def textrank_algorithm(self) -> None:
G, d = self._graph, self.damping_factor
k = len(G)
outgoing = G.sum(0)
scores = np.ones((k,)) * 1/k
sse = lambda x, y: ((x - y)**2).sum()
for step in range(10):
newscores = np.empty((k,))
for j in range(k):
newscores[j] = d / k + (1-d) * np.sum([
scores[l] / outgoing[l]
for l in range(k)
if l != j and G[j,l] != 0
])
logger.debug(f"{step} SSE:{sse(scores, newscores):.2e}")
if sse(scores, newscores) < self.convergence_thresh:
break
scores = newscores
self._scores = newscores
def fit(self, tokens:List[Tuple[str,str,str]], sentences:Iterator[Any]) -> 'TextRank':
logger.debug("Start TextRank analysis")
pos_filter = lambda token: token[2] in self.INCLUDE_PART_OF_SPEECH
tokens = list(filter(pos_filter, tokens))
self.build_graph(tokens)
self.textrank_algorithm()
lemma2scores = dict(zip(self._lemmas, self._scores))
self._lemma2word = l2w = {lemma: word for word, lemma, _ in tokens}
word2scores = {l2w[lemma]: score for lemma, score in lemma2scores.items()}
phrase2scores = self.reconstruct_phrases(word2scores, sentences)
# Normalise and apply sigmoid function to the resulting scores
weights = list(phrase2scores.values())
mu, sigma = np.mean(weights), np.std(weights)
norm = lambda weight: (weight - mu) / sigma
sigmoid = lambda weight: (1 + np.exp(-weight))**(-1)
scale = lambda weight: sigmoid(norm(weight))
normalised_scores = {node: scale(weight) for node, weight in phrase2scores.items()}
if not normalised_scores:
raise ValueError("No keyword found! There might be something wrong with the input features.")
self.keywords_ = pd.DataFrame(normalised_scores.items(), columns=["keyword", "score"])
self.keywords_.sort_values("score", ascending=False, inplace=True)
logger.debug(f"Top 5 keywords: {' '.join(self.keywords_.head(5)['keyword'].values)}")
return self
def test_ui(self):
logger.debug(f"Start ui test @ {UI_LOCATION}")
csrf_token = self._get_csrf_token()
assert bool(csrf_token)
for i, (_, text) in enumerate(load_texts()):
self._test_post_request(text, csrf_token)
def test_ui_under_pressure(self):
logger.debug("Start hammering the server")
queue = Queue()
csrf_token = self._get_csrf_token()
def threader():
while True:
text = queue.get()
self._test_post_request(text, csrf_token)
sleep(.5)
queue.task_done()
for _ in range(self.N_WORKERS):
t = Thread(target=threader)
t.daemon = True
t.start()
texts = list(load_texts("articles.txt"))
i = 0
while i < self.MAX_REQUESTS:
i += 1
_, text = random.choice(texts)
queue.put(text)
queue.join()
async def init_session(self, session: Optional[ClientSession] = None):
"""
初始化 ClientSession, 使用 get/post/head 方法之前需要调用一次,
ClientSession 内部维护了连接池, 因此不建议每一个请求创建一个 session,
这里默认为每一个类创建一个 persistent session, 或者手动设置一个, 以实现复用,
在 __init__.py 中初始化 session 会出现 warning, 官方在 aiohttp 4.0 之后将只允许在协程中创建 session,
See:
https://github.com/aio-libs/aiohttp/issues/3658
https://github.com/aio-libs/aiohttp/issues/4932
:param session: 用于复用的 ClientSession 对象
"""
if not self.session:
if session:
self.session = session
return
if self._dns_server:
logger.debug(f"Use custom DNS Server: {self._dns_server}")
resolver = AsyncResolver(nameservers=self._dns_server)
con = TCPConnector(ssl=False,
ttl_dns_cache=300,
resolver=resolver)
else:
con = TCPConnector(ssl=False, ttl_dns_cache=300)
jar = CookieJar(unsafe=True)
self.session = ClientSession(connector=con, cookie_jar=jar)
def test_analyser(self):
analyser = TextAnalyser(related=False)
self.assertIsInstance(analyser, TextAnalyser)
for _, text in load_texts():
try:
analyser.fit(text)
self.assertTrue(hasattr(analyser, 'textrank_'))
self.assertIsInstance(analyser.textrank_, TextRank)
self.assertTrue(hasattr(analyser, 'articles_'))
output = analyser.to_dict()
self.assertIs(type(output), dict)
self.assertIn('articles', output)
self.assertIn('graph', output)
keywords = analyser.textrank_.get_keywords(max_kws=10)
self.assertIs(type(keywords), list)
self.assertTrue(all(type(kw) is dict for kw in keywords))
logger.debug(str(keywords))
except NLPModelNotFound as e:
logger.error(e)
def transmit(self, request):
"""百度统计转发"""
args = dict(request.args)
ref_page_u = args.get("u",
"") # u = (file|http):///path/to/index.html#/
ref_page_su = args.get("su", "")
pat = re.compile(r".+?:///.+?/index\.html#(?P<route>/[^/]+).*"
) # route= index|detail|tvlive|result
args["u"] = pat.sub(rf"{self._flag_domain}\g<route>",
ref_page_u) # 替换 index 文件路径为标记域名 host/route
args["su"] = pat.sub(rf"{self._flag_domain}\g<route>", ref_page_su)
cookies_str = ""
for key, value in request.cookies.items():
cookies_str += f"{key}={value};"
stat_headers = {
"User-Agent": request.headers.get("User-Agent"),
"Referer": args["u"] or self._flag_domain,
"Cookie": cookies_str,
}
logger.debug(args)
logger.debug(stat_headers)
resp = requests.get(self._hm_status_url,
params=args,
headers=stat_headers)
return resp.content
async def make_response(self, range_field: str = None):
"""
读取远程的视频流，并伪装成本地的响应返回给客户端,
206 连续请求会导致连接中断, asyncio 库在 Windows 平台触发 ConnectionAbortedError,
偶尔出现 LocalProtocolError, 是 RFC2616 与 RFC7231 HEAD 请求冲突导致,
See:
https://bugs.python.org/issue26509
https://gitlab.com/pgjones/quart/-/issues/45
"""
if self._url.is_available():
return Response("resource not available", status=404)
if self._url.format == "hls": # m3u8 不用代理
return redirect(self._url.real_url)
url = self._url.real_url
proxy_headers = self._get_proxy_headers(url)
if range_field is not None:
proxy_headers["range"] = range_field
logger.debug(f"Client request stream range: {range_field}")
await self.init_session()
resp = await self.get(url, headers=proxy_headers)
if not resp:
return Response(b"", status=404)
if self._url.format == "hls":
return redirect(url) # url 不以 m3u8 结尾的跳过 Content-Type 识别
@stream_with_context
async def stream_iter():
while chunk := await resp.content.read(4096):
yield chunk
async def make_response_with_range(self,
range_field: str = None) -> Response:
"""
读取远程的视频流，并伪装成本地的响应返回给客户端,
206 连续请求会导致连接中断, asyncio 库在 Windows 平台触发 ConnectionAbortedError,
偶尔出现 LocalProtocolError, 是 RFC2616 与 RFC7231 HEAD 请求冲突导致,
See:
https://bugs.python.org/issue26509
https://gitlab.com/pgjones/quart/-/issues/45
"""
url = self._info.real_url
proxy_headers = self._get_proxy_headers(url)
if range_field is not None:
proxy_headers["range"] = range_field
logger.debug(f"Client request stream range: {range_field}")
await self.init_session()
resp = await self.get(url, headers=proxy_headers)
if not resp:
return Response(b"", status=404)
@stream_with_context
async def stream_iter():
while chunk := await resp.content.read(4096):
yield chunk
def _test_request(self, params):
response = self._make_request(params)
if "message" in response:
logger.debug(response)
return
self.assertIs(type(response), dict)
self.assertIn("articles", response)
self._test_groups(response["articles"], params["groupby_options"])
async def make_response_for_m3u8(self) -> Response:
if not self._cache_m3u8_text:
self._cache_m3u8_text = await self._get_fixed_m3u8_text()
logger.debug(
f"Cache m3u8 text, size: {len(self._cache_m3u8_text) // 1024}kb"
)
return Response(self._cache_m3u8_text,
mimetype="application/vnd.apple.mpegurl")
def _make_request(self, params):
resp = requests.post(self.ENDPOINT, json=params)
try:
return resp.json()
except Exception as err:
logger.exception(err)
logger.debug(resp.text)
raise err
def _test_article(self, article):
self.assertIs(type(article), dict)
expected = [("source", dict), ("category", str), ("title", str),
("body", str), ("publication_date", dt.datetime)]
for key, typ in expected:
self.assertIn(key, article)
self.assertIs(type(article[key]), typ)
logger.debug(article["title"])
logger.debug(article["body"])
def test_translate(self):
translator = IBMTranslator()
preds = translator.translate(
"The parrot is in the cage.",
source="en", target="nl",
return_all=True
)
self.assertIs(type(preds), list)
self.assertTrue(all(type(pred) is dict for pred in preds))
logger.debug(preds[0])
def store(self, obj: object) -> str:
"""储存一个对象，返回其 key"""
if hasattr(obj, "hash"):
key = obj.hash # 如果对象自定义了 hash
else:
hash_str = str(id(obj)) # 临时计算一个
key = md5(hash_str.encode("utf-8")).hexdigest()
if key not in self._db:
logger.debug(f"Store {obj} -> {key}")
self._db[key] = obj
return key
def _test_post_request(self, text, csrf_token):
params = {"text": text, "csrf_token": csrf_token}
resp = requests.post(UI_LOCATION, params)
resp.raise_for_status()
soup = BeautifulSoup(resp.text, "html.parser")
graph_container = soup.find("div", {"id": "graph-container"})
if not graph_container:
warnings.warn("No graph found")
articles = soup.find_all("div", {"class": "thumbnail article"})
title = text.strip().split('\n')[0]
logger.debug(f"{title[:50]}... {len(articles)} results")
def _test_article_format(self, articles):
self.assertIs(type(articles), list)
for article in articles:
self.assertIsInstance(article, dict)
expected = (
"title", "body", "language", "relevance",
"image_url", "url",
"source", "category"
)
self.assertTrue(all(key in article for key in expected))
logger.debug(article["title"])
async def parse_danmaku_data(self, danmaku: Danmaku) -> DanmakuData:
"""解析一集弹幕的数据"""
data_parser = self._loader.get_danmaku_data_parser(danmaku.module)
logger.debug(f"{data_parser.__class__.__name__} parsing {danmaku.cid}")
if data_parser is not None:
start_time = perf_counter()
data = await data_parser._parse(danmaku.cid)
end_time = perf_counter()
logger.info(f"Reading danmaku data finished in {end_time - start_time:.2f}s")
return data
return DanmakuData()
def load_model(lang: Optional[str] = None, path: Optional[str] = None) -> Any:
if path is None:
if not lang:
raise ValueError("Must provide one of language or path to model")
elif lang not in SPACY_LANG_MODELS:
raise NLPModelNotFound(f"Model not available for {lang}")
path = find_model(SPACY_LANG_MODELS[lang])
logger.debug(f"Loading model {path}")
t0 = time()
nlp = spacy.load(path)
logger.debug(f"Model loaded in {time() - t0:.2f}s")
return nlp
def build_anime_meta(self, hash_str: str):
"""尝试通过 hash 生成一个 AnimeMetaInfo"""
try:
engine, detail_page_url = b16decode(hash_str.upper()).decode("utf-8").split("|")
meta = AnimeMetaInfo()
meta.engine = engine
meta.detail_page_url = detail_page_url
logger.debug(f"Build AnimeMetaInfo from hash {hash_str}")
logger.debug(f"engine: {engine} detail_page_url: {detail_page_url}")
return meta
except Exception:
return
def post(url: str,
data=None,
html_encoding="utf-8",
**kwargs) -> requests.Response:
""""封装 POST 方法, 默认网页编码为 utf-8"""
try:
logger.debug(f"url: {url}, data: {data}")
kwargs.setdefault("timeout", 5)
kwargs.setdefault("headers", HtmlParseHelper._headers)
ret = requests.post(url, data, verify=False, **kwargs)
ret.encoding = html_encoding
return ret
except requests.RequestException as e:
logger.exception(e)
return requests.Response()
def get(url: str,
params=None,
html_encoding="utf-8",
**kwargs) -> requests.Response:
"""封装 GET 方法, 默认网页编码为 utf-8"""
try:
logger.debug(f"url: {url}, params: {params}")
kwargs.setdefault("timeout", 5)
kwargs.setdefault("headers", HtmlParseHelper._headers)
ret = requests.get(url, params, verify=False, **kwargs)
ret.encoding = html_encoding # 有些网页仍然使用 gb2312/gb18030 之类的编码, 需要单独设置
return ret
except requests.RequestException as e:
logger.exception(e)
return requests.Response()
def wrapper(*args: Any, **kwargs: Any) -> Union[Json, List[Json]]:
logger.info(f"{func.__name__.title()}: {args[1:]} {kwargs}")
return_all = kwargs.pop("return_all", True)
response = func(*args, **kwargs)
result = response.get_result()
top_level_key = json_key + "s"
if top_level_key in result:
predictions = result[top_level_key]
prediction = predictions[0]
if "confidence" in prediction:
logger.debug(
"Language: {language} Confidence: {confidence:.2%}".
format(**prediction))
predictions = merge_languages(predictions)
return predictions if return_all else predictions[0][json_key]
raise Exception("API Error: {}".format(result))
async def head(self,
url: str,
params: dict = None,
**kwargs) -> Optional[ClientResponse]:
"""
HEAD 方法, 使用随机 User-Agent, 出现异常时返回 None
"""
try:
url = self.set_headers(url, kwargs)
logger.debug(f"HEAD {url} | Params: {params} | Args: {kwargs}")
resp = await self.session.head(url, params=params, **kwargs)
logger.debug(
f"Code: {resp.status} | Type: {resp.content_type} | Length: {resp.content_length} ({url})"
)
return resp
except Exception as e:
logger.warning(f"Exception in {self.__class__}: {e}")
async def post(self,
url: str,
data: dict = None,
**kwargs) -> Optional[ClientResponse]:
"""
POST 方法, 使用随机 User-Agent, 出现异常时返回 None
"""
try:
url = self.set_headers(url, kwargs)
logger.debug(f"POST {url} | Data: {data} | Args: {kwargs}")
resp = await self.session.post(url, data=data, **kwargs)
logger.debug(
f"Code: {resp.status} | Type: {resp.content_type} | Length: {resp.content_length} ({url})"
)
return resp
except Exception as e:
logger.warning(f"Exception in {self.__class__}: {e}")
def store(self, obj: Any, key: str = None, overwrite: bool = False) -> str:
"""
存储一个对象, 返回其 key
:param obj: 待存储的对象
:param key: 若不指定, 随机生成一个运行期间不会重复的 key
:param overwrite: 存在相同的 key 时是否覆盖
:return: 对象的 key
"""
if not key:
hash_str = str(id(obj))
key = md5(hash_str.encode("utf-8")).hexdigest()
exist = key in self._db
if (not exist) or (exist and overwrite):
logger.debug(f"Store {obj} -> <Key {key}>")
self._db[key] = obj
return key
def head(url: str,
params=None,
allow_redirects=True,
**kwargs) -> requests.Response:
"""封装 HEAD 方法, 默认开启 302 重定向, 用于获取目标直链"""
try:
logger.debug(
f"url: {url}, params: {params}, allow_redirects: {allow_redirects}"
)
kwargs.setdefault("timeout", 5)
kwargs.setdefault("headers", HtmlParseHelper._headers)
return requests.head(url,
params=params,
verify=False,
allow_redirects=allow_redirects,
**kwargs)
except requests.RequestException as e:
logger.exception(e)
return requests.Response()
def get_hm_js(self, localhost: str, cookies: dict) -> str:
cookies_str = ""
for key, value in cookies.items():
cookies_str += f"{key}={value};"
stat_headers = {
"Referer": self._flag_domain,
"Cookie": cookies_str, # chrome blocked
}
logger.debug(stat_headers)
resp = requests.get(self._hm_js_url, headers=stat_headers)
if resp.status_code != 200:
return ""
localhost = localhost.replace("http://", "") # ip:host
text = resp.text.replace("https", "http") \
.replace("hm.baidu.com/hm.gif", localhost + "/statistics") \
.replace("hm.baidu.com", localhost) \
.replace(f"{self._flag_domain}/statistics", localhost + "/statistics")
return text
def get_real_url(self) -> str:
# detail_page_url: https://www.k1080.net/vodplay/410172-1-12.html
sessions = requests.Session()
resp = sessions.get(self.get_raw_url())
if resp.status_code != 200:
return ""
player_data = re.search(r"player_data=({.+?\})", resp.text).group(1)
player_data = json.loads(player_data)
video_url = unquote(b64decode(player_data.get("url")).decode("utf8"))
logger.debug(f"Video URL: {video_url}")
if video_url.endswith(".mp4") or video_url.endswith(".m3u8"):
return video_url
if video_url.endswith(".html"):
return ""
# 需要再重定向一次
resp = sessions.head(video_url, allow_redirects=False)
if resp.status_code != 302:
return ""
return resp.headers.get("location", "")
def pager(self,
method: Callable,
page_size: Optional[int] = 100,
**kwargs: Any) -> Results:
logger.debug(f"{method.__name__}: {kwargs}")
n_articles = 0
total_results = 1
while n_articles < total_results:
kwargs["page_size"] = page_size
kwargs["page"] = n_articles // page_size + 1
response = method(**kwargs)
total_results = response["totalResults"]
if not n_articles:
logger.debug(f"{total_results} results")
cat, lang = kwargs.get("category", ""), kwargs.get("language", "")
yield from map(self.parse(cat, lang), response["articles"])
n_articles += page_size
break # Developer accounts are limited to a max of 100 results.
