def purchase(item, image=None, budget=None, quantity=1, **kwargs):
# Buys a quantity of items from user shops, sticking within a budget.
# Returns actual amount spent, or None if not successful.
market = next(iter(item_db.get_market(item, image, **kwargs).values()))
true_cost = 0
qty_left = quantity
buy_nps = []
for price, stock, link in market:
np2 = NeoPage()
np2.get(link)
buy_link, image, item, in_stock, cost = shop_item_re.search(np2.content).groups()
in_stock = util.amt(in_stock)
cost = util.amt(cost)
if cost <= price:
to_buy = min(in_stock, qty_left)
true_cost += cost * to_buy
qty_left -= to_buy
buy_nps.append((np2, buy_link, to_buy))
if qty_left <= 0:
break
if budget != None and true_cost > budget:
return None
ensure_np(true_cost)
for np2, buy_link, to_buy in buy_nps:
referer = np2.referer
for _ in range(to_buy):
print(f'Buying {item} from {buy_link}')
np2.set_referer(referer)
np2.get(f'/{buy_link}')
return true_cost
def clean_shop_till():
log = open(SALES_LOG_FILE, 'a')
np = NeoPage()
np.get('/market.phtml', 'type=sales')
referer = np.referer
if 'Nobody has bought anything' in np.content:
print('No new sales.')
else:
tbl = re.search(
'''<table align=center width=530 cellpadding=3 cellspacing=0>(.*?)</table>''',
np.content)[1]
rows = util.table_to_tuples(tbl)
total_sales = 0
for date, item, buyer, price in rows[1:-1]:
price = util.amt(price)
print(f'{date}: {buyer} bought {item} for {price} NP')
log.write(f'{date},{buyer},{item},{price}\n')
total_sales += price
print(f'Total sales cleared: {total_sales} NP')
print(f'Saved to {SALES_LOG_FILE}. Clearing history.')
np.post('/market.phtml', 'type=sales', 'clearhistory=true')
np.set_referer(referer)
np.get('/market.phtml', 'type=till')
amt = util.amt(
re.search(r'''You currently have <b>(.*?)</b> in your till.''',
np.content)[1])
if amt:
print(f'Withdrawing {amt} NP from shop till.')
np.post('/process_market.phtml', 'type=withdraw', f'amount={amt}')
else:
print(f'Shop till is empty.')
def clean_shop_till():
log = open(SALES_LOG_FILE, 'a')
np = NeoPage()
np.get('/market.phtml', 'type=sales')
referer = np.referer
if 'Nobody has bought anything' in np.content:
print('No new sales.')
else:
tbl = re.search('''<table align=center width=530 cellpadding=3 cellspacing=0>(.*?)</table>''', np.content)[1]
rows = util.table_to_tuples(tbl)
total_sales = 0
for date, item, buyer, price in rows[1:-1]:
price = util.amt(price)
print(f'{date}: {buyer} bought {item} for {price} NP')
log.write(f'{date},{buyer},{item},{price}\n')
total_sales += price
print(f'Total sales cleared: {total_sales} NP')
print(f'Saved to {SALES_LOG_FILE}. Clearing history.')
np.post('/market.phtml', 'type=sales', 'clearhistory=true')
np.set_referer(referer)
np.get('/market.phtml', 'type=till')
amt = util.amt(re.search(r'''You currently have <b>(.*?)</b> in your till.''', np.content)[1])
if amt:
print(f'Withdrawing {amt} NP from shop till.')
np.post('/process_market.phtml', 'type=withdraw', f'amount={amt}')
else:
print(f'Shop till is empty.')
def purchase(item, image=None, budget=None, quantity=1, **kwargs):
# Buys a quantity of items from user shops, sticking within a budget.
# Returns actual amount spent, or None if not successful.
market = next(iter(item_db.get_market(item, image, **kwargs).values()))
true_cost = 0
qty_left = quantity
buy_nps = []
for price, stock, link in market:
np2 = NeoPage()
np2.get(link)
buy_link, image, item, in_stock, cost = shop_item_re.search(
np2.content).groups()
in_stock = util.amt(in_stock)
cost = util.amt(cost)
if cost <= price:
to_buy = min(in_stock, qty_left)
true_cost += cost * to_buy
qty_left -= to_buy
buy_nps.append((np2, buy_link, to_buy))
if qty_left <= 0:
break
if budget != None and true_cost > budget:
return None
ensure_np(true_cost)
for np2, buy_link, to_buy in buy_nps:
referer = np2.referer
for _ in range(to_buy):
print(f'Buying {item} from {buy_link}')
np2.set_referer(referer)
np2.get(f'/{buy_link}')
return true_cost
def faerieland_jobs(jobs_to_do):
np = NeoPage()
np.get(path, 'type=jobs', 'voucher=basic')
start = 0
jobs_by_profit = []
try:
while jobs_to_do > 0:
jobs = job_re.findall(np.content)
has_more_pages = bool(re.search('<A HREF="employment.phtml.*?">Next 10</A>', np.content))
for image, job_link, count, name, prize in jobs:
count = int(count)
prize = util.amt(prize)
revenue = prize * 1.25
if revenue < MIN_PROFIT:
print(f'Skipping {name} (can only make {revenue})')
continue
price = item_db.get_price(name, image)
profit = revenue - count * price
print(f'Can profit by about {profit} NP: Buy {count}x {name} ({price} NP each), turn in for {revenue}')
bisect.insort(jobs_by_profit, (profit, name, count, job_link))
if profit < MIN_PROFIT:
continue
print('Taking the job!')
true_cost = inventory.purchase(name, image=image, budget=revenue - MIN_PROFIT, quantity=count)
if not true_cost:
print(f'Failed to acquire all the items within budget')
continue
# Do the job!
np.get(f'/faerieland/employ/{job_link}')
if 'Good job! You got all the items' in np.content:
prize = re.search(r'You have been paid <b>(.*?) Neopoints</b>.', np.content)[1]
prize = util.amt(prize)
print(f'Turned in {count}x {name} for {prize} NP. (Profit: {prize - true_cost})')
elif 'You got the job!' in np.content:
print(f'Job was not completed before applying? TODO')
print(np.last_file_path)
return
else:
print(f'Error applying for job. TODO')
print(np.last_file_path)
return
jobs_to_do -= 1
if jobs_to_do <= 0:
return
if has_more_pages:
start += 10
np.get(path, 'type=jobs', 'voucher=basic', f'start={start}')
else:
break
except item_db.ShopWizardBannedException:
return
print(jobs_by_profit)
print('Did not find enough appropriate jobs.')
def faerieland_jobs(jobs_to_do):
np = NeoPage()
np.get(path, 'type=jobs', 'voucher=basic')
start = 0
jobs_by_profit = []
try:
while jobs_to_do > 0:
jobs = job_re.findall(np.content)
has_more_pages = bool(
re.search('<A HREF="employment.phtml.*?">Next 10</A>',
np.content))
for image, job_link, count, name, prize in jobs:
count = int(count)
prize = util.amt(prize)
revenue = prize * 1.25
if revenue < MIN_PROFIT:
print(f'Skipping {name} (can only make {revenue})')
continue
price = item_db.get_price(name, image)
profit = revenue - count * price
print(
f'Can profit by about {profit} NP: Buy {count}x {name} ({price} NP each), turn in for {revenue}'
)
bisect.insort(jobs_by_profit, (profit, name, count, job_link))
if profit < MIN_PROFIT:
continue
print('Taking the job!')
true_cost = inventory.purchase(name,
image=image,
budget=revenue - MIN_PROFIT,
quantity=count)
if not true_cost:
print(f'Failed to acquire all the items within budget')
continue
# Do the job!
np.get(f'/faerieland/employ/{job_link}')
if 'Good job! You got all the items' in np.content:
prize = re.search(
r'You have been paid <b>(.*?) Neopoints</b>.',
np.content)[1]
prize = util.amt(prize)
print(
f'Turned in {count}x {name} for {prize} NP. (Profit: {prize - true_cost})'
)
elif 'You got the job!' in np.content:
print(f'Job was not completed before applying? TODO')
print(np.last_file_path)
return
else:
print(f'Error applying for job. TODO')
print(np.last_file_path)
return
jobs_to_do -= 1
if jobs_to_do <= 0:
return
if has_more_pages:
start += 10
np.get(path, 'type=jobs', 'voucher=basic', f'start={start}')
else:
break
except item_db.ShopWizardBannedException:
return
print(jobs_by_profit)
print('Did not find enough appropriate jobs.')
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!')
def fetch(verbose=False):
log = open('fetch.log', 'a')
np = NeoPage()
# TODO: Figure out how to continue on from existing game.
np.get(path, 'deletegame=1')
# Start new game.
UNKNOWN_COST = random.choice([1,2,3,4,5])
diffs = re.findall(r'<A HREF="maze.phtml\?create=1&diff=(\d+)">', np.content)
diff = '4' if '4' in diffs else '3'
np.get(path, 'create=1', f'diff={diff}')
maze_size = maze_sizes[diff]
goal_item_img, goal_item = re.search(r'<IMG SRC="http://images.neopets.com/games/maze/(item_.*?)" WIDTH="80" HEIGHT="80"><br><b>(.*?)</b>', np.content).group(1, 2)
print(f'Asked to find {goal_item} (img: {goal_item_img})')
np.post(path)
# State for a single game.
maze = {}
x_start = 0
y_start = 0
x_cur = x_start
y_cur = y_start
x_lower = -maze_size + 1
x_upper = maze_size - 1
y_lower = -maze_size + 1
y_upper = maze_size - 1
xy_item = None
xy_exit = None
while True:
# Check end conditions.
if np.contains('Success! You fetched the item and reached the exit!'):
prize = util.amt(re.search(r'You have been awarded <b>(.*?)</b> for your efforts!', np.content)[1])
print(f'Won! Got {prize} NP')
if np.contains('You have achieved a streak'):
streak, cumul = re.search(r'You have achieved a streak of <b>(.*?)</b> victories, for a running total of <b>(.*?)</b> points', np.content).group(1, 2)
print(f'Streak is {streak}, total score {cumul}')
# Don't get too high of a score!
if int(cumul) > 0:
np.get(path, 'deletegame=1')
np.get(path, 'create=1', 'diff=1')
else:
streak = 1
cumul = prize
log.write(f'{diff},{UNKNOWN_COST},1,{prize},{streak},{cumul}\n')
return (prize, streak, cumul)
elif np.contains("Your master is very displeased!"):
print(f'Ran out of time! :(')
log.write(f'{diff},{UNKNOWN_COST},0,0,0,0\n')
return
moves_remaining = int(re.search(r'Moves Remaining: <b>(.*?)</b>', np.content)[1].split()[0])
# Update knowledge.
tbl = re.search(r'<TABLE BORDER="0" CELLPADDING="0" CELLSPACING="0" WIDTH="400">(.*?)</TABLE>', np.content, flags=re.DOTALL)[1]
tiles = re.findall(r'<TD BACKGROUND="http://images.neopets.com/games/maze/(.*?).gif" WIDTH="80" HEIGHT="80".*?>(.*?)</TD>', tbl)
for jitter_x, jitter_y in [(0, 0), (1, 0), (-1, 0), (0, 1), (0, -1)]:
tiles_iter = iter(tiles)
good = True
for dy in range(-2, 3):
for dx in range(-2, 3):
img, content = next(tiles_iter)
x = x_cur + jitter_x + dx
y = y_cur + jitter_y + dy
if (x, y) in maze and maze[x, y] != img_to_dirs[img]:
good = False
if good:
x_cur += jitter_x
y_cur += jitter_y
break
tiles_iter = iter(tiles)
for dy in range(-2, 3):
for dx in range(-2, 3):
img, content = next(tiles_iter)
x = x_cur + dx
y = y_cur + dy
dirs = img_to_dirs[img]
maze[x, y] = dirs
if 'http://images.neopets.com/games/maze/item_' in content:
xy_item = (x, y)
# Update knowledge of bounds
if dirs == 0:
if dx == 0:
if dy < 0:
y_lower = max(y_lower, y_cur + dy + 1)
y_upper = y_lower + maze_size - 1
elif dy > 0:
y_upper = min(y_upper, y_cur + dy - 1)
y_lower = y_upper - maze_size + 1
if dy == 0:
if dx < 0:
x_lower = max(x_lower, x_cur + dx + 1)
x_upper = x_lower + maze_size - 1
elif dx > 0:
x_upper = min(x_upper, x_cur + dx - 1)
x_lower = x_upper - maze_size + 1
# Path leading out of bounds indicates an exit
if x_lower <= x <= x_upper and y_lower <= y <= y_upper:
for d in DIRS:
ddx, ddy = dir_to_delta[d]
if dirs & d and not (x_lower <= x + ddx <= x_upper and y_lower <= y + ddy <= y_upper):
xy_exit = (x, y)
# Compute the goals.
got_item = not np.contains('Searching for:')
goals = []
if got_item:
# Find the exit!!
if xy_exit:
goals = [xy_exit]
else:
# All points on any side opposite the side you started on.
candidates = []
if x_lower == 0: candidates.extend((x_upper, y) for y in range(y_lower, y_upper + 1))
if x_upper == 0: candidates.extend((x_lower, y) for y in range(y_lower, y_upper + 1))
if y_lower == 0: candidates.extend((x, y_upper) for x in range(x_lower, x_upper + 1))
if y_upper == 0: candidates.extend((x, y_lower) for x in range(x_lower, x_upper + 1))
# ... that has not been a confirmed dud
goals = []
for x, y in candidates:
good = False
for d in DIRS:
dx, dy = dir_to_delta[d]
if not (x_lower <= x + dx <= x_upper and y_lower <= y + dy <= y_upper) and (maze.get((x, y), -1) & d) and (maze.get((x + dx, y + dy), -1) & opp_dir[d]):
good = True
break
if good:
goals.append((x, y))
else:
if xy_item:
goals = [xy_item]
else:
# Possibilities for item location.
padding = maze_size // 2 - 1
goals = [(x, y)
for x in range(x_lower + padding, x_upper - padding + 1)
for y in range(y_lower + padding, y_upper - padding + 1)
if (x, y) not in maze]
# Dijkstra's to figure out how to best reach a goal.
# Distance is (# ? tiles, # known steps).
prevs = {}
Q = [(0, (x_cur, y_cur), None)]
reached_goal = None
while Q:
c, (x, y), prev = heapq.heappop(Q)
if (x, y) in prevs: continue
if (x, y) not in maze and not (x_lower <= x <= x_upper and y_lower <= y <= y_upper): continue
prevs[x, y] = prev
if (x, y) in goals:
reached_goal = (x, y)
break
dirs = maze.get((x, y), -1)
c_ = c + (UNKNOWN_COST if dirs == -1 else 1)
for d in DIRS:
dx, dy = dir_to_delta[d]
dirs_ = maze.get((x + dx, y + dy), -1)
if dirs & d and dirs_ & opp_dir[d]:
heapq.heappush(Q, (c_, (x + dx, y + dy), (x, y)))
if not reached_goal:
print(f'Ended up in a bad aimless state.')
log.write(f'{diff},{UNKNOWN_COST},0,0,0,0,ERROR\n')
return
# Backtrace route to find which direction to walk in.
cur = reached_goal
route = []
while cur:
route.append(cur)
cur = prevs[cur]
route = route[::-1]
x_nxt, y_nxt = route[1]
dxdy = (x_nxt - x_cur, y_nxt - y_cur)
movedir = None
if dxdy == (-1, 0): movedir = 2
elif dxdy == (1, 0): movedir = 3
elif dxdy == (0, -1): movedir = 0
elif dxdy == (0, 1): movedir = 1
# Print the maze.
movechar = "↑↓←→"[movedir]
if verbose:
coords = list(maze.keys()) + goals
min_x = max(x_lower - 2, min(xs(coords)))
max_x = min(x_upper + 2, max(xs(coords)))
min_y = max(y_lower - 2, min(ys(coords)))
max_y = min(y_upper + 2, max(ys(coords)))
for y in range(min_y - 1, max_y + 2):
for x in range(min_x - 1, max_x + 2):
c = dirs_to_unicode[maze.get((x, y), -1)]
if (x, y) == (x_cur, y_cur):
c = '@'
if (x, y) in goals:
c = C_YELLOW + c + C_ENDC
elif (x, y) in route:
c = (C_GREEN if got_item else C_RED) + c + C_ENDC
elif abs(x - x_cur) <= 2 and abs(y - y_cur) <= 2:
c = C_CYAN + c + C_ENDC
if c == '?':
c = C_GREY + c + C_ENDC
print(c, end='')
print()
print(f'Moves left: {moves_remaining}')
print(f'Min distance to goal: {len(route)}')
print(f'Moving {movechar}')
print()
else:
print(f'\r[{moves_remaining} {movechar}] ', end='')
if len(route) > moves_remaining:
print(f'No hope of winning. Giving up.')
log.write(f'{diff},{UNKNOWN_COST},0,0,0,0\n')
return
s = re.search(r'<AREA SHAPE="poly" COORDS="57,57,57,0,91,0,91,57" HREF="maze.phtml\?action=move&movedir=0&s=(\d+)"', np.content)[1]
np.get(path, 'action=move', f'movedir={movedir}', f's={s}')
x_cur, y_cur = x_nxt, y_nxt