def jhudora_quest(): np = NeoPage(save_pages=True) np.get(path) if 'I Accept!' in np.content: # TODO: Search your SDB, gallery, shop, and Neohome Superstore for item as well. user = os.environ['NP_USER'] np.post(path_process, 'type=accept', f'username={user}') m = re.search( r"<br>Where is my <b>(.*?)</b>\?<p><img src='http://images.neopets.com/items/(.*?)'.*?>", np.content) item = m[1] image = m[2] print(f'Jhudora asked for {item} ({image})') cost = inventory.purchase(item, image=image) print(f'Bought it for {cost} NP.') np.set_referer_path(path) np.post(path_process, 'type=finished') if 'You have completed' in np.content: print(f'Quest shouuuuld be completed?') else: print(f"Quest doesn't seem to have completed") elif 'I am not ready' in np.content: print("Too early for Jhudora's Quest.") else: print("Jhudora's quest: Error!")
def goto_level(lvl): np = NeoPage() #np.set_referer_path(path_game) #np.post(path_process, 'type=reset_this_thing', 'username={os.environ["NP_USER"]}') #print(np.last_file_path) #if shapeshifter(timeout=0) == 2: # print('Shapeshifter: Already done.') # return np.set_referer_path(path_game) np.post(path_process + '?type=init', f'past_level={lvl}') print(np.last_file_path)
def goto_level(lvl): np = NeoPage() #np.set_referer_path(path_game) #np.post(path_process, 'type=reset_this_thing', 'username={os.environ["NP_USER"]}') #print(np.last_file_path) #if shapeshifter(timeout=0) == 2: # print('Shapeshifter: Already done.') # return np.set_referer_path(path_game) np.post(path_process + '?type=init', f'past_level={lvl}') print(np.last_file_path)
def jhudora_quest(): np = NeoPage(save_pages=True) np.get(path) if 'I Accept!' in np.content: # TODO: Search your SDB, gallery, shop, and Neohome Superstore for item as well. user = os.environ['NP_USER'] np.post(path_process, 'type=accept', f'username={user}') m = re.search(r"<br>Where is my <b>(.*?)</b>\?<p><img src='http://images.neopets.com/items/(.*?)'.*?>", np.content) item = m[1] image = m[2] print(f'Jhudora asked for {item} ({image})') cost = inventory.purchase(item, image=image) print(f'Bought it for {cost} NP.') np.set_referer_path(path) np.post(path_process, 'type=finished') if 'You have completed' in np.content: print(f'Quest shouuuuld be completed?') else: print(f"Quest doesn't seem to have completed") elif 'I am not ready' in np.content: print("Too early for Jhudora's Quest.") else: print("Jhudora's quest: Error!")
def shapeshifter(timeout=10 * 60): np = NeoPage() np.get(path_index) starting_np = np.current_np() if np.contains('Continue Game!'): np.get(path_game) elif np.contains('Start Game!'): np.post(path_process, f'type=init') # Just in case we won but left it in the completed state if np.contains('You Won!') or np.contains('You Lost!'): np.post(path_process + '?type=init') tbl = np.search(r'''<table border=1 bordercolor='gray'>(.*?)</table>''')[1] imgs = re.findall( r'''<img src='(.*?)' border=0 name='i_'>(<br><b><small>GOAL</small></b></td>)?''', tbl) imgs = imgs[:-1] N = len(imgs) goal_idx = next(i for i, (_, goal) in enumerate(imgs) if goal) to_idx = {img: i for i, (img, _) in enumerate(imgs)} tbl = np.search( r'''<table align=center cellpadding=0 cellspacing=0 border=0>(.*?)</table>''' )[1] goal_grid = [] for row in re.findall(r'''<tr>(.*?)</tr>''', tbl, flags=re.DOTALL): imgs = re.findall(r'''<img src='(.*?)' .*?>''', row) goal_row = [to_idx[img] for img in imgs] goal_grid.append(goal_row) tbl = np.search( r'''<center><b><big>ACTIVE SHAPE</big></b><p>(.*?)</table>\n''')[1] shape_grids = [] for shape_info in re.findall(r'''<table.*?>(.*?)</table>''', tbl): grid = [] for row_info in re.findall(r'''<tr>(.*?)</tr>''', shape_info): tiles = re.findall(r'''<td.*?>(.*?)</td>''', row_info) grid.append( [int('square.gif' in tile_info) for tile_info in tiles]) shape_grids.append(grid) # Compute kvho difficulty. R = len(goal_grid) C = len(goal_grid[0]) min_shifts_needed = R * C * (N - 1) - sum(map(sum, goal_grid)) shifts_available = sum( sum(sum(rows) for rows in grid) for grid in shape_grids) num_overshifts = shifts_available - min_shifts_needed num_flips = num_overshifts // N print(f'Puzzle permits {num_flips} flips ({num_overshifts} overshifts)') kvho_input = make_kvho_input(goal_grid, shape_grids, goal_idx) print(f'Waiting for kvho.') start_time = datetime.now() positions = [] try: proc = subprocess.run(['c/ss'], input=kvho_input, encoding='utf-8', capture_output=True, timeout=timeout) for line in proc.stdout.splitlines(): if 'x' in line and '=' in line: x = list( map( int, line.replace('x', ' ').replace('=', ' ').strip().split())) for c, r, _ in zip(x[::3], x[1::3], x[2::3]): positions.append((r, c)) print(f'Solution found in {datetime.now() - start_time}: {positions}') except subprocess.TimeoutExpired: print( f'Solution not found in time. Throwing this puzzle to get a new one.' ) for _ in shape_grids: positions.append((0, 0)) for i, (shape, (r, c)) in enumerate(zip(shape_grids, positions)): print(f'\rPlacing piece {i+1}/{len(positions)}', end='') np.set_referer_path(path_game) np.get(path_process, 'type=action', f'posx={c}', f'posy={r}') time.sleep(0.5) print() if np.contains('You Won!'): np.set_referer_path(path_game) np.post(path_process + '?type=init') ending_np = np.current_np() print(f'Done level, earned {ending_np - starting_np} NP') return 1 elif np.contains('reached your max neopoints'): print('Done for today.') return 2 else: print('Did not solve level??') return 0
def shapeshifter(timeout=10*60): np = NeoPage() np.get(path_index) starting_np = np.current_np() if np.contains('Continue Game!'): np.get(path_game) elif np.contains('Start Game!'): np.post(path_process, f'type=init') # Just in case we won but left it in the completed state if np.contains('You Won!') or np.contains('You Lost!'): np.post(path_process + '?type=init') tbl = np.search(r'''<table border=1 bordercolor='gray'>(.*?)</table>''')[1] imgs = re.findall(r'''<img src='(.*?)' border=0 name='i_'>(<br><b><small>GOAL</small></b></td>)?''', tbl) imgs = imgs[:-1] N = len(imgs) goal_idx = next(i for i, (_, goal) in enumerate(imgs) if goal) to_idx = {img: i for i, (img, _) in enumerate(imgs)} tbl = np.search(r'''<table align=center cellpadding=0 cellspacing=0 border=0>(.*?)</table>''')[1] goal_grid = [] for row in re.findall(r'''<tr>(.*?)</tr>''', tbl, flags=re.DOTALL): imgs = re.findall(r'''<img src='(.*?)' .*?>''', row) goal_row = [to_idx[img] for img in imgs] goal_grid.append(goal_row) tbl = np.search(r'''<center><b><big>ACTIVE SHAPE</big></b><p>(.*?)</table>\n''')[1] shape_grids = [] for shape_info in re.findall(r'''<table.*?>(.*?)</table>''', tbl): grid = [] for row_info in re.findall(r'''<tr>(.*?)</tr>''', shape_info): tiles = re.findall(r'''<td.*?>(.*?)</td>''', row_info) grid.append([int('square.gif' in tile_info) for tile_info in tiles]) shape_grids.append(grid) # Compute kvho difficulty. R = len(goal_grid) C = len(goal_grid[0]) min_shifts_needed = R * C * (N - 1) - sum(map(sum, goal_grid)) shifts_available = sum(sum(sum(rows) for rows in grid) for grid in shape_grids) num_overshifts = shifts_available - min_shifts_needed num_flips = num_overshifts // N print(f'Puzzle permits {num_flips} flips ({num_overshifts} overshifts)') kvho_input = make_kvho_input(goal_grid, shape_grids, goal_idx) print(f'Waiting for kvho.') start_time = datetime.now() positions = [] try: proc = subprocess.run(['c/ss'], input=kvho_input, encoding='utf-8', capture_output=True, timeout=timeout) for line in proc.stdout.splitlines(): if 'x' in line and '=' in line: x = list(map(int, line.replace('x', ' ').replace('=', ' ').strip().split())) for c, r, _ in zip(x[::3], x[1::3], x[2::3]): positions.append((r, c)) print(f'Solution found in {datetime.now() - start_time}: {positions}') except subprocess.TimeoutExpired: print(f'Solution not found in time. Throwing this puzzle to get a new one.') for _ in shape_grids: positions.append((0, 0)) for i, (shape, (r, c)) in enumerate(zip(shape_grids, positions)): print(f'\rPlacing piece {i+1}/{len(positions)}', end='') np.set_referer_path(path_game) np.get(path_process, 'type=action', f'posx={c}', f'posy={r}') time.sleep(0.5) print() if np.contains('You Won!'): np.set_referer_path(path_game) np.post(path_process + '?type=init') ending_np = np.current_np() print(f'Done level, earned {ending_np - starting_np} NP') return 1 elif np.contains('reached your max neopoints'): print('Done for today.') return 2 else: print('Did not solve level??') return 0
def battledome(forever=False): np = NeoPage(path) np.get(path_arena) neopoints_left = True prizes_left = True while prizes_left or forever: battle_id = None if np.contains('battleid:'): print('Battledome: Already in fight.') battle_id = np.search(r"battleid:'(\d+)',")[1] else: print('Battledome: Starting fight.') np.post(path_start_fight, 'type=2', f'pet={PET_NAME}', f'npcId={npc_id}', f'toughness={toughness}') battle = json.loads(np.content) if not battle['success']: print('Battledome: Error.') return battle_id = battle['battle']['id'] time.sleep(2) np.set_referer_path(path) np.get(path_arena) ts = int(time.time() * 1000) for step in itertools.count(): intro = 1 if step == 0 else 0 np.set_referer_path(path_arena) np.post(path_arena_ajax, f'battleid={battle_id}', f'step={step}', f'intro={intro}', 'status=1') resp = json.loads(np.content) abils = resp['p1']['abils'] chosen_abil = '' for abil in ['21', '2', '14', '17', '1']: if abil in abils and not abils[abil]['hasCooldown']: chosen_abil = abil break items = re.findall( r'<li><img.*?id="(\d+)".*?title="(.*?)".*?/></li>', resp['p1']['items']) item1id = items[0][0] item2id = items[1][0] opts = [] opts.append(f'p1s=') opts.append(f'eq1={item1id}') opts.append(f'eq2={item2id}') opts.append(f'p1a={chosen_abil}') opts.append(f'chat=') opts.append('action=attack') opts.append(f'ts={ts}') opts.append(f'battleid={battle_id}') opts.append(f'step={step}') opts.append(f'intro=0') opts.append('status=1') print( f'Battledome: Attacking with {items[0][1]} and {items[1][1]}') np.set_referer_path(path_arena) np.post(path_arena_ajax, *opts) resp = json.loads(np.content) if resp['battle']['prizes'] or 'prize_messages' in resp['battle']: prizes = ', '.join( x['name'] for x in resp['battle']['prizes']) or "nothing" print(f'Battledome: Won {prizes}') if 'prize_messages' in resp['battle']: prize_messages = resp['battle']['prize_messages'] if any('reached the item limit' in m for m in prize_messages): prizes_left = False if any('reached the NP limit' in m for m in prize_messages): neopoints_left = False print(f'Battledome: {prize_messages}') break # TODO: Detect defeat. elif step > 5: print( f'Battledome: Took more than 5 steps. Something went wrong.' )