print(\"You remove some of the waters, you see a comb floating. You do a minor attempt at uncloggin the bathtub.\")\n", + " print(\"A voice behind you says \" + color.BOLD + \"DEEPER\" + color.END + \" in a very sinister way.\")\n", + " bathtub[\"counter\"] +=1\n", + " play_room(game_state[\"current_room\"])\n", + " if (bathtub[\"counter\"] == 1):\n", + " play_my_sound(bathtub[\"sound\"])\n", + " print(\"You hear the same voice shouting \" + color.BOLD + \"I SAID DEEPER, BLYAT\" + color.END + \".\")\n", + " print(\"Better comply...\")\n", + " bathtub[\"counter\"] +=1\n", + " play_room(game_state[\"current_room\"])\n", + " if (bathtub[\"counter\"] == 2):\n", + " play_my_sound(bathtub[\"sound\"])\n", + " print(\"You are tired of of putting your arm elbow-deep into the pipes. Yet, within the cold water, you are able to find a cork stuck. \\n\"\n", + " \"After a few seconds you can take it off and drain the bathtub slowly. In the bottom you see what looks like a \" + color.UNDERLINE + \"toilet lever\" + color.END + \".\")\n", + " game_state[\"knowledge_collected\"].append(lever)\n", + " bathtub[\"useful\"] = False\n", + " play_room(game_state[\"current_room\"])\n", + "\n", + "def toilet_check():\n", + " furniture = toilet\n", + " have_tool = False\n", + " for tool in game_state[\"knowledge_collected\"]:\n", + " if(tool[\"target\"] == furniture):\n", + " have_tool = True\n", + " if(have_tool):\n", + " game_state[\"knowledge_collected\"].append(wrench)\n", + " print(\"You can work with the lever to flush it until midpoint. You see a shiny object and pick it up. It’s a \" + color.UNDERLINE + \"rusty steel wrench\" + color.END + \".\")\n", + " toilet[\"useful\"] = False\n", + " play_room(game_state[\"current_room\"])\n", + " else:\n", + " print(\"Eeeew. You can’t possibly get your arm onto that mess... the devs are not that mean.\")\n", + " play_room(game_state[\"current_room\"])\n", + " return None\n", + "\n", + "def sink_check():\n", + " furniture = sink\n", + " have_tool = False\n", + " for tool in game_state[\"knowledge_collected\"]:\n", + " if(tool[\"target\"] == furniture):\n", + " have_tool = True\n", + " if(have_tool):\n", + " print(\"You are a man of culture and go for the piping. You can easen some bolts until it falls apart and all water furiously drains down and something metallic shines and bounces to the rug.\")\n", + " sink[\"useful\"] = False\n", + " play_room(game_state[\"current_room\"])\n", + " else:\n", + " print(\"You put your right arm deep into the water and can’t unplug the thick substance. Looks like you could fix it by easing the water pipe.\")\n", + " play_room(game_state[\"current_room\"])\n", + "\n", + "def rug_check():\n", + " furniture = rug\n", + " if sink[\"useful\"] == False:\n", + " game_state[\"keys_collected\"].append(key_kitchen)\n", + " print(\"You pick the \"+ color.UNDERLINE + \"key\" + color.END + \" from the mushy floor that comes attached to a beer opener.\")\n", + " rug[\"useful\"] = False\n", + " play_room(game_state[\"current_room\"])\n", + " else:\n", + " print(\"Who the hell has a rug on a bathroom? I’ll keep looking somewhere else, maybe on the bathtub?\")\n", + " play_room(game_state[\"current_room\"])\n", + "\n", + "toilet[\"play\"] = toilet_check\n", + "sink[\"play\"] = sink_check\n", + "bathtub[\"play\"] = bathtub_check\n", + "rug[\"play\"] = rug_check" + ] + }, + { + "cell_type": "code", + "execution_count": 75, + "metadata": { + "id": "Fq827loV7cT-" + }, + "outputs": [], + "source": [ + "# KITCHEN\n", + "def open_cutlery_drawer():\n", + " have_wrench = False\n", + " if wrench in game_state[\"knowledge_collected\"]:\n", + " have_wrench = True\n", + " if (have_wrench == True):\n", + " play_my_sound(cutlery_drawer[\"sound\"])\n", + " print(\"You feel empowered enough to force the drawer and open it with the wrench. After the hit, you encounter something soft, yet crunchy. After inspection it was the putrid corpse of a rat that you moved and, below it, there is a \" + color.BOLD + \"wine opener.\" + color.END)\n", + " game_state[\"knowledge_collected\"].append(wine_opener)\n", + " cutlery_drawer[\"useful\"] = False\n", + " print(\"You have found a wine opener\")\n", + " play_room(game_state[\"current_room\"])\n", + " elif (wine_opener in game_state[\"knowledge_collected\"]):\n", + " print(\"There is just some old fashion cutlery.\")\n", + " else:\n", + " print(cutlery_drawer[\"flavour_text\"])\n", + " play_room(game_state[\"current_room\"])\n", + " return None\n", + "\n", + "def examine_pantry ():\n", + " print (pantry[\"flavour_text\"])\n", + " have_wine_opener = False\n", + " ### RUI'S COMMENT: We never talk about the exit command. I THINK IT WORKS DIFFERENTLY IN GOOGLE COLABORATIVE AND IN JUPYTER, SO I GUESS WE SHOULD REMOVE IT.\n", + " print(\"What would you like to examine? Type \" + (color.DARKCYAN + \" or \".join(pantry[\"object\"]) + color.END) + \". Type \\\"exit\\\" if you would like to go back to the kitchen.\")\n", + " to_examine = input()\n", + " if wine_opener in game_state[\"knowledge_collected\"]:\n", + " have_wine_opener = True\n", + " #### RUI'S COMMENT: I THINK THAT INSTEAD of to_examine == \"wine\" (or == \"food can\") we need \"old wines\" or \"food cans\" HERE !!!\n", + " if to_examine == \"wine\":\n", + " if have_wine_opener == False:\n", + " linebreak()\n", + " print(\"You pick a bottle and try the cork, but without the proper tool you can’t open it. On the tag you can read горули мцване 1890 so it’s been there for a while. The wine looks surprisingly well preserved.\")\n", + " print(\"Perhaps it was an important gift.\")\n", + " examine_pantry()\n", + " elif have_wine_opener == True:\n", + " linebreak()\n", + " print(\"Looks like a very Georgian wine. You imagine this is what rich people drink.\")\n", + " game_state[\"knowledge_collected\"].append(wine)\n", + " print(\"You have found \" + color.UNDERLINE + \"wine\" + color.END + \".\")\n", + " examine_pantry()\n", + " elif wine in game_state[\"knowledge_collected\"]:\n", + " linebreak()\n", + " print(\"Just some old fancy wines.\")\n", + " examine_pantry()\n", + " elif to_examine == \"food can\":\n", + " linebreak()\n", + " print (\"You take a can and see the tag has written Cрок годности 01-09-//////// on it. Looks like a date in which the year has faded over the time.\")\n", + " examine_pantry()\n", + " elif to_examine == \"exit\":\n", + " play_room(kitchen)\n", + " else:\n", + " print(\"Object not found. Try it again.\")\n", + " linebreak()\n", + " examine_pantry()\n", + " \n", + "\n", + "pantry[\"play\"] = examine_pantry\n", + "cutlery_drawer[\"play\"] = open_cutlery_drawer" + ] + }, + { + "cell_type": "code", + "execution_count": 76, + "metadata": { + "id": "utdxs7mvghUg" + }, + "outputs": [], + "source": [ + "#Living Room Functions\n", + "\n", + "def crib_check():\n", + " furniture = crib\n", + " print(\"You look into the crib. There is a one-eyed, bald baby doll and a mobile over it. You feel the doll follows your sight...\")\n", + " check = input(\"Want to check mobile or doll?\\n\").strip().lower()\n", + " if (check == \"doll\"):\n", + " print(\"You realize it is an old doll, without hair and with signs of violence, and it's looking to the mobile over it.\")\n", + " play_room(game_state[\"current_room\"])\n", + " if(check == \"mobile\"):\n", + " print(\"It is made of different wooden birds, and it starts playing a lullaby that makes the old woman wakes up and starts babling.\"\n", + " \"You feel nothing good will come from staying longer in this house\")\n", + " old_lady[\"status\"] = \"awaken\"\n", + " crib[\"useful\"] = False\n", + " play_room(game_state[\"current_room\"])\n", + " else:\n", + " print(\"Please enter either option given.\")\n", + " crib_check()\n", + "\n", + "def old_lady_check():\n", + " furniture = old_lady\n", + " have_hammer = False\n", + " if (old_lady[\"status\"] == \"sleeping\"):\n", + " print(\"She is a very old lady, wearing all black clothes and sitting on a wooden chair. You can't tell if she's asleep or dead but you'd better be carefull\")\n", + " play_room(game_state[\"current_room\"])\n", + " if (old_lady[\"status\"] == \"awaken\"):\n", + " if (wine in game_state[\"knowledge_collected\"]):\n", + " print(\"She wants the wine, do you want to open it for her? Go to the kitchen and use this hammer\")\n", + " if (wine_opener in game_state[\"knowledge_collected\"]):\n", + " old_lady[\"status\"] = \"drunk\"\n", + " game_state[\"knowledge_collected\"].append(keys_pendulum)\n", + " old_lady[\"useful\"] = False\n", + " play_my_sound(old_lady[\"sound\"])\n", + " print(\"She jumps and takes the bottle and the opener and proceeds to chug it. When doing so, a \" + color.UNDERLINE + \"set of small keys\" + color.END + \" fall from her lap to your hands.\")\n", + " else:\n", + " print(\"Maybe in the kitchen there's a tool to open it... The old woman salivates looking to the wine and shouts incohesive words to you, that most certainly aren’t compliments\")\n", + " else:\n", + " print(\"The old woman speaks in a broken voice but you can just recognise two word in russian that you learned in a pub a few years back. “wiii----ne p-----leeeeeeas---e\")\n", + " play_room(game_state[\"current_room\"])\n", + " else:\n", + " print(\"test\")\n", + " play_room(game_state[\"current_room\"])\n", + "\n", + "def pendulum_check():\n", + " furniture = pendulum\n", + " if (pendulum[\"status\"] == \"closed\"):\n", + " print(\"The pendulum clock is set at 9:15 AM, but it's stopped. you see yet another 4 digit locker on the door to access it.\")\n", + " print(\"Sigh... you wish there were password hints here. Everyone puts their codes on those.\")\n", + " try_password = input(\"Enter the 4 digit combination\").strip()\n", + " if (furniture[\"code\"] == try_password):\n", + " pendulum[\"status\"] = \"open\"\n", + " print(\"The lock opens but there is another issue...\")\n", + " if (try_password == \"exit\"):\n", + " play_room(game_state[\"current_room\"])\n", + " if(furniture[\"code\"] != try_password):\n", + " print('\"Wrong password.\" You try again')\n", + " pendulum_check()\n", + " if (pendulum[\"status\"] == \"open\"):\n", + " if (keys_pendulum in game_state[\"knowledge_collected\"]):\n", + " pendulum[\"useful\"] = False\n", + " print(\"You find a small paper \" + color.UNDERLINE + \"The last digit is 7\" + color.END + \"looks like some musical code\")\n", + " else:\n", + " print(\"There is a smaller box inside that could be opened with a set of keys\")\n", + " play_room(game_state[\"current_room\"])\n", + " else:\n", + " print(\"What a gorgeous clock this must have been.\")\n", + " play_room(game_state[\"current_room\"])\n", + "\n", + "crib[\"play\"] = crib_check\n", + "old_lady[\"play\"] = old_lady_check\n", + "pendulum[\"play\"] = pendulum_check\n" + ] + }, + { + "cell_type": "code", + "execution_count": 77, + "metadata": { + "id": "7TC2r1MyIMyE" + }, + "outputs": [], + "source": [ + "def piano_check():\n", + " furniture = piano\n", + " print(\"The piano there is a 4 digit locker on the lid. Pianos don't have lockers unless they have something inside that you want.\")\n", + " try_password = input(\"Enter the 4 digit combination\").strip()\n", + " if (piano[\"code\"] == try_password):\n", + " piano[\"useful\"] = False\n", + " game_state[\"keys_collected\"].append(key_outside)\n", + " print(\"It is open!\")\n", + " if (try_password == \"exit\"):\n", + " return\n", + " if (furniture[\"code\"] != try_password):\n", + " print('\"Wrong password.\" You try again')\n", + " piano_check()" + ] + }, + { + "cell_type": "code", + "execution_count": 78, + "metadata": { + "id": "IkA-BsKlWKzD" + }, + "outputs": [], + "source": [ + "# Enter password \n", + "def enter_password(item):\n", + " print((\"The \" + item[\"name\"] + \" has a password! Enter the password or type \\\"exit\\\" to go back to room\"))\n", + " try_password = input().strip().lower()\n", + " output = \"\"\n", + " if (item[\"password\"] == try_password):\n", + " output = \"Correct password!\"\n", + " linebreak()\n", + " if(item[\"name\"] in object_relations and len(object_relations[item[\"name\"]])>0):\n", + " item_found = object_relations[item[\"name\"]].pop()\n", + " game_state[\"keys_collected\"].append(item_found)\n", + " output = \"You find \" + item_found[\"name\"] + \".\"\n", + " print (output)\n", + " elif (try_password == \"exit\"):\n", + " play_room(game_state[\"current_room\"])\n", + " else:\n", + " output += \"Wrong password.\"\n", + " print (output)\n", + " enter_password(item)\n", + "\n", + "vault[\"play\"] = enter_password\n", + "stove_oven[\"play\"] = enter_password\n", + "piano[\"play\"] = enter_password" + ] + }, + { + "cell_type": "code", + "execution_count": 79, + "metadata": { + "id": "WhuLmtzySq2e" + }, + "outputs": [], + "source": [ + "# Here is where the \"main\" cycles are.\n", + "def start_game():\n", + " #Resetting variables which are changed throughout code execution.\n", + " side_table[\"flavour_text\"] = \"A table with a picture of an old lady reading a book on top of it. She is devouring the book called \" + color.BOLD + \"книга джунглей.\" + color.END\n", + " print(\"You wake up on a couch and find yourself in a strange house with no windows which you have never been to before.\")\n", + " print(\"You don't remember why you are here and what had happened before. You feel some unknown danger is approaching and you must get out of the house, NOW!\")\n", + " play_room(game_state[\"current_room\"])\n", + "\n", + "def play_room(room):\n", + " \"\"\"\n", + " Play a room. First check if the room being played is the target room.\n", + " If it is, the game will end with success. Otherwise, let player either \n", + " explore (list all items in this room) or examine an item found here.\n", + " \"\"\"\n", + " game_state[\"current_room\"] = room\n", + " if(game_state[\"current_room\"] == game_state[\"target_room\"]):\n", + " #play_my_sound(sound_victory)\n", + " print(color.GREEN + color.BOLD + \"Congrats! You escaped the room!\" + color.END)\n", + " else:\n", + " print(\"You are now in \" + room[\"name\"])\n", + " print(\"What would you like to do? Type 'explore' or 'examine'? \\n\")\n", + " intended_action = input(\"\").strip().lower()\n", + " if intended_action == \"explore\": ### Here we should use the are_words_similar(s1,s2) function instead.\n", + " explore_room(room)\n", + " print(\"\\n\")\n", + " play_room(room)\n", + " elif intended_action == \"examine\": ### Here we should use the are_words_similar(s1,s2) function instead.\n", + " print(\"What would you like to examine?\")\n", + " use_item_choice = input(\"\").strip().lower()\n", + " \n", + " if examine_silent(use_item_choice) != None:\n", + " room = examine_item(use_item_choice)\n", + " print(\"\\n\")\n", + " play_room(room)\n", + " else:\n", + " print(\"\\n\")\n", + " play_room(room)\n", + " elif intended_action == \"exit\": ### Here we should use the are_words_similar(s1,s2) function instead.\n", + " quit(keep_kernel=True)\n", + " else:\n", + " print(\"Not sure what you mean. Type 'explore' or 'examine'.\")\n", + " play_room(room)\n", + " print(\"\\n\")\n", + "\n", + "def explore_room(room):\n", + " \"\"\"Explore a room. List all items belonging to this room.\"\"\"\n", + " items = [i[\"name\"] for i in object_relations[room[\"name\"]]]\n", + " print(\"You explore the room. This is \" + room[\"name\"] + \". You find \" + \", \".join(items))\n", + " keys_in_pocket()\n", + " print(\"You scrapped some notes about the layout of the house. Do you want to see them? Write: \" + color.DARKCYAN + color.BOLD + \"Yes\" + color.END + \" or \"+ color.DARKCYAN + color.BOLD + \"No\" + color.END)\n", + " yes_no_show_map = input().strip().lower()\n", + " if yes_no_show_map == \"yes\":\n", + " show_map()\n", + " return\n", + " elif yes_no_show_map == \"no\":\n", + " return\n", + " else:\n", + " print(\"Not sure what you mean...\")\n", + " explore_room(room)\n", + "\n", + "def get_next_room_of_door(door, current_room):\n", + " \"\"\"From object_relations, find the two rooms connected to the given door. Return the room that is not the current_room.\"\"\"\n", + " connected_rooms = object_relations[door[\"name\"]]\n", + " play_my_sound(sound_door_creaking)\n", + " for room in connected_rooms:\n", + " if(not current_room == room):\n", + " return room\n", + "\n", + "# Function to examine item. Similar to that of the original project.\n", + "def examine_item(item_name):\n", + " \n", + " room = game_state[\"current_room\"]\n", + " \n", + " #### RUI: I THINK THAT THE REASON WHY THE \"Thanks to the key, you move on to the next room.\" APPEARS TWICE IS.\n", + " #### BECAUSE THIS LOOP ALWAYS LOOPS THROUGH THE TWO ITEMS THAT ARE IN EACH OF THE OBJECT RELATIONS OF EACH ROOM.\n", + " #### NOT SURE HOW TO FIX IT THOUGH.\n", + " \n", + " for item in object_relations[room[\"name\"]]:\n", + " if(item[\"name\"] == item_name):\n", + " #The if below governs what happens if we are not interaction with a door.\n", + " if item[\"type\"] != \"door\": \n", + " output = \"You examine \" + item_name + \":\"\n", + " # ... if the item is not useful we just throw in the flavour text\n", + " # \n", + " if(item[\"useful\"] == False):\n", + " print(item[\"flavour_text\"])\n", + " return None\n", + " play_room(room)\n", + " # ... if it is useful we throw in the function which is stored in the key \"play\" of the object.\n", + " elif (item[\"useful\"] == True):\n", + " if (\"password\" in item):\n", + " print(item[\"flavour_text\"])\n", + " item.get(\"play\")(item)\n", + " elif (\"password\" not in item):\n", + " item.get(\"play\")()\n", + " return None\n", + " # if it is a door, we have the same interaction as in the sample (to open it).\n", + " elif (item[\"type\"] == \"door\"):\n", + " have_key = False\n", + " for key in game_state[\"keys_collected\"]:\n", + " if(key[\"target\"] == item):\n", + " have_key = True\n", + " if(have_key):\n", + " print(\"Thanks to the key, you move on to the next room. The door slowly shuts itself behind you.\")\n", + " next_room = get_next_room_of_door(item, room)\n", + " game_state[\"map_collected\"].append(next_room)\n", + " return next_room\n", + " else:\n", + " print(\"It is locked but you don't have the key.\")\n", + " return None\n", + " #else: return\n", + "\n", + "def examine_silent(item_name):\n", + " \n", + " room = game_state[\"current_room\"]\n", + " for item in object_relations[room[\"name\"]]:\n", + " if(item[\"name\"] == item_name):\n", + " #The if below governs what happens if we are not interaction with a door.\n", + " if item[\"type\"] != \"door\": \n", + " output = \"You examine \" + item_name + \":\"\n", + " # ... if the item is not useful we just throw in the flavour text\n", + " # \n", + " if(item[\"useful\"] == False):\n", + " print(item[\"flavour_text\"])\n", + " return None\n", + " play_room(room)\n", + " # ... if it is useful we throw in the function which is stored in the key \"play\" of the object.\n", + " elif (item[\"useful\"] == True):\n", + " if (\"password\" in item):\n", + " print(item[\"flavour_text\"])\n", + " item.get(\"play\")(item)\n", + " elif (\"password\" not in item):\n", + " item.get(\"play\")()\n", + " return None\n", + " # if it is a door, we have the same interaction as in the sample (to open it).\n", + " elif (item[\"type\"] == \"door\"):\n", + " have_key = False\n", + " for key in game_state[\"keys_collected\"]:\n", + " if(key[\"target\"] == item):\n", + " have_key = True\n", + " if(have_key):\n", + " next_room = get_next_room_of_door(item, room)\n", + " game_state[\"map_collected\"].append(next_room)\n", + " return next_room\n", + " else:\n", + " return None" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "game_state = INIT_GAME_STATE.copy()\n", + "start_game()" + ] + }, + { + "cell_type": "code", + "execution_count": 80, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "You wake up on a couch and find yourself in a strange house with no windows which you have never been to before.\n", + "You don't remember why you are here and what had happened before. You feel some unknown danger is approaching and you must get out of the house, NOW!\n", + "You are now in game room\n", + "What would you like to do? Type 'explore' or 'examine'? \n", + "\n" + ] + }, + { + "ename": "KeyboardInterrupt", + "evalue": "Interrupted by user", + "output_type": "error", + "traceback": [ + "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[1;31mKeyboardInterrupt\u001b[0m Traceback (most recent call last)", + "\u001b[1;32m\u001b[0m in \u001b[0;36m\u001b[1;34m\u001b[0m\n\u001b[0;32m 1\u001b[0m \u001b[0mgame_state\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mINIT_GAME_STATE\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mcopy\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 2\u001b[1;33m \u001b[0mstart_game\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m", + "\u001b[1;32m\u001b[0m in \u001b[0;36mstart_game\u001b[1;34m()\u001b[0m\n\u001b[0;32m 5\u001b[0m \u001b[0mprint\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m\"You wake up on a couch and find yourself in a strange house with no windows which you have never been to before.\"\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 6\u001b[0m \u001b[0mprint\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m\"You don't remember why you are here and what had happened before. You feel some unknown danger is approaching and you must get out of the house, NOW!\"\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 7\u001b[1;33m \u001b[0mplay_room\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mgame_state\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;34m\"current_room\"\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 8\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 9\u001b[0m \u001b[1;32mdef\u001b[0m \u001b[0mplay_room\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mroom\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n", + "\u001b[1;32m\u001b[0m in \u001b[0;36mplay_room\u001b[1;34m(room)\u001b[0m\n\u001b[0;32m 20\u001b[0m \u001b[0mprint\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m\"You are now in \"\u001b[0m \u001b[1;33m+\u001b[0m \u001b[0mroom\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;34m\"name\"\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 21\u001b[0m \u001b[0mprint\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m\"What would you like to do? Type 'explore' or 'examine'? \\n\"\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m---> 22\u001b[1;33m \u001b[0mintended_action\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0minput\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m\"\"\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mstrip\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mlower\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 23\u001b[0m \u001b[1;32mif\u001b[0m \u001b[0mintended_action\u001b[0m \u001b[1;33m==\u001b[0m \u001b[1;34m\"explore\"\u001b[0m\u001b[1;33m:\u001b[0m \u001b[1;31m### Here we should use the are_words_similar(s1,s2) function instead.\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 24\u001b[0m \u001b[0mexplore_room\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mroom\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n", + "\u001b[1;32mc:\\users\\eloi pc\\appdata\\local\\programs\\python\\python38-32\\lib\\site-packages\\ipykernel\\kernelbase.py\u001b[0m in \u001b[0;36mraw_input\u001b[1;34m(self, prompt)\u001b[0m\n\u001b[0;32m 858\u001b[0m \u001b[1;34m\"raw_input was called, but this frontend does not support input requests.\"\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 859\u001b[0m )\n\u001b[1;32m--> 860\u001b[1;33m return self._input_request(str(prompt),\n\u001b[0m\u001b[0;32m 861\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_parent_ident\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 862\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_parent_header\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n", + "\u001b[1;32mc:\\users\\eloi pc\\appdata\\local\\programs\\python\\python38-32\\lib\\site-packages\\ipykernel\\kernelbase.py\u001b[0m in \u001b[0;36m_input_request\u001b[1;34m(self, prompt, ident, parent, password)\u001b[0m\n\u001b[0;32m 902\u001b[0m \u001b[1;32mexcept\u001b[0m \u001b[0mKeyboardInterrupt\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 903\u001b[0m \u001b[1;31m# re-raise KeyboardInterrupt, to truncate traceback\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 904\u001b[1;33m \u001b[1;32mraise\u001b[0m \u001b[0mKeyboardInterrupt\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m\"Interrupted by user\"\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;32mfrom\u001b[0m \u001b[1;32mNone\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 905\u001b[0m \u001b[1;32mexcept\u001b[0m \u001b[0mException\u001b[0m \u001b[1;32mas\u001b[0m \u001b[0me\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 906\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mlog\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mwarning\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m\"Invalid Message:\"\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mexc_info\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;32mTrue\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n", + "\u001b[1;31mKeyboardInterrupt\u001b[0m: Interrupted by user" + ] + } + ], + "source": [ + "game_state = INIT_GAME_STATE.copy() \n", + "start_game()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "colab": { + "collapsed_sections": [], + "name": "Python Escape Room.ipynb", + "provenance": [] + }, + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.8.3" + } + }, + "nbformat": 4, + "nbformat_minor": 1 +} diff --git a/your-code/.ipynb_checkpoints/Escape_Room_Angel_Eloi_Rui-checkpoint.ipynb b/your-code/.ipynb_checkpoints/Escape_Room_Angel_Eloi_Rui-checkpoint.ipynb new file mode 100644 index 00000000..eceaf874 --- /dev/null +++ b/your-code/.ipynb_checkpoints/Escape_Room_Angel_Eloi_Rui-checkpoint.ipynb @@ -0,0 +1,1581 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 85 + }, + "id": "uRjaA6neUGcr", + "outputId": "26d6a096-bc21-4165-819d-f4277543cab4" + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "zsh:1: command not found: pip\r\n" + ] + }, + { + "ename": "ModuleNotFoundError", + "evalue": "No module named 'soundfile'", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mModuleNotFoundError\u001b[0m Traceback (most recent call last)", + "\u001b[0;32m\u001b[0m in \u001b[0;36m\u001b[0;34m\u001b[0m\n\u001b[1;32m 9\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0mmultiprocessing\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 10\u001b[0m \u001b[0mget_ipython\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msystem\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'pip install soundfile'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 11\u001b[0;31m \u001b[0;32mimport\u001b[0m \u001b[0msoundfile\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0msf\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 12\u001b[0m \u001b[0mget_ipython\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msystem\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'pip install playsound'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 13\u001b[0m \u001b[0;32mfrom\u001b[0m \u001b[0mplaysound\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0mplaysound\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;31mModuleNotFoundError\u001b[0m: No module named 'soundfile'" + ] + } + ], + "source": [ + "# Here we should import all packages and define other things such as classes\n", + "import time\n", + "import numpy as np\n", + "import pandas as pd\n", + "from IPython.display import Audio\n", + "from IPython.display import Image\n", + "from IPython.display import display\n", + "\n", + "import multiprocessing\n", + "!pip install soundfile\n", + "import soundfile as sf\n", + "!pip install playsound\n", + "from playsound import playsound\n", + "\n", + "class color:\n", + " ### How to use:\n", + " ### print(color.BOLD + 'Hello World !' + color.END)\n", + " ### print(color.DARKCYAN + color.BOLD + 'Hello World !' + color.END)\n", + " PURPLE = '\\033[95m'\n", + " CYAN = '\\033[96m'\n", + " DARKCYAN = '\\033[36m'\n", + " BLUE = '\\033[94m'\n", + " GREEN = '\\033[92m'\n", + " YELLOW = '\\033[93m'\n", + " RED = '\\033[91m'\n", + " BOLD = '\\033[1m'\n", + " UNDERLINE = '\\033[4m'\n", + " END = '\\033[0m'\n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": { + "id": "IHF3ccywR3zo" + }, + "outputs": [], + "source": [ + "# Object declaration/initialization.\n", + "\n", + "# RUI: Library of Images and sounds\n", + "# [RUI: to be done, now dummy data just to test // sounds will not run properly on colaborative]\n", + "map_game_room = Image(filename=\"sounds_and_images\\map_game_room.png\")\n", + "map_corridor = Image(filename=\"sounds_and_images\\map_corridor.png\")\n", + "map_bathroom = Image(filename=\"sounds_and_images\\map_bathroom.png\")\n", + "map_kitchen = Image(filename=\"sounds_and_images\\map_kitchen.png\")\n", + "map_living_room = Image(filename=\"sounds_and_images\\map_living_room.png\")\n", + "\n", + "#[Rui, these soun]\n", + "sound_bathtub = \"sounds_and_images\\clogged_bathtub.wav\"\n", + "sound_old_lady = \"sounds_and_images\\gulping_bottle.wav\"\n", + "sound_cutlery_drawer = \"sounds_and_images\\smashing_wood.wav\"\n", + "\n", + "# [RUI: This one could be called maybe when we write \"congratulations\".]\n", + "sound_victory = \"sounds_and_images\\victory.wav\"\n", + "# [RUI: This one can be called maybe when we call the function to get the next room.]\n", + "sound_door_creaking = \"sounds_and_images\\door_creaking.wav\"\n", + "\n", + "# Definition of ROOMS:\n", + "game_room = {\n", + " \"name\": \"game room\",\n", + " \"type\": \"room\",\n", + " \"map\": map_game_room}\n", + "corridor = {\n", + " \"name\": \"corridor\",\n", + " \"type\": \"room\",\n", + " \"map\": map_corridor}\n", + "bathroom = {\n", + " \"name\": \"bathroom\",\n", + " \"type\": \"room\",\n", + " \"map\": map_bathroom}\n", + "kitchen = {\n", + " \"name\": \"kitchen\",\n", + " \"type\": \"room\",\n", + " \"map\": map_kitchen}\n", + "living_room = {\n", + " \"name\": \"living room\",\n", + " \"type\": \"room\",\n", + " \"map\": map_living_room}\n", + "\n", + "# Definition of DOORS\n", + "door_gameroom = {\n", + " \"name\": \"game room door\",\n", + " \"type\": \"door\",}\n", + "door_bathroom = {\n", + " \"name\": \"bathroom door\",\n", + " \"type\": \"door\",}\n", + "door_kitchen = {\n", + " \"name\": \"kitchen door\",\n", + " \"type\": \"door\",}\n", + "door_livingroom = {\n", + " \"name\": \"living room door\",\n", + " \"type\": \"door\",}\n", + "door_other = {\n", + " \"name\": \"other door\",\n", + " \"type\": \"door\",}\n", + "\n", + "# FURNITURE AND PEOPLE\n", + "\n", + "# GAME ROOM\n", + "side_table = {\n", + " \"name\": \"side table\",\n", + " \"type\": \"furniture\",\n", + " \"useful\": False,\n", + " #flavour_text of side table is set at start with the start game function.\n", + " \"flavour_text\": \"\"}\n", + "couch = {\n", + " \"name\": \"couch\",\n", + " \"type\": \"furniture\",\n", + " \"useful\": False,\n", + " \"flavour_text\": \"Potato.\",\n", + "}\n", + "piano = {\n", + " \"name\": \"piano\",\n", + " \"type\": \"furniture\",\n", + " \"useful\": True,\n", + " \"status\": \"closed\",\n", + " \"code\": \"9857\",\n", + " \"flavour_text\": \"You would be surprised if it was working.\",\n", + "}\n", + "chairs = {\n", + " \"name\": \"chairs\",\n", + " \"type\": \"furniture\",\n", + " \"useful\": False,\n", + " \"flavour_text\": \"Previously owned by a dictator.\",\n", + "}\n", + "bookshelf = {\n", + " \"name\": \"bookshelf\",\n", + " \"type\": \"furniture\",\n", + " \"useful\": True,\n", + " \"books_in_russian\": [\"Преступление и наказание\",\"Маленькие женщины\",\"Большие надежды\",\"Война и мир\",\"Les Misérables\",\"Записки из метро\", \"Белые ночи\", \"Сон о смехотворном человеке\",\"Идиот\",\"Женщина в белом\",\"Отцы и сыновья\",\"Лунный камень\",\"Сайлас Марнер\",\"Путешествие к центру Земли\",\"Мельница на зубной нити\",\"Русско-английский словарь/English–Russian Dictionary\",\"книга джунглей\"],\n", + " \"books_in_english\": [\"Crime and Punishment\",\"Little Women\",\"Great Expectations\",\"War and Peace\",\"Les Misérables\", \"Notes from Underground\",\"White Nights\",\"Dreams of a ridiculous man\",\"The Idiot\",\"The Woman in White\",\"Fathers and Sons\",\"The Moonstone\",\"Silas Marner\",\"Journey to the Center of the Earth\",\"The Mill on the Floss\",\"Russian-English Dictionary/English–Russian Dictionary\",\"The Jungle Book\"],\n", + " \"flavour_text\": \"Packed!\",\n", + " # Bookshelf will have another property key \"play\" with a function attributed as value.\n", + "}\n", + "wall_clock = {\n", + " \"name\": \"wall clock\",\n", + " \"type\": \"furniture\",\n", + " \"useful\": False,\n", + " \"flavour_text\": color.BOLD + \"Antique! \" + color.END + \"Would be worth millions if it was not broken, cracked nor the home of a million of bugs.\",\n", + "}\n", + "piano = {\n", + " \"name\": \"piano\",\n", + " \"type\": \"furniture\",\n", + " \"useful\": True,\n", + " \"code\": \"9857\",\n", + " \"flavour_text\": \"Cords and... bones. Even not creepy pianos have bones\",\n", + "}\n", + "\n", + "# CORRIDOR\n", + "vault = {\n", + " \"name\": \"vault\",\n", + " \"type\": \"furniture\",\n", + " \"password\": \"volga\",\n", + " \"useful\": True,\n", + " \"flavour_text\": \"The lock has a message: \\\"For the sake of the future of this family, the answer is kept secret in the very heart of this great surname.\\\" <>\",\n", + "}\n", + "old_picture = {\n", + " \"name\": \"old picture\",\n", + " \"type\": \"furniture\",\n", + " \"useful\": False,\n", + " \"flavour_text\": \"2.8 - Oglav family at their Dacha close by a famous river.\",\n", + "}\n", + "# BATHROOM\n", + "bathtub = {\n", + " \"name\": \"bathtub\",\n", + " \"type\": \"furniture\",\n", + " \"useful\": True,\n", + " \"counter\": 0,\n", + " \"flavour_text\": \"The bathtub is filled with rain from the gap on the ceiling\",\n", + " \"sound\": sound_bathtub}\n", + "toilet = {\n", + " \"name\": \"toilet\",\n", + " \"type\": \"furniture\",\n", + " \"useful\": True,\n", + " \"flavour_text\": \"There's no time for number 1's or 2's, you have to leave this dacha!\",}\n", + "sink = {\n", + " \"name\": \"sink\",\n", + " \"type\": \"furniture\",\n", + " \"useful\": True,\n", + " \"flavour_text\": \"You feel bad for breaking the sink but you ain't no plumer\",}\n", + "cabinet = {\n", + " \"name\": \"toilet\",\n", + " \"type\": \"furniture\",\n", + " \"useful\": False,\n", + " \"flavour_text\": \"There is a shatered mirror and a small medicine box that says аспирин 3,5 миллиграмма\",}\n", + "rug = {\n", + " \"name\": \"rug\",\n", + " \"type\": \"furniture\",\n", + " \"useful\": True,\n", + " \"flavour_text\": \"Who the hell has a rug on a bathroom? I’ll keep looking somewhere else, maybe on the bathtub?\",}\n", + "\n", + "# KITCHEN\n", + "plate_cabinet = {\n", + " \"name\": \"plate cabinet\",\n", + " \"type\": \"furniture\",\n", + " \"useful\": False,\n", + " \"flavour_text\": \"Just some old fancy plates.\"\n", + "}\n", + "cutlery_drawer = {\n", + " \"name\": \"cutlery drawer\",\n", + " \"type\": \"furniture\",\n", + " \"useful\": False,\n", + " \"flavour_text\": \"It is full of stuff and things, nothing useful though.\",\n", + " \"sound\": sound_cutlery_drawer\n", + "}\n", + "table_with_chairs = {\n", + " \"name\": \"old table with chairs\",\n", + " \"type\": \"furniture\",\n", + " \"useful\": False,\n", + " \"flavour_text\": \"There are some cutlery and an old tsarist newspaper that says: \\\"Правда - 22 апреля 1912 года\\\". \\n It seems that reading a dictionary doesn't make you that fluent after all!\"\n", + "}\n", + "pantry = {\n", + " \"name\": \"pantry\",\n", + " \"type\": \"furniture\",\n", + " \"useful\": True,\n", + " \"object\": [\"wine\" , \"food can\"],\n", + " \"flavour_text\": \"It's full of food cans and wine bottles from another era, the tags barely visible.\"\n", + "}\n", + "stove_oven = {\n", + " \"name\": \"oven\",\n", + " \"type\": \"furniture\",\n", + " \"useful\": True,\n", + " \"password\": \"1890\",\n", + " \"flavour_text\": \"It is an old stove, the wood fueled kind. It is very scratched... life took a toll on it. \\n There is a small lock to open it, with 4 rotating numerical pieces.\",\n", + "}\n", + "# LIVING ROOM\n", + "old_lady = {\n", + " \"name\": \"old lady\",\n", + " \"type\": \"furniture\",\n", + " \"status\": \"sleeping\",\n", + " \"useful\": True,\n", + " \"flavour_text\": \"All dressed in black, no teeth and sitted on a wooden chair. You doubt she is still alive\",\n", + " \"sound\": sound_old_lady\n", + "}\n", + "pendulum = {\n", + " \"name\": \"pendulum\",\n", + " \"type\": \"furniture\",\n", + " \"useful\": True,\n", + " \"status\": \"closed\",\n", + " \"code\": \"0915\",\n", + " \"flavour_text\": \"What a gorgeous clock this must have been.\",\n", + "}\n", + "crib = {\n", + " \"name\": \"crib\",\n", + " \"type\": \"furniture\",\n", + " \"useful\": True,\n", + " \"flavour_text\": \"Do you really felt like checking this twice?\",\n", + "}\n", + "\n", + "# KNOWLEDGE\n", + "\n", + "russian = {\n", + "#Learn from bookshelf interaction\n", + " \"name\": \"russian\",\n", + " \"type\": \"knowledge\",\n", + " \"target\": side_table,\n", + "}\n", + "\n", + "wrench = {\n", + " \"name\": \"wrench\",\n", + " \"type\": \"knowledge\",\n", + " \"target\": sink,}\n", + "lever = {\n", + " \"name\": \"lever\",\n", + " \"type\": \"knowledge\",\n", + " \"target\": toilet,}\n", + "wine = {\n", + " \"name\": \"open wine\",\n", + " \"type\": \"knowledge\",\n", + " \"target\": old_lady}\n", + "wine_opener = {\n", + " \"name\": \"wine opener\",\n", + " \"type\": \"knowledge\",\n", + " \"target\": wine}\n", + "keys_pendulum = {\n", + " \"name\": \"keys pendulum\",\n", + " \"type\": \"knowledge\",\n", + " \"target\": pendulum, }\n", + "hammer = {\n", + " \"name\": \"hammer\",\n", + " \"type\": \"knowledge\",\n", + " \"target\": cutlery_drawer}\n", + "\n", + "\n", + "#KEYS\n", + "key_gameroom = {\n", + " \"name\": \"key for game room\",\n", + " \"type\": \"key\",\n", + " \"target\": door_gameroom,}\n", + "key_bathroom = {\n", + " \"name\": \"key for bathroom\",\n", + " \"type\": \"key\",\n", + " \"target\": door_bathroom,}\n", + "key_kitchen = {\n", + " \"name\": \"key for kitchen\",\n", + " \"type\": \"key\",\n", + " \"target\": door_kitchen,}\n", + "key_livingroom = {\n", + " \"name\": \"key for living room\",\n", + " \"type\": \"key\",\n", + " \"target\": door_livingroom,}\n", + "key_outside = {\n", + " \"name\": \"key for outside\",\n", + " \"type\": \"key\",\n", + " \"target\": door_other,}\n", + "\n", + "\n", + "# OUTSIDE\n", + "outside = {\n", + " \"name\": \"outside\"}\n", + "\n", + "# ALL\n", + "all_rooms = [game_room, corridor, bathroom, kitchen, living_room, outside]\n", + "all_doors = [door_gameroom, door_bathroom, door_livingroom, door_kitchen, door_other]\n", + "all_knowledge = [bookshelf, wrench, lever, wine_opener, wine, hammer]\n", + "# Here we should define all object relations\n", + " # At least these should be: \n", + " # For rooms: which objects (furnitures and doors - probably not knowledge) it contains.\n", + " # For furniture/people: which items(keys) it contains.\n", + " # For doors: which rooms they connect.\n", + " \n", + "object_relations = {\n", + " \"game room\": [couch, chairs, bookshelf, piano, side_table, wall_clock, door_gameroom],\n", + " \"bathroom\":[toilet, bathtub, sink, cabinet, rug, door_bathroom],\n", + " \"corridor\": [old_picture, vault, door_gameroom, door_bathroom, door_kitchen, door_livingroom],\n", + " \"kitchen\": [plate_cabinet, cutlery_drawer, stove_oven, table_with_chairs, pantry, door_kitchen],\n", + " \"living room\": [old_lady, pendulum, crib, door_livingroom, door_other],\n", + "\n", + " \"book shelf\": [key_gameroom],\n", + " \"vault\": [key_bathroom],\n", + "\n", + " #### RUI: Would making this Rug lower case (rug) make any difference ? It is lower case everywhere else.\n", + " \"Rug\": [key_kitchen],\n", + " \"oven\": [key_livingroom],\n", + " \"piano\": [key_outside],\n", + " \n", + "\n", + " \"bathtub\": [lever],\n", + " \"toilet\": [wrench],\n", + "\n", + " \"game room door\": [game_room, corridor],\n", + " \"living room door\": [corridor, living_room],\n", + " \"kitchen door\": [corridor, kitchen],\n", + " \"bathroom door\": [corridor, bathroom],\n", + " \"other door\": [living_room, outside],\n", + "\n", + " \"outside\": [door_other],\n", + "\n", + "}\n", + "# Here we need to define the original/starting state of the game.\n", + "# We need to say which is the starting room.\n", + "# We need to make empty lists for our keys_collected or for our knowledge.\n", + "# We need to establish the target (which is outside.) \n", + "\n", + "INIT_GAME_STATE = {\n", + " \"current_room\": game_room,\n", + " \"keys_collected\": [],\n", + " \"knowledge_collected\": [],\n", + " \"map_collected\": [game_room],\n", + " \"target_room\": outside\n", + "}" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": { + "id": "pVI6VLkaS-lN" + }, + "outputs": [], + "source": [ + "# Here we should try to put all new functions of general use we make\n", + "def linebreak():\n", + " \"\"\"\n", + " Print a line break\n", + " \"\"\"\n", + " print(\"\\n\")\n", + "\n", + "def play_my_sound(audio_string):\n", + " f = sf.SoundFile(audio_string)\n", + " lengh_audio = len(f) / f.samplerate\n", + " p = multiprocessing.Process(target=playsound, args=(audio_string,))\n", + " p.start()\n", + " time.sleep(lengh_audio)\n", + " p.terminate()\n", + "\n", + "def keys_in_pocket():\n", + " \"\"\"\n", + " List all keys currently obtained.\n", + " \"\"\"\n", + " #The for-loop gets all key_names. \n", + " #It looks inside the game_state dictonary for the value corresponding to the \"keys_collected\" key.\n", + " #It prints a message if no keys have been collected and another message if keys have been collected.\n", + " #The difference between the print in the elif and else is just to make sure \n", + " #that the last two keys are separated by a word \"and\" instead of a comma.\n", + " \n", + " myList = []\n", + " for i in range(len(game_state[\"keys_collected\"])):\n", + " myList.append(game_state[\"keys_collected\"][i].get(\"name\"))\n", + " \n", + " if len(myList)==0:\n", + " print('You have nothing on your pocket.')\n", + " elif len(myList)==1:\n", + " print('In your pocked you find: ' + ''.join(myList) + '.')\n", + " else:\n", + " print('In your pocked you find: ' + \" and \".join([\", \".join(myList[:-1]),myList[-1]]) + '.')\n", + "\n", + "def are_words_similar(s1,s2):\n", + " \"\"\"\n", + " Compares the lower case version of two words.\n", + " Allows for words to have one typo.\n", + " \"\"\"\n", + " s1 = s1.strip().lower()\n", + " s2 = s2.strip().lower()\n", + " if len(s1) > len(s2):\n", + " s1,s2 = s2,s1\n", + " s = sum([s1[i] != s2[i] for i in range(len(s1))])\n", + " if s == 1:\n", + " return True\n", + " else:\n", + " return False\n", + "\n", + "def show_map():\n", + " if game_room in game_state[\"map_collected\"] and corridor not in game_state[\"map_collected\"]:\n", + " display(game_room[\"map\"])\n", + " time.sleep(0.1)\n", + " return\n", + " elif corridor in game_state[\"map_collected\"] and bathroom not in game_state[\"map_collected\"]:\n", + " display(game_room[\"map\"])\n", + " time.sleep(0.1)\n", + " return\n", + " elif bathroom in game_state[\"map_collected\"] and kitchen not in game_state[\"map_collected\"]:\n", + " display(bathroom[\"map\"])\n", + " time.sleep(0.1)\n", + " return\n", + " elif kitchen in game_state[\"map_collected\"] and living_room not in game_state[\"map_collected\"]:\n", + " display(kitchen[\"map\"])\n", + " time.sleep(0.1)\n", + " return\n", + " elif living_room in game_state[\"map_collected\"]:\n", + " display(living_room[\"map\"])\n", + " time.sleep(0.1)\n", + " return" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": { + "id": "55EMPCGHDvIO" + }, + "outputs": [], + "source": [ + "# Game Room.\n", + "# Bookshelf Interactions (Function)\n", + "\n", + "def consult_books(knows_russian):\n", + " if knows_russian == False:\n", + " print(\"You look at the bookshelf. You find the following books:\")\n", + " for book in (bookshelf.get(\"books_in_russian\")):\n", + " print(str(bookshelf.get(\"books_in_russian\").index(book)) + str(\" - \" + book))\n", + " elif knows_russian == True:\n", + " print(\"You go to the bookshelf, you find many books in russian. Their tittles in English are:\")\n", + " for book in (bookshelf.get(\"books_in_english\")):\n", + " print(str(bookshelf.get(\"books_in_english\").index(book)) + str(\" - \" + book))\n", + "\n", + "def take_book(): \n", + " print('Do you want to take a book? Write: ' + color.DARKCYAN + color.BOLD + \"Yes\" + color.END + \" or \"+ color.DARKCYAN + color.BOLD + \"No\" + color.END)\n", + " take_book_yes_no = input('').lower().strip()\n", + " if take_book_yes_no == \"no\":\n", + " return \"no\"\n", + " elif take_book_yes_no == \"yes\":\n", + " return \"yes\" \n", + "\n", + "def choose_book(knows_russian):\n", + " print('Which book do you want to take? Write the number which identifies the book')\n", + " book_chosen = input('').lower().strip()\n", + " if knows_russian == False:\n", + " if book_chosen == str(15):\n", + " print('A dictionary! It helps reading russian. ' + color.UNDERLINE + 'You feel like you learnt something today.' + color.END)\n", + " game_state[\"knowledge_collected\"].append(russian)\n", + " side_table[\"flavour_text\"] = \"A table with a picture of an old lady reading a book on top of it. She is devouring the book called \" + color.BOLD + \"The Jungle Book.\" + color.END\n", + " return str(book_chosen)\n", + " elif book_chosen == str(4):\n", + " print('You do not speak baguette. You wonder why do French always copy English words... croissant comes to mind.')\n", + " print('You put back the book.')\n", + " return str(book_chosen)\n", + " elif book_chosen in str([0, 1, 2, 3, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 16]) or book_chosen in [\"zero\", \"one\", \"two\", \"three\", \"five\", \"six\", \"seven\", \"eight\", \"nine\", \"ten\", \"eleven\", \"twelve\", \"thirteen\", \"fourteen\", \"sixteen\"]:\n", + " print('These characters are somewhat familiar, but you have no idea how to prounounce anything.')\n", + " print('You put back the book.')\n", + " return str(book_chosen)\n", + " else:\n", + " print('Input unclear.')\n", + " choose_book(knows_russian)\n", + " return\n", + " elif knows_russian == True:\n", + " if book_chosen == str(15):\n", + " print('A dictionary! It helps reading russian... which you already know!')\n", + " print('You put back the book.')\n", + " return str(book_chosen)\n", + " elif book_chosen == str(16):\n", + " if key_gameroom in game_state[\"keys_collected\"]:\n", + " print('Classic literature... boring.')\n", + " return str(book_chosen)\n", + " else:\n", + " print('You open The Jungle. You find a key inside! ' + color.UNDERLINE + 'You take it with you!' + color.END)\n", + " game_state[\"keys_collected\"].append(key_gameroom)\n", + " return str(book_chosen)\n", + " elif book_chosen in str([0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14]) or book_chosen in [\"zero\", \"one\", \"two\", \"three\", \"four\", \"five\", \"six\", \"seven\", \"eight\", \"nine\", \"ten\", \"eleven\", \"twelve\", \"thirteen\", \"fourteen\"]:\n", + " print('Classic literature... boring.')\n", + " print('You put back the book.')\n", + " return str(book_chosen)\n", + " else:\n", + " print('Input unclear.')\n", + " choose_book(knows_russian)\n", + " return\n", + "\n", + "def play_bookshelf():\n", + " consult_books(russian in game_state[\"knowledge_collected\"])\n", + " if take_book() == \"yes\":\n", + " cycle_break = False\n", + " while not(cycle_break):\n", + " if choose_book(russian in game_state[\"knowledge_collected\"]) == \"15\" and not (russian in game_state[\"knowledge_collected\"]):\n", + " cycle_break = True\n", + " elif (russian in game_state[\"knowledge_collected\"]):\n", + " cycle_break = True\n", + " else:\n", + " return\n", + " \n", + "#The statement below adds the function above to the bookshelf dictionary/object.\n", + "bookshelf[\"play\"] = play_bookshelf" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": { + "id": "0mt-b6f_4d8S" + }, + "outputs": [], + "source": [ + "#Bathroom Functions, one per interactable furniture.\n", + "\n", + "def bathtub_check():\n", + " furniture = bathtub\n", + " have_tool = False\n", + " if (bathtub[\"counter\"] == 0):\n", + " play_my_sound(bathtub[\"sound\"])\n", + " print(\"You remove some of the waters, you see a comb floating. You do a minor attempt at uncloggin the bathtub.\")\n", + " print(\"A voice behind you says \" + color.BOLD + \"DEEPER\" + color.END + \" in a very sinister way.\")\n", + " bathtub[\"counter\"] +=1\n", + " play_room(game_state[\"current_room\"])\n", + " if (bathtub[\"counter\"] == 1):\n", + " play_my_sound(bathtub[\"sound\"])\n", + " print(\"You hear the same voice shouting \" + color.BOLD + \"I SAID DEEPER, BLYAT\" + color.END + \".\")\n", + " print(\"Better comply...\")\n", + " bathtub[\"counter\"] +=1\n", + " play_room(game_state[\"current_room\"])\n", + " if (bathtub[\"counter\"] == 2):\n", + " play_my_sound(bathtub[\"sound\"])\n", + " print(\"You are tired of of putting your arm elbow-deep into the pipes. Yet, within the cold water, you are able to find a cork stuck. \\n\"\n", + " \"After a few seconds you can take it off and drain the bathtub slowly. In the bottom you see what looks like a \" + color.UNDERLINE + \"toilet lever\" + color.END + \".\")\n", + " game_state[\"knowledge_collected\"].append(lever)\n", + " bathtub[\"useful\"] = False\n", + " play_room(game_state[\"current_room\"])\n", + "\n", + "def toilet_check():\n", + " furniture = toilet\n", + " have_tool = False\n", + " for tool in game_state[\"knowledge_collected\"]:\n", + " if(tool[\"target\"] == furniture):\n", + " have_tool = True\n", + " if(have_tool):\n", + " game_state[\"knowledge_collected\"].append(wrench)\n", + " print(\"You can work with the lever to flush it until midpoint. You see a shiny object and pick it up. It’s a \" + color.UNDERLINE + \"rusty steel wrench\" + color.END + \".\")\n", + " toilet[\"useful\"] = False\n", + " play_room(game_state[\"current_room\"])\n", + " else:\n", + " print(\"Eeeew. You can’t possibly get your arm onto that mess... the devs are not that mean.\")\n", + " play_room(game_state[\"current_room\"])\n", + " return None\n", + "\n", + "def sink_check():\n", + " furniture = sink\n", + " have_tool = False\n", + " for tool in game_state[\"knowledge_collected\"]:\n", + " if(tool[\"target\"] == furniture):\n", + " have_tool = True\n", + " if(have_tool):\n", + " print(\"You are a man of culture and go for the piping. You can easen some bolts until it falls apart and all water furiously drains down and something metallic shines and bounces to the rug.\")\n", + " sink[\"useful\"] = False\n", + " play_room(game_state[\"current_room\"])\n", + " else:\n", + " print(\"You put your right arm deep into the water and can’t unplug the thick substance. Looks like you could fix it by easing the water pipe.\")\n", + " play_room(game_state[\"current_room\"])\n", + "\n", + "def rug_check():\n", + " furniture = rug\n", + " if sink[\"useful\"] == False:\n", + " game_state[\"keys_collected\"].append(key_kitchen)\n", + " print(\"You pick the \"+ color.UNDERLINE + \"key\" + color.END + \" from the mushy floor that comes attached to a beer opener.\")\n", + " rug[\"useful\"] = False\n", + " play_room(game_state[\"current_room\"])\n", + " else:\n", + " print(\"Who the hell has a rug on a bathroom? I’ll keep looking somewhere else, maybe on the bathtub?\")\n", + " play_room(game_state[\"current_room\"])\n", + "\n", + "toilet[\"play\"] = toilet_check\n", + "sink[\"play\"] = sink_check\n", + "bathtub[\"play\"] = bathtub_check\n", + "rug[\"play\"] = rug_check" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": { + "id": "Fq827loV7cT-" + }, + "outputs": [], + "source": [ + "# KITCHEN\n", + "def open_cutlery_drawer():\n", + " have_hammer = False\n", + " if hammer in game_state[\"knowledge_collected\"]:\n", + " have_hammer = True\n", + " if (have_hammer == True):\n", + " play_my_sound(cutlery_drawer[\"sound\"])\n", + " print(\"You feel empowered enough to break the drawer and open it. After the hit, you encounter something soft, yet crunchy. After inspection it was the putrid corpse of a rat that you moved and, below it, there is a \" + color.BOLD + \"wine opener.\" + color.END)\n", + " game_state[\"knowledge_collected\"].append(wine_opener)\n", + " cutlery_drawer[\"useful\"] = False\n", + " print(\"You have found a wine opener\")\n", + " play_room(game_state[\"current_room\"])\n", + " elif (wine_opener in game_state[\"knowledge_collected\"]):\n", + " print(\"There is just some old fashion cutlery.\")\n", + " else:\n", + " print(cutlery_drawer[\"flavour_text\"])\n", + " play_room(game_state[\"current_room\"])\n", + " return None\n", + "\n", + "def examine_pantry ():\n", + " print (pantry[\"flavour_text\"])\n", + " have_wine_opener = False\n", + " ### RUI'S COMMENT: We never talk about the exit command. I THINK IT WORKS DIFFERENTLY IN GOOGLE COLABORATIVE AND IN JUPYTER, SO I GUESS WE SHOULD REMOVE IT.\n", + " print(\"What would you like to examine? Type \" + (color.DARKCYAN + \" or \".join(pantry[\"object\"]) + color.END) + \". Type \\\"exit\\\" if you would like to go back to the kitchen.\")\n", + " to_examine = input()\n", + " if wine_opener in game_state[\"knowledge_collected\"]:\n", + " have_wine_opener = True\n", + " #### RUI'S COMMENT: I THINK THAT INSTEAD of to_examine == \"wine\" (or == \"food can\") we need \"old wines\" or \"food cans\" HERE !!!\n", + " if to_examine == \"wine\":\n", + " if have_wine_opener == False:\n", + " linebreak()\n", + " print(\"You pick a bottle and try the cork, but without the proper tool you can’t open it. On the tag you can read горули мцване 1890 so it’s been there for a while. The wine looks surprisingly well preserved.\")\n", + " print(\"Perhaps it was an important gift.\")\n", + " examine_pantry()\n", + " elif have_wine_opener == True:\n", + " linebreak()\n", + " print(\"Looks like a very Georgian wine. You imagine this is what rich people drink.\")\n", + " game_state[\"knowledge_collected\"].append(wine)\n", + " print(\"You have found \" + color.UNDERLINE + \"wine\" + color.END + \".\")\n", + " examine_pantry()\n", + " elif wine in game_state[\"knowledge_collected\"]:\n", + " linebreak()\n", + " print(\"Just some old fancy wines.\")\n", + " examine_pantry()\n", + " elif to_examine == \"food can\":\n", + " linebreak()\n", + " print (\"You take a can and see the tag has written Cрок годности 01-09-//////// on it. Looks like a date in which the year has faded over the time.\")\n", + " examine_pantry()\n", + " elif to_examine == \"exit\":\n", + " play_room(kitchen)\n", + " else:\n", + " print(\"Object not found. Try it again.\")\n", + " linebreak()\n", + " examine_pantry()\n", + " \n", + "\n", + "pantry[\"play\"] = examine_pantry\n", + "cutlery_drawer[\"play\"] = open_cutlery_drawer" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": { + "id": "utdxs7mvghUg" + }, + "outputs": [], + "source": [ + "#Living Room Functions\n", + "\n", + "def crib_check():\n", + " furniture = crib\n", + " print(\"You look into the crib. There is a one-eyed, bald baby doll and a mobile over it. You feel the doll follows your sight...\")\n", + " check = input(\"Want to check mobile or doll?\\n\").strip().lower()\n", + " if (check == \"doll\"):\n", + " print(\"You realize it is an old doll, without hair and with signs of violence, and it's looking to the mobile over it.\")\n", + " play_room(game_state[\"current_room\"])\n", + " if(check == \"mobile\"):\n", + " print(\"It is made of different wooden birds, and it starts playing a lullaby that makes the old woman wakes up and starts babling.\"\n", + " \"You feel nothing good will come from staying longer in this house\")\n", + " old_lady[\"status\"] = \"awaken\"\n", + " crib[\"useful\"] = False\n", + " play_room(game_state[\"current_room\"])\n", + " else:\n", + " print(\"Please enter either option given.\")\n", + " crib_check()\n", + "\n", + "def old_lady_check():\n", + " furniture = old_lady\n", + " if (old_lady[\"status\"] == \"sleeping\"):\n", + " print(\"She is a very old lady, wearing all black clothes and sitting on a wooden chair. You can't tell if she's asleep or dead but you'd better be carefull\")\n", + " play_room(game_state[\"current_room\"])\n", + " if (old_lady[\"status\"] == \"awaken\"):\n", + " if (wine in game_state[\"knowledge_collected\"]):\n", + " print(\"She wants the wine, do you want to open it for her?\")\n", + " if (wine_opener in game_state[\"knowledge_collected\"]):\n", + " old_lady[\"status\"] = \"drunk\"\n", + " game_state[\"knowledge_collected\"].append(keys_pendulum)\n", + " old_lady[\"useful\"] = False\n", + " play_my_sound(old_lady[\"sound\"])\n", + " print(\"She jumps and takes the bottle and the opener and proceeds to chug it. When doing so, a \" + color.UNDERLINE + \"set of small keys\" + color.END + \" fall from her lap to your hands.\")\n", + " else:\n", + " print(\"Maybe in the kitchen there's a tool to open it... The old woman salivates looking to the wine and shouts incohesive words to you, that most certainly aren’t compliments\")\n", + " else:\n", + " print(\"The old woman speaks in a broken voice but you can just recognise two word in russian that you learned in a pub a few years back. “wiii----ne p-----leeeeeeas---e\")\n", + " play_room(game_state[\"current_room\"])\n", + " else:\n", + " print(\"test\")\n", + " play_room(game_state[\"current_room\"])\n", + "\n", + "def pendulum_check():\n", + " furniture = pendulum\n", + " if (pendulum[\"status\"] == \"closed\"):\n", + " print(\"The pendulum clock is set at 9:15 AM, but it's stopped. you see yet another 4 digit locker on the door to access it.\")\n", + " print(\"Sigh... you wish there were password hints here. Everyone puts their codes on those.\")\n", + " try_password = input(\"Enter the 4 digit combination\").strip()\n", + " if (furniture[\"code\"] == try_password):\n", + " pendulum[\"status\"] = \"open\"\n", + " print(\"The lock opens but there is another issue...\")\n", + " if (try_password == \"exit\"):\n", + " play_room(game_state[\"current_room\"])\n", + " if(furniture[\"code\"] != try_password):\n", + " print('\"Wrong password.\" You try again')\n", + " pendulum_check()\n", + " if (pendulum[\"status\"] == \"open\"):\n", + " if (keys_pendulum in game_state[\"knowledge_collected\"]):\n", + " game_state[\"knowledge_collected\"].append(hammer)\n", + " pendulum[\"useful\"] = False\n", + " print(\"You find a \" + color.UNDERLINE + \"hammer\" + color.END + \"on the small box inside! You may be able to break something with this for sure.\")\n", + " play_room(game_state[\"current_room\"])\n", + " else:\n", + " print(\"There is a smaller box inside that could be opened with a set of keys\")\n", + " play_room(game_state[\"current_room\"])\n", + " else:\n", + " print(\"What a gorgeous clock this must have been.\")\n", + " play_room(game_state[\"current_room\"])\n", + "\n", + "crib[\"play\"] = crib_check\n", + "old_lady[\"play\"] = old_lady_check\n", + "pendulum[\"play\"] = pendulum_check\n" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": { + "id": "7TC2r1MyIMyE" + }, + "outputs": [], + "source": [ + "def piano_check():\n", + " furniture = piano\n", + " print(\"The piano there is a 4 digit locker on the lid. Pianos don't have lockers unless they have something inside that you want.\")\n", + " try_password = input(\"Enter the 4 digit combination\").strip()\n", + " if (piano[\"code\"] == try_password):\n", + " piano[\"useful\"] = False\n", + " game_state[\"keys_collected\"].append(key_outside)\n", + " print(\"It is open!\")\n", + " if (try_password == \"exit\"):\n", + " return\n", + " if (furniture[\"code\"] != try_password):\n", + " print('\"Wrong password.\" You try again')\n", + " piano_check()" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": { + "id": "IkA-BsKlWKzD" + }, + "outputs": [], + "source": [ + "# Enter password \n", + "def enter_password(item):\n", + " print((\"The \" + item[\"name\"] + \" has a password! Enter the password or type \\\"exit\\\" to go back to room\"))\n", + " try_password = input().strip().lower()\n", + " output = \"\"\n", + " if (item[\"password\"] == try_password):\n", + " output = \"Correct password!\"\n", + " linebreak()\n", + " if(item[\"name\"] in object_relations and len(object_relations[item[\"name\"]])>0):\n", + " item_found = object_relations[item[\"name\"]].pop()\n", + " game_state[\"keys_collected\"].append(item_found)\n", + " output = \"You find \" + item_found[\"name\"] + \".\"\n", + " print (output)\n", + " elif (try_password == \"exit\"):\n", + " play_room(game_state[\"current_room\"])\n", + " else:\n", + " output += \"Wrong password.\"\n", + " print (output)\n", + " enter_password(item)\n", + "\n", + "vault[\"play\"] = enter_password\n", + "stove_oven[\"play\"] = enter_password\n", + "piano[\"play\"] = enter_password" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": { + "id": "WhuLmtzySq2e" + }, + "outputs": [], + "source": [ + "# Here is where the \"main\" cycles are.\n", + "def start_game():\n", + " #Resetting variables which are changed throughout code execution.\n", + " side_table[\"flavour_text\"] = \"A table with a picture of an old lady reading a book on top of it. She is devouring the book called \" + color.BOLD + \"книга джунглей.\" + color.END\n", + " print(\"You wake up on a couch and find yourself in a strange house with no windows which you have never been to before.\")\n", + " print(\"You don't remember why you are here and what had happened before. You feel some unknown danger is approaching and you must get out of the house, NOW!\")\n", + " play_room(game_state[\"current_room\"])\n", + "\n", + "def play_room(room):\n", + " \"\"\"\n", + " Play a room. First check if the room being played is the target room.\n", + " If it is, the game will end with success. Otherwise, let player either \n", + " explore (list all items in this room) or examine an item found here.\n", + " \"\"\"\n", + " game_state[\"current_room\"] = room\n", + " if(game_state[\"current_room\"] == game_state[\"target_room\"]):\n", + " play_my_sound(sound_victory)\n", + " print(color.GREEN + color.BOLD + \"Congrats! You escaped the room!\" + color.END)\n", + " else:\n", + " print(\"You are now in \" + room[\"name\"])\n", + " print(\"What would you like to do? Type 'explore' or 'examine'? \\n\")\n", + " intended_action = input(\"\").strip().lower()\n", + " if intended_action == \"explore\": ### Here we should use the are_words_similar(s1,s2) function instead.\n", + " explore_room(room)\n", + " print(\"\\n\")\n", + " play_room(room)\n", + " elif intended_action == \"examine\": ### Here we should use the are_words_similar(s1,s2) function instead.\n", + " print(\"What would you like to examine?\")\n", + " use_item_choice = input(\"\").strip().lower()\n", + " \n", + " if examine_silent(use_item_choice) != None:\n", + " room = examine_item(use_item_choice)\n", + " print(\"\\n\")\n", + " play_room(room)\n", + " else:\n", + " print(\"\\n\")\n", + " play_room(room)\n", + " elif intended_action == \"exit\": ### Here we should use the are_words_similar(s1,s2) function instead.\n", + " quit(keep_kernel=True)\n", + " else:\n", + " print(\"Not sure what you mean. Type 'explore' or 'examine'.\")\n", + " play_room(room)\n", + " print(\"\\n\")\n", + "\n", + "def explore_room(room):\n", + " \"\"\"Explore a room. List all items belonging to this room.\"\"\"\n", + " items = [i[\"name\"] for i in object_relations[room[\"name\"]]]\n", + " print(\"You explore the room. This is \" + room[\"name\"] + \". You find \" + \", \".join(items))\n", + " keys_in_pocket()\n", + " print(\"You scrapped some notes about the layout of the house. Do you want to see them? Write: \" + color.DARKCYAN + color.BOLD + \"Yes\" + color.END + \" or \"+ color.DARKCYAN + color.BOLD + \"No\" + color.END)\n", + " yes_no_show_map = input().strip().lower()\n", + " if yes_no_show_map == \"yes\":\n", + " show_map()\n", + " return\n", + " elif yes_no_show_map == \"no\":\n", + " return\n", + " else:\n", + " print(\"Not sure what you mean...\")\n", + " explore_room(room)\n", + "\n", + "def get_next_room_of_door(door, current_room):\n", + " \"\"\"From object_relations, find the two rooms connected to the given door. Return the room that is not the current_room.\"\"\"\n", + " connected_rooms = object_relations[door[\"name\"]]\n", + " play_my_sound(sound_door_creaking)\n", + " for room in connected_rooms:\n", + " if(not current_room == room):\n", + " return room\n", + "\n", + "# Function to examine item. Similar to that of the original project.\n", + "def examine_item(item_name):\n", + " \n", + " room = game_state[\"current_room\"]\n", + " \n", + " #### RUI: I THINK THAT THE REASON WHY THE \"Thanks to the key, you move on to the next room.\" APPEARS TWICE IS.\n", + " #### BECAUSE THIS LOOP ALWAYS LOOPS THROUGH THE TWO ITEMS THAT ARE IN EACH OF THE OBJECT RELATIONS OF EACH ROOM.\n", + " #### NOT SURE HOW TO FIX IT THOUGH.\n", + " \n", + " for item in object_relations[room[\"name\"]]:\n", + " if(item[\"name\"] == item_name):\n", + " #The if below governs what happens if we are not interaction with a door.\n", + " if item[\"type\"] != \"door\": \n", + " output = \"You examine \" + item_name + \":\"\n", + " # ... if the item is not useful we just throw in the flavour text\n", + " # \n", + " if(item[\"useful\"] == False):\n", + " print(item[\"flavour_text\"])\n", + " return None\n", + " play_room(room)\n", + " # ... if it is useful we throw in the function which is stored in the key \"play\" of the object.\n", + " elif (item[\"useful\"] == True):\n", + " if (\"password\" in item):\n", + " print(item[\"flavour_text\"])\n", + " item.get(\"play\")(item)\n", + " elif (\"password\" not in item):\n", + " item.get(\"play\")()\n", + " return None\n", + " # if it is a door, we have the same interaction as in the sample (to open it).\n", + " elif (item[\"type\"] == \"door\"):\n", + " have_key = False\n", + " for key in game_state[\"keys_collected\"]:\n", + " if(key[\"target\"] == item):\n", + " have_key = True\n", + " if(have_key):\n", + " print(\"Thanks to the key, you move on to the next room. The door slowly shuts itself behind you.\")\n", + " next_room = get_next_room_of_door(item, room)\n", + " game_state[\"map_collected\"].append(next_room)\n", + " return next_room\n", + " else:\n", + " print(\"It is locked but you don't have the key.\")\n", + " return None\n", + " #else: return\n", + "\n", + "def examine_silent(item_name):\n", + " \n", + " room = game_state[\"current_room\"]\n", + " for item in object_relations[room[\"name\"]]:\n", + " if(item[\"name\"] == item_name):\n", + " #The if below governs what happens if we are not interaction with a door.\n", + " if item[\"type\"] != \"door\": \n", + " output = \"You examine \" + item_name + \":\"\n", + " # ... if the item is not useful we just throw in the flavour text\n", + " # \n", + " if(item[\"useful\"] == False):\n", + " print(item[\"flavour_text\"])\n", + " return None\n", + " play_room(room)\n", + " # ... if it is useful we throw in the function which is stored in the key \"play\" of the object.\n", + " elif (item[\"useful\"] == True):\n", + " if (\"password\" in item):\n", + " print(item[\"flavour_text\"])\n", + " item.get(\"play\")(item)\n", + " elif (\"password\" not in item):\n", + " item.get(\"play\")()\n", + " return None\n", + " # if it is a door, we have the same interaction as in the sample (to open it).\n", + " elif (item[\"type\"] == \"door\"):\n", + " have_key = False\n", + " for key in game_state[\"keys_collected\"]:\n", + " if(key[\"target\"] == item):\n", + " have_key = True\n", + " if(have_key):\n", + " next_room = get_next_room_of_door(item, room)\n", + " game_state[\"map_collected\"].append(next_room)\n", + " return next_room\n", + " else:\n", + " return None" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "You wake up on a couch and find yourself in a strange house with no windows which you have never been to before.\n", + "You don't remember why you are here and what had happened before. You feel some unknown danger is approaching and you must get out of the house, NOW!\n", + "You are now in game room\n", + "What would you like to do? Type 'explore' or 'examine'? \n", + "\n", + "examine\n", + "What would you like to examine?\n", + "bookshelf\n", + "You look at the bookshelf. You find the following books:\n", + "0 - Преступление и наказание\n", + "1 - Маленькие женщины\n", + "2 - Большие надежды\n", + "3 - Война и мир\n", + "4 - Les Misérables\n", + "5 - Записки из метро\n", + "6 - Белые ночи\n", + "7 - Сон о смехотворном человеке\n", + "8 - Идиот\n", + "9 - Женщина в белом\n", + "10 - Отцы и сыновья\n", + "11 - Лунный камень\n", + "12 - Сайлас Марнер\n", + "13 - Путешествие к центру Земли\n", + "14 - Мельница на зубной нити\n", + "15 - Русско-английский словарь/English–Russian Dictionary\n", + "16 - книга джунглей\n", + "Do you want to take a book? Write: \u001b[36m\u001b[1mYes\u001b[0m or \u001b[36m\u001b[1mNo\u001b[0m\n", + "yes\n", + "Which book do you want to take? Write the number which identifies the book\n", + "15\n", + "A dictionary! It helps reading russian. \u001b[4mYou feel like you learnt something today.\u001b[0m\n", + "\n", + "\n", + "You are now in game room\n", + "What would you like to do? Type 'explore' or 'examine'? \n", + "\n", + "examine\n", + "What would you like to examine?\n", + "bookshelf\n", + "You go to the bookshelf, you find many books in russian. Their tittles in English are:\n", + "0 - Crime and Punishment\n", + "1 - Little Women\n", + "2 - Great Expectations\n", + "3 - War and Peace\n", + "4 - Les Misérables\n", + "5 - Notes from Underground\n", + "6 - White Nights\n", + "7 - Dreams of a ridiculous man\n", + "8 - The Idiot\n", + "9 - The Woman in White\n", + "10 - Fathers and Sons\n", + "11 - The Moonstone\n", + "12 - Silas Marner\n", + "13 - Journey to the Center of the Earth\n", + "14 - The Mill on the Floss\n", + "15 - Russian-English Dictionary/English–Russian Dictionary\n", + "16 - The Jungle Book\n", + "Do you want to take a book? Write: \u001b[36m\u001b[1mYes\u001b[0m or \u001b[36m\u001b[1mNo\u001b[0m\n", + "yes\n", + "Which book do you want to take? Write the number which identifies the book\n", + "16\n", + "You open The Jungle. You find a key inside! \u001b[4mYou take it with you!\u001b[0m\n", + "\n", + "\n", + "You are now in game room\n", + "What would you like to do? Type 'explore' or 'examine'? \n", + "\n", + "examine\n", + "What would you like to examine?\n", + "game room door\n", + "Thanks to the key, you move on to the next room. The door shuts itself behind you.\n", + "\n", + "\n", + "You are now in corridor\n", + "What would you like to do? Type 'explore' or 'examine'? \n", + "\n", + "examine\n", + "What would you like to examine?\n", + "vault\n", + "The lock has a message: \"For the sake of the future of this family, the answer is kept secret in the very heart of this great surname.\" <>\n", + "The vault has a password! Enter the password or type \"exit\" to go back to room\n", + "volga\n", + "\n", + "\n", + "You find key for bathroom.\n", + "\n", + "\n", + "You are now in corridor\n", + "What would you like to do? Type 'explore' or 'examine'? \n", + "\n", + "examine\n", + "What would you like to examine?\n", + "bathroom door\n", + "Thanks to the key, you move on to the next room. The door shuts itself behind you.\n", + "\n", + "\n", + "You are now in bathroom\n", + "What would you like to do? Type 'explore' or 'examine'? \n", + "\n", + "examine\n", + "What would you like to examine?\n", + "bathtub\n", + "You superficially remove the waters and get some floating comb, a voice behind you says \u001b[1mDEEPER\u001b[0m in a very sinister way.\n", + "You are now in bathroom\n", + "What would you like to do? Type 'explore' or 'examine'? \n", + "\n", + "examine\n", + "What would you like to examine?\n", + "toilet\n", + "Eeeew. You can’t possibly get your arm onto that mess... the devs are not that mean.\n", + "You are now in bathroom\n", + "What would you like to do? Type 'explore' or 'examine'? \n", + "\n", + "examine\n", + "What would you like to examine?\n", + "bathtub\n", + "You hear the same voice shouting \u001b[1mI SAID DEEPER, BLYAT\u001b[0m.\n", + "You are now in bathroom\n", + "What would you like to do? Type 'explore' or 'examine'? \n", + "\n", + "examine\n", + "What would you like to examine?\n", + "toilet\n", + "Eeeew. You can’t possibly get your arm onto that mess... the devs are not that mean.\n", + "You are now in bathroom\n", + "What would you like to do? Type 'explore' or 'examine'? \n", + "\n", + "examine\n", + "What would you like to examine?\n", + "bathtub\n", + "You are tired of trying and you put your full arm, elbow-deep, into the cold water and are able to find a \u001b[4mcork\u001b[0m. \n", + "After a few seconds you can take it off and drain the bathtub slowly. On one end you find what looks like the toilet lever.\n", + "You are now in bathroom\n", + "What would you like to do? Type 'explore' or 'examine'? \n", + "\n", + "examine\n", + "What would you like to examine?\n", + "toilet\n", + "You can work with the lever to flush it until midpoint. You see a shiny object and pick it up. It’s an \u001b[4mold steel wrench\u001b[0m.\n", + "You are now in bathroom\n", + "What would you like to do? Type 'explore' or 'examine'? \n", + "\n", + "examine\n", + "What would you like to examine?\n", + "sink\n", + "You are a man of culture and go for the piping. You can easen some bolts until it falls apart and all water furiously drains down and something metallic shines and bounces to the rug.\n", + "You are now in bathroom\n", + "What would you like to do? Type 'explore' or 'examine'? \n", + "\n", + "examine\n", + "What would you like to examine?\n", + "rug\n", + "You pick the \u001b[4mkey\u001b[0m from the mushy floor that comes attached to a beer opener.\n", + "You are now in bathroom\n", + "What would you like to do? Type 'explore' or 'examine'? \n", + "\n", + "examine\n", + "What would you like to examine?\n", + "bathroom door\n", + "Thanks to the key, you move on to the next room. The door shuts itself behind you.\n", + "\n", + "\n", + "You are now in corridor\n", + "What would you like to do? Type 'explore' or 'examine'? \n", + "\n", + "examine\n", + "What would you like to examine?\n", + "kitchen door\n", + "Thanks to the key, you move on to the next room. The door shuts itself behind you.\n", + "\n", + "\n", + "You are now in kitchen\n", + "What would you like to do? Type 'explore' or 'examine'? \n", + "\n", + "explore\n", + "You explore the room. This is kitchen. You find plate cabinet, cutlery drawer, oven, old table with chairs, pantry, kitchen door\n", + "In your pocked you find: key for game room, key for bathroom and key for kitchen.\n", + "You scrapped some notes about the layout of the house. Do you want to see them? Write: \u001b[36m\u001b[1mYes\u001b[0m or \u001b[36m\u001b[1mNo\u001b[0m\n", + "yes\n" + ] + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "\n", + "You are now in kitchen\n", + "What would you like to do? Type 'explore' or 'examine'? \n", + "\n", + "examine\n", + "What would you like to examine?\n", + "pantry\n", + "It's full of food cans and wine bottles from another era, the tags barely visible.\n", + "What would you like to examine? Type \u001b[36mwine or food can\u001b[0m. Type \"exit\" if you would like to go back to the kitchen.\n", + "wine\n", + "\n", + "\n", + "You pick a bottle and try the cork, but without the proper tool you can’t open it. On the tag you can read горули мцване 1890 so it’s been there for a while. The wine looks surprisingly well preserved.\n", + "It's full of food cans and wine bottles from another era, the tags barely visible.\n", + "What would you like to examine? Type \u001b[36mwine or food can\u001b[0m. Type \"exit\" if you would like to go back to the kitchen.\n", + "food can\n", + "\n", + "\n", + "You take a can and see the tag has written Cрок годности 01-09-//////// on it. Looks like a date in which the year has faded over the time.\n", + "It's full of food cans and wine bottles from another era, the tags barely visible.\n", + "What would you like to examine? Type \u001b[36mwine or food can\u001b[0m. Type \"exit\" if you would like to go back to the kitchen.\n", + "exit\n", + "You are now in kitchen\n", + "What would you like to do? Type 'explore' or 'examine'? \n", + "\n", + "explore\n", + "You explore the room. This is kitchen. You find plate cabinet, cutlery drawer, oven, old table with chairs, pantry, kitchen door\n", + "In your pocked you find: key for game room, key for bathroom and key for kitchen.\n", + "You scrapped some notes about the layout of the house. Do you want to see them? Write: \u001b[36m\u001b[1mYes\u001b[0m or \u001b[36m\u001b[1mNo\u001b[0m\n", + "no\n", + "\n", + "\n", + "You are now in kitchen\n", + "What would you like to do? Type 'explore' or 'examine'? \n", + "\n", + "examine\n", + "What would you like to examine?\n", + "old table with chairs\n", + "There are some cutlery and an old tsarist newspaper that says: \"Правда - 22 апреля 1912 года\". I don't really know what it means.\n", + "\n", + "\n", + "You are now in kitchen\n", + "What would you like to do? Type 'explore' or 'examine'? \n", + "\n", + "plate cabinet\n", + "Not sure what you mean. Type 'explore' or 'examine'.\n", + "You are now in kitchen\n", + "What would you like to do? Type 'explore' or 'examine'? \n", + "\n", + "examine\n", + "What would you like to examine?\n", + "plate cabinet\n", + "Just some old fancy plates.\n", + "\n", + "\n", + "You are now in kitchen\n", + "What would you like to do? Type 'explore' or 'examine'? \n", + "\n", + "examine\n", + "What would you like to examine?\n", + "oven\n", + "It is an old stove, the wood fueled kind. It is very used and scratched, but closed. There is a small lock to open it, with 4 rotating numerical pieces.\n", + "The oven has a password! Enter the password or type \"exit\" to go back to room\n", + "1890\n", + "\n", + "\n", + "You find key for living room.\n", + "\n", + "\n", + "You are now in kitchen\n", + "What would you like to do? Type 'explore' or 'examine'? \n", + "\n", + "examine\n", + "What would you like to examine?\n", + "kitchen door\n", + "Thanks to the key, you move on to the next room. The door shuts itself behind you.\n", + "\n", + "\n", + "You are now in corridor\n", + "What would you like to do? Type 'explore' or 'examine'? \n", + "\n", + "examine\n", + "What would you like to examine?\n", + "living room door\n", + "Thanks to the key, you move on to the next room. The door shuts itself behind you.\n", + "\n", + "\n", + "You are now in living room\n", + "What would you like to do? Type 'explore' or 'examine'? \n", + "\n", + "explore\n", + "You explore the room. This is living room. You find old lady, pendulum, crib, living room door, other door\n", + "In your pocked you find: key for game room, key for bathroom, key for kitchen and key for living room.\n", + "You scrapped some notes about the layout of the house. Do you want to see them? Write: \u001b[36m\u001b[1mYes\u001b[0m or \u001b[36m\u001b[1mNo\u001b[0m\n", + "yes\n" + ] + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "\n", + "You are now in living room\n", + "What would you like to do? Type 'explore' or 'examine'? \n", + "\n", + "examine\n", + "What would you like to examine?\n", + "pendulum\n", + "The pendulum clock is set at 9:15 AM, but it's stopped. you see a 4 digit locker on the door to access it.\n", + "Enter the 4 digit combination0915\n", + "The lock opens but there is another issue...\n", + "There is a smaller box inside that could be opened with a set of keys\n", + "You are now in living room\n", + "What would you like to do? Type 'explore' or 'examine'? \n", + "\n", + "examine\n", + "What would you like to examine?\n", + "a\n", + "\n", + "\n", + "You are now in living room\n", + "What would you like to do? Type 'explore' or 'examine'? \n", + "\n", + "explore\n", + "You explore the room. This is living room. You find old lady, pendulum, crib, living room door, other door\n", + "In your pocked you find: key for game room, key for bathroom, key for kitchen and key for living room.\n", + "You scrapped some notes about the layout of the house. Do you want to see them? Write: \u001b[36m\u001b[1mYes\u001b[0m or \u001b[36m\u001b[1mNo\u001b[0m\n", + "no\n", + "\n", + "\n", + "You are now in living room\n", + "What would you like to do? Type 'explore' or 'examine'? \n", + "\n", + "examine\n", + "What would you like to examine?\n", + "crib\n", + "You look into the crib. There is a one-eyed, bald baby doll and a mobile over it. You feel the doll follows your sight...\n", + "Want to check mobile or doll?\n", + "mobile\n", + "It is made of different wooden birds, and it starts playing a lullaby that makes the old woman wakes up and starts babling.You feel nothing good will come from staying longer in this house\n", + "You are now in living room\n", + "What would you like to do? Type 'explore' or 'examine'? \n", + "\n", + "examine\n", + "What would you like to examine?\n", + "crib\n", + "Do you really felt like checking this twice?\n", + "\n", + "\n", + "You are now in living room\n", + "What would you like to do? Type 'explore' or 'examine'? \n", + "\n", + "doll\n", + "Not sure what you mean. Type 'explore' or 'examine'.\n", + "You are now in living room\n", + "What would you like to do? Type 'explore' or 'examine'? \n", + "\n", + "examine\n", + "What would you like to examine?\n", + "crib\n", + "Do you really felt like checking this twice?\n", + "\n", + "\n", + "You are now in living room\n", + "What would you like to do? Type 'explore' or 'examine'? \n", + "\n", + "examine\n", + "What would you like to examine?\n", + "explor\n", + "\n", + "\n", + "You are now in living room\n", + "What would you like to do? Type 'explore' or 'examine'? \n", + "\n", + "explore\n", + "You explore the room. This is living room. You find old lady, pendulum, crib, living room door, other door\n", + "In your pocked you find: key for game room, key for bathroom, key for kitchen and key for living room.\n", + "You scrapped some notes about the layout of the house. Do you want to see them? Write: \u001b[36m\u001b[1mYes\u001b[0m or \u001b[36m\u001b[1mNo\u001b[0m\n", + "examine\n", + "Not sure what you mean...\n", + "You explore the room. This is living room. You find old lady, pendulum, crib, living room door, other door\n", + "In your pocked you find: key for game room, key for bathroom, key for kitchen and key for living room.\n", + "You scrapped some notes about the layout of the house. Do you want to see them? Write: \u001b[36m\u001b[1mYes\u001b[0m or \u001b[36m\u001b[1mNo\u001b[0m\n", + "no\n", + "\n", + "\n", + "You are now in living room\n", + "What would you like to do? Type 'explore' or 'examine'? \n", + "\n", + "examine\n", + "What would you like to examine?\n", + "old lady\n", + "The old woman speaks in a broken voice but you can just recognise two word in russian that you learned in a pub a few years back. “wiii----ne p-----leeeeeeas---e\n", + "You are now in living room\n", + "What would you like to do? Type 'explore' or 'examine'? \n", + "\n", + "examine\n", + "What would you like to examine?\n", + "living room door\n", + "Thanks to the key, you move on to the next room. The door shuts itself behind you.\n", + "\n", + "\n", + "You are now in corridor\n", + "What would you like to do? Type 'explore' or 'examine'? \n", + "\n", + "explore\n", + "You explore the room. This is corridor. You find old picture, vault, game room door, bathroom door, kitchen door, living room door\n", + "In your pocked you find: key for game room, key for bathroom, key for kitchen and key for living room.\n", + "You scrapped some notes about the layout of the house. Do you want to see them? Write: \u001b[36m\u001b[1mYes\u001b[0m or \u001b[36m\u001b[1mNo\u001b[0m\n", + "yes\n" + ] + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "\n", + "You are now in corridor\n", + "What would you like to do? Type 'explore' or 'examine'? \n", + "\n", + "examine\n", + "What would you like to examine?\n", + "kitchen door\n", + "Thanks to the key, you move on to the next room. The door shuts itself behind you.\n", + "\n", + "\n", + "You are now in kitchen\n", + "What would you like to do? Type 'explore' or 'examine'? \n", + "\n", + "examine\n", + "What would you like to examine?\n", + "a\n", + "\n", + "\n", + "You are now in kitchen\n", + "What would you like to do? Type 'explore' or 'examine'? \n", + "\n", + "explore\n", + "You explore the room. This is kitchen. You find plate cabinet, cutlery drawer, oven, old table with chairs, pantry, kitchen door\n", + "In your pocked you find: key for game room, key for bathroom, key for kitchen and key for living room.\n", + "You scrapped some notes about the layout of the house. Do you want to see them? Write: \u001b[36m\u001b[1mYes\u001b[0m or \u001b[36m\u001b[1mNo\u001b[0m\n", + "no\n", + "\n", + "\n", + "You are now in kitchen\n", + "What would you like to do? Type 'explore' or 'examine'? \n", + "\n", + "examine\n", + "What would you like to examine?\n", + "cutlery drawer\n", + "It is full of stuff and things, nothing useful though\n", + "\n", + "\n", + "You are now in kitchen\n", + "What would you like to do? Type 'explore' or 'examine'? \n", + "\n", + "examine\n", + "What would you like to examine?\n", + "a\n", + "\n", + "\n", + "You are now in kitchen\n", + "What would you like to do? Type 'explore' or 'examine'? \n", + "\n", + "explore\n", + "You explore the room. This is kitchen. You find plate cabinet, cutlery drawer, oven, old table with chairs, pantry, kitchen door\n", + "In your pocked you find: key for game room, key for bathroom, key for kitchen and key for living room.\n", + "You scrapped some notes about the layout of the house. Do you want to see them? Write: \u001b[36m\u001b[1mYes\u001b[0m or \u001b[36m\u001b[1mNo\u001b[0m\n", + "no\n", + "\n", + "\n", + "You are now in kitchen\n", + "What would you like to do? Type 'explore' or 'examine'? \n", + "\n", + "examine\n", + "What would you like to examine?\n", + "kitchen door\n", + "Thanks to the key, you move on to the next room. The door shuts itself behind you.\n", + "\n", + "\n", + "You are now in corridor\n", + "What would you like to do? Type 'explore' or 'examine'? \n", + "\n", + "examine\n", + "What would you like to examine?\n", + "living room door\n", + "Thanks to the key, you move on to the next room. The door shuts itself behind you.\n", + "\n", + "\n", + "You are now in living room\n", + "What would you like to do? Type 'explore' or 'examine'? \n", + "\n", + "examine\n", + "What would you like to examine?\n", + "pendulum\n", + "There is a smaller box inside that could be opened with a set of keys\n", + "You are now in living room\n", + "What would you like to do? Type 'explore' or 'examine'? \n", + "\n" + ] + } + ], + "source": [ + "#MAIN CODE\n", + "game_state = INIT_GAME_STATE.copy()\n", + "start_game()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "colab": { + "collapsed_sections": [], + "name": "Python Escape Room.ipynb", + "provenance": [] + }, + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.8.3" + } + }, + "nbformat": 4, + "nbformat_minor": 1 +} diff --git a/your-code/.ipynb_checkpoints/main-checkpoint.ipynb b/your-code/.ipynb_checkpoints/main-checkpoint.ipynb new file mode 100644 index 00000000..34f374f2 --- /dev/null +++ b/your-code/.ipynb_checkpoints/main-checkpoint.ipynb @@ -0,0 +1,32 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.8.3" + } + }, + "nbformat": 4, + "nbformat_minor": 4 +} diff --git a/your-code/.ipynb_checkpoints/sample-code-checkpoint.ipynb b/your-code/.ipynb_checkpoints/sample-code-checkpoint.ipynb new file mode 100644 index 00000000..71f298f9 --- /dev/null +++ b/your-code/.ipynb_checkpoints/sample-code-checkpoint.ipynb @@ -0,0 +1,248 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], + "source": [ + "# define rooms and items\n", + "\n", + "couch = {\n", + " \"name\": \"couch\",\n", + " \"type\": \"furniture\",\n", + "}\n", + "\n", + "door_a = {\n", + " \"name\": \"door a\",\n", + " \"type\": \"door\",\n", + "}\n", + "\n", + "key_a = {\n", + " \"name\": \"key for door a\",\n", + " \"type\": \"key\",\n", + " \"target\": door_a,\n", + "}\n", + "\n", + "piano = {\n", + " \"name\": \"piano\",\n", + " \"type\": \"furniture\",\n", + "}\n", + "\n", + "game_room = {\n", + " \"name\": \"game room\",\n", + " \"type\": \"room\",\n", + "}\n", + "\n", + "outside = {\n", + " \"name\": \"outside\"\n", + "}\n", + "\n", + "all_rooms = [game_room, outside]\n", + "\n", + "all_doors = [door_a]\n", + "\n", + "# define which items/rooms are related\n", + "\n", + "object_relations = {\n", + " \"game room\": [couch, piano, door_a],\n", + " \"piano\": [key_a],\n", + " \"outside\": [door_a],\n", + " \"door a\": [game_room, outside]\n", + "}\n", + "\n", + "# define game state. Do not directly change this dict. \n", + "# Instead, when a new game starts, make a copy of this\n", + "# dict and use the copy to store gameplay state. This \n", + "# way you can replay the game multiple times.\n", + "\n", + "INIT_GAME_STATE = {\n", + " \"current_room\": game_room,\n", + " \"keys_collected\": [],\n", + " \"target_room\": outside\n", + "}" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [], + "source": [ + "def linebreak():\n", + " \"\"\"\n", + " Print a line break\n", + " \"\"\"\n", + " print(\"\\n\\n\")\n", + "\n", + "def start_game():\n", + " \"\"\"\n", + " Start the game\n", + " \"\"\"\n", + " print(\"You wake up on a couch and find yourself in a strange house with no windows which you have never been to before. You don't remember why you are here and what had happened before. You feel some unknown danger is approaching and you must get out of the house, NOW!\")\n", + " play_room(game_state[\"current_room\"])\n", + "\n", + "def play_room(room):\n", + " \"\"\"\n", + " Play a room. First check if the room being played is the target room.\n", + " If it is, the game will end with success. Otherwise, let player either \n", + " explore (list all items in this room) or examine an item found here.\n", + " \"\"\"\n", + " game_state[\"current_room\"] = room\n", + " if(game_state[\"current_room\"] == game_state[\"target_room\"]):\n", + " print(\"Congrats! You escaped the room!\")\n", + " else:\n", + " print(\"You are now in \" + room[\"name\"])\n", + " intended_action = input(\"What would you like to do? Type 'explore' or 'examine'?\").strip()\n", + " if intended_action == \"explore\":\n", + " explore_room(room)\n", + " play_room(room)\n", + " elif intended_action == \"examine\":\n", + " examine_item(input(\"What would you like to examine?\").strip())\n", + " else:\n", + " print(\"Not sure what you mean. Type 'explore' or 'examine'.\")\n", + " play_room(room)\n", + " linebreak()\n", + "\n", + "def explore_room(room):\n", + " \"\"\"\n", + " Explore a room. List all items belonging to this room.\n", + " \"\"\"\n", + " items = [i[\"name\"] for i in object_relations[room[\"name\"]]]\n", + " print(\"You explore the room. This is \" + room[\"name\"] + \". You find \" + \", \".join(items))\n", + "\n", + "def get_next_room_of_door(door, current_room):\n", + " \"\"\"\n", + " From object_relations, find the two rooms connected to the given door.\n", + " Return the room that is not the current_room.\n", + " \"\"\"\n", + " connected_rooms = object_relations[door[\"name\"]]\n", + " for room in connected_rooms:\n", + " if(not current_room == room):\n", + " return room\n", + "\n", + "def examine_item(item_name):\n", + " \"\"\"\n", + " Examine an item which can be a door or furniture.\n", + " First make sure the intended item belongs to the current room.\n", + " Then check if the item is a door. Tell player if key hasn't been \n", + " collected yet. Otherwise ask player if they want to go to the next\n", + " room. If the item is not a door, then check if it contains keys.\n", + " Collect the key if found and update the game state. At the end,\n", + " play either the current or the next room depending on the game state\n", + " to keep playing.\n", + " \"\"\"\n", + " current_room = game_state[\"current_room\"]\n", + " next_room = \"\"\n", + " output = None\n", + " \n", + " for item in object_relations[current_room[\"name\"]]:\n", + " if(item[\"name\"] == item_name):\n", + " output = \"You examine \" + item_name + \". \"\n", + " if(item[\"type\"] == \"door\"):\n", + " have_key = False\n", + " for key in game_state[\"keys_collected\"]:\n", + " if(key[\"target\"] == item):\n", + " have_key = True\n", + " if(have_key):\n", + " output += \"You unlock it with a key you have.\"\n", + " next_room = get_next_room_of_door(item, current_room)\n", + " else:\n", + " output += \"It is locked but you don't have the key.\"\n", + " else:\n", + " if(item[\"name\"] in object_relations and len(object_relations[item[\"name\"]])>0):\n", + " item_found = object_relations[item[\"name\"]].pop()\n", + " game_state[\"keys_collected\"].append(item_found)\n", + " output += \"You find \" + item_found[\"name\"] + \".\"\n", + " else:\n", + " output += \"There isn't anything interesting about it.\"\n", + " print(output)\n", + " break\n", + "\n", + " if(output is None):\n", + " print(\"The item you requested is not found in the current room.\")\n", + " \n", + " if(next_room and input(\"Do you want to go to the next room? Ener 'yes' or 'no'\").strip() == 'yes'):\n", + " play_room(next_room)\n", + " else:\n", + " play_room(current_room)" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "You wake up on a couch and find yourself in a strange house with no windows which you have never been to before. You don't remember why you are here and what had happened before. You feel some unknown danger is approaching and you must get out of the house, NOW!\n", + "You are now in game room\n", + "What would you like to do? Type 'explore' or 'examine'?explore\n", + "You explore the room. This is game room. You find couch, piano, door a\n", + "You are now in game room\n", + "What would you like to do? Type 'explore' or 'examine'?examine\n", + "What would you like to examine?door a\n", + "You examine door a. It is locked but you don't have the key.\n", + "You are now in game room\n", + "What would you like to do? Type 'explore' or 'examine'?examine\n", + "What would you like to examine?piano\n", + "You examine piano. You find key for door a.\n", + "You are now in game room\n", + "What would you like to do? Type 'explore' or 'examine'?examine\n", + "What would you like to examine?door a\n", + "You examine door a. You unlock it with a key you have.\n", + "Do you want to go to the next room? Ener 'yes' or 'no'yes\n", + "Congrats! You escaped the room!\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n" + ] + } + ], + "source": [ + "game_state = INIT_GAME_STATE.copy()\n", + "\n", + "start_game()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.8.3" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/your-code/BACKGROUND.jpg b/your-code/BACKGROUND.jpg new file mode 100644 index 00000000..f2a13192 Binary files /dev/null and b/your-code/BACKGROUND.jpg differ diff --git a/your-code/Dacha_Escape_Room.ipynb b/your-code/Dacha_Escape_Room.ipynb new file mode 100644 index 00000000..f1d3f0a9 --- /dev/null +++ b/your-code/Dacha_Escape_Room.ipynb @@ -0,0 +1,1104 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 4, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 85 + }, + "id": "uRjaA6neUGcr", + "outputId": "26d6a096-bc21-4165-819d-f4277543cab4" + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Requirement already satisfied: soundfile in c:\\users\\eloi pc\\appdata\\local\\programs\\python\\python38-32\\lib\\site-packages (0.10.3.post1)\n", + "Requirement already satisfied: cffi>=1.0 in c:\\users\\eloi pc\\appdata\\local\\programs\\python\\python38-32\\lib\\site-packages (from soundfile) (1.14.2)\n", + "Requirement already satisfied: pycparser in c:\\users\\eloi pc\\appdata\\local\\programs\\python\\python38-32\\lib\\site-packages (from cffi>=1.0->soundfile) (2.20)\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING: You are using pip version 20.1.1; however, version 20.2.4 is available.\n", + "You should consider upgrading via the 'c:\\users\\eloi pc\\appdata\\local\\programs\\python\\python38-32\\python.exe -m pip install --upgrade pip' command.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Requirement already satisfied: playsound in c:\\users\\eloi pc\\appdata\\local\\programs\\python\\python38-32\\lib\\site-packages (1.2.2)\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING: You are using pip version 20.1.1; however, version 20.2.4 is available.\n", + "You should consider upgrading via the 'c:\\users\\eloi pc\\appdata\\local\\programs\\python\\python38-32\\python.exe -m pip install --upgrade pip' command.\n" + ] + } + ], + "source": [ + "# Here we should import all packages and define other things such as classes\n", + "import time\n", + "import numpy as np\n", + "import pandas as pd\n", + "from IPython.display import Audio\n", + "from IPython.display import Image\n", + "from IPython.display import display\n", + "\n", + "import multiprocessing\n", + "!pip install soundfile\n", + "import soundfile as sf\n", + "!pip install playsound\n", + "from playsound import playsound\n", + "\n", + "class color:\n", + " ### How to use:\n", + " ### print(color.BOLD + 'Hello World !' + color.END)\n", + " ### print(color.DARKCYAN + color.BOLD + 'Hello World !' + color.END)\n", + " PURPLE = '\\033[95m'\n", + " CYAN = '\\033[96m'\n", + " DARKCYAN = '\\033[36m'\n", + " BLUE = '\\033[94m'\n", + " GREEN = '\\033[92m'\n", + " YELLOW = '\\033[93m'\n", + " RED = '\\033[91m'\n", + " BOLD = '\\033[1m'\n", + " UNDERLINE = '\\033[4m'\n", + " END = '\\033[0m'\n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": 71, + "metadata": { + "id": "IHF3ccywR3zo" + }, + "outputs": [], + "source": [ + "# Object declaration/initialization.\n", + "\n", + "# RUI: Library of Images and sounds\n", + "# [RUI: to be done, now dummy data just to test // sounds will not run properly on colaborative]\n", + "map_game_room = Image(filename=\"sounds_and_images\\map_game_room.png\")\n", + "map_corridor = Image(filename=\"sounds_and_images\\map_corridor.png\")\n", + "map_bathroom = Image(filename=\"sounds_and_images\\map_bathroom.png\")\n", + "map_kitchen = Image(filename=\"sounds_and_images\\map_kitchen.png\")\n", + "map_living_room = Image(filename=\"sounds_and_images\\map_living_room.png\")\n", + "\n", + "#[Rui, these soun]\n", + "sound_bathtub = \"sounds_and_images\\clogged_bathtub.wav\"\n", + "sound_old_lady = \"sounds_and_images\\gulping_bottle.wav\"\n", + "sound_cutlery_drawer = \"sounds_and_images\\smashing_wood.wav\"\n", + "\n", + "# [RUI: This one could be called maybe when we write \"congratulations\".]\n", + "sound_victory = \"sounds_and_images\\win.wav\"\n", + "# [RUI: This one can be called maybe when we call the function to get the next room.]\n", + "sound_door_creaking = \"sounds_and_images\\door_creaking.wav\"\n", + "\n", + "# Definition of ROOMS:\n", + "game_room = {\n", + " \"name\": \"game room\",\n", + " \"type\": \"room\",\n", + " \"map\": map_game_room}\n", + "corridor = {\n", + " \"name\": \"corridor\",\n", + " \"type\": \"room\",\n", + " \"map\": map_corridor}\n", + "bathroom = {\n", + " \"name\": \"bathroom\",\n", + " \"type\": \"room\",\n", + " \"map\": map_bathroom}\n", + "kitchen = {\n", + " \"name\": \"kitchen\",\n", + " \"type\": \"room\",\n", + " \"map\": map_kitchen}\n", + "living_room = {\n", + " \"name\": \"living room\",\n", + " \"type\": \"room\",\n", + " \"map\": map_living_room}\n", + "\n", + "# Definition of DOORS\n", + "door_gameroom = {\n", + " \"name\": \"game room door\",\n", + " \"type\": \"door\",}\n", + "door_bathroom = {\n", + " \"name\": \"bathroom door\",\n", + " \"type\": \"door\",}\n", + "door_kitchen = {\n", + " \"name\": \"kitchen door\",\n", + " \"type\": \"door\",}\n", + "door_livingroom = {\n", + " \"name\": \"living room door\",\n", + " \"type\": \"door\",}\n", + "door_other = {\n", + " \"name\": \"other door\",\n", + " \"type\": \"door\",}\n", + "\n", + "# FURNITURE AND PEOPLE\n", + "\n", + "# GAME ROOM\n", + "side_table = {\n", + " \"name\": \"side table\",\n", + " \"type\": \"furniture\",\n", + " \"useful\": False,\n", + " #flavour_text of side table is set at start with the start game function.\n", + " \"flavour_text\": \"\"}\n", + "couch = {\n", + " \"name\": \"couch\",\n", + " \"type\": \"furniture\",\n", + " \"useful\": False,\n", + " \"flavour_text\": \"Potato.\",\n", + "}\n", + "piano = {\n", + " \"name\": \"piano\",\n", + " \"type\": \"furniture\",\n", + " \"useful\": True,\n", + " \"status\": \"closed\",\n", + " \"code\": \"9857\",\n", + " \"flavour_text\": \"You would be surprised if it was working.\",\n", + "}\n", + "chairs = {\n", + " \"name\": \"chairs\",\n", + " \"type\": \"furniture\",\n", + " \"useful\": False,\n", + " \"flavour_text\": \"Previously owned by a dictator.\",\n", + "}\n", + "bookshelf = {\n", + " \"name\": \"bookshelf\",\n", + " \"type\": \"furniture\",\n", + " \"useful\": True,\n", + " \"books_in_russian\": [\"Преступление и наказание\",\"Маленькие женщины\",\"Большие надежды\",\"Война и мир\",\"Les Misérables\",\"Записки из метро\", \"Белые ночи\", \"Сон о смехотворном человеке\",\"Идиот\",\"Женщина в белом\",\"Отцы и сыновья\",\"Лунный камень\",\"Сайлас Марнер\",\"Путешествие к центру Земли\",\"Мельница на зубной нити\",\"Русско-английский словарь/English–Russian Dictionary\",\"книга джунглей\"],\n", + " \"books_in_english\": [\"Crime and Punishment\",\"Little Women\",\"Great Expectations\",\"War and Peace\",\"Les Misérables\", \"Notes from Underground\",\"White Nights\",\"Dreams of a ridiculous man\",\"The Idiot\",\"The Woman in White\",\"Fathers and Sons\",\"The Moonstone\",\"Silas Marner\",\"Journey to the Center of the Earth\",\"The Mill on the Floss\",\"Russian-English Dictionary/English–Russian Dictionary\",\"The Jungle Book\"],\n", + " \"flavour_text\": \"Packed!\",\n", + " # Bookshelf will have another property key \"play\" with a function attributed as value.\n", + "}\n", + "wall_clock = {\n", + " \"name\": \"wall clock\",\n", + " \"type\": \"furniture\",\n", + " \"useful\": False,\n", + " \"flavour_text\": color.BOLD + \"Antique! \" + color.END + \"Would be worth millions if it was not broken, cracked nor the home of a million of bugs.\",\n", + "}\n", + "piano = {\n", + " \"name\": \"piano\",\n", + " \"type\": \"furniture\",\n", + " \"useful\": True,\n", + " \"password\": \"9857\",\n", + " \"flavour_text\": \"Cords and... bones. Even not creepy pianos have bones\",\n", + "}\n", + "\n", + "# CORRIDOR\n", + "vault = {\n", + " \"name\": \"vault\",\n", + " \"type\": \"furniture\",\n", + " \"password\": \"volga\",\n", + " \"useful\": True,\n", + " \"flavour_text\": \"The lock has a message: \\\"For the sake of the future of this family, the answer is kept secret in the very heart of this great surname.\\\" <>\",\n", + "}\n", + "old_picture = {\n", + " \"name\": \"old picture\",\n", + " \"type\": \"furniture\",\n", + " \"useful\": False,\n", + " \"flavour_text\": \"2.8 - Oglav family at their Dacha close by a famous river.\",\n", + "}\n", + "# BATHROOM\n", + "bathtub = {\n", + " \"name\": \"bathtub\",\n", + " \"type\": \"furniture\",\n", + " \"useful\": True,\n", + " \"counter\": 0,\n", + " \"flavour_text\": \"The bathtub is filled with rain from the gap on the ceiling\",\n", + " \"sound\": sound_bathtub}\n", + "toilet = {\n", + " \"name\": \"toilet\",\n", + " \"type\": \"furniture\",\n", + " \"useful\": True,\n", + " \"flavour_text\": \"There's no time for number 1's or 2's, you have to leave this dacha!\",}\n", + "sink = {\n", + " \"name\": \"sink\",\n", + " \"type\": \"furniture\",\n", + " \"useful\": True,\n", + " \"flavour_text\": \"You feel bad for breaking the sink but you ain't no plumer\",}\n", + "cabinet = {\n", + " \"name\": \"toilet\",\n", + " \"type\": \"furniture\",\n", + " \"useful\": False,\n", + " \"flavour_text\": \"There is a shatered mirror and a small medicine box that says аспирин 3,5 миллиграмма\",}\n", + "rug = {\n", + " \"name\": \"rug\",\n", + " \"type\": \"furniture\",\n", + " \"useful\": True,\n", + " \"flavour_text\": \"Who the hell has a rug on a bathroom? I’ll keep looking somewhere else, maybe on the bathtub?\",}\n", + "\n", + "# KITCHEN\n", + "plate_cabinet = {\n", + " \"name\": \"plate cabinet\",\n", + " \"type\": \"furniture\",\n", + " \"useful\": False,\n", + " \"flavour_text\": \"Just some old fancy plates.\"\n", + "}\n", + "cutlery_drawer = {\n", + " \"name\": \"cutlery drawer\",\n", + " \"type\": \"furniture\",\n", + " \"useful\": True,\n", + " \"flavour_text\": \"It is full of stuff and things, nothing useful though.\",\n", + " \"sound\": sound_cutlery_drawer\n", + "}\n", + "table_with_chairs = {\n", + " \"name\": \"old table with chairs\",\n", + " \"type\": \"furniture\",\n", + " \"useful\": False,\n", + " \"flavour_text\": \"There are some cutlery and an old tsarist newspaper that says: \\\"Правда - 22 апреля 1912 года\\\". \\n It seems that reading a dictionary doesn't make you that fluent after all!\"\n", + "}\n", + "pantry = {\n", + " \"name\": \"pantry\",\n", + " \"type\": \"furniture\",\n", + " \"useful\": True,\n", + " \"object\": [\"wine\" , \"food can\"],\n", + " \"flavour_text\": \"It's full of food cans and wine bottles from another era, the tags barely visible.\"\n", + "}\n", + "stove_oven = {\n", + " \"name\": \"oven\",\n", + " \"type\": \"furniture\",\n", + " \"useful\": True,\n", + " \"password\": \"1890\",\n", + " \"flavour_text\": \"It is an old stove, the wood fueled kind. It is very scratched... life took a toll on it. \\n There is a small lock to open it, with 4 rotating numerical pieces.\",\n", + "}\n", + "# LIVING ROOM\n", + "old_lady = {\n", + " \"name\": \"old lady\",\n", + " \"type\": \"furniture\",\n", + " \"status\": \"sleeping\",\n", + " \"useful\": True,\n", + " \"flavour_text\": \"All dressed in black, no teeth and sitted on a wooden chair. You doubt she is still alive\",\n", + " \"sound\": sound_old_lady\n", + "}\n", + "pendulum = {\n", + " \"name\": \"pendulum\",\n", + " \"type\": \"furniture\",\n", + " \"useful\": True,\n", + " \"status\": \"closed\",\n", + " \"code\": \"0915\",\n", + " \"flavour_text\": \"What a gorgeous clock this must have been.\",\n", + "}\n", + "crib = {\n", + " \"name\": \"crib\",\n", + " \"type\": \"furniture\",\n", + " \"useful\": True,\n", + " \"flavour_text\": \"Do you really felt like checking this twice?\",\n", + "}\n", + "\n", + "# KNOWLEDGE\n", + "\n", + "russian = {\n", + "#Learn from bookshelf interaction\n", + " \"name\": \"russian\",\n", + " \"type\": \"knowledge\",\n", + " \"target\": side_table,\n", + "}\n", + "\n", + "wrench = {\n", + " \"name\": \"wrench\",\n", + " \"type\": \"knowledge\",\n", + " \"target\": sink,}\n", + "lever = {\n", + " \"name\": \"lever\",\n", + " \"type\": \"knowledge\",\n", + " \"target\": toilet,}\n", + "wine = {\n", + " \"name\": \"open wine\",\n", + " \"type\": \"knowledge\",\n", + " \"target\": old_lady}\n", + "wine_opener = {\n", + " \"name\": \"wine opener\",\n", + " \"type\": \"knowledge\",\n", + " \"target\": wine}\n", + "keys_pendulum = {\n", + " \"name\": \"keys pendulum\",\n", + " \"type\": \"knowledge\",\n", + " \"target\": pendulum, }\n", + "hammer = {\n", + " \"name\": \"hammer\",\n", + " \"type\": \"knowledge\",\n", + " \"target\": cutlery_drawer}\n", + "\n", + "\n", + "#KEYS\n", + "key_gameroom = {\n", + " \"name\": \"key for game room\",\n", + " \"type\": \"key\",\n", + " \"target\": door_gameroom,}\n", + "key_bathroom = {\n", + " \"name\": \"key for bathroom\",\n", + " \"type\": \"key\",\n", + " \"target\": door_bathroom,}\n", + "key_kitchen = {\n", + " \"name\": \"key for kitchen\",\n", + " \"type\": \"key\",\n", + " \"target\": door_kitchen,}\n", + "key_livingroom = {\n", + " \"name\": \"key for living room\",\n", + " \"type\": \"key\",\n", + " \"target\": door_livingroom,}\n", + "key_outside = {\n", + " \"name\": \"key for outside\",\n", + " \"type\": \"key\",\n", + " \"target\": door_other,}\n", + "\n", + "\n", + "# OUTSIDE\n", + "outside = {\n", + " \"name\": \"outside\"}\n", + "\n", + "# ALL\n", + "all_rooms = [game_room, corridor, bathroom, kitchen, living_room, outside]\n", + "all_doors = [door_gameroom, door_bathroom, door_livingroom, door_kitchen, door_other]\n", + "all_knowledge = [bookshelf, wrench, lever, wine_opener, wine, hammer]\n", + "# Here we should define all object relations\n", + " # At least these should be: \n", + " # For rooms: which objects (furnitures and doors - probably not knowledge) it contains.\n", + " # For furniture/people: which items(keys) it contains.\n", + " # For doors: which rooms they connect.\n", + " \n", + "object_relations = {\n", + " \"game room\": [couch, chairs, bookshelf, piano, side_table, wall_clock, door_gameroom],\n", + " \"bathroom\":[toilet, bathtub, sink, cabinet, rug, door_bathroom],\n", + " \"corridor\": [old_picture, vault, door_gameroom, door_bathroom, door_kitchen, door_livingroom],\n", + " \"kitchen\": [plate_cabinet, cutlery_drawer, stove_oven, table_with_chairs, pantry, door_kitchen],\n", + " \"living room\": [old_lady, pendulum, crib, door_livingroom, door_other],\n", + "\n", + " \"book shelf\": [key_gameroom],\n", + " \"vault\": [key_bathroom],\n", + "\n", + " #### RUI: Would making this Rug lower case (rug) make any difference ? It is lower case everywhere else.\n", + " \"Rug\": [key_kitchen],\n", + " \"oven\": [key_livingroom],\n", + " \"piano\": [key_outside],\n", + " \n", + "\n", + " \"bathtub\": [lever],\n", + " \"toilet\": [wrench],\n", + "\n", + " \"game room door\": [game_room, corridor],\n", + " \"living room door\": [corridor, living_room],\n", + " \"kitchen door\": [corridor, kitchen],\n", + " \"bathroom door\": [corridor, bathroom],\n", + " \"other door\": [living_room, outside],\n", + "\n", + " \"outside\": [door_other],\n", + "\n", + "}\n", + "# Here we need to define the original/starting state of the game.\n", + "# We need to say which is the starting room.\n", + "# We need to make empty lists for our keys_collected or for our knowledge.\n", + "# We need to establish the target (which is outside.) \n", + "\n", + "INIT_GAME_STATE = {\n", + " \"current_room\": game_room,\n", + " \"keys_collected\": [],\n", + " \"knowledge_collected\": [],\n", + " \"map_collected\": [game_room],\n", + " \"target_room\": outside\n", + "}" + ] + }, + { + "cell_type": "code", + "execution_count": 72, + "metadata": { + "id": "pVI6VLkaS-lN" + }, + "outputs": [], + "source": [ + "# Here we should try to put all new functions of general use we make\n", + "def linebreak():\n", + " \"\"\"\n", + " Print a line break\n", + " \"\"\"\n", + " print(\"\\n\")\n", + "\n", + "def play_my_sound(audio_string):\n", + " f = sf.SoundFile(audio_string)\n", + " lengh_audio = len(f) / f.samplerate\n", + " p = multiprocessing.Process(target=playsound, args=(audio_string,))\n", + " p.start()\n", + " time.sleep(lengh_audio)\n", + " p.terminate()\n", + "\n", + "def keys_in_pocket():\n", + " \"\"\"\n", + " List all keys currently obtained.\n", + " \"\"\"\n", + " #The for-loop gets all key_names. \n", + " #It looks inside the game_state dictonary for the value corresponding to the \"keys_collected\" key.\n", + " #It prints a message if no keys have been collected and another message if keys have been collected.\n", + " #The difference between the print in the elif and else is just to make sure \n", + " #that the last two keys are separated by a word \"and\" instead of a comma.\n", + " \n", + " myList = []\n", + " for i in range(len(game_state[\"keys_collected\"])):\n", + " myList.append(game_state[\"keys_collected\"][i].get(\"name\"))\n", + " \n", + " if len(myList)==0:\n", + " print('You have nothing on your pocket.')\n", + " elif len(myList)==1:\n", + " print('In your pocked you find: ' + ''.join(myList) + '.')\n", + " else:\n", + " print('In your pocked you find: ' + \" and \".join([\", \".join(myList[:-1]),myList[-1]]) + '.')\n", + "\n", + "def are_words_similar(s1,s2):\n", + " \"\"\"\n", + " Compares the lower case version of two words.\n", + " Allows for words to have one typo.\n", + " \"\"\"\n", + " s1 = s1.strip().lower()\n", + " s2 = s2.strip().lower()\n", + " if len(s1) > len(s2):\n", + " s1,s2 = s2,s1\n", + " s = sum([s1[i] != s2[i] for i in range(len(s1))])\n", + " if s == 1:\n", + " return True\n", + " else:\n", + " return False\n", + "\n", + "def show_map():\n", + " if game_room in game_state[\"map_collected\"] and corridor not in game_state[\"map_collected\"]:\n", + " display(game_room[\"map\"])\n", + " time.sleep(0.1)\n", + " return\n", + " elif corridor in game_state[\"map_collected\"] and bathroom not in game_state[\"map_collected\"]:\n", + " display(corridor[\"map\"])\n", + " time.sleep(0.1)\n", + " return\n", + " elif bathroom in game_state[\"map_collected\"] and kitchen not in game_state[\"map_collected\"]:\n", + " display(bathroom[\"map\"])\n", + " time.sleep(0.1)\n", + " return\n", + " elif kitchen in game_state[\"map_collected\"] and living_room not in game_state[\"map_collected\"]:\n", + " display(kitchen[\"map\"])\n", + " time.sleep(0.1)\n", + " return\n", + " elif living_room in game_state[\"map_collected\"]:\n", + " display(living_room[\"map\"])\n", + " time.sleep(0.1)\n", + " return" + ] + }, + { + "cell_type": "code", + "execution_count": 73, + "metadata": { + "id": "55EMPCGHDvIO" + }, + "outputs": [], + "source": [ + "# Game Room.\n", + "# Bookshelf Interactions (Function)\n", + "\n", + "def consult_books(knows_russian):\n", + " if knows_russian == False:\n", + " print(\"You look at the bookshelf. You find the following books:\")\n", + " for book in (bookshelf.get(\"books_in_russian\")):\n", + " print(str(bookshelf.get(\"books_in_russian\").index(book)) + str(\" - \" + book))\n", + " elif knows_russian == True:\n", + " print(\"You go to the bookshelf, you find many books in russian. Their tittles in English are:\")\n", + " for book in (bookshelf.get(\"books_in_english\")):\n", + " print(str(bookshelf.get(\"books_in_english\").index(book)) + str(\" - \" + book))\n", + "\n", + "def take_book(): \n", + " print('Do you want to take a book? Write: ' + color.DARKCYAN + color.BOLD + \"Yes\" + color.END + \" or \"+ color.DARKCYAN + color.BOLD + \"No\" + color.END)\n", + " take_book_yes_no = input('').lower().strip()\n", + " if take_book_yes_no == \"no\":\n", + " return \"no\"\n", + " elif take_book_yes_no == \"yes\":\n", + " return \"yes\" \n", + "\n", + "def choose_book(knows_russian):\n", + " print('Which book do you want to take? Write the number which identifies the book')\n", + " book_chosen = input('').lower().strip()\n", + " if knows_russian == False:\n", + " if book_chosen == str(15):\n", + " print('A dictionary! It helps reading russian. ' + color.UNDERLINE + 'You feel like you learnt something today.' + color.END)\n", + " game_state[\"knowledge_collected\"].append(russian)\n", + " side_table[\"flavour_text\"] = \"A table with a picture of an old lady reading a book on top of it. She is devouring the book called \" + color.BOLD + \"The Jungle Book.\" + color.END\n", + " return str(book_chosen)\n", + " elif book_chosen == str(4):\n", + " print('You do not speak baguette. You wonder why do French always copy English words... croissant comes to mind.')\n", + " print('You put back the book.')\n", + " return str(book_chosen)\n", + " elif book_chosen in str([0, 1, 2, 3, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 16]) or book_chosen in [\"zero\", \"one\", \"two\", \"three\", \"five\", \"six\", \"seven\", \"eight\", \"nine\", \"ten\", \"eleven\", \"twelve\", \"thirteen\", \"fourteen\", \"sixteen\"]:\n", + " print('These characters are somewhat familiar, but you have no idea how to prounounce anything.')\n", + " print('You put back the book.')\n", + " return str(book_chosen)\n", + " else:\n", + " print('Input unclear.')\n", + " choose_book(knows_russian)\n", + " return\n", + " elif knows_russian == True:\n", + " if book_chosen == str(15):\n", + " print('A dictionary! It helps reading russian... which you already know!')\n", + " print('You put back the book.')\n", + " return str(book_chosen)\n", + " elif book_chosen == str(16):\n", + " if key_gameroom in game_state[\"keys_collected\"]:\n", + " print('Classic literature... boring.')\n", + " return str(book_chosen)\n", + " else:\n", + " print('You open The Jungle. You find a key inside! ' + color.UNDERLINE + 'You take it with you!' + color.END)\n", + " game_state[\"keys_collected\"].append(key_gameroom)\n", + " return str(book_chosen)\n", + " elif book_chosen in str([0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14]) or book_chosen in [\"zero\", \"one\", \"two\", \"three\", \"four\", \"five\", \"six\", \"seven\", \"eight\", \"nine\", \"ten\", \"eleven\", \"twelve\", \"thirteen\", \"fourteen\"]:\n", + " print('Classic literature... boring.')\n", + " print('You put back the book.')\n", + " return str(book_chosen)\n", + " else:\n", + " print('Input unclear.')\n", + " choose_book(knows_russian)\n", + " return\n", + "\n", + "def play_bookshelf():\n", + " consult_books(russian in game_state[\"knowledge_collected\"])\n", + " if take_book() == \"yes\":\n", + " cycle_break = False\n", + " while not(cycle_break):\n", + " if choose_book(russian in game_state[\"knowledge_collected\"]) == \"15\" and not (russian in game_state[\"knowledge_collected\"]):\n", + " cycle_break = True\n", + " elif (russian in game_state[\"knowledge_collected\"]):\n", + " cycle_break = True\n", + " else:\n", + " return\n", + " \n", + "#The statement below adds the function above to the bookshelf dictionary/object.\n", + "bookshelf[\"play\"] = play_bookshelf" + ] + }, + { + "cell_type": "code", + "execution_count": 74, + "metadata": { + "id": "0mt-b6f_4d8S" + }, + "outputs": [], + "source": [ + "#Bathroom Functions, one per interactable furniture.\n", + "\n", + "def bathtub_check():\n", + " furniture = bathtub\n", + " have_tool = False\n", + " if (bathtub[\"counter\"] == 0):\n", + " play_my_sound(bathtub[\"sound\"])\n", + " print(\"You remove some of the waters, you see a comb floating. You do a minor attempt at uncloggin the bathtub.\")\n", + " print(\"A voice behind you says \" + color.BOLD + \"DEEPER\" + color.END + \" in a very sinister way.\")\n", + " bathtub[\"counter\"] +=1\n", + " play_room(game_state[\"current_room\"])\n", + " if (bathtub[\"counter\"] == 1):\n", + " play_my_sound(bathtub[\"sound\"])\n", + " print(\"You hear the same voice shouting \" + color.BOLD + \"I SAID DEEPER, BLYAT\" + color.END + \".\")\n", + " print(\"Better comply...\")\n", + " bathtub[\"counter\"] +=1\n", + " play_room(game_state[\"current_room\"])\n", + " if (bathtub[\"counter\"] == 2):\n", + " play_my_sound(bathtub[\"sound\"])\n", + " print(\"You are tired of of putting your arm elbow-deep into the pipes. Yet, within the cold water, you are able to find a cork stuck. \\n\"\n", + " \"After a few seconds you can take it off and drain the bathtub slowly. In the bottom you see what looks like a \" + color.UNDERLINE + \"toilet lever\" + color.END + \".\")\n", + " game_state[\"knowledge_collected\"].append(lever)\n", + " bathtub[\"useful\"] = False\n", + " play_room(game_state[\"current_room\"])\n", + "\n", + "def toilet_check():\n", + " furniture = toilet\n", + " have_tool = False\n", + " for tool in game_state[\"knowledge_collected\"]:\n", + " if(tool[\"target\"] == furniture):\n", + " have_tool = True\n", + " if(have_tool):\n", + " game_state[\"knowledge_collected\"].append(wrench)\n", + " print(\"You can work with the lever to flush it until midpoint. You see a shiny object and pick it up. It’s a \" + color.UNDERLINE + \"rusty steel wrench\" + color.END + \".\")\n", + " toilet[\"useful\"] = False\n", + " play_room(game_state[\"current_room\"])\n", + " else:\n", + " print(\"Eeeew. You can’t possibly get your arm onto that mess... the devs are not that mean.\")\n", + " play_room(game_state[\"current_room\"])\n", + " return None\n", + "\n", + "def sink_check():\n", + " furniture = sink\n", + " have_tool = False\n", + " for tool in game_state[\"knowledge_collected\"]:\n", + " if(tool[\"target\"] == furniture):\n", + " have_tool = True\n", + " if(have_tool):\n", + " print(\"You are a man of culture and go for the piping. You can easen some bolts until it falls apart and all water furiously drains down and something metallic shines and bounces to the rug.\")\n", + " sink[\"useful\"] = False\n", + " play_room(game_state[\"current_room\"])\n", + " else:\n", + " print(\"You put your right arm deep into the water and can’t unplug the thick substance. Looks like you could fix it by easing the water pipe.\")\n", + " play_room(game_state[\"current_room\"])\n", + "\n", + "def rug_check():\n", + " furniture = rug\n", + " if sink[\"useful\"] == False:\n", + " game_state[\"keys_collected\"].append(key_kitchen)\n", + " print(\"You pick the \"+ color.UNDERLINE + \"key\" + color.END + \" from the mushy floor that comes attached to a beer opener.\")\n", + " rug[\"useful\"] = False\n", + " play_room(game_state[\"current_room\"])\n", + " else:\n", + " print(\"Who the hell has a rug on a bathroom? I’ll keep looking somewhere else, maybe on the bathtub?\")\n", + " play_room(game_state[\"current_room\"])\n", + "\n", + "toilet[\"play\"] = toilet_check\n", + "sink[\"play\"] = sink_check\n", + "bathtub[\"play\"] = bathtub_check\n", + "rug[\"play\"] = rug_check" + ] + }, + { + "cell_type": "code", + "execution_count": 75, + "metadata": { + "id": "Fq827loV7cT-" + }, + "outputs": [], + "source": [ + "# KITCHEN\n", + "def open_cutlery_drawer():\n", + " have_wrench = False\n", + " if wrench in game_state[\"knowledge_collected\"]:\n", + " have_wrench = True\n", + " if (have_wrench == True):\n", + " play_my_sound(cutlery_drawer[\"sound\"])\n", + " print(\"You feel empowered enough to force the drawer and open it with the wrench. After the hit, you encounter something soft, yet crunchy. After inspection it was the putrid corpse of a rat that you moved and, below it, there is a \" + color.BOLD + \"wine opener.\" + color.END)\n", + " game_state[\"knowledge_collected\"].append(wine_opener)\n", + " cutlery_drawer[\"useful\"] = False\n", + " print(\"You have found a wine opener\")\n", + " play_room(game_state[\"current_room\"])\n", + " elif (wine_opener in game_state[\"knowledge_collected\"]):\n", + " print(\"There is just some old fashion cutlery.\")\n", + " else:\n", + " print(cutlery_drawer[\"flavour_text\"])\n", + " play_room(game_state[\"current_room\"])\n", + " return None\n", + "\n", + "def examine_pantry ():\n", + " print (pantry[\"flavour_text\"])\n", + " have_wine_opener = False\n", + " ### RUI'S COMMENT: We never talk about the exit command. I THINK IT WORKS DIFFERENTLY IN GOOGLE COLABORATIVE AND IN JUPYTER, SO I GUESS WE SHOULD REMOVE IT.\n", + " print(\"What would you like to examine? Type \" + (color.DARKCYAN + \" or \".join(pantry[\"object\"]) + color.END) + \". Type \\\"exit\\\" if you would like to go back to the kitchen.\")\n", + " to_examine = input()\n", + " if wine_opener in game_state[\"knowledge_collected\"]:\n", + " have_wine_opener = True\n", + " #### RUI'S COMMENT: I THINK THAT INSTEAD of to_examine == \"wine\" (or == \"food can\") we need \"old wines\" or \"food cans\" HERE !!!\n", + " if to_examine == \"wine\":\n", + " if have_wine_opener == False:\n", + " linebreak()\n", + " print(\"You pick a bottle and try the cork, but without the proper tool you can’t open it. On the tag you can read горули мцване 1890 so it’s been there for a while. The wine looks surprisingly well preserved.\")\n", + " print(\"Perhaps it was an important gift.\")\n", + " examine_pantry()\n", + " elif have_wine_opener == True:\n", + " linebreak()\n", + " print(\"Looks like a very Georgian wine. You imagine this is what rich people drink.\")\n", + " game_state[\"knowledge_collected\"].append(wine)\n", + " print(\"You have found \" + color.UNDERLINE + \"wine\" + color.END + \".\")\n", + " examine_pantry()\n", + " elif wine in game_state[\"knowledge_collected\"]:\n", + " linebreak()\n", + " print(\"Just some old fancy wines.\")\n", + " examine_pantry()\n", + " elif to_examine == \"food can\":\n", + " linebreak()\n", + " print (\"You take a can and see the tag has written Cрок годности 01-09-//////// on it. Looks like a date in which the year has faded over the time.\")\n", + " examine_pantry()\n", + " elif to_examine == \"exit\":\n", + " play_room(kitchen)\n", + " else:\n", + " print(\"Object not found. Try it again.\")\n", + " linebreak()\n", + " examine_pantry()\n", + " \n", + "\n", + "pantry[\"play\"] = examine_pantry\n", + "cutlery_drawer[\"play\"] = open_cutlery_drawer" + ] + }, + { + "cell_type": "code", + "execution_count": 76, + "metadata": { + "id": "utdxs7mvghUg" + }, + "outputs": [], + "source": [ + "#Living Room Functions\n", + "\n", + "def crib_check():\n", + " furniture = crib\n", + " print(\"You look into the crib. There is a one-eyed, bald baby doll and a mobile over it. You feel the doll follows your sight...\")\n", + " check = input(\"Want to check mobile or doll?\\n\").strip().lower()\n", + " if (check == \"doll\"):\n", + " print(\"You realize it is an old doll, without hair and with signs of violence, and it's looking to the mobile over it.\")\n", + " play_room(game_state[\"current_room\"])\n", + " if(check == \"mobile\"):\n", + " print(\"It is made of different wooden birds, and it starts playing a lullaby that makes the old woman wakes up and starts babling.\"\n", + " \"You feel nothing good will come from staying longer in this house\")\n", + " old_lady[\"status\"] = \"awaken\"\n", + " crib[\"useful\"] = False\n", + " play_room(game_state[\"current_room\"])\n", + " else:\n", + " print(\"Please enter either option given.\")\n", + " crib_check()\n", + "\n", + "def old_lady_check():\n", + " furniture = old_lady\n", + " have_hammer = False\n", + " if (old_lady[\"status\"] == \"sleeping\"):\n", + " print(\"She is a very old lady, wearing all black clothes and sitting on a wooden chair. You can't tell if she's asleep or dead but you'd better be carefull\")\n", + " play_room(game_state[\"current_room\"])\n", + " if (old_lady[\"status\"] == \"awaken\"):\n", + " if (wine in game_state[\"knowledge_collected\"]):\n", + " print(\"She wants the wine, do you want to open it for her? Go to the kitchen and use this hammer\")\n", + " if (wine_opener in game_state[\"knowledge_collected\"]):\n", + " old_lady[\"status\"] = \"drunk\"\n", + " game_state[\"knowledge_collected\"].append(keys_pendulum)\n", + " old_lady[\"useful\"] = False\n", + " play_my_sound(old_lady[\"sound\"])\n", + " print(\"She jumps and takes the bottle and the opener and proceeds to chug it. When doing so, a \" + color.UNDERLINE + \"set of small keys\" + color.END + \" fall from her lap to your hands.\")\n", + " else:\n", + " print(\"Maybe in the kitchen there's a tool to open it... The old woman salivates looking to the wine and shouts incohesive words to you, that most certainly aren’t compliments\")\n", + " else:\n", + " print(\"The old woman speaks in a broken voice but you can just recognise two word in russian that you learned in a pub a few years back. “wiii----ne p-----leeeeeeas---e\")\n", + " play_room(game_state[\"current_room\"])\n", + " else:\n", + " print(\"test\")\n", + " play_room(game_state[\"current_room\"])\n", + "\n", + "def pendulum_check():\n", + " furniture = pendulum\n", + " if (pendulum[\"status\"] == \"closed\"):\n", + " print(\"The pendulum clock is set at 9:15 AM, but it's stopped. you see yet another 4 digit locker on the door to access it.\")\n", + " print(\"Sigh... you wish there were password hints here. Everyone puts their codes on those.\")\n", + " try_password = input(\"Enter the 4 digit combination\").strip()\n", + " if (furniture[\"code\"] == try_password):\n", + " pendulum[\"status\"] = \"open\"\n", + " print(\"The lock opens but there is another issue...\")\n", + " if (try_password == \"exit\"):\n", + " play_room(game_state[\"current_room\"])\n", + " if(furniture[\"code\"] != try_password):\n", + " print('\"Wrong password.\" You try again')\n", + " pendulum_check()\n", + " if (pendulum[\"status\"] == \"open\"):\n", + " if (keys_pendulum in game_state[\"knowledge_collected\"]):\n", + " pendulum[\"useful\"] = False\n", + " print(\"You find a small paper \" + color.UNDERLINE + \"The last digit is 7\" + color.END + \"looks like some musical code\")\n", + " else:\n", + " print(\"There is a smaller box inside that could be opened with a set of keys\")\n", + " play_room(game_state[\"current_room\"])\n", + " else:\n", + " print(\"What a gorgeous clock this must have been.\")\n", + " play_room(game_state[\"current_room\"])\n", + "\n", + "crib[\"play\"] = crib_check\n", + "old_lady[\"play\"] = old_lady_check\n", + "pendulum[\"play\"] = pendulum_check\n" + ] + }, + { + "cell_type": "code", + "execution_count": 77, + "metadata": { + "id": "7TC2r1MyIMyE" + }, + "outputs": [], + "source": [ + "def piano_check():\n", + " furniture = piano\n", + " print(\"The piano there is a 4 digit locker on the lid. Pianos don't have lockers unless they have something inside that you want.\")\n", + " try_password = input(\"Enter the 4 digit combination\").strip()\n", + " if (piano[\"code\"] == try_password):\n", + " piano[\"useful\"] = False\n", + " game_state[\"keys_collected\"].append(key_outside)\n", + " print(\"It is open!\")\n", + " if (try_password == \"exit\"):\n", + " return\n", + " if (furniture[\"code\"] != try_password):\n", + " print('\"Wrong password.\" You try again')\n", + " piano_check()" + ] + }, + { + "cell_type": "code", + "execution_count": 78, + "metadata": { + "id": "IkA-BsKlWKzD" + }, + "outputs": [], + "source": [ + "# Enter password \n", + "def enter_password(item):\n", + " print((\"The \" + item[\"name\"] + \" has a password! Enter the password or type \\\"exit\\\" to go back to room\"))\n", + " try_password = input().strip().lower()\n", + " output = \"\"\n", + " if (item[\"password\"] == try_password):\n", + " output = \"Correct password!\"\n", + " linebreak()\n", + " if(item[\"name\"] in object_relations and len(object_relations[item[\"name\"]])>0):\n", + " item_found = object_relations[item[\"name\"]].pop()\n", + " game_state[\"keys_collected\"].append(item_found)\n", + " output = \"You find \" + item_found[\"name\"] + \".\"\n", + " print (output)\n", + " elif (try_password == \"exit\"):\n", + " play_room(game_state[\"current_room\"])\n", + " else:\n", + " output += \"Wrong password.\"\n", + " print (output)\n", + " enter_password(item)\n", + "\n", + "vault[\"play\"] = enter_password\n", + "stove_oven[\"play\"] = enter_password\n", + "piano[\"play\"] = enter_password" + ] + }, + { + "cell_type": "code", + "execution_count": 79, + "metadata": { + "id": "WhuLmtzySq2e" + }, + "outputs": [], + "source": [ + "# Here is where the \"main\" cycles are.\n", + "def start_game():\n", + " #Resetting variables which are changed throughout code execution.\n", + " side_table[\"flavour_text\"] = \"A table with a picture of an old lady reading a book on top of it. She is devouring the book called \" + color.BOLD + \"книга джунглей.\" + color.END\n", + " print(\"You wake up on a couch and find yourself in a strange house with no windows which you have never been to before.\")\n", + " print(\"You don't remember why you are here and what had happened before. You feel some unknown danger is approaching and you must get out of the house, NOW!\")\n", + " play_room(game_state[\"current_room\"])\n", + "\n", + "def play_room(room):\n", + " \"\"\"\n", + " Play a room. First check if the room being played is the target room.\n", + " If it is, the game will end with success. Otherwise, let player either \n", + " explore (list all items in this room) or examine an item found here.\n", + " \"\"\"\n", + " game_state[\"current_room\"] = room\n", + " if(game_state[\"current_room\"] == game_state[\"target_room\"]):\n", + " #play_my_sound(sound_victory)\n", + " print(color.GREEN + color.BOLD + \"Congrats! You escaped the room!\" + color.END)\n", + " else:\n", + " print(\"You are now in \" + room[\"name\"])\n", + " print(\"What would you like to do? Type 'explore' or 'examine'? \\n\")\n", + " intended_action = input(\"\").strip().lower()\n", + " if intended_action == \"explore\": ### Here we should use the are_words_similar(s1,s2) function instead.\n", + " explore_room(room)\n", + " print(\"\\n\")\n", + " play_room(room)\n", + " elif intended_action == \"examine\": ### Here we should use the are_words_similar(s1,s2) function instead.\n", + " print(\"What would you like to examine?\")\n", + " use_item_choice = input(\"\").strip().lower()\n", + " \n", + " if examine_silent(use_item_choice) != None:\n", + " room = examine_item(use_item_choice)\n", + " print(\"\\n\")\n", + " play_room(room)\n", + " else:\n", + " print(\"\\n\")\n", + " play_room(room)\n", + " elif intended_action == \"exit\": ### Here we should use the are_words_similar(s1,s2) function instead.\n", + " quit(keep_kernel=True)\n", + " else:\n", + " print(\"Not sure what you mean. Type 'explore' or 'examine'.\")\n", + " play_room(room)\n", + " print(\"\\n\")\n", + "\n", + "def explore_room(room):\n", + " \"\"\"Explore a room. List all items belonging to this room.\"\"\"\n", + " items = [i[\"name\"] for i in object_relations[room[\"name\"]]]\n", + " print(\"You explore the room. This is \" + room[\"name\"] + \". You find \" + \", \".join(items))\n", + " keys_in_pocket()\n", + " print(\"You scrapped some notes about the layout of the house. Do you want to see them? Write: \" + color.DARKCYAN + color.BOLD + \"Yes\" + color.END + \" or \"+ color.DARKCYAN + color.BOLD + \"No\" + color.END)\n", + " yes_no_show_map = input().strip().lower()\n", + " if yes_no_show_map == \"yes\":\n", + " show_map()\n", + " return\n", + " elif yes_no_show_map == \"no\":\n", + " return\n", + " else:\n", + " print(\"Not sure what you mean...\")\n", + " explore_room(room)\n", + "\n", + "def get_next_room_of_door(door, current_room):\n", + " \"\"\"From object_relations, find the two rooms connected to the given door. Return the room that is not the current_room.\"\"\"\n", + " connected_rooms = object_relations[door[\"name\"]]\n", + " play_my_sound(sound_door_creaking)\n", + " for room in connected_rooms:\n", + " if(not current_room == room):\n", + " return room\n", + "\n", + "# Function to examine item. Similar to that of the original project.\n", + "def examine_item(item_name):\n", + " \n", + " room = game_state[\"current_room\"]\n", + " \n", + " #### RUI: I THINK THAT THE REASON WHY THE \"Thanks to the key, you move on to the next room.\" APPEARS TWICE IS.\n", + " #### BECAUSE THIS LOOP ALWAYS LOOPS THROUGH THE TWO ITEMS THAT ARE IN EACH OF THE OBJECT RELATIONS OF EACH ROOM.\n", + " #### NOT SURE HOW TO FIX IT THOUGH.\n", + " \n", + " for item in object_relations[room[\"name\"]]:\n", + " if(item[\"name\"] == item_name):\n", + " #The if below governs what happens if we are not interaction with a door.\n", + " if item[\"type\"] != \"door\": \n", + " output = \"You examine \" + item_name + \":\"\n", + " # ... if the item is not useful we just throw in the flavour text\n", + " # \n", + " if(item[\"useful\"] == False):\n", + " print(item[\"flavour_text\"])\n", + " return None\n", + " play_room(room)\n", + " # ... if it is useful we throw in the function which is stored in the key \"play\" of the object.\n", + " elif (item[\"useful\"] == True):\n", + " if (\"password\" in item):\n", + " print(item[\"flavour_text\"])\n", + " item.get(\"play\")(item)\n", + " elif (\"password\" not in item):\n", + " item.get(\"play\")()\n", + " return None\n", + " # if it is a door, we have the same interaction as in the sample (to open it).\n", + " elif (item[\"type\"] == \"door\"):\n", + " have_key = False\n", + " for key in game_state[\"keys_collected\"]:\n", + " if(key[\"target\"] == item):\n", + " have_key = True\n", + " if(have_key):\n", + " print(\"Thanks to the key, you move on to the next room. The door slowly shuts itself behind you.\")\n", + " next_room = get_next_room_of_door(item, room)\n", + " game_state[\"map_collected\"].append(next_room)\n", + " return next_room\n", + " else:\n", + " print(\"It is locked but you don't have the key.\")\n", + " return None\n", + " #else: return\n", + "\n", + "def examine_silent(item_name):\n", + " \n", + " room = game_state[\"current_room\"]\n", + " for item in object_relations[room[\"name\"]]:\n", + " if(item[\"name\"] == item_name):\n", + " #The if below governs what happens if we are not interaction with a door.\n", + " if item[\"type\"] != \"door\": \n", + " output = \"You examine \" + item_name + \":\"\n", + " # ... if the item is not useful we just throw in the flavour text\n", + " # \n", + " if(item[\"useful\"] == False):\n", + " print(item[\"flavour_text\"])\n", + " return None\n", + " play_room(room)\n", + " # ... if it is useful we throw in the function which is stored in the key \"play\" of the object.\n", + " elif (item[\"useful\"] == True):\n", + " if (\"password\" in item):\n", + " print(item[\"flavour_text\"])\n", + " item.get(\"play\")(item)\n", + " elif (\"password\" not in item):\n", + " item.get(\"play\")()\n", + " return None\n", + " # if it is a door, we have the same interaction as in the sample (to open it).\n", + " elif (item[\"type\"] == \"door\"):\n", + " have_key = False\n", + " for key in game_state[\"keys_collected\"]:\n", + " if(key[\"target\"] == item):\n", + " have_key = True\n", + " if(have_key):\n", + " next_room = get_next_room_of_door(item, room)\n", + " game_state[\"map_collected\"].append(next_room)\n", + " return next_room\n", + " else:\n", + " return None" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "game_state = INIT_GAME_STATE.copy()\n", + "start_game()" + ] + }, + { + "cell_type": "code", + "execution_count": 80, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "You wake up on a couch and find yourself in a strange house with no windows which you have never been to before.\n", + "You don't remember why you are here and what had happened before. You feel some unknown danger is approaching and you must get out of the house, NOW!\n", + "You are now in game room\n", + "What would you like to do? Type 'explore' or 'examine'? \n", + "\n" + ] + }, + { + "ename": "KeyboardInterrupt", + "evalue": "Interrupted by user", + "output_type": "error", + "traceback": [ + "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[1;31mKeyboardInterrupt\u001b[0m Traceback (most recent call last)", + "\u001b[1;32m\u001b[0m in \u001b[0;36m\u001b[1;34m\u001b[0m\n\u001b[0;32m 1\u001b[0m \u001b[0mgame_state\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mINIT_GAME_STATE\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mcopy\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 2\u001b[1;33m \u001b[0mstart_game\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m", + "\u001b[1;32m\u001b[0m in \u001b[0;36mstart_game\u001b[1;34m()\u001b[0m\n\u001b[0;32m 5\u001b[0m \u001b[0mprint\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m\"You wake up on a couch and find yourself in a strange house with no windows which you have never been to before.\"\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 6\u001b[0m \u001b[0mprint\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m\"You don't remember why you are here and what had happened before. You feel some unknown danger is approaching and you must get out of the house, NOW!\"\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 7\u001b[1;33m \u001b[0mplay_room\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mgame_state\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;34m\"current_room\"\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 8\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 9\u001b[0m \u001b[1;32mdef\u001b[0m \u001b[0mplay_room\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mroom\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n", + "\u001b[1;32m\u001b[0m in \u001b[0;36mplay_room\u001b[1;34m(room)\u001b[0m\n\u001b[0;32m 20\u001b[0m \u001b[0mprint\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m\"You are now in \"\u001b[0m \u001b[1;33m+\u001b[0m \u001b[0mroom\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;34m\"name\"\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 21\u001b[0m \u001b[0mprint\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m\"What would you like to do? Type 'explore' or 'examine'? \\n\"\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m---> 22\u001b[1;33m \u001b[0mintended_action\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0minput\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m\"\"\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mstrip\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mlower\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 23\u001b[0m \u001b[1;32mif\u001b[0m \u001b[0mintended_action\u001b[0m \u001b[1;33m==\u001b[0m \u001b[1;34m\"explore\"\u001b[0m\u001b[1;33m:\u001b[0m \u001b[1;31m### Here we should use the are_words_similar(s1,s2) function instead.\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 24\u001b[0m \u001b[0mexplore_room\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mroom\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n", + "\u001b[1;32mc:\\users\\eloi pc\\appdata\\local\\programs\\python\\python38-32\\lib\\site-packages\\ipykernel\\kernelbase.py\u001b[0m in \u001b[0;36mraw_input\u001b[1;34m(self, prompt)\u001b[0m\n\u001b[0;32m 858\u001b[0m \u001b[1;34m\"raw_input was called, but this frontend does not support input requests.\"\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 859\u001b[0m )\n\u001b[1;32m--> 860\u001b[1;33m return self._input_request(str(prompt),\n\u001b[0m\u001b[0;32m 861\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_parent_ident\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 862\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_parent_header\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n", + "\u001b[1;32mc:\\users\\eloi pc\\appdata\\local\\programs\\python\\python38-32\\lib\\site-packages\\ipykernel\\kernelbase.py\u001b[0m in \u001b[0;36m_input_request\u001b[1;34m(self, prompt, ident, parent, password)\u001b[0m\n\u001b[0;32m 902\u001b[0m \u001b[1;32mexcept\u001b[0m \u001b[0mKeyboardInterrupt\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 903\u001b[0m \u001b[1;31m# re-raise KeyboardInterrupt, to truncate traceback\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 904\u001b[1;33m \u001b[1;32mraise\u001b[0m \u001b[0mKeyboardInterrupt\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m\"Interrupted by user\"\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;32mfrom\u001b[0m \u001b[1;32mNone\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 905\u001b[0m \u001b[1;32mexcept\u001b[0m \u001b[0mException\u001b[0m \u001b[1;32mas\u001b[0m \u001b[0me\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 906\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mlog\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mwarning\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m\"Invalid Message:\"\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mexc_info\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;32mTrue\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n", + "\u001b[1;31mKeyboardInterrupt\u001b[0m: Interrupted by user" + ] + } + ], + "source": [ + "game_state = INIT_GAME_STATE.copy() \n", + "start_game()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "colab": { + "collapsed_sections": [], + "name": "Python Escape Room.ipynb", + "provenance": [] + }, + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.8.3" + } + }, + "nbformat": 4, + "nbformat_minor": 1 +} diff --git a/your-code/sample-code.ipynb b/your-code/sample-code.ipynb index a6f8a94d..bf62ae22 100644 --- a/your-code/sample-code.ipynb +++ b/your-code/sample-code.ipynb @@ -2,7 +2,7 @@ "cells": [ { "cell_type": "code", - "execution_count": 1, + "execution_count": 3, "metadata": {}, "outputs": [], "source": [ @@ -65,7 +65,7 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": 4, "metadata": {}, "outputs": [], "source": [ @@ -170,7 +170,7 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 5, "metadata": {}, "outputs": [ { @@ -179,34 +179,23 @@ "text": [ "You wake up on a couch and find yourself in a strange house with no windows which you have never been to before. You don't remember why you are here and what had happened before. You feel some unknown danger is approaching and you must get out of the house, NOW!\n", "You are now in game room\n", - "What would you like to do? Type 'explore' or 'examine'?explore\n", - "You explore the room. This is game room. You find couch, piano, door a\n", - "You are now in game room\n", - "What would you like to do? Type 'explore' or 'examine'?examine\n", - "What would you like to examine?door a\n", - "You examine door a. It is locked but you don't have the key.\n", - "You are now in game room\n", "What would you like to do? Type 'explore' or 'examine'?examine\n", - "What would you like to examine?piano\n", - "You examine piano. You find key for door a.\n", - "You are now in game room\n", - "What would you like to do? Type 'explore' or 'examine'?examine\n", - "What would you like to examine?door a\n", - "You examine door a. You unlock it with a key you have.\n", - "Do you want to go to the next room? Ener 'yes' or 'no'yes\n", - "Congrats! You escaped the room!\n", - "\n", - "\n", - "\n", - "\n", - "\n", - "\n", - "\n", - "\n", - "\n", - "\n", - "\n", - "\n" + "What would you like to examine?couch\n", + "You examine couch. There isn't anything interesting about it.\n" + ] + }, + { + "ename": "KeyError", + "evalue": "'couch'", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mKeyError\u001b[0m Traceback (most recent call last)", + "\u001b[0;32m\u001b[0m in \u001b[0;36m\u001b[0;34m\u001b[0m\n\u001b[1;32m 1\u001b[0m \u001b[0mgame_state\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mINIT_GAME_STATE\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcopy\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 2\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 3\u001b[0;31m \u001b[0mstart_game\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m", + "\u001b[0;32m\u001b[0m in \u001b[0;36mstart_game\u001b[0;34m()\u001b[0m\n\u001b[1;32m 10\u001b[0m \"\"\"\n\u001b[1;32m 11\u001b[0m \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"You wake up on a couch and find yourself in a strange house with no windows which you have never been to before. You don't remember why you are here and what had happened before. You feel some unknown danger is approaching and you must get out of the house, NOW!\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 12\u001b[0;31m \u001b[0mplay_room\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mgame_state\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m\"current_room\"\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 13\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 14\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0mplay_room\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mroom\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;32m\u001b[0m in \u001b[0;36mplay_room\u001b[0;34m(room)\u001b[0m\n\u001b[1;32m 28\u001b[0m \u001b[0mplay_room\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mroom\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 29\u001b[0m \u001b[0;32melif\u001b[0m \u001b[0mintended_action\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0;34m\"examine\"\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 30\u001b[0;31m \u001b[0mexamine_item\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0minput\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"What would you like to examine?\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mstrip\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 31\u001b[0m \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 32\u001b[0m \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"Not sure what you mean. Type 'explore' or 'examine'.\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;32m\u001b[0m in \u001b[0;36mexamine_item\u001b[0;34m(item_name)\u001b[0m\n\u001b[1;32m 87\u001b[0m \u001b[0moutput\u001b[0m \u001b[0;34m+=\u001b[0m \u001b[0;34m\"There isn't anything interesting about it.\"\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 88\u001b[0m \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0moutput\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 89\u001b[0;31m \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mlen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mobject_relations\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mitem\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m\"name\"\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m>\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 90\u001b[0m \u001b[0;32mbreak\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 91\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;31mKeyError\u001b[0m: 'couch'" ] } ], @@ -240,7 +229,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.7.2" + "version": "3.8.3" } }, "nbformat": 4, diff --git a/your-code/sounds_and_images/clogged_bathtub.wav b/your-code/sounds_and_images/clogged_bathtub.wav new file mode 100644 index 00000000..725f5b70 Binary files /dev/null and b/your-code/sounds_and_images/clogged_bathtub.wav differ diff --git a/your-code/sounds_and_images/door_creaking.wav b/your-code/sounds_and_images/door_creaking.wav new file mode 100644 index 00000000..972cc3b3 Binary files /dev/null and b/your-code/sounds_and_images/door_creaking.wav differ diff --git a/your-code/sounds_and_images/gulping_bottle.wav b/your-code/sounds_and_images/gulping_bottle.wav new file mode 100644 index 00000000..2a777f4e Binary files /dev/null and b/your-code/sounds_and_images/gulping_bottle.wav differ diff --git a/your-code/sounds_and_images/map_bathroom.png b/your-code/sounds_and_images/map_bathroom.png new file mode 100644 index 00000000..0115d683 Binary files /dev/null and b/your-code/sounds_and_images/map_bathroom.png differ diff --git a/your-code/sounds_and_images/map_corridor.png b/your-code/sounds_and_images/map_corridor.png new file mode 100644 index 00000000..71e8d5df Binary files /dev/null and b/your-code/sounds_and_images/map_corridor.png differ diff --git a/your-code/sounds_and_images/map_game_room.png b/your-code/sounds_and_images/map_game_room.png new file mode 100644 index 00000000..b5f9eed9 Binary files /dev/null and b/your-code/sounds_and_images/map_game_room.png differ diff --git a/your-code/sounds_and_images/map_kitchen.png b/your-code/sounds_and_images/map_kitchen.png new file mode 100644 index 00000000..0dd44910 Binary files /dev/null and b/your-code/sounds_and_images/map_kitchen.png differ diff --git a/your-code/sounds_and_images/map_living_room.png b/your-code/sounds_and_images/map_living_room.png new file mode 100644 index 00000000..cfa63d6c Binary files /dev/null and b/your-code/sounds_and_images/map_living_room.png differ diff --git a/your-code/sounds_and_images/opening_bottle.wav b/your-code/sounds_and_images/opening_bottle.wav new file mode 100644 index 00000000..3298dd39 Binary files /dev/null and b/your-code/sounds_and_images/opening_bottle.wav differ diff --git a/your-code/sounds_and_images/smashing_wood.wav b/your-code/sounds_and_images/smashing_wood.wav new file mode 100644 index 00000000..7f49e060 Binary files /dev/null and b/your-code/sounds_and_images/smashing_wood.wav differ diff --git a/your-code/sounds_and_images/victory.wav b/your-code/sounds_and_images/victory.wav new file mode 100644 index 00000000..f6664946 Binary files /dev/null and b/your-code/sounds_and_images/victory.wav differ