def anchor_management():
np = NeoPage(path)
if np.contains('form-fire-cannon'):
action = np.search('<input name="action" type="hidden" value="(.*?)">')[1]
np.post(path, action=action)
if np.contains('prize-item-name'):
prize = np.search('<span class="prize-item-name">(.*?)</span>')[1]
print(f'Blasted krawken; got {prize}')
else:
print('Blasted krawken; got unknown prize')
elif np.contains('safe from sea monsters for one day'):
print('Already did anchor management.')
else:
print("Couldn't find anchor management.")
def anchor_management():
np = NeoPage(path)
if np.contains('form-fire-cannon'):
action = np.search(
'<input name="action" type="hidden" value="(.*?)">')[1]
np.post(path, action=action)
if np.contains('prize-item-name'):
prize = np.search('<span class="prize-item-name">(.*?)</span>')[1]
print(f'Blasted krawken; got {prize}')
else:
print('Blasted krawken; got unknown prize')
elif np.contains('safe from sea monsters for one day'):
print('Already did anchor management.')
else:
print("Couldn't find anchor management.")
def scorchy_slots():
np = NeoPage()
np.get(path)
_ref_ck = np.search(r"<input type='hidden' name='_ref_ck' value='(.*?)'>")[1]
np.post(path, f'_ref_ck={_ref_ck}', 'play=yes')
while True:
def bank_interest():
path = '/bank.phtml'
np = NeoPage(path)
if np.contains('You have already collected your interest today.'):
print('Already collected interest today.')
elif np.contains('Collect Interest ('):
amount = np.search(r'Collect Interest \((.*?)\)')[1]
print(f"Collecting {amount} interest.")
np.post('/process_bank.phtml', 'type=interest')
else:
print("Error collecting bank interest.")
def apple_bobbing():
np = NeoPage(path)
if np.contains('Give it a shot!'):
np.get(path, bobbing=1)
message = np.search("<div id='bob_middle'>(.*?)</div>")[1].strip()
message = strip_tags(message)
print(message)
elif np.contains('blind underneath this hat'):
print('Already apple bobbed today.')
else:
print("Couldn't find apple bobbing.")
def bank_interest():
path = '/bank.phtml'
np = NeoPage(path)
if np.contains('You have already collected your interest today.'):
print('Already collected interest today.')
elif np.contains('Collect Interest ('):
amount = np.search(r'Collect Interest \((.*?)\)')[1]
print(f"Collecting {amount} interest.")
np.post('/process_bank.phtml', 'type=interest')
else:
print("Error collecting bank interest.")
def apple_bobbing():
np = NeoPage(path)
if np.contains('Give it a shot!'):
np.get(path, bobbing=1)
message = np.search("<div id='bob_middle'>(.*?)</div>")[1].strip()
message = strip_tags(message)
print(message)
elif np.contains('blind underneath this hat'):
print('Already apple bobbed today.')
else:
print("Couldn't find apple bobbing.")
def stats():
np = NeoPage()
np.get(path)
tbl = np.search(r'<table align=center cellpadding=3 cellspacing=0 border=0>(.*?)</table>')[0]
rows = util.table_to_tuples(tbl)
freqs = {i: 0 for i in range(1, 31)}
for date, prize, winners, share, matches_needed, numbers in rows[1:]:
nums = map(int, numbers.split(','))
for n in nums:
freqs[n] += 1
for n, freq in sorted(freqs.items()):
print(f'{n}, {freq}')
def ensure_np(amount):
# Withdraws from the bank to get up at least [amount] NP.
np = NeoPage()
np.get('/bank.phtml')
if np.contains('Collect Interest ('):
bank_interest.bank_interest()
nps = np.search(
r'''<a id='npanchor' href="/inventory.phtml">(.*?)</a>''')[1]
nps = int(nps.replace(',', ''))
if nps >= amount: return
need = amount - nps
denom = 10**max(len(str(need)), len(str(amount)))
need = (need // denom + 1) * denom
np.post('/process_bank.phtml', 'type=withdraw', f'amount={need}')
print(f'Withdrawing {need} NP')
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 update_prices(item_name, laxness=1):
char_groups = 'an0 bo1 cp2 dq3 er4 fs5 gt6 hu7 iv8 jw9 kx_ ly mz'.split()
c2g = dict(sum(([(c, i) for c in cs] for i, cs in enumerate(char_groups)), []))
markets = defaultdict(dict)
ub_count = 0
search_count = 0
np = NeoPage('/market.phtml?type=wizard')
opts = []
opts.append('type=process_wizard')
opts.append('feedset=0')
opts.append(f'shopwizard={item_name}')
opts.append('table=shop')
opts.append('criteria=exact')
opts.append('min_price=0')
opts.append('max_price=999999')
# Repeatedly search the shop wizard, collecting all results seen.
while not markets or any(len(market_data) < len(char_groups) - laxness for market_data in markets.values()):
print(f'\r({sum(len(md) for md in markets.values())}/{len(markets) * len(char_groups)}) ', end='')
np.post('/market.phtml', *opts)
tbl = np.search(r'<table width="600".*?>(.*?)</table>')
if not tbl:
if np.contains('Whoa there, too many'):
print('Shop wizard banned.')
raise ShopWizardBannedException
ub_count += 1
if ub_count >= 5: break
continue
tbl = tbl[1]
rows = lib.table_to_tuples(tbl, raw=True)[1:]
search_count += 1
if search_count >= 50: break
market_data = []
obj_info_id = None
for owner, item, stock, price in rows:
result = re.search(r'<a href="(.*?)"><b>(.*?)</b></a>', owner)
link = result[1]
owner = result[2]
result = re.search(r'/browseshop.phtml\?owner=(.*?)&buy_obj_info_id=(.*?)&buy_cost_neopoints=(\d+)', link)
obj_info_id = int(result[2])
price = lib.amt(lib.strip_tags(price))
stock = lib.amt(stock)
market_data.append((price, stock, link))
g = c2g[lib.strip_tags(rows[0][0])[0]]
markets[obj_info_id][g] = market_data
level2_by_item = {}
# Consolidate results for each item into a quote.
if markets:
for obj_info_id, market_data in markets.items():
# TODO: Check suspiciously cheap prices to see if owners are frozen.
level2 = sorted(sum(market_data.values(), []))
level2_by_item[obj_info_id] = level2
# The price of an item for our purposes is the price of the 2nd
# cheapest item in the market.
cur_amt = 0
cur_price = UNBUYABLE_PRICE
for price, stock, link in level2:
cur_price = price
cur_amt += stock
if cur_amt >= 2:
break
print(f'The price of {item_name} (id {obj_info_id}) is {cur_price} NP.')
cur_amt = 0
for price, stock, link in level2:
cur_amt += stock
if cur_amt >= 30:
break
c = conn.cursor()
c.execute('''
SELECT name FROM items WHERE obj_info_id=?
''', (obj_info_id,))
result = c.fetchone()
if not result or result[0][0] != item_name:
for market_data in level2:
# Visit the shop and populate a bunch of fields
np.get(market_data[2])
res = np.search(r'''<A href=".*?" onClick=".*?"><img src="http://images.neopets.com/items/(.*?)" .*? title="(.*?)" border="1"></a> <br> <b>(.*?)</b>''')
if not res:
print(f'{market_data[2]} is froze?')
continue
image = res[1]
desc = res[2]
name = res[3]
c.execute('''
INSERT INTO items (name, image, desc, obj_info_id, last_updated)
VALUES (?, ?, ?, ?, datetime('now'))
ON CONFLICT (name, image)
DO UPDATE SET desc=?, obj_info_id=?, last_updated=datetime('now')
''', (name, image, desc, obj_info_id, desc, obj_info_id))
print(f'The object id of {name} is {obj_info_id}')
break
else:
print('Unable to find legit seller for {obj_info_id}. Will not store it in itemdb.')
continue
c.execute('''
UPDATE items SET price=?, price_last_updated=datetime('now') WHERE obj_info_id=?
''', (cur_price, obj_info_id))
else:
print(f'It seems {item_name} is unbuyable.')
# Item could not be found; assume it's unbuyable.
# We use a cheap price estimate of 1,000,001 NP.
# TODO: Items inserted in this way will have a wonky image property.
c = conn.cursor()
c.execute('''
INSERT INTO items (name, image, last_updated, price, price_last_updated)
VALUES (?, NULL, datetime('now'), 1000001, datetime('now'))
ON CONFLICT (name, image)
DO UPDATE SET last_updated=datetime('now'), price=1000001, price_last_updated=datetime('now')
''', (item_name,))
conn.commit()
return level2_by_item
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.'
)
def food_club():
np = NeoPage()
np.get(path, 'type=bet')
if np.contains('All betting gates are now closed!'):
print(f"Dangit, we're late.")
return
maxbet = util.amt(
re.search(r'You can only place up to <b>(.*?)</b> NeoPoints per bet',
np.content)[1])
print(f'Max bet is {maxbet}')
# We compute the current round number because it seems there's no way to
# find it explicitly unless you actually make a bet.
day = int(
re.search(
r'Next match: <b>.*?</b> the <b>(\d+).*?</b> at <b>02:00 PM NST</b>',
np.content)[1])
date = neotime.now_nst().replace(day=day, hour=14, minute=0, second=0)
epoch = datetime(2018, 10, 7, 14, 0, 0)
from_epoch = round((date - epoch) / timedelta(days=1))
cur_round = 7093 + from_epoch
print(f'Food Club round {cur_round}')
dl_fc_history(cur_round - 1, cur_round)
table = stats()
rnd = get_rounds(table[table['round'] == cur_round])[0]
for i, arena in enumerate(arena_names):
participants = ', '.join(pirate_names[p.pirate]
for p in rnd.pirates[i])
print(f'{arena} Arena: {participants}')
bets = maxter_strategy(rnd, 1000000 / maxbet)
total_bet_amt = 0
total_exp_win = 0
TER = 0
for exp_win, spend, bet in bets:
if exp_win < 1.0:
print('Not making -EV bet: {bet}')
continue
bet_amt = round(spend * maxbet)
print(f'Bet {bet_amt} NP on {bet}. EV: {exp_win * bet_amt:.1f} NP')
opts = []
total_odds = 1
for i, (ps, b) in enumerate(zip(rnd.pirates, bet)):
if b == None:
continue
ps[b].pirate
opts.append(f'winner{i+1}={ps[b].pirate}')
opts.append(f'matches[]={i+1}')
total_odds *= ps[b].closing_odds
opts.append(f'bet_amount={bet_amt}')
opts.append(f'total_odds={total_odds}')
opts.append(f'winnings={bet_amt * total_odds}')
opts.append('type=bet')
np.post('/pirates/process_foodclub.phtml', *opts)
total_bet_amt += bet_amt
total_exp_win += bet_amt * exp_win
TER += exp_win
print(
f'Made {total_bet_amt} NP of bets. Expect to win {total_exp_win:.1f} NP. (TER {TER:.2f}; ROI {total_exp_win / total_bet_amt:.3f})'
)
np.get('/pirates/foodclub.phtml', 'type=collect')
if np.contains("<input type='submit' value='Collect Your Winnings!'>"):
tbl = np.search(r"<table border='0' .*?>(.*?)</table>")[1]
tuples = util.table_to_tuples(tbl)
earliest_rnd = int(tuples[2][0])
total_winnings = tuples[-1][-1]
print(
f'Note: We have {total_winnings} winnings dating from round {earliest_rnd}.'
)
if cur_round - earliest_rnd >= 7:
print(f'Should collect winnings before they vanish!')
def food_club():
np = NeoPage()
np.get(path, 'type=bet')
if np.contains('All betting gates are now closed!'):
print(f"Dangit, we're late.")
return
maxbet = util.amt(re.search(r'You can only place up to <b>(.*?)</b> NeoPoints per bet', np.content)[1])
print(f'Max bet is {maxbet}')
# We compute the current round number because it seems there's no way to
# find it explicitly unless you actually make a bet.
day = int(re.search(r'Next match: <b>.*?</b> the <b>(\d+).*?</b> at <b>02:00 PM NST</b>', np.content)[1])
date = neotime.now_nst().replace(day=day, hour=14, minute=0, second=0)
epoch = datetime(2018, 10, 7, 14, 0, 0)
from_epoch = round((date - epoch) / timedelta(days=1))
cur_round = 7093 + from_epoch
print(f'Food Club round {cur_round}')
dl_fc_history(cur_round - 1, cur_round)
table = stats()
rnd = get_rounds(table[table['round'] == cur_round])[0]
for i, arena in enumerate(arena_names):
participants = ', '.join(pirate_names[p.pirate] for p in rnd.pirates[i])
print(f'{arena} Arena: {participants}')
bets = maxter_strategy(rnd, 1000000 / maxbet)
total_bet_amt = 0
total_exp_win = 0
TER = 0
for exp_win, spend, bet in bets:
if exp_win < 1.0:
print('Not making -EV bet: {bet}')
continue
bet_amt = round(spend * maxbet)
print(f'Bet {bet_amt} NP on {bet}. EV: {exp_win * bet_amt:.1f} NP')
opts = []
total_odds = 1
for i, (ps, b) in enumerate(zip(rnd.pirates, bet)):
if b == None:
continue
ps[b].pirate
opts.append(f'winner{i+1}={ps[b].pirate}')
opts.append(f'matches[]={i+1}')
total_odds *= ps[b].closing_odds
opts.append(f'bet_amount={bet_amt}')
opts.append(f'total_odds={total_odds}')
opts.append(f'winnings={bet_amt * total_odds}')
opts.append('type=bet')
np.post('/pirates/process_foodclub.phtml', *opts)
total_bet_amt += bet_amt
total_exp_win += bet_amt * exp_win
TER += exp_win
print(f'Made {total_bet_amt} NP of bets. Expect to win {total_exp_win:.1f} NP. (TER {TER:.2f}; ROI {total_exp_win / total_bet_amt:.3f})')
np.get('/pirates/foodclub.phtml', 'type=collect')
if np.contains("<input type='submit' value='Collect Your Winnings!'>"):
tbl = np.search(r"<table border='0' .*?>(.*?)</table>")[1]
tuples = util.table_to_tuples(tbl)
earliest_rnd = int(tuples[2][0])
total_winnings = tuples[-1][-1]
print(f'Note: We have {total_winnings} winnings dating from round {earliest_rnd}.')
if cur_round - earliest_rnd >= 7:
print(f'Should collect winnings before they vanish!')