def single_picky(slug='test'):
try:
f = open(PICKY_DIR + slug + '.md')
except IOError:
abort(404)
picky = f.read()
f.close()
meta_regex = re.compile(
r"^\s*(?:-|=){3,}\s*\n((?:.|\n)+?)\n\s*(?:-|=){3,}\s*\n*",
re.MULTILINE
)
match = re.match(meta_regex, picky)
if not match:
abort(404)
metas = match.group(1)
title = None
date = None
meta = metas.split("\n")
try:
title = meta[0].split("=>")[1]
except IndexError:
title = meta[0].split("=>")[0]
try:
date = meta[1].split("=>")[1]
except IndexError:
date = meta[1].split("=>")[0]
cont = to_unicode(picky[match.end():])
content = to_markdown(cont)
return template('picky.html', content=content, title=to_unicode(title),
date=to_unicode(date), slug=slug)
def __init__(self, input, transposed=True):
"""
Initialize the matrix reader.
The `input` refers to a file on local filesystem, which is expected to
be in the sparse (coordinate) Matrix Market format. Documents are assumed
to be rows of the matrix (and document features are columns).
`input` is either a string (file path) or a file-like object that supports
`seek()` (e.g. gzip.GzipFile, bz2.BZ2File).
"""
logger.info("initializing corpus reader from %s" % input)
self.input, self.transposed = input, transposed
with utils.file_or_filename(self.input) as lines:
try:
header = utils.to_unicode(next(lines)).strip()
if not header.lower().startswith('%%matrixmarket matrix coordinate real general'):
raise ValueError("File %s not in Matrix Market format with coordinate real general; instead found: \n%s" %
(self.input, header))
except StopIteration:
pass
self.num_docs = self.num_terms = self.num_nnz = 0
for lineno, line in enumerate(lines):
line = utils.to_unicode(line)
if not line.startswith('%'):
self.num_docs, self.num_terms, self.num_nnz = map(int, line.split())
if not self.transposed:
self.num_docs, self.num_terms = self.num_terms, self.num_docs
break
logger.info("accepted corpus with %i documents, %i features, %i non-zero entries" %
(self.num_docs, self.num_terms, self.num_nnz))
def load_cat2vec_format(cls, cat_model=None, sent_model=None, word_model=None):
"""
Load sentence vectors
"""
model = Category2Vec(None)
count = 0
if cat_model:
logger.info("loading %s object(cat) from %s" % (cls.__name__, cat_model))
for line in open(cat_model,"r"):
line = line.rstrip()
if count == 0:
info = line.split()
model.cat_len = int(info[0])
model.layer1_size = int(info[1])
model.sg = int(info[2])
model.hs = int(info[3])
model.negative = int(info[4])
model.cbow_mean = int(info[5])
model.cats = empty((model.cat_len, model.layer1_size), dtype=REAL)
model.cat_no_hash = {}
model.cat_id_list = []
else:
idx = count - 1
row = line.split("\t")
cat_id = utils.to_unicode(row[0])
model.cat_no_hash[cat_id] = idx
model.cat_id_list.append(cat_id)
vals = row[1].split()
for j in xrange(model.layer1_size):
model.cats[idx][j] = float(vals[j])
count += 1
count = 0
if sent_model:
logger.info("loading %s object(sentence) from %s" % (cls.__name__, sent_model))
for line in open(sent_model,"r"):
line = line.rstrip()
if count == 0:
info = line.split()
model.sents_len = int(info[0])
model.sents = empty((model.sents_len, model.layer1_size), dtype=REAL)
model.sent_no_hash = {}
model.sent_id_list = []
else:
idx = count - 1
row = line.split("\t")
sent_id = utils.to_unicode(row[0])
model.sent_no_hash[sent_id] = idx
model.sent_id_list.append(sent_id)
vals = row[1].split()
for j in xrange(model.layer1_size):
model.sents[idx][j] = float(vals[j])
count += 1
if word_model:
logger.info("loading word2vec from %s" % word_model)
model.w2v = Word2Vec.load(word_model)
model.vocab = model.w2v.vocab
return model
def __init__ (self, id, uri, name, type):
if id is None:
self.id = DBRepository.id_counter
DBRepository.id_counter += 1
else:
self.id = id
self.uri = to_unicode (uri)
self.name = to_unicode (name)
self.type = to_unicode (type)
def __init__ (self, id, commit):
if id is None:
self.id = DBLog.id_counter
DBLog.id_counter += 1
else:
self.id = id
self.rev = to_unicode (commit.revision)
self.committer = None
self.author = None
self.date = commit.date
self.message = to_unicode (commit.message)
self.composed_rev = commit.composed_rev
def __iter__(self):
"""Iterate through the lines in the source."""
try:
# Assume it is a file-like object and try treating it as such
# Things that don't have seek will trigger an exception
self.source.seek(0)
for line in self.source:
yield utils.to_unicode(line).split()
except AttributeError:
# If it didn't work like a file, use it as a string filename
with utils.smart_open(self.source) as fin:
for line in fin:
yield utils.to_unicode(line).split()
def response(self,msg,**kwargs):
## msg is parsed and your handled data.Actually,it is a dict.
## Your could specify a type by assign.ex response(type='music').I list all legal types.
'''
ex: response(message,type='yourType')
optional kwargs:
type='legal_types',content='yourContent',handler=foo,count=1
ps:when type is news,the count kwarg is nessceary
support types:
text,image,voice,video,music,news
'''
msg['receiver'],msg['sender'] = msg['sender'],msg['receiver']
legal_types = ['text','music','image','voice','video','news']
## get some kwargs ##
# key word content ---- which force type to textand return a static string
if kwargs.get('type'):
type = kwargs.get('type')
else:type = msg['type']
if type == 'music':
if not msg['hq_musurl']:
msg['hq_musurl'] = msg['musurl']
# charge receiver and sender
if kwargs.get('content'):
msg['type'] = type = 'text'
msg['content'] = to_unicode(kwargs.get('content'))
if not type in legal_types:
raise Exception("Illgal type!You could only choose one type from legal_types!")
# key word handler ---- which is a function object,accept a dict and return a modified dict
else:
msg['type'] = type
if kwargs.get('handler'):
msg = kwargs.get('handler')(msg)
## more kwargs ##
if not type == 'news':
template = to_unicode(getattr(Template(),type))
else:
count = kwargs.get('count')
if count:
temp = Template()
template = to_unicode(temp.news(count))
else:
raise Exception('When type is set to news,the count kwarg is necessary!')
logging.info(template.format(**msg))
try:
retdata = template.format(**msg)
except:
raise Exception("You did't pass enough args or pass wrong args,please check args which template needed.Read template.py maybe inspire your mind")
return retdata
def __init__(self, unique_name, base_filepath, parameters):
"""
Arguments
---------
keyword_name : feature unique name
base_filepath : filepath of feature config
parameters : lexicon parameters, presented by dictionary
"""
self.unique_name = unique_name
self.parameters = parameters
filepath = os.path.join(
base_filepath,
parameters[BagOfClustersFeature.PARAM_CLUSTERED_WORDS_FILEPATH])
if parameters[BagOfClustersFeature.PARAM_ENABLED] == 'false':
return
print "Loading file with clusters of words: {}".format(filepath)
with io.open(filepath, 'r', encoding='utf-8') as f:
self.clustered_words = json.load(f, encoding='utf-8')
print "Create dictionary with all clusters, accessed by cluster_id ..."
self.clusters = {}
for word in self.clustered_words.iterkeys():
cluster_id = self.clustered_words[word]
if cluster_id not in self.clusters:
self.clusters[cluster_id] = []
self.clusters[cluster_id].append(utils.to_unicode(word))
def add_header(self):
if self.file is not None :
dis = ""
dis += "Script file : %s\n" % sys.argv[0]
dis += "Date : %s\n" % time.strftime("%d/%m/%Y %H:%M:%S", self.gtime.start_date)
dis += "\n%s\n" % self.format("Time(s)", "Scope", "Info")
self.file.write(utils.to_unicode(dis))
def get_search_string(search_string=None):
"""Ask the user for a search string"""
keyboard = xbmc.Keyboard(search_string, localize(30134))
keyboard.doModal()
if keyboard.isConfirmed():
search_string = to_unicode(keyboard.getText())
return search_string
def get_property(key, default=None, window_id=10000):
"""Get a Window property"""
from xbmcgui import Window
value = to_unicode(Window(window_id).getProperty(key))
if value == '' and default is not None:
return default
return value
def get_project(self):
""" get the project """
ret = ""
mid = self.fields['project']
if mid is not None:
ret = mid['key']
return to_unicode(ret)
def get_reporter(self):
""" Get the issue reporter """
ret = ""
mid = self.fields['reporter']
if mid is not None:
ret = mid['displayName']
return to_unicode(ret)
def get_type(self):
""" Get the Issue type """
ret = ""
mid = self.fields['issuetype']
if mid is not None:
ret = mid['name']
return to_unicode(ret)
def get_assignee(self):
""" Get the assignee """
ret = ""
mid = self.fields['assignee']
if mid is not None:
ret = mid['displayName']
return to_unicode(ret)
def get_cluster_id(self, word):
"""
Returns
-------
Returns id of cluster, which is contain the 'word'
"""
return self.clustered_words[utils.to_unicode(word)]
def __iter__(self):
# the entire corpus is one gigantic line -- there are no sentence marks at all
# so just split the sequence of tokens arbitrarily: 1 sentence = 1000 tokens
sentence, rest, max_sentence_length = [], b'', 1000
with utils.smart_open(self.fname) as fin:
while True:
text = rest + fin.read(
8192) # avoid loading the entire file (=1 line) into RAM
if text == rest: # EOF
sentence.extend(
rest.split()
) # return the last chunk of words, too (may be shorter/longer)
if sentence:
yield sentence
break
last_token = text.rfind(
b' '
) # the last token may have been split in two... keep it for the next iteration
words, rest = (
utils.to_unicode(text[:last_token]).split(),
text[last_token:].strip()) if last_token >= 0 else ([],
text)
sentence.extend(words)
while len(sentence) >= max_sentence_length:
yield sentence[:max_sentence_length]
sentence = sentence[max_sentence_length:]
def _create_des_(msg):
if msg is None :
return {}
elif not(isinstance(msg, types.StringTypes)):
raise pexception.PytestembError("Msg must be a string")
else:
return dict({"msg":"%s" % utils.to_unicode(msg)})
def get_priority(self):
""" Get the priority """
ret = ""
pri = self.fields['priority']
if pri is not None:
ret = pri['name']
return to_unicode(ret)
def get_local_features(token, word_freq=None):
assert len(token) >= 1
features = []
ntoken = normalize(token, lowercase=False)
if token.isalpha():
if 'UpperCase' in features_on:
if first_upper_case(ntoken):
features += ['IsUpperCase']
if 'AllUpperCase' in features_on:
if all_upper_case(ntoken):
features += ['IsAllUpperCase']
if 'AllLowerCase' in features_on:
if all_lower_case(ntoken):
features += ['IsAllLowerCase']
if 'Freq' in features_on:
features += ['Freq:%s' % str(word_freq[ntoken])]
if 'Rare' in features_on:
if word_freq[ntoken] <= rare_thr:
features += ['IsRare']
if 'IsWord' in features_on:
features += ['IsWord']
elif token.isdigit():
if 'Number' in features_on:
features += ['IsNumber']
elif token.isalnum():
if 'AlphaNum' in features_on:
features += ['IsAlphaNum']
elif len(to_unicode(token)) == 1:
if is_punct(token):
if 'Separator' in features_on:
features += ['IsSeparator']
else:
if 'NonAlphanum' in features_on:
features += ['IsNonAlphanum']
if 'Word' in features_on:
if not any(x in features for x in ['IsNumber', 'IsAlphaNum']):
features += ['W=%s' % ntoken]
if 'Length' in features_on:
features += ['Length:%s' % str(len(ntoken))]
return features
def unfollow(program_name, title, program_id=None):
"""The API interface to unfollow a program used by the context menu"""
move_down = bool(plugin.args.get('move_down'))
from favorites import Favorites
Favorites().unfollow(program_name=program_name,
title=to_unicode(unquote_plus(from_unicode(title))),
program_id=program_id,
move_down=move_down)
def __iter__(self):
try:
self.source.seek(0)
for line in self.source:
k = utils.to_unicode(line.rstrip()).split("\t")
categories = k[3].split(" ")
for cat in categories:
if "/" in cat: continue
yield k[4:], k[1], cat
except AttributeError:
with utils.smart_open(self.source) as fin:
for line in fin:
k = utils.to_unicode(line.rstrip()).split("\t")
categories = k[3].split(" ")
for cat in categories:
if "/" in cat: continue
yield k[4:], k[1], cat
def __init__(self, id, name):
if id is None:
self.id = DBTag.id_counter
DBTag.id_counter += 1
else:
self.id = id
self.name = to_unicode(name)
def __init__ (self, id, name):
if id is None:
self.id = DBTag.id_counter
DBTag.id_counter += 1
else:
self.id = id
self.name = to_unicode (name)
def _check_same_origin(self, current_url):
"""
检查两个URL是否同源
"""
current_url = to_unicode(current_url)
url_part = urlparse.urlparse(current_url)
url_origin = (url_part.scheme, url_part.netloc)
return url_origin == self.origin
def replace(infile,
outfile,
find_what,
replace_with,
match_case=False,
output_paragraphs=False):
u"""Replace find_what with replace_with in docx or docm.
:param infile: file in which replacement will be performed
:type infile: str | unicode
:param outfile: file in which the new content will be saved
:type outfile: str | unicode
:param find_what: text to search for
:type find_what: str | unicode
:param replace_with: text to replace find_what with
:type replace_with: str | unicode
:param match_case: True to make search case-sensitive
:type match_case: bool
:param output_paragraphs: True to output the paragraphs replaced
:type output_paragraphs: bool
"""
if not os.path.isfile(infile):
raise ValueError('infile not found.')
if not outfile:
raise ValueError('outfile must be specified.')
if not find_what:
raise ValueError('find_what must be specified')
if replace_with is None:
replace_with = u''
infile = to_unicode(infile)
outfile = to_unicode(outfile)
find_what = to_unicode(find_what)
replace_with = to_unicode(replace_with)
global count
count = 0
parts = extract_parts(infile)
for part in parts:
part['content'] = __replace_part(etree.fromstring(part['content']),
find_what, replace_with, match_case,
output_paragraphs)
save_parts(parts, infile, outfile)
print('Paragraphs replaced: {0}'.format(count))
def get_terms_info(self, term):
"""
returns: dict
amount of documents which includes 'term' for different sentiment
classes and at all (DocVocabulary.ALL)
"""
uterm = to_unicode(term)
return self.terms_info[uterm]
def createI18NFile(data):
columns = json.loads(data.get("columns"))
strprefix = data.get("strprefix")
cns, ens = [], []
for column in columns:
if column.get("creat_i18n") == 'on':
i18nStr = strprefix + column.get("column_name")
if column.get("data_type") in ("date", "datetime"):
cns.append({
"key":
i18nStr + "_search",
"value":
utils.to_unicode("查询" + column.get("cn_name"))
})
ens.append({
"key": i18nStr + "_search",
"value": "Search" + column.get("en_name")
})
cns.append({
"key": i18nStr,
"value": utils.to_unicode(column.get("cn_name"))
})
ens.append({"key": i18nStr, "value": column.get("en_name")})
cns.append({
"key": "com.zhiyin.mes.app.to",
"value": utils.to_unicode("到")
})
ens.append({"key": "com.zhiyin.mes.app.to", "value": "To"})
if data.get("checkFactory") == 'on':
cns.append({
"key": "com.zhiyin.mes.app.factory_name",
"value": utils.to_unicode("所属工厂")
})
ens.append({
"key": "com.zhiyin.mes.app.factory_name",
"value": "FactoryName"
})
utils.create_file(
data.get("packageName") + "/i18n",
render_template('/generate/i18n.txt', data=cns),
data.get("packageName") + ".datagrid_zh_CN.properties")
utils.create_file(
data.get("packageName") + "/i18n",
render_template('/generate/i18n.txt', data=ens),
data.get("packageName") + ".datagrid_en_US.properties")
def __init__ (self, id, person):
if id is None:
self.id = DBPerson.id_counter
DBPerson.id_counter += 1
else:
self.id = id
self.name = to_unicode (person.name)
self.email = person.email or None
def ReplyText(ToUserName,FromUserName,Content):
Temp="""<xml>
<ToUserName><![CDATA[%s]]></ToUserName>
<FromUserName><![CDATA[%s]]></FromUserName>
<CreateTime>%s</CreateTime>
<MsgType><![CDATA[text]]></MsgType>
<Content><![CDATA[%s]]></Content>
</xml>"""
return Temp % (ToUserName,FromUserName,str(int(time.time())),to_unicode(Content))
def __getitem__(self, name):
'''Get a header value, from the message, decoded and as a
unicode string.
If the header does not exist, None is returned'''
value = self._msg[name]
if value is None:
return None
return u''.join(to_unicode(*tupl) for tupl in decode_header(value))
def __getitem__(self, name):
'''Get a header value, from the message, decoded and as a
unicode string.
If the header does not exist, None is returned'''
value = self._msg[name]
if value is None:
return None
return u''.join(to_unicode(*tupl) for tupl in decode_header(value))
def __init__ (self, id, file_name):
if id is None:
self.id = DBFile.id_counter
DBFile.id_counter += 1
else:
self.id = id
self.file_name = to_unicode (file_name)
self.repository_id = None
def get_setting(key, default=None):
"""Get an add-on setting as string"""
try:
value = to_unicode(ADDON.getSetting(key))
except RuntimeError: # Occurs when the add-on is disabled
return default
if value == '' and default is not None:
return default
return value
def __init__(self, id, person):
if id is None:
self.id = DBPerson.id_counter
DBPerson.id_counter += 1
else:
self.id = id
self.name = to_unicode(person.name)
self.email = person.email or None
def __init__(self, id, file_name):
if id is None:
self.id = DBFile.id_counter
DBFile.id_counter += 1
else:
self.id = id
self.file_name = to_unicode(file_name)
self.repository_id = None
def push_upnext(self):
"""Push episode info to Up Next service add-on"""
if has_addon('service.upnext') and get_setting_bool(
'useupnext', default=True) and self.isPlaying():
info_tag = self.getVideoInfoTag()
next_info = self.apihelper.get_upnext(
dict(
program=to_unicode(info_tag.getTVShowTitle()),
playcount=info_tag.getPlayCount(),
rating=info_tag.getRating(),
path=self.path,
runtime=self.total,
))
if next_info:
from base64 import b64encode
from json import dumps
data = [to_unicode(b64encode(dumps(next_info).encode()))]
sender = '{addon_id}.SIGNAL'.format(addon_id=addon_id())
notify(sender=sender, message='upnext_data', data=data)
def get_term_in_voc_count(self, term, sentiment=None):
"""
term : string
sentiment: '-1', '0', '1'
Describes the sentiment class
"""
uterm = to_unicode(term)
term_counters = self.term_in_voc_count[self.get_term_index(uterm)]
return term_counters[sentiment] if sentiment is not None \
else term_counters[self.ALL]
def __iter__(self):
try:
self.source.seek(0)
for line in self.source:
k = utils.to_unicode(line.rstrip()).split("\t")
categories = k[3].split(" ")
for cat in categories:
if "/" in cat:
continue
yield k[4:], k[1], cat
except AttributeError:
with utils.smart_open(self.source) as fin:
for line in fin:
k = utils.to_unicode(line.rstrip()).split("\t")
categories = k[3].split(" ")
for cat in categories:
if "/" in cat:
continue
yield k[4:], k[1], cat
def get_release_note(self):
if self.notes is None:
field = self.parent.field_id_map['Release Note']
if field in self.fields:
self.notes = to_unicode(self.fields[field])
elif self.get_incompatible_change() or self.get_important():
self.notes = self.get_description()
else:
self.notes = ""
return self.notes
def filter_wiki(raw):
"""
Filter out wiki mark-up from `raw`, leaving only text. `raw` is either unicode
or utf-8 encoded string.
"""
# parsing of the wiki markup is not perfect, but sufficient for our purposes
# contributions to improving this code are welcome :)
text = utils.to_unicode(raw, 'utf8', errors='ignore')
text = utils.decode_htmlentities(text) # '&nbsp;' --> '\xa0'
return remove_markup(text)
def get_release_note(self):
if self.notes is None:
field = self.parent.field_id_map['Release Note']
if field in self.fields:
self.notes = to_unicode(self.fields[field])
elif self.get_incompatible_change() or self.get_important():
self.notes = self.get_description()
else:
self.notes = ""
return self.notes
def get_all_tones_from_table(self):
logging.info("Loading lexicon '%s': %s ..." % (self.unique_name,
self.table_filepath))
df = pd.read_csv(self.table_filepath, sep=',')
for row in df.index:
name = df[self.term_column_name][row]
value = df[self.value_column_name][row]
self.cache[utils.to_unicode(name)] = float(value)
def get_term_in_voc_count(self, term, sentiment=None):
"""
term : string
sentiment: '-1', '0', '1'
Describes the sentiment class
"""
uterm = to_unicode(term)
term_counters = self.term_in_voc_count[self.get_term_index(uterm)]
return term_counters[sentiment] if sentiment is not None \
else term_counters[self.ALL]
def load_model(self, model: str, model_path: str):
try:
encoding = 'utf-8'
unicode_errors = 'strict'
model_file = [
f for f in os.listdir(model_path)
if os.path.isfile(os.path.join(model_path, f))
]
f = open(os.path.join(model_path, model_file[0]), 'rb')
header = to_unicode(f.readline(), encoding=encoding)
vocab_size, vector_size = (int(x) for x in header.split()
) # throws for invalid file format
binary_len = dtype(real).itemsize * vector_size
for _ in tqdm(range(vocab_size)):
word = []
while True:
ch = f.read(1)
if ch == b' ':
break
if ch == b'':
raise EOFError(
"unexpected end of input; is count incorrect or file otherwise damaged?"
)
if ch != b'\n': # ignore newlines in front of words (some binary files have)
word.append(ch)
word = to_unicode(b''.join(word),
encoding=encoding,
errors=unicode_errors)
weights = fromstring(f.read(binary_len),
dtype=real).astype(real)
self.word_vectors[word] = weights
self.model = model
print("Model loaded Successfully !")
return self
except Exception as e:
print('Error loading Model, ', str(e))
def get_terms_info_safe(self, term):
"""
returns : dict or 0
amount of documents which includes 'term' for different sentiment
classes and at all (DocVocabulary.ALL)
"""
uterm = to_unicode(term)
if (uterm in self.terms_info):
return self.get_terms_info(uterm)
else:
return None
def _download_url(self, url):
"""
Return a tuple (status, content), with content being the
content of the url as a string, and status a boolean marking
whether the download was succesful or not."""
try:
web = urllib2.urlopen(url)
except Exception as e:
result = (False, to_unicode(str(e)))
else:
result = (True, web.read())
return result
def main():
args = parse_args()
cfg = read_cfg(args.config)
if args.reloads is not None:
if 'all' in args.reloads:
tags = cfg.keys()
else:
tags = args.reloads
tags = tuple(
(to_unicode(tag) for tag in tags if to_unicode(tag) in cfg))
reload_cfg(cfg, tags)
elif args.failovers is not None:
if 'all' in args.failovers:
tags = cfg.keys()
else:
tags = args.failovers
tags = tuple(
(to_unicode(tag) for tag in tags if to_unicode(tag) in cfg))
do_failover(cfg, tags)
else:
start_scheduler(cfg, args.seconds)
def replace(infile, outfile, find_what, replace_with, match_case=False, output_paragraphs=False):
u"""Replace find_what with replace_with in pptx or pptm.
:param infile: file in which replacement will be performed
:type infile: str | unicode
:param outfile: file in which the new content will be saved
:type outfile: str | unicode
:param find_what: text to search for
:type find_what: str | unicode
:param replace_with: text to replace find_what with
:type replace_with: str | unicode
:param match_case: True to make search case-sensitive
:type match_case: bool
:param output_paragraphs: True to output the paragraphs replaced
:type match_case: bool
"""
if not os.path.isfile(infile):
raise ValueError('infile not found.')
if not outfile:
raise ValueError('outfile must be specified.')
if not find_what:
raise ValueError('find_what must be specified')
if replace_with is None:
replace_with = u''
infile = to_unicode(infile)
outfile = to_unicode(outfile)
find_what = to_unicode(find_what)
replace_with = to_unicode(replace_with)
global count
count = 0
parts = extract_parts(infile)
for part in parts:
part['content'] = __replace_part(etree.fromstring(part['content']), find_what, replace_with, match_case,
output_paragraphs)
save_parts(parts, infile, outfile)
print('Paragraphs replaced: {0}'.format(count))
def parse_user_msg(signature, xml):
"""
Parse xml from wechat server and return an Message
:param xml: raw xml from wechat server.
:return: an Message object
"""
if not xml:
return
_msg = dict((child.tag, to_unicode(child.text))
for child in ElementTree.fromstring(xml))
return pkgRequest(signature, **_msg)
def onNotification(self, sender, method, data): # pylint: disable=invalid-name
"""Handler for notifications"""
# log(2, '[Notification] sender={sender}, method={method}, data={data}', sender=sender, method=method, data=to_unicode(data))
# Handle play_action events from upnextprovider
if sender.startswith('upnextprovider') and method.endswith(
'plugin.video.vrt.nu_play_action'):
from json import loads
hexdata = loads(data)
if not hexdata:
return
# NOTE: With Python 3.5 and older json.loads() does not support bytes or bytearray, so we convert to unicode
from base64 import b64decode
data = loads(to_unicode(b64decode(hexdata[0])))
log(2,
'[Up Next notification] sender={sender}, method={method}, data={data}',
sender=sender,
method=method,
data=to_unicode(data))
self._playerinfo.add_upnext(data.get('video_id'))
def feed_url(self, url):
"""
设置初始爬取URL
"""
if isinstance(url, basestring):
url = to_unicode(url)
url = UrlData(url)
if self.same_origin:
url_part = urlparse.urlparse(unicode(url))
self.origin = (url_part.scheme, url_part.netloc)
self.fetcher_queue.put(url, block=True)
def feed_url(self, url):
'''
设置初始爬取URL
'''
if isinstance(url, basestring):
url = to_unicode(url)
url = UrlData(url)
if self.same_origin:
url_part = urlparse.urlparse(unicode(url))
self.origin = (url_part.scheme, url_part.netloc)
self.fetcher_queue.put(url, block=True)
def get_term_in_docs_count(self, term, sentiment=None):
"""
term : str
sentiment : None or '-1', '0', '1'
sentiment class name
returns : int
amount of 'term' appeared in all documents or in a documents of
the certain 'sentiment' class
"""
uterm = to_unicode(term)
term_info = self.terms_info[uterm]
return term_info[self.ALL] if sentiment is None \
else self.__get_term_in_sentiment_docs_count(term_info, sentiment)
def get_json_data(response, fail=None):
"""Return json object from HTTP response"""
from json import load, loads
try:
if (3, 0, 0) <= version_info < (
3, 6, 0): # the JSON object must be str, not 'bytes'
return loads(to_unicode(response.read()))
return load(response)
except TypeError as exc: # 'NoneType' object is not callable
log_error('JSON TypeError: {exc}', exc=exc)
return fail
except ValueError as exc: # No JSON object could be decoded
log_error('JSON ValueError: {exc}', exc=exc)
return fail