def test_stats(self):
for size in SIZES:
l = LRU(size)
for i in range(size):
l[i] = str(i)
self.assertTrue(l.get_stats() == (0, 0))
val = l[0]
self.assertTrue(l.get_stats() == (1, 0))
val = l.get(0, None)
self.assertTrue(l.get_stats() == (2, 0))
val = l.get(-1, None)
self.assertTrue(l.get_stats() == (2, 1))
try:
val = l[-1]
except:
pass
self.assertTrue(l.get_stats() == (2, 2))
l.clear()
self.assertTrue(len(l) == 0)
self.assertTrue(l.get_stats() == (0, 0))
class AnnoyanceFilters(commands.Cog):
""" Filter out content which is poorly behaved on Discord """
def __init__(self, bot):
self.bot = bot
self._settings_cache = LRU(1024)
def get_guild_settings(self, guild_id: int) -> GuildSettings:
if r := self._settings_cache.get(guild_id, None):
return r
cursor = self.bot._conn.cursor()
res = cursor.execute(
"""
SELECT mods_immune, admins_immune, remove_apngs, remove_excessive_html_elements
FROM annoyance_filters
WHERE guild_id = ?
""",
(guild_id, ),
).fetchone()
cursor.close()
self._settings_cache[guild_id] = settings = (GuildSettings(
*res) if res else GuildSettings())
return settings
def test_stats(self):
for size in SIZES:
l = LRU(size)
for i in range(size):
l[i] = str(i)
self.assertTrue(l.get_stats() == (0, 0))
val = l[0]
self.assertTrue(l.get_stats() == (1, 0))
val = l.get(0, None)
self.assertTrue(l.get_stats() == (2, 0))
val = l.get(-1, None)
self.assertTrue(l.get_stats() == (2, 1))
try:
val = l[-1]
except:
pass
self.assertTrue(l.get_stats() == (2, 2))
l.clear()
self.assertTrue(len(l) == 0)
self.assertTrue(l.get_stats() == (0, 0))
def test_hits(self):
for size in SIZES:
l = LRU(size)
for i in range(size):
l[i] = str(i)
val = l[0]
self.assertTrue(l.get_hits() == 1)
self.assertTrue(l.get_misses() == 0)
val = l.get(0, None)
self.assertTrue(l.get_hits() == 2)
self.assertTrue(l.get_misses() == 0)
val = l.get(-1, None)
self.assertTrue(l.get_hits() == 2)
self.assertTrue(l.get_misses() == 1)
try:
val = l[-1]
except:
pass
self.assertTrue(l.get_hits() == 2)
self.assertTrue(l.get_misses() == 2)
l.clear()
self.assertTrue(len(l) == 0)
self.assertTrue(l.get_hits() == 0)
self.assertTrue(l.get_misses() == 0)
def testLRU():
print ('######### LRU ########\n')
lru = LRU(5)
for i in range(8):
lru.put(str(i), i)
if i == 5:
lru.get(str(i))
lru.remove('3')
lru.showNodes()
def test_get_and_del(self):
l = LRU(2)
l[1] = '1'
self.assertEqual('1', l.get(1))
self.assertEqual('1', l.get(2, '1'))
self.assertIsNone(l.get(2))
self.assertEqual('1', l[1])
self.assertRaises(KeyError, lambda: l['2'])
with self.assertRaises(KeyError):
del l['2']
def test_get_and_del(self):
l = LRU(2)
l[1] = "1"
self.assertEqual("1", l.get(1))
self.assertEqual("1", l.get(2, "1"))
self.assertIsNone(l.get(2))
self.assertEqual("1", l[1])
self.assertRaises(KeyError, lambda: l["2"])
with self.assertRaises(KeyError):
del l["2"]
def test_get_and_del(self):
l = LRU(2)
l[1] = '1'
self.assertEqual('1', l.get(1))
self.assertEqual('1', l.get(2, '1'))
self.assertIsNone(l.get(2))
self.assertEqual('1', l[1])
self.assertRaises(KeyError, lambda: l['2'])
with self.assertRaises(KeyError):
del l['2']
class topic4:
def __init__(self, c_hash, c_user, c_words):
self.topic_count =1
self.l1 = LRU(c_hash)
self.l2 = LRU(c_user)
def set_hashLRU(self,l):
self.set(self.l1, l)
def set_userLRU(self,l):
self.set(self.l2, l)
def set(self, lru, l):
for k in l:
v = lru.get(k,0)
lru[k]=v+1
def set_cluster(self, hashtags, users, words):
for k in hashtags:
self.l1[k]=self.l1.get(k,0)+1
for k in users:
self.l2[k]=self.l2.get(k,0)+1
self.topic_count+=1
def get_similarity(self,hashtags,users,words):
h_sum = 1
u_sum = 1
w_sum = 1
h_match =0
h_ind =0
u_ind =0
w_ind =0
c=0
h1 = self.l1.get_size()
u1 = self.l2.get_size()
for h in hashtags:
# l1_items=zip(*self.l1.items())
h_sum+= self.l1.get(h,0)
if(self.l1.has_key(h)):
ind = self.l1.keys().index(h)
h_ind+= h1 - ind
h_match+= 1 if ind<250 else 0
for u in users:
u_sum+= self.l2.get(u,0)
if(self.l2.has_key(u)):
u_ind+= u1 - self.l2.keys().index(u)
if(h_match !=0):
c = h_match -1
# print(h_ind,h1,u_ind,u1,w_ind,w1, h_sum,w_sum,)
similarity = (h_ind/(h1+1))*(h_sum/sum(self.l1.values() +[1])) + (u_ind/(u1+1))*(u_sum/sum(self.l2.values()+[1])) +c
return similarity
def random_read(lru_len=100,times=20000):
key_list=get_random_int(0,1500,times)
lru_obj=LRU(lru_len)
for key in key_list:
lru_obj.put(key,key)
beg_time=time.time()
for key in key_list:
lru_obj.get(key)
end_time=time.time()
print("测试随机读操作{}次,lru_len长度为{},情况下耗时{} ".format(times,lru_len,end_time-beg_time))
time.time()
def test_update_item(self):
lru = LRU(5)
lru.set("name", "john")
self.assertEqual(lru.cnt, 1)
lru.set("age", 30)
self.assertEqual(lru.get("name"), "john")
lru.set("yob", 1990)
self.assertEqual(lru.cnt, 3)
lru.set("name", "jim")
self.assertEqual(lru.get("name"), "jim")
self.assertEqual(lru.cnt, 3)
def test_set_above_cap(self):
lru = LRU(3)
lru.set("name", "john")
self.assertEqual(lru.cnt, 1)
lru.set("age", 30)
lru.set("yob", 1990)
self.assertEqual(lru.get("name"), "john")
self.assertEqual(lru.get("age"), 30)
self.assertEqual(lru.cnt, 3)
self.assertEqual(lru.tail.prev.key, "yob")
lru.set("loc", "CA")
self.assertEqual(lru.cnt, 3)
self.assertEqual(lru.tail.prev.key, "name")
with self.assertRaises(KeyError):
lru.get("yob")
def cached_mnubo_object_exists(device_id):
""" Method to wrap the object existence checking in a cached object
:param device_id: The device id of the object
:return: True of the object exists or False if it doesn't
"""
global global_cache
global config
now = int(time.time())
if not isinstance(global_cache, LRU):
if not isinstance(config['cache_max_entries'], int):
raise ValueError('cache_max_entries must be an integer')
global_cache = LRU(config['cache_max_entries'])
if not isinstance(config['cache_validity_period'], int):
raise ValueError('cache_validity_period must be an integer')
found = global_cache.get(device_id, None)
if found and found > now:
rc = True
else:
rc = mnubo_object_exists(device_id)
if rc:
global_cache[device_id] = now + config['cache_validity_period']
return rc
def random_read_write(lru_len=100,times=20000):
"""
随机读写
"""
key_list=get_random_int(0,1500,times)
lru_obj=LRU(lru_len)
beg_time=time.time()
for index,key in enumerate(key_list):
if index%2==0:
lru_obj.put(key,key)
else:
lru_obj.get(key)
end_time=time.time()
print("测试随机读写操作{}次,lru_len长度为{},情况下耗时{} ".format(times,lru_len,end_time-beg_time))
time.time()
def test_access_within_size(self):
for size in SIZES:
l = LRU(size)
for i in xrange(size):
l[i] = str(i)
for i in xrange(size):
self.assertEquals(l[i], str(i))
self.assertEquals(l.get(i,None), str(i))
def test_access_within_size(self):
for size in SIZES:
l = LRU(size)
for i in range(size):
l[i] = str(i)
for i in range(size):
self.assertEqual(l[i], str(i))
self.assertEqual(l.get(i,None), str(i))
class SocketCommunicator():
def __init__(self, maxUnacceptConnections=5):
self.sock = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
server_address = ('', 10000)
self.sock.bind(server_address)
self.sock.listen(maxUnacceptConnections)
self.theData = []
self.theDataLock = Lock()
self.shutdown_event = Event()
self.theThread = None
self.connections = LRU(10)
def startServer(self):
if self.theThread is not None:
return
def start():
while not self.shutdown_event.is_set():
print('waiting for connection...')
connection, client_address = self.sock.accept()
print('accepted connection from: {}'.format(client_address))
data = connection.recv(1)
if data:
data = data.decode()
print(data)
print()
if self.connections.get(client_address) is None:
self.connections[client_address] = data
with self.theDataLock:
self.theData.append(data)
self.sock.close()
servThread = Thread(target=start, daemon=True)
servThread.start()
self.theThread = servThread
def sendMessage(self, addr, port, data):
connection = socket.create_connection((addr, port))
connection.sendall(data)
connection.close()
def stop(self):
self.shutdown_event.set()
if self.theThread is not None:
self.theThread.join()
def getTheData(self):
with self.theDataLock:
tmp = self.theData.copy()
self.theData = []
return tmp
def whoSent(self, data):
items = self.connections.items()
for addr, msg in items:
if msg==data:
return addr
return None
def test_access(self):
for size in SIZES:
l = LRU(size)
n = size * 2
for i in xrange(n):
l[i] = str(i)
self._check_kvi(range(n-1,size-1,-1), l)
for i in xrange(size, n):
self.assertEquals(l[i], str(i))
self.assertEquals(l.get(i,None), str(i))
def test_access(self):
for size in SIZES:
l = LRU(size)
n = size * 2
for i in range(n):
l[i] = str(i)
self._check_kvi(range(n-1,size-1,-1), l)
for i in range(size, n):
self.assertEqual(l[i], str(i))
self.assertEqual(l.get(i,None), str(i))
class CertificateCache(object):
def __init__(self, cache_size):
self.certificates = LRU(cache_size)
def get(self, cache_id):
"""
Get the CachedCertificate for the given cache_id.
"""
return self.certificates.get(cache_id)
def lock(self, cache_id):
"""
Lock the CachedCertificate for the given cache_id. If the id is not in
the cache, create a CachedCertificate for the cache_id, add it to the
cache, and lock it.
"""
if cache_id in self.certificates:
self.certificates[cache_id].lock = True
else:
self.certificates[cache_id] = CachedCertificate(
lock=True,
response=None,
)
def release(self, cache_id):
if cache_id in self.certificates:
self.certificates[cache_id].lock = False
else:
logging.warning(
'Attempting to release a non-existent lock in the certificate'
' cache.')
def set_response(self, cache_id, response):
self.certificates[cache_id].response = response
def get_cache_id(self, cn, validity, san):
"""
Return a unique string from the provided arguments, for use in the
certificate cache. The current day is included in the id, to ensure
cache invalidation (minumum validity is 1 day).
"""
date = datetime.datetime.today().strftime('%Y-%m-%d')
return '{}{}{}{}'.format(cn, validity, san, date)
class topic:
def __init__(self, c_hash, c_user, c_words):
self.topic_count =1
self.l1 = LRU(c_hash)
self.l2 = LRU(c_user)
self.l3 = LRU(c_words)
def set_hashLRU(self,l):
self.set(self.l1, l)
def set_userLRU(self,l):
self.set(self.l2, l)
def set_wordLRU(self,l):
self.set(self.l3, l)
def set(self, lru, l):
for k in l:
v = lru.get(k,0)
lru[k]=v+1
def set_cluster(self, hashtags, users, words):
for k in hashtags:
v = self.l1.get(k,0)
self.l1[k]=v+1
for k in users:
v = self.l2.get(k,0)
self.l2[k]=v+1
for k in words:
v = self.l3.get(k,0)
self.l3[k]=v+1
self.topic_count+=1
def get_similarity(self,hashtags,users,words):
h_sum = 0
u_sum = 0
w_sum = 0
for h in hashtags:
h_sum+= self.l1.get(h,0)
for u in users:
u_sum+= self.l2.get(u,0)
for w in words:
w_sum+= self.l3.get(w,0)
similarity = 0.5*h_sum + 0.2*u_sum + 0.3*w_sum
return similarity
class EasyRequests:
__slots__ = ("bot", "loop", "session", "lock", "cache")
def __init__(self, bot, session):
self.bot = bot
self.loop = bot.loop
self.session = session
self.lock = asyncio.Lock(loop=bot.loop)
self.cache = LRU(64)
@classmethod
async def start(cls, bot):
session = aiohttp.ClientSession(loop=bot.loop,
headers=bot.http_headers)
LOG.info("Session opened.")
return cls(bot, session)
def fmt_cache(self, m, url, param):
p = ":".join([f"{k}:{v}" for k, v in param.items()])
return f"{m}:{url}:{p}"
def clear_cache(self, new_size=64):
self.cache = LRU(new_size)
LOG.info("Cleared cache, size set to %d", new_size)
async def request(self, __method, __url, *, cache=False, **params):
async with CacheLock(self.lock, do_lock=cache):
check = self.cache.get(self.fmt_cache(__method, __url, params),
None)
if check and cache:
return check
kwargs = dict()
kwargs["headers"] = params.pop("headers", None)
kwargs["data"] = params.pop("data", None)
kwargs["json"] = params.pop("json", None)
for tries in range(1, 6):
async with self.session.request(__method,
__url,
params=params,
**kwargs) as r:
if "application/json" in r.headers["Content-Type"]:
data = await r.json()
elif "text/" in r.headers["Content-Type"]:
data = await r.text("utf-8")
else:
data = await r.read()
request_fmt = f"{r.status} {r.method} {r.url}"
LOG.debug("%s returned %s", request_fmt, data)
# f**k zerochan 200 = 404 apparently
if 300 > r.status >= 200 or __url == "https://www.zerochan.net/search":
LOG.info("%s succeeded", request_fmt)
if cache:
self.cache[self.fmt_cache(__method, __url,
params)] = data
return data
if r.status == 429:
time = tries + 1
LOG.warning("%s RATE LIMITED (retrying in: %d)",
request_fmt, time)
await asyncio.sleep(time, loop=self.loop)
continue
if r.status in {500, 502}:
time = 1 + (tries * 2)
LOG.warning("%s INTERNAL ERROR (retrying in: %d)",
request_fmt, time)
await asyncio.sleep(time, loop=self.loop)
continue
LOG.error("%s errored.", request_fmt)
raise WebException(r, data)
LOG.fatal("%s out of tries.", request_fmt)
raise WebException(r, data)
async def close(self):
LOG.info("Session closed.")
await self.session.close()
class PrefixManager(metaclass=MainThreadSingletonMeta):
def __init__(self, bot: Salamander):
self._bot: Salamander = bot
self._cache = LRU(128)
def get_guild_prefixes(self, guild_id: int) -> Sequence[str]:
base = self._cache.get(guild_id, ())
if base:
return base
cursor = self._bot._conn.cursor()
res = tuple(
pfx
for (pfx,) in cursor.execute(
"""
SELECT prefix FROM guild_prefixes
WHERE guild_id=?
ORDER BY prefix DESC
""",
(guild_id,),
)
)
self._cache[guild_id] = res
return res
def add_guild_prefixes(self, guild_id: int, *prefixes: str):
cursor = self._bot._conn.cursor()
with self._bot._conn:
cursor.execute(
"""
INSERT INTO guild_settings (guild_id) VALUES (?)
ON CONFLICT (guild_id) DO NOTHING
""",
(guild_id,),
)
cursor.executemany(
"""
INSERT INTO guild_prefixes (guild_id, prefix)
VALUES (?, ?)
ON CONFLICT (guild_id, prefix) DO NOTHING
""",
tuple((guild_id, pfx) for pfx in prefixes),
)
# Extremely likely to be cached already
try:
del self._cache[guild_id]
except KeyError:
pass
def remove_guild_prefixes(self, guild_id: int, *prefixes: str):
cursor = self._bot._conn.cursor()
with self._bot._conn:
cursor.executemany(
"""
DELETE FROM guild_prefixes WHERE guild_id=? AND prefix=?
""",
tuple((guild_id, pfx) for pfx in prefixes),
)
# Extremely likely to be cached already
try:
del self._cache[guild_id]
except KeyError:
pass
class DND:
def __init__(self, kernel, num_neighbors, max_memory, embedding_size):
# self.dictionary = LRUCache(max_memory)
# self.kd_tree = kdtree.create(dimensions=embedding_size)
# rnd_projection = RandomBinaryProjections("RBP", 8)
# distance = EuclideanDistance()
# nearest = NearestFilter(num_neighbors)
# self.nearpy = Engine(dim=embedding_size, lshashes=[rnd_projection], distance=distance, vector_filters=[nearest], fetch_vector_filters=[])
self.kd_tree = None
# self.data = []
# self.lshash = LSHash(hash_size=embedding_size, input_dim=embedding_size, num_hashtables=10)
self.lru = LRU(size=max_memory)
self.num_neighbors = num_neighbors
self.kernel = kernel
self.max_memory = max_memory
self.embedding_size = embedding_size
# self.keys_added = []
def is_present(self, key):
return tuple(key) in self.lru # self.lru.has_key(tuple(key))
# return self.dictionary.get(tuple(key)) is not None
# return self.dictionary.get(tuple(key.data.cpu().numpy()[0])) is not None
def get_value(self, key):
return self.lru[tuple(key)]
# return self.dictionary.get(tuple(key))
# return self.dictionary.get(tuple(key.data.cpu().numpy()[0]))
def lookup(self, lookup_key):
# TODO: Speed up search knn
# keys = [key[0].data for key in self.kd_tree.search_knn(lookup_key, self.num_neighbors)]
lookup_key_numpy = lookup_key.data[0].numpy()
# lookup_key_tuple = tuple(lookup_key_numpy)
# print(lookup_key)
# keys = [key[0] for key in self.lshash.query_no_data(lookup_key_numpy, num_results=self.num_neighbors)]
# keys = [key[1] for key in self.nearpy.neighbours(lookup_key_numpy)]
if self.kd_tree is not None:
# print(len(self.lru.keys()), lookup_key_numpy)
# things_distances, things_index = self.kd_tree.query(lookup_key_numpy, k=self.num_neighbors, eps=1.0)
things_index = self.kd_tree.query([lookup_key_numpy],
k=min(self.num_neighbors,
len(self.kd_tree.data)),
return_distance=False,
sort_results=False)
# print(things_index)
keys = [self.lru.keys()[ii[0]] for ii in things_index]
# print(keys)
else:
keys = []
# print(keys)
# print(keys)
# output, kernel_sum = Variable(FloatTensor([0])), Variable(FloatTensor([0]))
output, kernel_sum = 0, 0
# if len(keys) != 0:
# print(keys)
# TODO: Speed this up since the kernel takes a significant amount of time
for key in keys:
# print("Key:",key, lookup_key)
# if not np.allclose(key, lookup_key_numpy): #(key == lookup_key).data.all():
if not np.all(key == lookup_key_numpy):
# print("Here")
# gg = Variable(FloatTensor(np.array(key)))
# print(key)
# gg = Variable(FloatTensor(key))
gg = Variable(torch.from_numpy(np.array(key)))
# print(tuple(key))
# hh = lookup_key[0] - gg
# print("Key:", gg, "Lookup key", lookup_key[0])
# print(lookup_key[0] + gg)
kernel_val = self.kernel(gg, lookup_key[0])
# print("key:", self.lru.get(tuple(key)))
# if not self.lru.has_key(tuple(key)):
# print(keys)
# print(tuple(key))
# print(key in self.keys_added)
# print(len(self.lru))
# if tuple(key) not in self.lru:
# print("NOT IN:", tuple(key))
# print(len(keys))
output += kernel_val * self.lru.get(tuple(key))
# output += kernel_val * self.dictionary.get(tuple(key))
# print("Key", key.requires_grad, key.volatile)
# print("Kernel key", self.kernel(key, lookup_key).requires_grad)
# print("Output in loop", output.requires_grad)
kernel_sum += kernel_val #self.kernel(key, lookup_key)
# print(kernel_sum)
# if len(keys) == 0:
# return (lookup_key * 0)[0][0]
if isinstance(kernel_sum, int):
return (lookup_key * 0)[0][0]
# if kernel_sum == 0:
# print("0 Kernel", kernel_sum)
# if len(keys) == 0:
# print("0 keys", len(keys))
if kernel_sum.data[0] == 0 or len(keys) == 0:
# print(lookup_key)
# zeroed = (lookup_key * 0)[0][0]
# print("Zero Lookup.", output.data, kernel_sum.data, len(keys))
return (lookup_key * 0)[0][0]
# print("lookup_key", lookup_key.requires_grad, lookup_key.volatile)
# print("kernled", self.kernel(keys[0], lookup_key).requires_grad)
# print("output", output.requires_grad, output.volatile)
# print("ks", kernel_sum.requires_grad, kernel_sum.volatile)
# print("Non-Zero Lookup for {}".format(lookup_key))
output = output / kernel_sum
# print(output)
return output
def upsert(self, key, value):
# key = key.data[0].numpy()
# print(key)
# self.keys_added.append(key)
# if not self.lru.has_key(tuple(key)):# self.is_present(key):
# self.kd_tree.add(key)
# print("Key going in", key)
# self.lshash.index(input_point=key)
# self.nearpy.store_vector(key, data=key)
# print("Adding", tuple(key), key)
# neighbours = self.nearpy.neighbours(key)
# print(neighbours)
self.lru[tuple(key)] = value
# self.kd_tree = KDTree(data=self.lru.keys(), compact_nodes=False, copy_data=False, balanced_tree=False)
self.kd_tree = KDTree(self.lru.keys())
return
if len(self.lru) == self.max_memory:
# Expel least recently used key from self.dictionary and self.kd_tree if memory used is at capacity
# deleted_key = self.dictionary.delete_least_recently_used()[0]
# deleted_key = self.lru.peek_last_item()[0]
# print("Deleted key:",deleted_key)
# deleted_key = np.array(deleted_key)
# thing = Variable(torch.from_numpy(deleted_key).float()).unsqueeze(0)
# thing = Variable(FloatTensor(deleted_key)).unsqueeze(0)
# print("Thing:",thing)
# print(self.dictionary.cache.keys())
key_to_delete = self.lru.peek_last_item()
self.lru[tuple(key)] = value
# self.kd_tree.remove(Variable(FloatTensor(deleted_key)).unsqueeze(0))
# self.kd_tree.remove(deleted_key)
# Remake the LSHASH with the deleted key
# print("remaking")
# self.lshash = LSHash(hash_size=self.embedding_size, input_dim=self.embedding_size)
# for k in self.lru.keys():
# self.lshash.index(np.array(k))
# print("Deleting", np.array(key_to_delete[0]))
# self.nearpy.delete_vector(key_to_delete[0])
# self.nearpy.clean_all_buckets()
# for k in self.lru.keys():
# self.nearpy.store_vector(np.array(k))
# Checking that the lru keys are the same as the keys in the lshash
# for key in self.lru.keys():
# keys_close = [key[0] for key in self.lshash.query(key, num_results=5)]
# # print(keys_close)
# for kk in keys_close:
# if kk not in self.lru:
# print("\n\nProblems! Key in LSHASH not in LRU\n\n")
# Check length of all lru keys
# all_lru_keys = self.lshash.query(key)
# print("\n", len(all_lru_keys), "\n")
else:
self.lru[tuple(key)] = value
self.kdtree = KDTree(self.data)
class Network(Service, NetworkAPI):
_bootnodes: Tuple[ENRAPI, ...]
_talk_protocols: Dict[bytes, TalkProtocolAPI]
def __init__(self, client: ClientAPI, bootnodes: Collection[ENRAPI],) -> None:
self.logger = get_extended_debug_logger("ddht.Network")
self.client = client
self._bootnodes = tuple(bootnodes)
self.routing_table = KademliaRoutingTable(
self.client.enr_manager.enr.node_id, ROUTING_TABLE_BUCKET_SIZE,
)
self._routing_table_ready = trio.Event()
self._last_pong_at = LRU(2048)
self._talk_protocols = {}
self._ping_handler_ready = trio.Event()
self._find_nodes_handler_ready = trio.Event()
async def ready(self) -> None:
await self._ping_handler_ready.wait()
await self._find_nodes_handler_ready.wait()
#
# Proxied ClientAPI properties
#
@property
def local_node_id(self) -> NodeID:
return self.client.local_node_id
@property
def events(self) -> EventsAPI:
return self.client.events
@property
def dispatcher(self) -> DispatcherAPI:
return self.client.dispatcher
@property
def enr_manager(self) -> ENRManagerAPI:
return self.client.enr_manager
@property
def pool(self) -> PoolAPI:
return self.client.pool
@property
def enr_db(self) -> QueryableENRDatabaseAPI:
return self.client.enr_db
#
# TALK API
#
def add_talk_protocol(self, protocol: TalkProtocolAPI) -> None:
if protocol.protocol_id in self._talk_protocols:
raise DuplicateProtocol(
f"A protocol is already registered for '{protocol.protocol_id!r}'"
)
self._talk_protocols[protocol.protocol_id] = protocol
#
# High Level API
#
async def bond(
self, node_id: NodeID, *, endpoint: Optional[Endpoint] = None
) -> bool:
self.logger.debug2(
"Bonding with %s", node_id.hex(),
)
try:
pong = await self.ping(node_id, endpoint=endpoint)
except trio.TooSlowError:
self.logger.debug("Bonding with %s timed out during ping", node_id.hex())
return False
except MissingEndpointFields:
self.logger.debug(
"Bonding with %s failed due to missing endpoint information",
node_id.hex(),
)
return False
try:
enr = await self.lookup_enr(
node_id, enr_seq=pong.enr_seq, endpoint=endpoint
)
except trio.TooSlowError:
self.logger.debug(
"Bonding with %s timed out during ENR retrieval", node_id.hex(),
)
return False
except EmptyFindNodesResponse:
self.logger.debug(
"Bonding with %s failed due to them not returing their ENR record",
node_id.hex(),
)
return False
self.routing_table.update(enr.node_id)
self.logger.debug(
"Bonded with %s successfully", node_id.hex(),
)
self._routing_table_ready.set()
return True
async def _bond(self, node_id: NodeID, endpoint: Optional[Endpoint] = None) -> None:
await self.bond(node_id, endpoint=endpoint)
async def ping(
self,
node_id: NodeID,
*,
endpoint: Optional[Endpoint] = None,
request_id: Optional[bytes] = None,
) -> PongMessage:
if endpoint is None:
endpoint = await self.endpoint_for_node_id(node_id)
response = await self.client.ping(node_id, endpoint, request_id=request_id)
return response.message
async def find_nodes(
self,
node_id: NodeID,
*distances: int,
endpoint: Optional[Endpoint] = None,
request_id: Optional[bytes] = None,
) -> Tuple[ENRAPI, ...]:
if not distances:
raise TypeError("Must provide at least one distance")
if endpoint is None:
endpoint = await self.endpoint_for_node_id(node_id)
responses = await self.client.find_nodes(
node_id, endpoint, distances=distances, request_id=request_id
)
# Validate that all responses are indeed at one of the
# specified distances.
for response in responses:
validate_found_nodes_distances(response.message.enrs, node_id, distances)
return tuple(enr for response in responses for enr in response.message.enrs)
def stream_find_nodes(
self,
node_id: NodeID,
endpoint: Endpoint,
distances: Collection[int],
*,
request_id: Optional[bytes] = None,
) -> AsyncContextManager[trio.abc.ReceiveChannel[ENRAPI]]:
return common_network_stream_find_nodes(
self, node_id, endpoint, distances, request_id=request_id
)
async def talk(
self,
node_id: NodeID,
*,
protocol: bytes,
payload: bytes,
endpoint: Optional[Endpoint] = None,
request_id: Optional[bytes] = None,
) -> bytes:
if endpoint is None:
endpoint = await self.endpoint_for_node_id(node_id)
response = await self.client.talk(
node_id, endpoint, protocol, payload, request_id=request_id
)
payload = response.message.payload
if not payload:
raise ProtocolNotSupported(protocol)
return response.message.payload
async def lookup_enr(
self, node_id: NodeID, *, enr_seq: int = 0, endpoint: Optional[Endpoint] = None
) -> ENRAPI:
if node_id == self.local_node_id:
raise Exception(f"Cannot lookup local ENR: node_id={node_id.hex()}")
try:
enr = self.enr_db.get_enr(node_id)
except KeyError:
if endpoint is None:
# Try to use a recursive network lookup to find the desired
# node.
async with self.recursive_find_nodes(node_id) as enr_aiter:
async for found_enr in enr_aiter:
if found_enr.node_id == node_id:
endpoint = Endpoint.from_enr(found_enr)
break
else:
# we weren't given an endpoint and we don't have an enr which would give
# us an endpoint, there's no way to reach this node.
raise KeyError(f"Could not find ENR: node_id={node_id.hex()}")
else:
if enr.sequence_number >= enr_seq:
return enr
enr = await self._fetch_enr(node_id, endpoint=endpoint)
try:
self.enr_db.set_enr(enr)
except OldSequenceNumber:
pass
return enr
async def _fetch_enr(
self, node_id: NodeID, *, endpoint: Optional[Endpoint]
) -> ENRAPI:
enrs = await self.find_nodes(node_id, 0, endpoint=endpoint)
if not enrs:
raise EmptyFindNodesResponse(f"{node_id.hex()} did not return its ENR")
# Assuming we're given enrs for a single node, this reduce returns the enr for
# that node with the highest sequence number
return reduce_enrs(enrs)[0]
def recursive_find_nodes(
self, target: NodeID
) -> AsyncContextManager[trio.abc.ReceiveChannel[ENRAPI]]:
return common_recursive_find_nodes(self, target)
@asynccontextmanager
async def explore(
self, target: NodeID, concurrency: int = 3,
) -> AsyncIterator[trio.abc.ReceiveChannel[ENRAPI]]:
explorer = Explorer(self, target, concurrency)
with trio.move_on_after(300) as scope:
async with background_trio_service(explorer):
await explorer.ready()
async with explorer.stream() as receive_channel:
yield receive_channel
if scope.cancelled_caught:
self.logger.error("Timeout from `stream_locate`")
#
# Long Running Processes
#
async def run(self) -> None:
self.manager.run_daemon_child_service(self.client)
await self.client.wait_listening()
self.manager.run_daemon_task(self._periodically_report_routing_table)
self.manager.run_daemon_task(self._ping_oldest_routing_table_entry)
self.manager.run_daemon_task(self._track_last_pong)
self.manager.run_daemon_task(self._manage_routing_table)
self.manager.run_daemon_task(self._pong_when_pinged)
self.manager.run_daemon_task(self._serve_find_nodes)
self.manager.run_daemon_task(self._handle_unhandled_talk_requests)
await self.manager.wait_finished()
async def _periodically_report_routing_table(self) -> None:
async for _ in every(30, initial_delay=10):
non_empty_buckets = tuple(
reversed(
tuple(
(idx, bucket)
for idx, bucket in enumerate(self.routing_table.buckets, 1)
if bucket
)
)
)
total_size = sum(len(bucket) for idx, bucket in non_empty_buckets)
bucket_info = "|".join(
tuple(
f"{idx}:{'F' if len(bucket) == self.routing_table.bucket_size else len(bucket)}"
for idx, bucket in non_empty_buckets
)
)
self.logger.debug(
"routing-table-info: size=%d buckets=%s", total_size, bucket_info,
)
async def _ping_oldest_routing_table_entry(self) -> None:
await self._routing_table_ready.wait()
while self.manager.is_running:
# Here we preserve the lazy iteration while still checking that the
# iterable is not empty before passing it into `min` below which
# throws an ambiguous `ValueError` otherwise if the iterable is
# empty.
nodes_iter = self.routing_table.iter_all_random()
try:
first_node_id = first(nodes_iter)
except StopIteration:
await trio.sleep(ROUTING_TABLE_KEEP_ALIVE)
continue
else:
least_recently_ponged_node_id = min(
cons(first_node_id, nodes_iter),
key=lambda node_id: self._last_pong_at.get(node_id, 0),
)
too_old_at = trio.current_time() - ROUTING_TABLE_KEEP_ALIVE
try:
last_pong_at = self._last_pong_at[least_recently_ponged_node_id]
except KeyError:
pass
else:
if last_pong_at > too_old_at:
await trio.sleep(last_pong_at - too_old_at)
continue
did_bond = await self.bond(least_recently_ponged_node_id)
if not did_bond:
self.routing_table.remove(least_recently_ponged_node_id)
async def _track_last_pong(self) -> None:
async with self.dispatcher.subscribe(PongMessage) as subscription:
async for message in subscription:
self._last_pong_at[message.sender_node_id] = trio.current_time()
async def _manage_routing_table(self) -> None:
# First load all the bootnode ENRs into our database
for enr in self._bootnodes:
try:
self.enr_db.set_enr(enr)
except OldSequenceNumber:
pass
# Now repeatedly try to bond with each bootnode until one succeeds.
while self.manager.is_running:
with trio.move_on_after(20):
async with trio.open_nursery() as nursery:
for enr in self._bootnodes:
if enr.node_id == self.local_node_id:
continue
endpoint = Endpoint.from_enr(enr)
nursery.start_soon(self._bond, enr.node_id, endpoint)
await self._routing_table_ready.wait()
break
# Now we enter into an infinite loop that continually probes the
# network to beep the routing table fresh. We both perform completely
# random lookups, as well as targeted lookups on the outermost routing
# table buckets which are not full.
#
# The `TokenBucket` allows us to burst at the beginning, making quick
# successive probes, then slowing down once the
#
# TokenBucket starts with 10 tokens, refilling at 1 token every 30
# seconds.
token_bucket = TokenBucket(1 / 30, 10)
async with trio.open_nursery() as nursery:
while self.manager.is_running:
await token_bucket.take()
# Get the logarithmic distance to the "largest" buckets
# that are not full.
non_full_bucket_distances = tuple(
idx + 1
for idx, bucket in enumerate(self.routing_table.buckets)
if len(bucket) < self.routing_table.bucket_size # noqa: E501
)[-16:]
# Probe one of the not-full-buckets with a weighted preference
# towards the largest buckets.
distance_to_probe = weighted_choice(non_full_bucket_distances)
target_node_id = at_log_distance(self.local_node_id, distance_to_probe)
async with self.recursive_find_nodes(target_node_id) as enr_aiter:
async for enr in enr_aiter:
if enr.node_id == self.local_node_id:
continue
try:
self.enr_db.set_enr(enr)
except OldSequenceNumber:
pass
nursery.start_soon(self._bond, enr.node_id)
async def _pong_when_pinged(self) -> None:
async def _maybe_add_to_routing_table(
request: InboundMessage[PingMessage],
) -> None:
try:
enr = await self.lookup_enr(
request.sender_node_id,
enr_seq=request.message.enr_seq,
endpoint=request.sender_endpoint,
)
except (trio.TooSlowError, EmptyFindNodesResponse):
return
self.routing_table.update(enr.node_id)
self._routing_table_ready.set()
async with trio.open_nursery() as nursery:
async with self.dispatcher.subscribe(PingMessage) as subscription:
self._ping_handler_ready.set()
async for request in subscription:
await self.dispatcher.send_message(
request.to_response(
PongMessage(
request.request_id,
self.enr_manager.enr.sequence_number,
request.sender_endpoint.ip_address,
request.sender_endpoint.port,
)
)
)
nursery.start_soon(_maybe_add_to_routing_table, request)
async def _serve_find_nodes(self) -> None:
async with self.dispatcher.subscribe(FindNodeMessage) as subscription:
self._find_nodes_handler_ready.set()
async for request in subscription:
response_enrs: List[ENRAPI] = []
distances = set(request.message.distances)
if len(distances) != len(request.message.distances):
self.logger.debug(
"Ignoring invalid FindNodeMessage from %s@%s: duplicate distances",
request.sender_node_id.hex(),
request.sender_endpoint,
)
continue
elif not distances:
self.logger.debug(
"Ignoring invalid FindNodeMessage from %s@%s: empty distances",
request.sender_node_id.hex(),
request.sender_endpoint,
)
continue
elif any(
distance > self.routing_table.num_buckets for distance in distances
):
self.logger.debug(
"Ignoring invalid FindNodeMessage from %s@%s: distances: %s",
request.sender_node_id.hex(),
request.sender_endpoint,
distances,
)
continue
for distance in distances:
if distance == 0:
response_enrs.append(self.enr_manager.enr)
elif distance <= self.routing_table.num_buckets:
node_ids_at_distance = self.routing_table.get_nodes_at_log_distance(
distance,
)
for node_id in node_ids_at_distance:
response_enrs.append(self.enr_db.get_enr(node_id))
else:
raise Exception("Should be unreachable")
await self.client.send_found_nodes(
request.sender_node_id,
request.sender_endpoint,
enrs=response_enrs,
request_id=request.request_id,
)
async def _handle_unhandled_talk_requests(self) -> None:
async with self.dispatcher.subscribe(TalkRequestMessage) as subscription:
async for request in subscription:
if request.message.protocol not in self._talk_protocols:
await self.client.send_talk_response(
request.sender_node_id,
request.sender_endpoint,
payload=b"",
request_id=request.message.request_id,
)
#
# Utility
#
async def endpoint_for_node_id(self, node_id: NodeID) -> Endpoint:
try:
enr = self.enr_db.get_enr(node_id)
except KeyError:
enr = await self.lookup_enr(node_id)
return Endpoint.from_enr(enr)
class RewardNet():
"""Interacts with and learns from the environment."""
def __init__(self, state_action_size, reward_size):
"""Initialize an RewardNet object.
Params
======
state_size (int): dimension of each state
action_size (int): dimension of each action
"""
self.state_action_size = state_action_size
self.reward_size = reward_size
set_seed()
# Reward-Network
self.reward_net = Network(state_action_size, reward_size).to(device)
self.optimizer = optim.Adam(self.reward_net.parameters(), lr=LR)
self.criterion = nn.MSELoss()
# Replay memory
self.memory = ReplayBuffer(BUFFER_SIZE, BATCH_SIZE, 0)
# Reward dict - LRFU implementation not found, therefore just LRU
self.M = LRU(BUFFER_SIZE)
self.S = []
self.V = 0
# Initialize loss for tracking the progress
self.loss = 0
def add(self, state_action, reward):
# Save experience in replay memory
self.memory.add(state_action, reward)
def add_to_M(self, sa, reward):
# Add records to the reward dict
self.M[sa] = reward
if len(self.M) >= BUFFER_SIZE:
del self.M[self.M.peek_last_item()[0]] # discard LRU key
def get_from_M(self, sa):
# Retrieve items from M
return (self.M.get(sa, 0))
def step(self):
# If enough samples are available in memory, get random subset and learn
if len(self.memory) > BATCH_SIZE:
experiences = self.memory.sample()
self.learn(experiences)
def act(self, state_action):
"""Returns actions for given state as per current policy.
state (array_like): current state
"""
sa = torch.from_numpy(state_action).float().unsqueeze(0).to(device)
return (self.reward_net(sa))
def learn(self, experiences):
"""Update value parameters using given batch of experience tuples.
experiences (Tuple[torch.Tensor]): tuple of (sa, r) tuples
"""
state_actions, rewards = experiences
# Get expected Reward values
R_pred = self.reward_net(state_actions)
# Compute loss
loss = self.criterion(R_pred, rewards)
print("RewardNet loss = {}".format(loss))
# Grad descent
self.optimizer.zero_grad()
loss.backward()
self.optimizer.step()
# Keep track of the loss for the history
self.loss = loss.item()
class Py2NeoHandler(object):
def __init__(self, host, user, pwd):
self.graph = Graph(host=host, user=user, password=pwd)
self.lru_cache = LRU(100)
# MATCH (a:Node)-[r]->(b:Node) where a.relevant_terms CONTAINS 'vino' or b.relevant_terms CONTAINS 'vino' RETURN a,r,b LIMIT 10
# MATCH (a:Node)-[r]->(b) where a.id_s > 0 and a.id_s < 100 and b.id_s > 0 and b.id_s < 100 return a,r,b LIMIT 1000
def _create_query_relevant_terms(self, query_terms, limit=10000):
base_query = "MATCH (a:Node)-[r]->(b:Node) "
base_where = " (a.relevant_terms contains '{}' and b.relevant_terms contains '{}') and "
base_return = " return a,r,b limit {};"
composed_query = base_query
term_split = query_terms.split()
print(term_split)
if len(term_split) > 0:
composed_query += " WHERE "
for term in query_terms.split():
mod_term = ' {}:'.format(term)
composed_query += base_where.format(mod_term, mod_term)
if len(term_split) > 0:
composed_query = composed_query[:-4]
composed_query += base_return.format(limit)
print('query ' + composed_query)
return composed_query
def _get_or_else(self, value, default):
if value:
return value
else:
return default
def _create_node(self, n):
props = dict(n)
node = Node(
type_id = self._get_or_else(props['type_id'], ''),
node_type = self._get_or_else(props['node_type'], ''),
id_s = self._get_or_else(props['id_s'], ''),
fiscal_code = self._get_or_else(props['fiscal_code'], ''),
relevant_terms = self._get_or_else(props['relevant_terms'], ''),
region = self._get_or_else(props['region'], ''),
province = self._get_or_else(props['province'], ''),
city = self._get_or_else(props['city'], ''),
address = self._get_or_else(props['address'], ''),
istat_code = self._get_or_else(props['istat_code'], ''),
adm_code = self._get_or_else(props['administrative_code'], ''),
name = self._get_or_else(props['name'], ''),
company_type = self._get_or_else(props['company_type'], ''),
nation = self._get_or_else(props['nation'], ''),
)
return node
def _create_link(self, src_id, rel, dst_id):
props = dict(rel)
return Link(src_id, dst_id, props['score'])
def query_by_relevant_terms(self, query_terms, limit=1000):
start = time.time()
if query_terms in self.lru_cache:
end = time.time()
print('query in time {}'.format(end - start))
return self.lru_cache.get(query_terms)
else:
querystring = self._create_query_relevant_terms(query_terms, limit)
nodes = set()
links = set()
for src, rel, dst in self.graph.run(querystring):
src_node = self._create_node(src)
dst_node = self._create_node(dst)
if len(str(src_node.id)) > 0 and len(str(dst_node.id)) > 0:
link = self._create_link(src_node.id, rel, dst_node.id)
nodes.add(src_node)
nodes.add(dst_node)
links.add(link)
end = time.time()
print('query in time {}'.format(end - start))
result = Result(list(nodes), list(links))
self.lru_cache[query_terms] = result
return result
if not i:
members = await app.rest.search_members(guild_id, name=name)
_update_cache(members)
return None
async def member_converter(arg: WrappedArg) -> hikari.Member:
if (msg := await caret_converter(arg)) is not None:
if msg.member is not None:
return msg.member
if (member := arg.context.guild.get_member(msg.author.id)) is not None:
return member
if member := _member_cache.get(
f'{arg.context.guild_id}:{arg.data.strip("<@!>")}'):
return member
try:
member = await member_converter_(arg)
_member_cache[f"{member.guild_id}:{member.id}"] = member
return member
except ConverterFailure:
member = await search_member(arg.context.bot, arg.context.guild_id,
arg.data)
if not member:
raise
return member
class topic4:
def __init__(self, c_hash, c_user, c_words):
self.topic_count =1
# self.time = (self.first,self.last)
self.l1 = LRU(c_hash)
self.first =""
self.last=""
self.lats=[]
self.longs=[]
self.l2 = LRU(c_user)
self.l3 = LRU(c_words)
self.l4 = LRU(400)
def set_hashLRU(self,l):
self.set(self.l1, l)
def set_userLRU(self,l):
self.set(self.l2, l)
def set_wordLRU(self,l):
self.set(self.l3, l)
def set(self, lru, l):
for k in l:
v = lru.get(k,0)
lru[k]=v+1
def set_cluster(self, hashtags, users, words,links, cords):
for k in hashtags:
self.l1[k]=self.l1.get(k,0)+1
for k in users:
self.l2[k]=self.l2.get(k,0)+1
for k in words:
self.l3[k]=self.l3.get(k,0)+1
for k in links:
self.l4[k]=self.l4.get(k,0)+1
if(cords is not None):
self.lats.append(cords["coordinates"][1])
self.longs.append(cords["coordinates"][0])
self.topic_count+=1
def get_similarity(self,hashtags,users,words):
h_sum = 1
u_sum = 1
w_sum = 1
h_match =0
h_ind =0
u_ind =0
w_ind =0
c=0
h1 = self.l1.get_size()
u1 = self.l2.get_size()
w1 = self.l3.get_size()
for h in hashtags:
# l1_items=zip(*self.l1.items())
h_sum+= self.l1.get(h,0)
if(self.l1.has_key(h)):
ind = self.l1.keys().index(h)
h_ind+= h1 - ind
h_match+= 1 if ind<250 else 0
for u in users:
u_sum+= self.l2.get(u,0)
if(self.l2.has_key(u)):
u_ind+= u1 - self.l2.keys().index(u)
for w in words:
w_sum+= self.l3.get(w,0)
if(self.l3.has_key(w)):
w_ind+= w1 - self.l3.keys().index(w)
if(h_match !=0):
c = h_match -1
# print(h_ind,h1,u_ind,u1,w_ind,w1, h_sum,w_sum,)
similarity = (h_ind/(h1+1))*(h_sum/sum(self.l1.values() +[1])) + (u_ind/(u1+1))*(u_sum/sum(self.l2.values()+[1])) + (w_ind/(w1+1))*(w_sum/sum(self.l3.values()+[1])) +c
return similarity
def flush1(self, cache, size):
if(len(cache.keys())>5):
tokens = reversed(cache.keys()[5])
cache.clear()
for i in tokens:
cache[i]=1
def flush(self):
self.flush1(self.l1,500)
self.flush1(self.l2, 500)
self.flush1(self.l3,3500)
self.topic_count=1
class MemoryStateManager:
'''
Meaningless for anyting other than tests
'''
def __init__(self, size=10):
self.size = size
self._data = LRU(self.size)
self._locks = {}
self._canceled = set()
self.worker_id = uuid.uuid4().hex
def set_loop(self, loop=None):
pass
async def update(self, task_id, data, ttl=None):
# Updates existing data with new data
existing = await self.get(task_id)
existing.update(data)
self._data[task_id] = existing
async def get(self, task_id):
return self._data.get(task_id, {})
async def exists(self, task_id):
return task_id in self._data
async def list(self):
for task_id in self._data.keys():
yield task_id
async def acquire(self, task_id, ttl):
already_locked = await self.is_locked(task_id)
if already_locked:
raise TaskAlreadyAcquired(task_id)
# Set new lock
from guillotina_amqp.utils import TimeoutLock
lock = TimeoutLock(self.worker_id)
await lock.acquire(ttl=ttl)
self._locks[task_id] = lock
async def is_mine(self, task_id):
if task_id not in self._locks:
raise TaskNotFoundException(task_id)
lock = self._locks[task_id]
return lock.locked() and lock.worker_id == self.worker_id
async def is_locked(self, task_id):
if task_id not in self._locks:
return False
return self._locks[task_id].locked()
async def release(self, task_id):
if not await self.is_mine(task_id):
# You can't refresh a lock that's not yours
raise TaskAccessUnauthorized(task_id)
# Release lock and pop it from data structure
self._locks[task_id].release()
self._locks.pop(task_id, None)
async def refresh_lock(self, task_id, ttl):
if task_id not in self._locks:
raise TaskNotFoundException(task_id)
if not await self.is_locked(task_id):
raise Exception(f'Task {task_id} is not locked')
if not await self.is_mine(task_id):
# You can't refresh a lock that's not yours
raise TaskAccessUnauthorized(task_id)
# Refresh
return await self._locks[task_id].refresh_lock(ttl)
async def cancel(self, task_id):
self._canceled.update({task_id})
return True
async def cancelation_list(self):
canceled = copy.deepcopy(self._canceled)
for task_id in canceled:
yield task_id
async def clean_canceled(self, task_id):
try:
self._canceled.remove(task_id)
return True
except KeyError:
# Task id wasn't canceled
return False
async def is_canceled(self, task_id):
return task_id in self._canceled
async def _clean(self):
self._data = LRU(self.size)
self._locks = {}
self._canceled = set()
class AlchemyModel(t.Generic[T],
QtCore.QAbstractTableModel,
metaclass=_SqlAlchemyTableModelMeta):
_columns: t.Sequence[ConvertibleColumn]
def __init__(
self,
model_type: t.Type[T],
order_by: QueryableAttribute,
*,
columns: t.Optional[t.Sequence[ConvertibleColumn]] = None,
page_size: int = 64,
auto_commit: bool = True,
):
super().__init__()
self._model_type = model_type
self._order_by_column = order_by
self._page_size = page_size
self._auto_commit = auto_commit
if columns is not None:
self._columns = columns
if not self._columns:
raise ValueError('Specify at least one column')
self._header_names = tuple(' '.join(v.capitalize()
for v in c.column.name.split('_'))
for c in self._columns)
self._cache = LRU(int(page_size * 2))
self._cached_size = None
def filter_query(self, query: Query) -> Query:
return query
def get_query(self) -> Query:
return self.filter_query(EDB.Session.query(self._model_type))
def clear_cache(self) -> None:
self._cache.clear()
self._cached_size = None
def _load_page(self, offset: int, limit: int) -> None:
for idx, model in enumerate(self.get_query().order_by(
self._order_by_column).limit(limit).offset(offset)):
self._cache[idx + offset] = model
def get_item_at_index(self, index: int) -> t.Optional[T]:
if index < 0:
return None
try:
return self._cache[index]
except KeyError:
self._load_page(index, self._page_size)
return self._cache.get(index, None)
def rowCount(self, parent: QModelIndex = ...) -> int:
if self._cached_size is None:
self._cached_size = self.get_query().count()
return self._cached_size
def columnCount(self, parent: QModelIndex = ...) -> int:
return len(self._columns)
def data(self, index: QModelIndex, role: int = ...) -> t.Any:
if not role in (Qt.DisplayRole, Qt.EditRole):
return None
row = self.get_item_at_index(index.row())
if not row:
return None
column = self._columns[index.column()]
return column.to_primitive(getattr(row, column.column.name))
def setData(self,
index: QModelIndex,
value: t.Any,
role: int = ...) -> bool:
if role != Qt.EditRole:
return False
row = self.get_item_at_index(index.row())
if not row:
return False
column = self._columns[index.column()]
setattr(row, column.column.name, column.from_primitive(value))
if self._auto_commit:
EDB.Session.commit()
if self._columns[index.column()] == self._order_by_column:
self.clear_cache()
return True
def flags(self, index: QModelIndex) -> Qt.ItemFlags:
return Qt.ItemIsSelectable | Qt.ItemIsEditable | Qt.ItemIsEnabled
def headerData(self,
section: int,
orientation: Qt.Orientation,
role: int = ...) -> t.Any:
if role != Qt.DisplayRole:
return None
if orientation == Qt.Vertical:
return str(section + 1)
return self._header_names[section]
def removeRows(self,
row: int,
count: int,
parent: QModelIndex = ...) -> bool:
self.beginRemoveRows(parent, row, row - 1 + count)
pk_column = self._model_type.__mapper__.primary_key[0]
items = list(
filter(lambda i: i is not None,
(getattr(self.get_item_at_index(idx), pk_column.name)
for idx in range(row, row + count))))
if not items:
return False
EDB.Session.query(self._model_type).filter(
pk_column.in_(items)).delete(syncronize_session='fetch', )
if self._auto_commit:
EDB.Session.commit()
self.clear_cache()
self.endRemoveRows()
return True
def pop(self, row: int) -> t.Optional[T]:
model = self.get_item_at_index(row)
if not model:
return
self.removeRows(row, 1)
return model
def moveRows(
self,
sourceParent: QModelIndex,
sourceRow: int,
count: int,
destinationParent: QModelIndex,
destinationChild: int,
) -> bool:
self.beginMoveRows(QModelIndex(), sourceRow, sourceRow + count - 1,
QModelIndex(), destinationChild)
floor = min(sourceRow, destinationChild)
items = [
_item for _item in (
self.get_item_at_index(idx)
for idx in range(floor,
max(sourceRow, destinationChild) + count))
if _item is not None
]
old_values = [
getattr(_item, self._order_by_column.name) for _item in items
]
for _ in range(count):
items.insert(destinationChild - floor,
items.pop(sourceRow - floor))
for item, new_value in zip(items, old_values):
setattr(item, self._order_by_column.name, new_value)
if self._auto_commit:
EDB.Session.commit()
self.clear_cache()
self.endMoveRows()
return True
def reset(self) -> None:
self.beginResetModel()
self.clear_cache()
self.endResetModel()
class SimplePluginBase(PluginBase):
iterator = None
@classmethod
def parse_url(cls, url):
"""
Checks if an url can be downloaded by this plugin.
Returns the remote id if the url corresponds to a single post,
a Dynamic object that can be passed to search if the url
corresponds to multiple posts, or None if this plugin can't
download or create a search using this url.
"""
return None
def __init__(self, session):
super().__init__(session)
# (category, tag) -> RemoteTag
self._tag_cache = LRU(100)
def _get_tag(self, category, tagstr):
tag = self._tag_cache.get((category, tagstr))
if tag is None:
tag = self.session.query(RemoteTag) \
.filter(
RemoteTag.source==self.source,
RemoteTag.category==category,
RemoteTag.tag==tagstr
).one_or_none()
if tag is None:
tag = RemoteTag(source=self.source, category=category, tag=tagstr)
self.session.add(tag)
self._tag_cache[category, tagstr] = tag
return tag
def _get_post(self, original_id):
return self.session.query(RemotePost) \
.filter(
RemotePost.source == self.source,
RemotePost.original_id == original_id
).one_or_none()
def download(self, id=None, remote_post=None, preview=False):
"""
Creates or updates a RemotePost entry along with all the associated Files,
and downloads all files and thumbnails that aren't present yet.
If remote_post is passed, its original_id will be used and it will be
updated in place.
If preview is set to True, then only the thumbnails are downloaded.
Returns the downloaded RemotePost object.
"""
raise NotImplementedError
def search_form(self):
"""
Returns the form or a list of forms used for searches and subscriptions.
(e.g.: user id, a search string, or advanced options available on the website)
"""
return None
def get_search_details(self, options):
"""
Returns a SearchDetails object with extra details about the search that would
be performed by this set of options (e.g.: user timeline).
May return None if no specific information is found (e.g.: global searches).
"""
return None
def search(self, options):
"""
Creates a temporary search for a given set of search options.
Returns a post iterator object.
"""
if self.iterator is None:
raise NotImplementedError
iterator = self.iterator(self, options=options)
iterator.init()
iterator.reconfigure(direction=FetchDirection.older, num_posts=None)
return iterator
def subscription_repr(self, options):
"""
Returns a simple representation of the subscription, used to find duplicate
subscriptions.
"""
raise NotImplementedError
def subscribe(self, name, options=None, iterator=None):
"""
Creates a Subscription entry for the given search options identified by the given name,
should not get any posts from the post source.
"""
if iterator is None:
iterator = self.iterator(self, options=options)
iterator.init()
sub = Subscription(
source=self.source,
name=name,
repr=self.subscription_repr(iterator.options),
options=iterator.options.to_json(),
state=iterator.state.to_json()
)
self.session.add(sub)
self.session.flush()
iterator.subscription = sub
return iterator
def create_iterator(self, subscription, direction=FetchDirection.newer, num_posts=None):
"""
Gets the post iterator for a specific subscription.
Returns a post iterator object.
"""
if self.iterator is None:
raise NotImplementedError
iterator = self.iterator(self, subscription=subscription)
iterator.init()
iterator.reconfigure(direction=direction, num_posts=num_posts)
return iterator
class MeituClipBatchIter(mx.io.DataIter):
def __init__(self,
datadir,
label_file,
batch_size=4,
n_frame=32,
crop_size=112,
scale_size=128,
train=True,
lru_buffer=120,
gpu_id=0):
super(MeituClipBatchIter, self).__init__(batch_size)
self.datadir = datadir
self.label_file = label_file
self.batch_size = batch_size
self.n_frame = n_frame
self.crop_size = crop_size
self.scale_size = scale_size
self.train = train
self.max_label = 0
self.clip_lst = []
self.load_data()
def evicted(k, v):
print('pop shape', k)
del v
self.nvvl_loader_dict = LRU(lru_buffer, evicted)
self.gpu_id = gpu_id
self.data_size = len(self.clip_lst)
self.process_pool = multiprocessing.Pool(processes=10)
def load_data(self):
if self.train:
video_dir = os.path.join(self.datadir, 'train_collection')
else:
video_dir = os.path.join(self.datadir, 'val_collection')
with open(self.label_file, 'r') as fin:
for line in fin.readlines():
vid_info = line.split(',')
file_name = os.path.join(video_dir, vid_info[0])
labels = [int(id) for id in vid_info[1:]]
self.max_label = max(self.max_label, max(labels))
self.clip_list.append((file_name, labels))
self.max_label = self.max_label + 1
logger.info("load data from %s,num_clip_List %d" %
(video_dir, len(self.clip_list)))
@property
def provide_data(self):
return [
mx.io.DataDesc(name='data',
shape=(self.batch_size, 3, self.n_frame,
self.crop_size, self.crop_size),
dtype=np.float32,
layout='NCTHW')
]
@property
def provide_label(self):
return [
mx.io.DataDesc(name='tags',
shape=(self.batch_size, self.max_label),
dtype=np.float32,
layout='NL')
]
def reset(self):
self.clip_p = 0 # self.clip_p is the index to read batch data
if self.train:
random.shuffle(self.clip_lst)
def next(self):
"""Get next data batch from iterator
:return: DataBatch raise StopIteration if the end of the data is reached
"""
# if self.clip_p<len(self.clip_lst):
# batch_clips = self.clip_lst[self.clip_p:min(self.data_size,self.clip_p+self.batch_size)]
# if len(batch_clips)<self.batch_size:
# batch_clips += random.sample(self.clip_lst,self.batch_size-len(batch_clips))
# #padding to batch_size
# file_names,labels = zip(*batch_clips)
# data = self.sample_clips(file_names)
# #data type is cupy,
# ret = mx.io.DataBatch([mx.nd.array(cupy.asnumpy(data))],[mx.nd.array(label)])
# self.clip_p +=self.batch_size
# return ret
# else:
# raise StopIteration
#Iter single video
# def sample_clips(self,file_names):
# self.process_pool.map(self.decode_func,[(file_names[p], p) for p in range(len(file_names))])
#
# def decode_func(self,filename,p):
if self.clip_p < self.data_size:
filename, tags = self.clip_lst[self.clip_p]
if (self.clip_p + 1) % 6 == 0:
with cupy.cuda.Device(self.gpu_id):
cupy.get_default_memory_pool().free_all_blocks()
video_shape = pynvvl.video_size_from_file(filename)
loader = self.nvvl_loader_dict.get(video_shape, None)
if loader is None:
loader = pynvvl.NVVLVideoLoader(device_id=self.gpu_id,
log_level='error')
self.nvvl_loader_dict[video_shape] = laoder
count = loader.frame_count(filename)
#aug for frame start index
if self.is_train:
if count <= self.n_frame:
frame_start = 0
else:
frame_start = np.random.randint(0,
count - self.n_frame,
dtype=np.int32)
else:
frame_start = (count - self.n_frame) // 2
# rescale argumentation
width, height = video_shape
ow, oh = width, height
if width < height:
ow = self.scale_size
oh = int(self.scale_size * height / width)
else:
oh = self.scale_size
ow = int(self.scale_size * width / height)
#random crop augu
if self.train:
crop_x = np.random.randint(0,
ow - self.crop_size,
dtype=np.int32)
crop_y = np.random.randint(0,
oh - self.crop_size,
dtype=np.int32)
else:
crop_x = (ow - self.crop_size) // 2
crop_y = (oh - self.crop_size) // 2
video = loader.read_sequence(filename,
frame_start,
count=self.n_frame,
sample_model=dense,
horiz_flip=False,
scale_height=oh,
scale_width=ow,
crop_y=crop_y,
crop_x=crop_x,
crop_height=self.crop_size,
crop_width=self.crop_size,
scale_method='Linear',
normalized=False)
labels = np.zeros(shape=(self.max_label), dtype=np.float32)
for tag_index in tags:
labels[tag_index] = 1
video = (video.transpose(0, 2, 3, 1) / 255 - cupy.array(
[0.485, 0.456, 0.406])) / cupy.array([0.229, 0.224, 0.225])
video = video.transpose(3, 0, 1, 2)
ret = mx.io.DataBatch([
mx.nd.aray(video.reshape(1, *video.shape)),
], [
mx.nd.array(labels),
])
self.clip_p += 1
return ret
else:
raise StopIteration
class MTPStorage(MTPEntry, MTPRefresh):
def __init__(self, mtp, pstorage=None):
global PATH_CACHE_SIZE
MTPRefresh.__init__(self)
self.mtp = mtp
self.libmtp = mtp.libmtp
self.open_device = mtp.open_device
self.directories = None
self.contents = LRU(PATH_CACHE_SIZE)
if pstorage is None:
MTPEntry.__init__(self, -3, '/')
self.storage = None
self.directories = []
for dirname in self.mtp.get_storage_descriptions():
#def __init__(self, path, id=-2, storageid=-2, folderid=-2, mtp=None, timestamp=0, is_refresh=True):
self.directories.append(MTPFolder(path=dirname, id= -3, storageid= -3, folderid= -2, is_refresh=False))
self.root = None
self.contents[utf8(os.sep)] = self
else:
self.storage = pstorage
storage = pstorage.contents
self.type = storage.StorageType
self.freespace = storage.FreeSpaceInBytes
self.capacity = storage.MaxCapacity
path = os.sep + storage.StorageDescription
MTPEntry.__init__(self, storage.id, path, storageid=None, folderid=0)
self.root = MTPFolder(path=path, id=0, storageid=storage.id, folderid=0, mtp=self.mtp)
self.contents[utf8(path)] = self.root
def is_directory(self):
return True
def get_attributes(self):
return { 'st_atime': self.timestamp, 'st_ctime': self.timestamp, 'st_gid': os.getgid(),
'st_mode': stat.S_IFDIR | 0755, 'st_mtime': self.timestamp, 'st_nlink': 1,
'st_size': 0, 'st_uid': os.getuid() }
def get_directories(self):
if self.directories is None:
if self.root is None:
return ()
else:
return self.root.get_directories()
else:
return self.directories
def get_files(self):
if self.root is None:
return ()
else:
return self.root.get_files()
def add_file(self, file):
if not self.root is None:
self.root.add_file(self, file)
def __str__(self):
s = "MTPStorage %s: id=%d, device=%s%s" % (self.name, self.id, self.open_device, os.linesep)
return s
def find_entry(self, path):
path = utf8(path)
self.log.debug('find_entry(%s)' % (path,))
try:
if path.strip() == '':
path = os.sep + self.name
entry = self.contents.get(path)
if entry is None:
components = [comp for comp in path.split(os.sep) if len(comp.strip()) != 0]
if len(components) == 0:
return None
if components[0] != self.name:
raise LookupError('Invalid storage (expected %s, was %s)' % (self.name, components[0]))
entry = self.__find_entry(self.root, components[1:])
else:
if entry.is_directory() and entry.must_refresh:
entry.refresh()
return entry
except:
self.log.exception("")
return None
def __find_entry(self, entry, components):
self.log.debug("__find_entry(%s, %s)" % (entry, str(components)))
if len(components) == 0:
return entry
name = components[0]
path = entry.path + os.sep + name
en = self.contents.get(utf8(path))
if not en is None:
if en.is_directory() and en.must_refresh:
en.refresh()
return self.__find_entry(en, components[1:])
en = entry.find_directory(name)
if not en is None and en.is_directory():
self.contents[utf8(path)] = en
if en.must_refresh:
en.refresh()
return self.__find_entry(en, components[1:])
return entry.find_file(name)
def remove_entry(self, path):
try:
return self.contents.pop(utf8(path))
except:
#self.log.warn('MTPStorage.remove_entry: %s not found' % (path,))
return None
def refresh(self):
if not self.root is None and self.must_refresh:
self.must_refresh = not self.root.refresh()
def close(self):
pass
class MTPFS(LoggingMixIn, Operations):
def __init__(self, mtp, mountpoint, is_debug=False, logger=None):
global VERBOSE
self.mtp = mtp
self.is_debug = is_debug
self.tempdir = tempfile.mkdtemp(prefix='pymtpfs')
if not bool(self.tempdir) or not os.path.exists(self.tempdir):
self.tempdir = tempfile.gettempdir()
self.read_timeout = 2
self.write_timeout = 2
self.openfile_t = namedtuple('openfile', 'handle, path, mtp_path, readonly')
self.openfiles = {}
self.log = logger
self.created = LRU(1000)
if VERBOSE:
print("Mounted %s on %s" % (self.mtp, ))
self.log.info("Mounted %s on %s" % (self.mtp, mountpoint))
def __openfile_by_path(self, path):
return next((en for en in self.openfiles.values() if en.mtp_path == path), None)
def destroy(self, path):
self.mtp.close()
for openfile in self.openfiles.values():
try:
os.close(openfile.handle)
except:
self.log.exception("")
try:
if self.tempdir != tempfile.gettempdir():
shutil.rmtree(self.tempdir)
except:
self.log.exception("")
return 0
def chmod(self, path, mode):
return 0
def chown(self, path, uid, gid):
return 0
# @log_calls
def getattr(self, path, fh=None):
attrib = {}
path = fix_path(path, self.log)
entry = self.mtp.get_path(path)
if entry is None:
entry = self.created.get(path)
if entry is None:
raise FuseOSError(errno.ENOENT)
else:
try:
attrib = entry.get_attributes()
except Exception, e:
self.log.exception("")
attrib = {}
exmess = ""
try:
exmess = str(e.message)
except:
exmess = "Unknown"
self.log.error('Error reading MTP attributes for %s (%s)' % (path, exmess))
raise FuseOSError(errno.ENOENT)
return attrib
class Network(Service, NetworkAPI):
logger = logging.getLogger("ddht.Network")
_bootnodes: Tuple[ENRAPI, ...]
def __init__(
self,
client: ClientAPI,
bootnodes: Collection[ENRAPI],
) -> None:
self.client = client
self._bootnodes = tuple(bootnodes)
self.routing_table = KademliaRoutingTable(
self.client.enr_manager.enr.node_id,
ROUTING_TABLE_BUCKET_SIZE,
)
self._routing_table_ready = trio.Event()
self._last_pong_at = LRU(2048)
#
# Proxied ClientAPI properties
#
@property
def local_node_id(self) -> NodeID:
return self.client.local_node_id
@property
def events(self) -> EventsAPI:
return self.client.events
@property
def dispatcher(self) -> DispatcherAPI:
return self.client.dispatcher
@property
def enr_manager(self) -> ENRManagerAPI:
return self.client.enr_manager
@property
def pool(self) -> PoolAPI:
return self.client.pool
@property
def enr_db(self) -> ENRDatabaseAPI:
return self.client.enr_db
#
# High Level API
#
async def bond(self,
node_id: NodeID,
*,
endpoint: Optional[Endpoint] = None) -> bool:
try:
pong = await self.ping(node_id, endpoint=endpoint)
except trio.TooSlowError:
self.logger.debug("Bonding with %s timed out during ping",
humanize_node_id(node_id))
return False
try:
enr = self.enr_db.get_enr(node_id)
except KeyError:
try:
enr = await self.get_enr(node_id, endpoint=endpoint)
except trio.TooSlowError:
self.logger.debug(
"Bonding with %s timed out during ENR retrieval",
humanize_node_id(node_id),
)
return False
else:
if pong.enr_seq > enr.sequence_number:
try:
enr = await self.get_enr(node_id, endpoint=endpoint)
except trio.TooSlowError:
self.logger.debug(
"Bonding with %s timed out during ENR retrieval",
humanize_node_id(node_id),
)
else:
self.enr_db.set_enr(enr)
self.routing_table.update(enr.node_id)
self._routing_table_ready.set()
return True
async def _bond(self, node_id: NodeID, endpoint: Endpoint) -> None:
await self.bond(node_id, endpoint=endpoint)
async def ping(self,
node_id: NodeID,
*,
endpoint: Optional[Endpoint] = None) -> PongMessage:
if endpoint is None:
endpoint = self._endpoint_for_node_id(node_id)
response = await self.client.ping(endpoint, node_id)
return response.message
async def find_nodes(
self,
node_id: NodeID,
*distances: int,
endpoint: Optional[Endpoint] = None,
) -> Tuple[ENRAPI, ...]:
if not distances:
raise TypeError("Must provide at least one distance")
if endpoint is None:
endpoint = self._endpoint_for_node_id(node_id)
responses = await self.client.find_nodes(endpoint,
node_id,
distances=distances)
return tuple(enr for response in responses
for enr in response.message.enrs)
async def get_enr(self,
node_id: NodeID,
*,
endpoint: Optional[Endpoint] = None) -> ENRAPI:
enrs = await self.find_nodes(node_id, 0, endpoint=endpoint)
if not enrs:
raise Exception("Invalid response")
# This reduce accounts for
return _reduce_enrs(enrs)[0]
async def recursive_find_nodes(self, target: NodeID) -> Tuple[ENRAPI, ...]:
self.logger.debug("Recursive find nodes: %s", humanize_node_id(target))
queried_node_ids = set()
unresponsive_node_ids = set()
received_enrs: List[ENRAPI] = []
received_node_ids: Set[NodeID] = set()
async def do_lookup(node_id: NodeID) -> None:
queried_node_ids.add(node_id)
distance = compute_log_distance(node_id, target)
try:
enrs = await self.find_nodes(node_id, distance)
except trio.TooSlowError:
unresponsive_node_ids.add(node_id)
return
for enr in enrs:
received_node_ids.add(enr.node_id)
try:
self.enr_db.set_enr(enr)
except OldSequenceNumber:
received_enrs.append(self.enr_db.get_enr(enr.node_id))
else:
received_enrs.append(enr)
for lookup_round_counter in itertools.count():
candidates = iter_closest_nodes(target, self.routing_table,
received_node_ids)
responsive_candidates = itertools.dropwhile(
lambda node: node in unresponsive_node_ids, candidates)
closest_k_candidates = take(self.routing_table.bucket_size,
responsive_candidates)
closest_k_unqueried_candidates = (
candidate for candidate in closest_k_candidates
if candidate not in queried_node_ids)
nodes_to_query = tuple(take(3, closest_k_unqueried_candidates))
if nodes_to_query:
self.logger.debug(
"Starting lookup round %d for %s",
lookup_round_counter + 1,
humanize_node_id(target),
)
async with trio.open_nursery() as nursery:
for peer in nodes_to_query:
nursery.start_soon(do_lookup, peer)
else:
self.logger.debug(
"Lookup for %s finished in %d rounds",
humanize_node_id(target),
lookup_round_counter,
)
break
# now sort and return the ENR records in order of closesness to the target.
return tuple(
sorted(
_reduce_enrs(received_enrs),
key=lambda enr: compute_distance(enr.node_id, target),
))
#
# Long Running Processes
#
async def run(self) -> None:
self.manager.run_daemon_child_service(self.client)
await self.client.wait_listening()
self.manager.run_daemon_task(self._ping_oldest_routing_table_entry)
self.manager.run_daemon_task(self._track_last_pong)
self.manager.run_daemon_task(self._manage_routing_table)
self.manager.run_daemon_task(self._pong_when_pinged)
self.manager.run_daemon_task(self._serve_find_nodes)
await self.manager.wait_finished()
async def _periodically_report_routing_table(self) -> None:
async for _ in every(30, initial_delay=30):
non_empty_buckets = tuple((idx, bucket)
for idx, bucket in enumerate(
reversed(self.routing_table.buckets))
if bucket)
total_size = sum(len(bucket) for idx, bucket in non_empty_buckets)
bucket_info = "|".join(
tuple(f"{idx}:{len(bucket)}"
for idx, bucket in non_empty_buckets))
self.logger.debug(
"routing-table-info: size=%d buckets=%s",
total_size,
bucket_info,
)
async def _ping_oldest_routing_table_entry(self) -> None:
await self._routing_table_ready.wait()
while self.manager.is_running:
# Here we preserve the lazy iteration while still checking that the
# iterable is not empty before passing it into `min` below which
# throws an ambiguous `ValueError` otherwise if the iterable is
# empty.
nodes_iter = self.routing_table.iter_all_random()
try:
first_node_id = first(nodes_iter)
except StopIteration:
await trio.sleep(ROUTING_TABLE_KEEP_ALIVE)
continue
else:
least_recently_ponged_node_id = min(
cons(first_node_id, nodes_iter),
key=lambda node_id: self._last_pong_at.get(node_id, 0),
)
too_old_at = trio.current_time() - ROUTING_TABLE_KEEP_ALIVE
try:
last_pong_at = self._last_pong_at[
least_recently_ponged_node_id]
except KeyError:
pass
else:
if last_pong_at > too_old_at:
await trio.sleep(last_pong_at - too_old_at)
continue
did_bond = await self.bond(least_recently_ponged_node_id)
if not did_bond:
self.routing_table.remove(least_recently_ponged_node_id)
async def _track_last_pong(self) -> None:
async with self.dispatcher.subscribe(PongMessage) as subscription:
async for message in subscription:
self._last_pong_at[
message.sender_node_id] = trio.current_time()
async def _manage_routing_table(self) -> None:
# First load all the bootnode ENRs into our database
for enr in self._bootnodes:
try:
self.enr_db.set_enr(enr)
except OldSequenceNumber:
pass
# Now repeatedly try to bond with each bootnode until one succeeds.
async with trio.open_nursery() as nursery:
while self.manager.is_running:
for enr in self._bootnodes:
if enr.node_id == self.local_node_id:
continue
endpoint = self._endpoint_for_enr(enr)
nursery.start_soon(self._bond, enr.node_id, endpoint)
with trio.move_on_after(10):
await self._routing_table_ready.wait()
break
# TODO: Need better logic here for more quickly populating the
# routing table. Should start off aggressively filling in the
# table, only backing off once the table contains some minimum
# number of records **or** searching for new records fails to find
# new nodes. Maybe use a TokenBucket
async for _ in every(30):
async with trio.open_nursery() as nursery:
target_node_id = NodeID(secrets.token_bytes(32))
found_enrs = await self.recursive_find_nodes(target_node_id)
for enr in found_enrs:
endpoint = self._endpoint_for_enr(enr)
nursery.start_soon(self._bond, enr.node_id, endpoint)
async def _pong_when_pinged(self) -> None:
async with self.dispatcher.subscribe(PingMessage) as subscription:
async for request in subscription:
await self.dispatcher.send_message(
request.to_response(
PongMessage(
request.message.request_id,
self.enr_manager.enr.sequence_number,
request.sender_endpoint.ip_address,
request.sender_endpoint.port,
)))
async def _serve_find_nodes(self) -> None:
async with self.dispatcher.subscribe(FindNodeMessage) as subscription:
async for request in subscription:
response_enrs: List[ENRAPI] = []
distances = set(request.message.distances)
if len(distances) != len(request.message.distances):
self.logger.debug(
"Ignoring invalid FindNodeMessage from %s@%s: duplicate distances",
humanize_node_id(request.sender_node_id),
request.sender_endpoint,
)
continue
elif not distances:
self.logger.debug(
"Ignoring invalid FindNodeMessage from %s@%s: empty distances",
humanize_node_id(request.sender_node_id),
request.sender_endpoint,
)
continue
elif any(distance > self.routing_table.num_buckets
for distance in distances):
self.logger.debug(
"Ignoring invalid FindNodeMessage from %s@%s: distances: %s",
humanize_node_id(request.sender_node_id),
request.sender_endpoint,
distances,
)
continue
for distance in distances:
if distance == 0:
response_enrs.append(self.enr_manager.enr)
elif distance <= self.routing_table.num_buckets:
node_ids_at_distance = self.routing_table.get_nodes_at_log_distance(
distance, )
for node_id in node_ids_at_distance:
response_enrs.append(self.enr_db.get_enr(node_id))
else:
raise Exception("Should be unreachable")
await self.client.send_found_nodes(
request.sender_endpoint,
request.sender_node_id,
enrs=response_enrs,
request_id=request.message.request_id,
)
#
# Utility
#
def _endpoint_for_enr(self, enr: ENRAPI) -> Endpoint:
try:
ip_address = enr[IP_V4_ADDRESS_ENR_KEY]
port = enr[UDP_PORT_ENR_KEY]
except KeyError:
raise Exception("Missing endpoint address information: ")
return Endpoint(ip_address, port)
def _endpoint_for_node_id(self, node_id: NodeID) -> Endpoint:
enr = self.enr_db.get_enr(node_id)
return self._endpoint_for_enr(enr)
class Osu(Cog):
"""osu! API commands."""
def __init__(self, config, attr):
self.attr = attr
self.api_key = config.register("api_key")
self.osuapi = osuapi.OsuApi(
self.api_key(),
connector=osuapi.AHConnector(
aiohttp.ClientSession(loop=asyncio.get_event_loop())))
self._osu_presence_username_cache = LRU(4 << 10)
self._beatmap_cache = LRU(256)
def cog_unload(self):
self.osuapi.close()
async def _set_osu_username(self, user, username):
"""Set :user's osu account to :username. Returns api result."""
osu_acct = await self._lookup_acct(username)
await self.attr.set_attributes(user, osu_id=osu_acct.user_id)
return osu_acct
async def _lookup_acct(self, username, mode=OsuMode.osu):
res = await self.osuapi.get_user(username, mode=mode)
if len(res) == 0:
raise errors.BadArgument(
"There is no osu user by the name {}".format(username))
return res[0]
@Cog.listener()
async def on_member_update(self, before, member):
if member.activity and member.activity.name == "osu!" and isinstance(
member.activity, discord.Activity):
rp = OsuRichPresence(member.activity)
if rp.username:
self._osu_presence_username_cache[member.id] = rp.username
@command()
async def setosu(self, ctx, *, username: str):
"""Set your osu account to be remembered by the bot."""
with ctx.typing():
osu_acct = await self._set_osu_username(ctx.message.author,
username)
await ctx.send(
"OK, set your osu account to {0.username} ({0.user_id})".format(
osu_acct))
@command(aliases=['osuwatch'])
async def watchosu(self, ctx, *, account: StringOrMentionConverter = None):
"""Shows a osu spectate link
Use + to give a raw account name. e.g.:
osu +cookiezi
osu @ppy
"""
account = account or ctx.message.author
if isinstance(account, discord.abc.User):
user_osu_id = await self.attr.get_attribute(account, 'osu_id')
if user_osu_id is None:
await ctx.send("I don't know your osu name! "
"Use {}setosu <name> to set it!".format(
ctx.prefix))
return
else:
user_osu_id = account
await ctx.send("<osu://spectate/{}>".format(user_osu_id))
async def _get_osu_account(self, ctx, user, mode):
osu_user_id = await self.attr.get_attribute(user, 'osu_id')
if osu_user_id:
return await self._lookup_acct(osu_user_id, mode=mode)
if ctx.author.id != user.id:
raise errors.BadArgument(
"I don't know {}'s osu username!".format(user))
presence_username = self._osu_presence_username_cache.get(user.id)
clean_prefix = utils.clean_double_backtick(ctx.prefix)
if presence_username:
await ctx.send(
"I don't know your osu username! I'm setting your osu username "
"to {}, which rich presence showed you recently playing as. "
"If this is wrong use ``{}setosu <username>``".format(
presence_username, clean_prefix))
return await self._set_osu_username(user, presence_username)
await ctx.send(
"I don't know your osu username! I'm setting your osu username "
"to {}, if this is wrong use ``{}setosu <username>``".format(
user.name, clean_prefix))
return await self._set_osu_username(user, user.name)
async def _get_beatmap(self, beatmap_id):
if beatmap_id in self._beatmap_cache:
return self._beatmap_cache[beatmap_id]
beatmaps = await self.osuapi.get_beatmaps(beatmap_id=beatmap_id)
if not beatmaps:
return None
self._beatmap_cache[beatmap_id] = beatmaps[0]
return beatmaps[0]
@command(aliases=['taikorecent', 'ctbrecent', 'maniarecent'])
async def osurecent(self,
ctx,
*,
account: StringOrMentionConverter = None):
"""Show a user's recent osu plays.
Use + to give a raw account name. e.g.:
osu +cookiezi
osu @ppy
"""
account = account or ctx.message.author
mode = {
'osurecent': OsuMode.osu,
'taikorecent': OsuMode.taiko,
'maniarecent': OsuMode.mania,
'ctbrecent': OsuMode.ctb
}[ctx.invoked_with]
with ctx.typing():
if account is None:
raise errors.BadArgument("Invalid mention...!")
if isinstance(account, discord.abc.User):
osu_acct = await self._get_osu_account(ctx, account, mode)
else:
osu_acct = await self._lookup_acct(account, mode=mode)
recent_scores = await self.osuapi.get_user_recent(osu_acct.user_id,
mode=mode)
embed = discord.Embed()
embed = discord.Embed()
embed.title = osu_acct.username
embed.url = "https://osu.ppy.sh/u/%s" % osu_acct.user_id
embed.color = hash(str(osu_acct.user_id)) % (1 << 24)
if isinstance(account, discord.abc.User):
embed.set_author(
name=str(account),
icon_url=account.avatar_url_as(static_format="png"))
if not recent_scores:
embed.description = "%s hasn't played %s recently" % (
osu_acct.username, mode.name)
else:
map_descriptions = []
expected_len = 0
for score in recent_scores:
beatmap = await self._get_beatmap(score.beatmap_id)
if not beatmap:
continue
entry = (
"**{rank}{mods} - {score.score:,} ({percent:.2f}%) {score.maxcombo}x - {map.difficultyrating:.2f} Stars** - {ago}\n"
"[{map.artist} - {map.title}[{map.version}]]({map.url}) by [{map.creator}](https://osu.ppy.sh/u/{map.creator_id})"
).format(rank=score.rank.upper(),
mods=" +{:s}".format(score.enabled_mods)
if score.enabled_mods.value else "",
percent=100 * score.accuracy(mode),
ago=humanize.naturaltime(score.date + DATE_OFFSET),
score=score,
map=beatmap)
if expected_len + len(entry) + 1 <= 2048:
map_descriptions.append(entry)
expected_len += len(entry) + 1
else:
break
embed.description = "\n".join(map_descriptions)
await ctx.send(embed=embed)
@command(pass_context=True, aliases=['taiko', 'ctb', 'mania'])
async def osu(self, ctx, *, account: StringOrMentionConverter = None):
"""Show a user's osu profile.
Use + to give a raw account name. e.g.:
osu +cookiezi
osu @ppy
"""
account = account or ctx.message.author
mode = {
'osu': OsuMode.osu,
'taiko': OsuMode.taiko,
'mania': OsuMode.mania,
'ctb': OsuMode.ctb
}[ctx.invoked_with]
with ctx.typing():
if account is None:
raise errors.BadArgument("Invalid mention...!")
if isinstance(account, discord.abc.User):
osu_acct = await self._get_osu_account(ctx, account, mode)
else:
osu_acct = await self._lookup_acct(account, mode=mode)
usrscore = await self.osuapi.get_user_best(osu_acct.user_id,
limit=100,
mode=mode)
embed = discord.Embed()
embed.title = osu_acct.username
embed.url = "https://osu.ppy.sh/u/%s" % osu_acct.user_id
embed.color = hash(str(osu_acct.user_id)) % (1 << 24)
if isinstance(account, discord.abc.User):
embed.set_author(
name=str(account),
icon_url=account.avatar_url_as(static_format="png"))
embed.set_thumbnail(url="http://a.ppy.sh/%s?_=%s" %
(osu_acct.user_id, time.time()))
if not usrscore:
embed.description = "%s has never played %s" % (osu_acct.username,
ctx.invoked_with)
else:
embed.description = "#{0.pp_rank:,} ({0.pp_raw} pp)".format(
osu_acct)
fave_mod = collections.Counter(
play.enabled_mods for play in usrscore).most_common()[0][0]
bplay = usrscore[0]
embed.add_field(name="Plays",
value="{:,}".format(osu_acct.playcount))
embed.add_field(name="Hits",
value="{:,}".format(osu_acct.total_hits))
embed.add_field(name="Acc",
value="{:.2f}".format(osu_acct.accuracy))
embed.add_field(name="Best Play",
value="{:,}pp {:s}".format(bplay.pp,
bplay.enabled_mods))
embed.add_field(name="Favorite Mod", value="{:l}".format(fave_mod))
await ctx.send(embed=embed)
class PolygonIndex(object):
include_only_properties = None
simplify_tolerance = 0.0001
preserve_topology = True
persistent_polygons = False
cache_size = 0
fix_invalid_polygons = False
INDEX_FILENAME = None
POLYGONS_DB_DIR = 'polygons'
def __init__(self, index=None, polygons=None, polygons_db=None, save_dir=None,
index_filename=None,
polygons_db_path=None,
include_only_properties=None):
if save_dir:
self.save_dir = save_dir
else:
self.save_dir = None
if not index_filename:
index_filename = self.INDEX_FILENAME
self.index_path = os.path.join(save_dir or '.', index_filename)
if not index:
self.create_index(overwrite=True)
else:
self.index = index
if include_only_properties and hasattr(include_only_properties, '__contains__'):
self.include_only_properties = include_only_properties
if not polygons and not self.persistent_polygons:
self.polygons = {}
elif polygons and not self.persistent_polygons:
self.polygons = polygons
elif self.persistent_polygons and self.cache_size > 0:
self.polygons = LRU(self.cache_size)
if polygons:
for key, value in six.iteritems(polygons):
self.polygons[key] = value
self.cache_hits = 0
self.cache_misses = 0
self.get_polygon = self.get_polygon_cached
if not polygons_db_path:
polygons_db_path = os.path.join(save_dir or '.', self.POLYGONS_DB_DIR)
if not polygons_db:
self.polygons_db = LevelDB(polygons_db_path)
else:
self.polygons_db = polygons_db
self.setup()
self.i = 0
def create_index(self, overwrite=False):
raise NotImplementedError('Children must implement')
def index_polygon(self, polygon):
raise NotImplementedError('Children must implement')
def setup(self):
pass
def clear_cache(self, garbage_collect=True):
if self.persistent_polygons and self.cache_size > 0:
self.polygons.clear()
if garbage_collect:
gc.collect()
def simplify_polygon(self, poly, simplify_tolerance=None, preserve_topology=None):
if simplify_tolerance is None:
simplify_tolerance = self.simplify_tolerance
if preserve_topology is None:
preserve_topology = self.preserve_topology
return poly.simplify(simplify_tolerance, preserve_topology=preserve_topology)
def index_polygon_properties(self, properties):
pass
def polygon_geojson(self, poly, properties):
return {
'type': 'Feature',
'geometry': mapping(poly),
}
def add_polygon(self, poly, properties, cache=False, include_only_properties=None):
if include_only_properties is not None:
properties = {k: v for k, v in properties.iteritems() if k in include_only_properties}
if not self.persistent_polygons or cache:
self.polygons[self.i] = prep(poly)
if self.persistent_polygons:
self.polygons_db.Put(self.polygon_key(self.i), json.dumps(self.polygon_geojson(poly, properties)))
self.polygons_db.Put(self.properties_key(self.i), json.dumps(properties))
self.index_polygon_properties(properties)
self.i += 1
@classmethod
def create_from_shapefiles(cls, inputs, output_dir,
index_filename=None,
include_only_properties=None):
index = cls(save_dir=output_dir, index_filename=index_filename or cls.INDEX_FILENAME)
for input_file in inputs:
if include_only_properties is not None:
include_props = include_only_properties.get(input_file, cls.include_only_properties)
else:
include_props = cls.include_only_properties
f = fiona.open(input_file)
index.add_geojson_like_file(f)
return index
@classmethod
def fix_polygon(cls, poly):
'''
Coerce to valid polygon
'''
if not poly.is_valid:
poly = poly.buffer(0)
if not poly.is_valid:
return None
return poly
@classmethod
def to_polygon(cls, coords, holes=None, test_point=None):
'''
Create shapely polygon from list of coordinate tuples if valid
'''
if not coords or len(coords) < 3:
return None
# Fix for polygons crossing the 180th meridian
lons = [lon for lon, lat in coords]
if (max(lons) - min(lons) > 180):
coords = [(lon + 360.0 if lon < 0 else lon, lat) for lon, lat in coords]
if holes:
holes = [(lon + 360.0 if lon < 0 else lon, lat) for lon, lat in holes]
poly = Polygon(coords, holes)
try:
if test_point is None:
test_point = poly.representative_point()
invalid = cls.fix_invalid_polygons and not poly.is_valid and not poly.contains(test_point)
except Exception:
invalid = True
if invalid:
try:
poly_fix = cls.fix_polygon(poly)
if poly_fix is not None and poly_fix.bounds and len(poly_fix.bounds) == 4 and poly_fix.is_valid and poly_fix.type == poly.type:
if test_point is None:
test_point = poly_fix.representative_point()
if poly_fix.contains(test_point):
poly = poly_fix
except Exception:
pass
return poly
def add_geojson_like_record(self, rec, include_only_properties=None):
if not rec or not rec.get('geometry') or 'type' not in rec['geometry']:
return
poly_type = rec['geometry']['type']
if poly_type == 'Polygon':
coords = rec['geometry']['coordinates'][0]
poly = self.to_polygon(coords)
if poly is None or not poly.bounds or len(poly.bounds) != 4:
return
self.index_polygon(poly)
self.add_polygon(poly, rec['properties'], include_only_properties=include_only_properties)
elif poly_type == 'MultiPolygon':
polys = []
poly_coords = rec['geometry']['coordinates']
for coords in poly_coords:
poly = self.to_polygon(coords[0])
if poly is None or not poly.bounds or len(poly.bounds) != 4:
continue
polys.append(poly)
self.index_polygon(poly)
self.add_polygon(MultiPolygon(polys), rec['properties'], include_only_properties=include_only_properties)
else:
return
def add_geojson_like_file(self, f, include_only_properties=None):
'''
Add either GeoJSON or a shapefile record to the index
'''
for rec in f:
self.add_geojson_like_record(rec, include_only_properties=include_only_properties)
@classmethod
def create_from_geojson_files(cls, inputs, output_dir,
index_filename=None,
polys_filename=DEFAULT_POLYS_FILENAME,
include_only_properties=None):
index = cls(save_dir=output_dir, index_filename=index_filename or cls.INDEX_FILENAME)
for input_file in inputs:
if include_only_properties is not None:
include_props = include_only_properties.get(input_file, cls.include_only_properties)
else:
include_props = cls.include_only_properties
f = json.load(open(input_file))
index.add_geojson_like_file(f['features'], include_only_properties=include_props)
return index
def compact_polygons_db(self):
self.polygons_db.CompactRange('\x00', '\xff')
def save(self):
self.save_index()
self.save_properties(os.path.join(self.save_dir, DEFAULT_PROPS_FILENAME))
if not self.persistent_polygons:
self.save_polygons(os.path.join(self.save_dir, DEFAULT_POLYS_FILENAME))
self.compact_polygons_db()
self.save_polygon_properties(self.save_dir)
def load_properties(self, filename):
properties = json.load(open(filename))
self.i = int(properties.get('num_polygons', self.i))
def save_properties(self, out_filename):
out = open(out_filename, 'w')
json.dump({'num_polygons': str(self.i)}, out)
def save_polygons(self, out_filename):
out = open(out_filename, 'w')
for i in xrange(self.i):
poly = self.polygons[i]
feature = {
'type': 'Feature',
'geometry': mapping(poly.context),
}
out.write(json.dumps(feature) + u'\n')
def save_index(self):
raise NotImplementedError('Children must implement')
def load_polygon_properties(self, d):
pass
def save_polygon_properties(self, d):
pass
@classmethod
def polygon_from_geojson(cls, feature):
poly_type = feature['geometry']['type']
if poly_type == 'Polygon':
coords = feature['geometry']['coordinates']
poly = cls.to_polygon(coords[0], holes=coords[1:] or None)
return poly
elif poly_type == 'MultiPolygon':
polys = []
for coords in feature['geometry']['coordinates']:
poly = cls.to_polygon(coords[0], holes=coords[1:] or None)
polys.append(poly)
return MultiPolygon(polys)
@classmethod
def load_polygons(cls, filename):
f = open(filename)
polygons = {}
cls.i = 0
for line in f:
feature = json.loads(line.rstrip())
polygons[cls.i] = prep(cls.polygon_from_geojson(feature))
cls.i += 1
return polygons
@classmethod
def load_index(cls, d, index_name=None):
raise NotImplementedError('Children must implement')
@classmethod
def load(cls, d, index_name=None, polys_filename=DEFAULT_POLYS_FILENAME,
properties_filename=DEFAULT_PROPS_FILENAME,
polys_db_dir=POLYGONS_DB_DIR):
index = cls.load_index(d, index_name=index_name or cls.INDEX_FILENAME)
if not cls.persistent_polygons:
polys = cls.load_polygons(os.path.join(d, polys_filename))
else:
polys = None
polygons_db = LevelDB(os.path.join(d, polys_db_dir))
polygon_index = cls(index=index, polygons=polys, polygons_db=polygons_db, save_dir=d)
polygon_index.load_properties(os.path.join(d, properties_filename))
polygon_index.load_polygon_properties(d)
return polygon_index
def get_candidate_polygons(self, lat, lon):
raise NotImplementedError('Children must implement')
def get_properties(self, i):
return json.loads(self.polygons_db.Get(self.properties_key(i)))
def get_polygon(self, i):
return self.polygons[i]
def get_polygon_cached(self, i):
poly = self.polygons.get(i, None)
if poly is None:
data = json.loads(self.polygons_db.Get(self.polygon_key(i)))
poly = prep(self.polygon_from_geojson(data))
self.polygons[i] = poly
self.cache_misses += 1
else:
self.cache_hits += 1
return poly
def __iter__(self):
for i in xrange(self.i):
yield self.get_properties(i), self.get_polygon(i)
def __len__(self):
return self.i
def polygons_contain(self, candidates, point, return_all=False):
containing = None
if return_all:
containing = []
for i in candidates:
poly = self.get_polygon(i)
contains = poly.contains(point)
if contains:
properties = self.get_properties(i)
if not return_all:
return properties
else:
containing.append(properties)
return containing
def polygon_key(self, i):
return 'poly:{}'.format(i)
def properties_key(self, i):
return 'props:{}'.format(i)
def point_in_poly(self, lat, lon, return_all=False):
candidates = self.get_candidate_polygons(lat, lon)
point = Point(lon, lat)
return self.polygons_contain(candidates, point, return_all=return_all)
class MTPFS(LoggingMixIn, Operations):
def __init__(self, mtp, mountpoint, is_debug=False, logger=None):
global VERBOSE
self.mtp = mtp
self.is_debug = is_debug
self.tempdir = tempfile.mkdtemp(prefix='pymtpfs')
if not bool(self.tempdir) or not os.path.exists(self.tempdir):
self.tempdir = tempfile.gettempdir()
self.read_timeout = 2
self.write_timeout = 2
self.openfile_t = namedtuple('openfile',
'handle, path, mtp_path, readonly')
self.openfiles = {}
self.log = logger
self.created = LRU(1000)
if VERBOSE:
print("Mounted %s on %s" % (self.mtp, ))
self.log.info("Mounted %s on %s" % (self.mtp, mountpoint))
def __openfile_by_path(self, path):
return next(
(en for en in self.openfiles.values() if en.mtp_path == path),
None)
def destroy(self, path):
self.mtp.close()
for openfile in self.openfiles.values():
try:
os.close(openfile.handle)
except:
self.log.exception("")
try:
if self.tempdir != tempfile.gettempdir():
shutil.rmtree(self.tempdir)
except:
self.log.exception("")
return 0
def chmod(self, path, mode):
return 0
def chown(self, path, uid, gid):
return 0
# @log_calls
def getattr(self, path, fh=None):
attrib = {}
path = fix_path(path, self.log)
entry = self.mtp.get_path(path)
if entry is None:
entry = self.created.get(path)
if entry is None:
raise FuseOSError(errno.ENOENT)
else:
try:
attrib = entry.get_attributes()
except Exception, e:
self.log.exception("")
attrib = {}
exmess = ""
try:
exmess = str(e.message)
except:
exmess = "Unknown"
self.log.error('Error reading MTP attributes for %s (%s)' %
(path, exmess))
raise FuseOSError(errno.ENOENT)
return attrib
class Cache:
# Replacement policies
LRU = "LRU"
FIFO = 'FIFO'
def __init__(self, name, size, policy):
self.name = name
self.size = size
self.free_space = size
self.policy = policy # Eviction policy
self.hashmap = {} # Mapping <objname,objsize>
if (self.policy == Cache.LRU):
self.cache = LRU(self.size)
elif (self.policy == Cache.FIFO):
self.cache = queue.Queue(maxsize=self.size)
# Statistics
self.hit_count = 0
self.miss_count = 0
def has_key(self, key):
if key in self.hashmap.keys():
return True
else:
return False
def update(self, key, size):
self.hashmap[key] = size
self.hit_count += 1
if (self.policy == Cache.LRU):
self.cache.update(key=size)
elif (self.policy == Cache.FIFO):
self.cache.put(key)
def insert(self, key, size, directory):
if (self.policy == Cache.LRU):
self.insertLRU(key, size, directory)
elif (self.policy == Cache.FIFO):
self.insertFIFO(key, size, directory)
def evictLRU(self, directory):
oid = self.cache.peek_last_item()[0]
directory.removeBlock(oid, self.name)
del [oid]
del self.hashmap[oid]
self.free_space += int(self.hashmap[oid])
def evictFIFO(self, directory):
oid = self.cache.get()
directory.removeBlock(oid, self.name)
self.free_space += int(self.hashmap[oid])
del self.hashmap[oid]
def insertLRU(self, key, size, directory):
while (int(size) >= self.free_space):
self.evictLRU(directory)
self.cache[key] = size
self.hashmap[key] = size
self.free_space += size
self.miss_count += 1
def insertFIFO(self, key, size, directory):
while (int(size) >= self.free_space):
self.evictFIFO(directory)
self.cache.put(key)
self.hashmap[key] = size
self.free_space += size
self.miss_count += 1
def put(self, key, size, directory):
if self.has_key(key):
self.update(key, size)
else:
self.insert(key, size, directory)
def print(self):
if (self.policy == Cache.LRU):
print(self.name, "LRU", self.hashmap, self.cache.items())
elif (self.policy == Cache.FIFO):
print(self.name, "LRU", self.hashmap, list(self.cache.queue))
def remove(self, key):
del self.hashmap[key]
if (self.policy == Cache.LRU):
del self.cache[key]
elif (self.policy == Cache.FIFO):
a = 5
session.close()
df_relevant_posts = get_relevant_posts(ssh, db_host, db_user,
db_password, db_port,
database_name, ssh_username,
ssh_password)
# print(df_relevant_posts)
relevant_posts = df_relevant_posts.to_dict('records')
logger.info(f'Relevant posts: {len(relevant_posts)}')
posts_to_update = []
for relevant_post in relevant_posts:
# message_id, conversation_replies, likes_total
current_id = relevant_post['message_id']
values = {}
current_post_prev_version = processed_posts.get(
current_id, None)
if relevant_post != current_post_prev_version:
processed_posts[current_id] = relevant_post
posts_to_update.append(
(current_id, compute_impact(relevant_post),
relevant_post['post_type']))
# Even if the post doesn't change, we may want to recalculate the impact every several seconds
delta_since_last_recalculation_ms = get_utc_now(
) - last_impact_recalculation_epoch_ms
logger.info(
f'Posts to update: {len(posts_to_update)}. Milisecs since last recalculation: {delta_since_last_recalculation_ms}'
)
if len(
