def check_materials(np):
#print('Plushie Tycoon: Checking on materials.')
np.get(path_materials)
material_prices = []
material_owned = []
buy_links = []
accessories_owned = defaultdict(int)
for cat in range(0, 4):
np.get(path_materials, f'Cat={cat}')
tbl = np.search(r"<table width='80%'.*?>(.*?)</table>")[1]
rows = lib.table_to_tuples(tbl, raw=True)
material_prices.append([amt(x) for x in rows[-1]])
if len(rows[-3]) > 1:
material_owned.append([amt(x) for x in rows[-3]])
else:
material_owned.append([0, 0, 0, 0])
links = []
for link_text in rows[1]:
links.append(re.search(r"onClick=buying\('(.*?)',", link_text)[1])
buy_links.append(links)
if cat == 2 and np.contains("table width='80%'"):
tbl2 = np.search(r"<table width='80%' .*?>(.*?)</table>")[1]
rows = lib.table_to_tuples(tbl2)[2:]
for s, quant, kind, _ in rows:
if quant:
accessories_owned[s] += amt(quant)
return material_prices, material_owned, accessories_owned, buy_links
def check_materials(np):
#print('Plushie Tycoon: Checking on materials.')
np.get(path_materials)
material_prices = []
material_owned = []
buy_links = []
accessories_owned = defaultdict(int)
for cat in range(0, 4):
np.get(path_materials, f'Cat={cat}')
tbl = np.search(r"<table width='80%'.*?>(.*?)</table>")[1]
rows = lib.table_to_tuples(tbl, raw=True)
material_prices.append([amt(x) for x in rows[-1]])
if len(rows[-3]) > 1:
material_owned.append([amt(x) for x in rows[-3]])
else:
material_owned.append([0, 0, 0, 0])
links = []
for link_text in rows[1]:
links.append(re.search(r"onClick=buying\('(.*?)',", link_text)[1])
buy_links.append(links)
if cat == 2 and np.contains("table width='80%'"):
tbl2 = np.search(r"<table width='80%' .*?>(.*?)</table>")[1]
rows = lib.table_to_tuples(tbl2)[2:]
for s, quant, kind, _ in rows:
if quant:
accessories_owned[s] += amt(quant)
return material_prices, material_owned, accessories_owned, buy_links
def check_store(np):
#print('Plushie Tycoon: Checking on store.')
species_stats = {}
np.get(path_store)
np.get(path_store, 'Cat=0', 'invent=2')
tbl = np.search(r"<table width='75%'.*?>(.*?)</table>")
inv = []
past_sales = []
if tbl:
tbl = tbl[1]
inv = lib.table_to_tuples(tbl)[1:]
plushies_to_sell = sum(int(x[1]) - int(x[4]) for x in inv)
jobs_to_sell = len(inv)
else:
plushies_to_sell = 0
jobs_to_sell = 0
print(
f'Plushie Tycoon: Store has {plushies_to_sell} plushies over {jobs_to_sell} jobs left to sell.'
)
np.get(path_store, 'Cat=0', 'invent=1')
tbl = np.search(r"<table width='75%'.*?>(.*?)</table>")
if tbl:
tbl = tbl[1]
past_sales = lib.table_to_tuples(tbl)[1:]
# TODO: Is inv in the correct order?
prices = defaultdict(list)
for row in past_sales + inv:
species = row[0]
price = int(row[2])
prices[species].append(price)
for species in prices.keys():
ps = prices[species]
n = len(ps)
last = ps[-1]
avg = sum(ps) / n
stdev = (sum((p - avg)**2 for p in ps) / n)**0.5
species_stats[species] = {
'n': n,
'last': last,
'min': min(ps),
'max': max(ps),
'avg': avg,
'med': ps[len(ps) // 2],
'stdev': stdev,
}
#np.get(path_store, 'Cat=2')
#size = int(np.search(r'You now have a size (\d+) store')[1])
return species_stats
def check_store(np):
#print('Plushie Tycoon: Checking on store.')
species_stats = {}
np.get(path_store)
np.get(path_store, 'Cat=0', 'invent=2')
tbl = np.search(r"<table width='75%'.*?>(.*?)</table>")
inv = []
past_sales = []
if tbl:
tbl = tbl[1]
inv = lib.table_to_tuples(tbl)[1:]
plushies_to_sell = sum(int(x[1]) - int(x[4]) for x in inv)
jobs_to_sell = len(inv)
else:
plushies_to_sell = 0
jobs_to_sell = 0
print(f'Plushie Tycoon: Store has {plushies_to_sell} plushies over {jobs_to_sell} jobs left to sell.')
np.get(path_store, 'Cat=0', 'invent=1')
tbl = np.search(r"<table width='75%'.*?>(.*?)</table>")
if tbl:
tbl = tbl[1]
past_sales = lib.table_to_tuples(tbl)[1:]
# TODO: Is inv in the correct order?
prices = defaultdict(list)
for row in past_sales + inv:
species = row[0]
price = int(row[2])
prices[species].append(price)
for species in prices.keys():
ps = prices[species]
n = len(ps)
last = ps[-1]
avg = sum(ps) / n
stdev = (sum((p - avg)**2 for p in ps) / n)**0.5
species_stats[species] = {
'n': n,
'last': last,
'min': min(ps),
'max': max(ps),
'avg': avg,
'med': ps[len(ps) // 2],
'stdev': stdev,
}
#np.get(path_store, 'Cat=2')
#size = int(np.search(r'You now have a size (\d+) store')[1])
return species_stats
def check_factory(np, hire=False):
# Check status of jobs.
# If less than 500 plushies remain, fire all workers.
# Else, hire up to 250 Trainees and 25 Managers.
#print('Plushie Tycoon: Checking on factory.')
np.get(path_factory, 'exist=1')
tbl = np.search(r"<table border='0' width='70%'.*?>(.*?)</table>")[1]
jobs = lib.table_to_tuples(tbl)[1:-1]
num_factory_jobs = len(jobs)
num_plushies = sum(int(total) - int(done) for pet, total, done in jobs)
print(
f'Plushie Tycoon: Factory has {num_plushies} plushies in {num_factory_jobs} jobs.'
)
if hire:
if num_plushies > 400 or num_factory_jobs >= 5:
np.get(path_factory, 'personnel=1')
if np.contains('many unemployed pets'):
# Use the default workforce
np.get(path_factory, 'set_def=2', 'personnel=1')
print('Plushie Tycoon: Hired the default workforce.')
# TODO: Calculate a good workforce and hire it.
#np.get(path_factory, 'personnel=2', 'hire=1')
#np.get(path_workers_hire, 'worker=2')
#np.post(path_process_hire, 'amt=250', 'worker=2')
#np.get(path_workers_hire, 'worker=4')
#np.post(path_process_hire, 'amt=10', 'worker=4')
#np.get(path_workers_hire, 'worker=4')
#np.post(path_process_hire, 'amt=10', 'worker=4')
#np.get(path_workers_hire, 'worker=4')
#np.post(path_process_hire, 'amt=4', 'worker=4')
#print('Plushie Tycoon: Hired up to 250 Trainees and 25 Managers.')
else:
print('Plushie Tycoon: Already have workers.')
else:
np.get(path_factory, 'personnel=1')
if np.contains('factory.phtml?personnel=2&fire=1'):
np.get(path_factory, 'personnel=2', 'fire=1')
if np.contains('fire_all=1'):
np.get(path_factory, 'fire_all=1')
print('Plushie Tycoon: Fired all workers.')
else:
print('Plushie Tycoon: Already fired all workers.')
return num_factory_jobs
def check_factory(np, hire=False):
# Check status of jobs.
# If less than 500 plushies remain, fire all workers.
# Else, hire up to 250 Trainees and 25 Managers.
#print('Plushie Tycoon: Checking on factory.')
np.get(path_factory, 'exist=1')
tbl = np.search(r"<table border='0' width='70%'.*?>(.*?)</table>")[1]
jobs = lib.table_to_tuples(tbl)[1:-1]
num_factory_jobs = len(jobs)
num_plushies = sum(int(total) - int(done) for pet, total, done in jobs)
print(f'Plushie Tycoon: Factory has {num_plushies} plushies in {num_factory_jobs} jobs.')
if hire:
if num_plushies > 400 or num_factory_jobs >= 5:
np.get(path_factory, 'personnel=1')
if np.contains('many unemployed pets'):
# Use the default workforce
np.get(path_factory, 'set_def=2', 'personnel=1')
print('Plushie Tycoon: Hired the default workforce.')
# TODO: Calculate a good workforce and hire it.
#np.get(path_factory, 'personnel=2', 'hire=1')
#np.get(path_workers_hire, 'worker=2')
#np.post(path_process_hire, 'amt=250', 'worker=2')
#np.get(path_workers_hire, 'worker=4')
#np.post(path_process_hire, 'amt=10', 'worker=4')
#np.get(path_workers_hire, 'worker=4')
#np.post(path_process_hire, 'amt=10', 'worker=4')
#np.get(path_workers_hire, 'worker=4')
#np.post(path_process_hire, 'amt=4', 'worker=4')
#print('Plushie Tycoon: Hired up to 250 Trainees and 25 Managers.')
else:
print('Plushie Tycoon: Already have workers.')
else:
np.get(path_factory, 'personnel=1')
if np.contains('factory.phtml?personnel=2&fire=1'):
np.get(path_factory, 'personnel=2', 'fire=1')
if np.contains('fire_all=1'):
np.get(path_factory, 'fire_all=1')
print('Plushie Tycoon: Fired all workers.')
else:
print('Plushie Tycoon: Already fired all workers.')
return num_factory_jobs
def check_warehouse(np):
#print('Plushie Tycoon: Checking on warehouse.')
np.get(path_warehouse)
tbl = np.search(r"<table border='0' width='90%'.*?>(.*?)</table>")[1]
to_ship = lib.table_to_tuples(tbl, raw=True)[2:-2]
if to_ship:
print(f'Plushie Tycoon: Warehouse is loading {len(to_ship)} jobs.')
args = []
for row in to_ship:
status = row[4]
if status == 'Loaded':
chkbox = row[5]
result = re.search(r"name='(.*?)' value='(.*?)'", chkbox)
name = result[1]
value = result[2]
args.append(f'{name}={value}')
if args:
# TODO: Only ship items to the store if it is advantageous.
# (tax situations?)
print(f'Plushie Tycoon: Shipping {len(args)} jobs to the store.')
args.append('submit=Ship Plushies')
np.post(path_warehouse, *args)
def check_warehouse(np):
#print('Plushie Tycoon: Checking on warehouse.')
np.get(path_warehouse)
tbl = np.search(r"<table border='0' width='90%'.*?>(.*?)</table>")[1]
to_ship = lib.table_to_tuples(tbl, raw=True)[2:-2]
if to_ship:
print(f'Plushie Tycoon: Warehouse is loading {len(to_ship)} jobs.')
args = []
for row in to_ship:
status = row[4]
if status == 'Loaded':
chkbox = row[5]
result = re.search(r"name='(.*?)' value='(.*?)'", chkbox)
name = result[1]
value = result[2]
args.append(f'{name}={value}')
if args:
# TODO: Only ship items to the store if it is advantageous.
# (tax situations?)
print(f'Plushie Tycoon: Shipping {len(args)} jobs to the store.')
args.append('submit=Ship Plushies')
np.post(path_warehouse, *args)
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 update_prices(item_name, laxness=5):
now = datetime.now()
if g.last_ban and (now - last_ban < timedelta(minutes=1) or (now - last_ban < timedelta(hours=1) and now.hour == last_ban.hour)):
print('Still wiz banned.')
raise ShopWizardBannedException
char_groups = 'an0 bo1 cp2 dq3 er4 fs5 gt6 hu7 iv8 jw9 kx_ ly mz'.split()
c2grp = dict(sum(([(c, i) for c in cs] for i, cs in enumerate(char_groups)), []))
obj_info_ids = set()
ub_count = 0
search_count = 0
lowest_price = UNBUYABLE_PRICE
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')
grps_needed = len(char_groups) - laxness
def print_status():
found = sum(min(grps_needed, len(g.markets[i])) for i in obj_info_ids)
total = len(obj_info_ids) * grps_needed
print(f'\r({item_name}: {lowest_price} NP; {found}/{total}; {search_count}) ', end='')
# Repeatedly search the shop wizard, collecting all results seen.
try:
while not obj_info_ids or any(len(g.markets[i]) < grps_needed for i in obj_info_ids):
print_status()
np.post('/market.phtml', *opts)
if np.contains('Whoa there, too many'):
print('Shop wizard banned.')
last_ban = datetime.now()
raise ShopWizardBannedException
search_count += 1
if not '<table width="600"' in np.content:
ub_count += 1
if ub_count >= 15: break
continue
tbl = np.search(r'<table width="600".*?>(.*?)</table>')
tbl = tbl[1]
rows = lib.table_to_tuples(tbl, raw=True)[1:]
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))
lowest_price = min(lowest_price, price)
obj_info_ids.add(obj_info_id)
grp = c2grp[lib.strip_tags(rows[0][0])[0]]
g.markets[obj_info_id][grp] = market_data
if search_count >= 30 * max(1, len(obj_info_ids)): break
except KeyboardInterrupt:
laxness = len(char_groups) - min(len(g.markets[i]) for i in obj_info_ids) if obj_info_ids else 0
print(f'Interrupted. Actual laxness is {laxness}')
print_status()
# Consolidate results for each item into a quote.
if obj_info_ids:
for obj_info_id in obj_info_ids:
level2 = sorted(sum(g.markets[obj_info_id].values(), []))
g.level2_cache[obj_info_id] = level2
cur_amt = 0
cur_price = 0
image, desc, name = None, None, None
# The price of an item for our purposes is the cheapest price such
# that:
# - it is the second cheapest price, OR
# - the next cheapest is at most 10% more expensive.
print()
if len(obj_info_ids) > 1:
print(f'({obj_info_id}):')
for price, stock, link in level2:
# Our own prices don't count for pricing purposes
if f'owner={os.environ.get("NP_USER")}' in link:
print('Skipping our own shop')
continue
np.get(link)
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'{link} is frozen?')
continue
image, desc, name = res[1], res[2], res[3]
print(f'{link} has {stock}')
if price < cur_price * 1.1:
break
cur_price = price
if stock >= 2:
break
cur_amt += stock
if cur_amt >= 2:
break
else:
print(f'Unable to find enough sellers for {obj_info_id}. Assuming unbuyable.')
cur_price = UNBUYABLE_PRICE
print(f'The price of {item_name} (id {obj_info_id}) is {cur_price} NP.')
for _ in range(2):
try:
update_item(name, image=image, desc=desc,
obj_info_id=obj_info_id, price=cur_price,
price_laxness=laxness)
break
except sqlite3.IntegrityError:
# TODO: IDK how we end up with bad obj_info_ids
c = conn.cursor()
c.execute('''DELETE FROM items WHERE obj_info_id = ?''', (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
# since we have no way to look up their image.
update_item(item_name, price=1000001, price_laxness=laxness)
conn.commit()