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.'
)