def ClientShutdown(self):
self.ServerRestart()
logger.info("closing connection ...")
self.socket.close()
logger.info(f"server connection closed on port: {self.port}")
def process_series_options(message: str) -> SendInformation:
logger.info(f"Processing received message: {message}")
series_name = ''
year = datetime.datetime.now().year
season = ''
episode = ''
quality = ''
parameters = message[7:].split(' -')[1:]
for parameter in parameters:
parameter = parameter.strip()
if parameter.startswith('n ') or parameter.startswith('name '):
series_name = parse_name(parameter)
elif parameter.startswith('y ') or parameter.startswith('year '):
year = parse_year(parameter)
elif parameter.startswith('s ') or parameter.startswith('season '):
season = parse_season(parameter)
elif parameter.startswith('e ') or parameter.startswith('episode '):
episode = parse_episode(parameter)
elif parameter.startswith('q ') or parameter.startswith('quality '):
quality = parse_quality(parameter)
if check_correct_parameters(series_name, year, season, episode, quality):
options = Options(series_name, year, season, episode, quality)
query_result = find_episode_torrents(options)
else:
query_result = SendInformation('', f"{INCORRECT_SERIES_FORMAT}")
return query_result
def generate_template(template_information: List[DisplaySubtitleInformation], cover_url: str, display_limit: int) -> SendInformation:
logger.info('Generating message with format for Telegram.')
first_message = ''
remaining_messages = []
for index, movie_subtitle in enumerate(template_information, start=1):
if index <= display_limit:
temp_text = f"<strong><u>Option {index}</u></strong>\n"
temp_text = temp_text + f"\n"
temp_text = temp_text + f"<strong>Rating:</strong> {movie_subtitle.rating}\n"
temp_text = temp_text + f"<strong>Language:</strong> {movie_subtitle.language}\n"
temp_text = temp_text + f"<strong>Uploader:</strong> {movie_subtitle.uploader}\n"
temp_text = temp_text + f"<strong>Compatible torrents:</strong>\n\n{movie_subtitle.compatible_torrents}\n\n"
temp_text = temp_text + f"\U0001F5C3<strong>:</strong> <a title=\"Subtitle File\" href=\"{movie_subtitle.download_link}\">" \
f"Subtitle File</a>\n"
temp_text = temp_text + f"\n"
exceeds_size = message_exceeds_size(first_message)
if exceeds_size:
remaining_messages.append(temp_text)
else:
first_message = first_message + temp_text
else:
break
if remaining_messages:
reduce_remaining_parts = join_remaining_parts(remaining_messages)
result = SendInformation(cover_url, first_message, reduce_remaining_parts)
else:
result = SendInformation(cover_url, first_message)
return result
def status_command(update: Update, context: CallbackContext) -> None:
"""Sends a message to the user to check if the bot is running when the /status command is issued."""
user_info = update.effective_message.from_user
identifier = get_user(user_info)
logger.info(f"Status check requested by user: {identifier}")
update.effective_message.reply_text(STATUS_COMMAND)
def filter_album_tracks(oauth_token: str, recent_tracks: list) -> list:
try:
tracks = []
for track in recent_tracks:
album_tracks = get_album_tracks(oauth_token, track['album_id'])
df_album_tracks = pd.DataFrame(album_tracks)
df_album_tracks = df_album_tracks.filter(['items'])
df_album_tracks = pd.json_normalize(
df_album_tracks.to_dict('records'))
df_album_tracks = df_album_tracks.filter(
['items.id', 'items.track_number'])
df_album_tracks.rename(columns={
'items.id': 'track_id',
'items.track_number': 'track_number'
},
inplace=True)
df_album_tracks[
'track_number'] = df_album_tracks['track_number'] - 1
current_track = pd.merge(pd.DataFrame(recent_tracks),
df_album_tracks,
on='track_id',
how='inner').to_dict('records')[0]
tracks.append(current_track)
logger.info('Album tracks have been filtered successfully')
return tracks
except Exception as error:
logger.error(f'Error to filter album tracks: {error}')
raise
def webhook(event, context):
"""
Reply to input message (only /start)
"""
bot = configure_telegram()
logger.info('Event: {}'.format(event))
if event.get('body'):
logger.info('Message received')
update = telegram.Update.de_json(json.loads(event.get('body')), bot)
chat_id = update.message.chat.id
text = update.message.text
if text == '/start':
try:
Chat.get(chat_id)
except DoesNotExist:
chat = Chat(chat_id)
chat.save()
reply_text = """카이스트 아라의 Food 게시판 업데이트 알림 봇입니다. 매일 오전 11시에 전날의 게시글이 전달됩니다."""
bot.send_message(chat_id=chat_id, text=reply_text)
logger.info('Message sent')
else:
logger.info('Input message ignored')
else:
logger.info('Input message ignored')
return OK_RESPONSE
return ERROR_RESPONSE
def send_remaining_messages(update: Update, identifier: str,
remaining_messages: List[str]) -> None:
logger.info(f"Sending remaining messages to the user: {identifier}")
for remaining_message in remaining_messages:
update.effective_message.reply_html(remaining_message,
disable_web_page_preview=True)
def _evaluate_and_order_asset(self, asset: Asset, value_to_order: float):
actual_positions = self._ordered_mapping[asset.market_type][
asset.asset_type]
# There might be multiple positions for the same asset. Find the least valued asset.
least_valued_pos = min(actual_positions.values(),
key=lambda x: x.updated_data.market_value)
pos_md = self._latest_market_data[
least_valued_pos.updated_data.contract_id]
# Quantity of stocks must be an integer. This might change for other markets.
ask_price = pos_md.ask_price
if ask_price is None:
raise SystemError(
f"Ask price is not available for: {least_valued_pos.name}")
quantity = int(value_to_order / ask_price)
logger.info(f"Placing order: BUY >> {least_valued_pos.name}, "
f"Quantity: {quantity}, "
f"Ask Price: {pos_md.ask_price}")
self._transaction_mgr.queue_for_execution(
self._broker_interface.place_single_order,
least_valued_pos.updated_data.contract_id,
least_valued_pos.name,
quantity,
OrderTypes.LIMIT,
OrderActions.BUY_ORDER,
least_valued_pos.updated_data.sec_type,
least_valued_pos.updated_data.currency,
limit_price=ask_price)
def main():
"""Main function
Run this file with `python app.py`
"""
print("\n")
logger.info("Success! Here is you're config:\n")
logger.info(json.dumps(config, indent=4))
def _persist_data(self,
var_data,
session_id="",
channel="",
business_name="",
flow_id="",
business_id=""):
# change this method to perform async
if var_data == {}:
return 1
object_id = str(uuid.uuid4())
timestamp = datetime.datetime.utcnow()
collection = DB["user_data"]
document = {
"_id": object_id,
"user_id": self.user_id,
"flow_id": flow_id,
"session_id": session_id,
"business_id": business_id,
"data": var_data,
"channel": channel,
"business_name": business_name,
"timestamp": timestamp
}
try:
saved_document_id = collection.insert_one(document).inserted_id
logger.info(
f"Variable data saved with object_id {saved_document_id}")
return 1
except Exception as err:
logger.error(err)
raise
def parse_settings(settings_file) -> dict:
""" Creates multiple dictionaries containing the settings parsed from a settings file.
Each type of plot has its own settings dictionary.
settings_file is the name of the text file containing the settings
Return values:
data is a pandas.DataFrame object which contains the alternative splicing data
hive_plot_settings is a dictionary containing the settings for the hive plot
struct_plot_settings is a dictionary containing the settings for the structure plot
"""
try:
config = configparser.ConfigParser()
logger.info('Reading settings from {0}...'.format(settings_file))
config.read(settings_file)
# hive_plot_settings = parse_hive_plot_settings(config)
# struct_plot_settings = parse_struct_plot_settings(config)
return parse_sashimi_settings(config)
# logger.error('Done reading settings.')
# return hive_plot_settings, struct_plot_settings, sashimi_plot_settings
except IOError:
logger.error('{0} is not a valid file path')
sys.exit(1)
def load_configuration():
global dropbox_client, local_cloud_path, upload_prefix, enable_upload, download_prefix, enable_download, \
thin_mode_byte_length, tmp_path, sync_interval_in_sec
file_handle = open(CONFIGURATION_FILE, 'r')
config_data = file_handle.read()
file_handle.close()
configs = json.loads(config_data)
init_logger(configs["server_configuration"]["log_path"])
local_cloud_path = configs["server_configuration"]["local_cloud_path"]
upload_prefix = configs["server_configuration"]["upload_filename_magic"]
download_prefix = configs["server_configuration"][
"download_filename_magic"]
enable_download = json.loads(
configs["server_configuration"]["enable_download"].lower())
enable_upload = json.loads(
configs["server_configuration"]["enable_upload"].lower())
thin_mode_byte_length = int(
configs["server_configuration"]["bytes_length_in_thin_mode"])
tmp_path = configs["server_configuration"]["tmp_path"]
sync_interval_in_sec = configs["server_configuration"][
"sync_interval_in_sec"]
if configs["cloud_credential"]["dropbox"][
"access_token"] is not DEFAULT_ACCESS_TOCKEN:
dropbox_client = DropboxClient(
configs["cloud_credential"]["dropbox"]["access_token"])
logger.info("Finish loading configuration")
def spawn_food(amount=1):
logger.info('Spawned %s food', amount)
for i in range(amount):
Food()
return
def set_wallpaper(path: str):
if system_platform == 'Windows':
logger.info("Windows platform")
set_set_wallpaper_win(path)
else:
logger.info("Unix platform")
set_set_wallpaper_unix(path)
def innateDbGene(data, filename):
"""
parser file (tsv) from innateDb
IN : dic + tsv file
OUT : dic
"""
number = 1 #number of lines
workInProgress = 100 #when inform user
with open(filename, newline='') as tsvFile:
for row in tsvFile.readlines()[1:]:
column = row.rstrip().split('\t')
geneID = column[3]
if geneID not in data:
#traitement GO terms
goTerms = column[14]
goTerms = goterms2xmlformat(goTerms)
data[geneID] = Gene(geneID, column[5], column[6], "innateDb", column[15], "", "", column[2], goTerms)
if data[geneID].accession == "":
#traitement accession
data[geneID].accEnsembl()
if data[geneID].sequence == "" and data[geneID].accession != "":
#traitement sequence
data[geneID].seqUniprot()
#log.debug(str(data[geneID].echo()))
number += 1
if number % workInProgress == 0:
log.info("Parsed " + str(number) + " lines")
log.info("Parsed a total of " + str(number) + " lines")
return data
def test_for_nans(data, name):
if not len(data):
raise ValueError('Data is empty!')
nan_rows = data[data.isnull().values.any(axis=1)]
if not len(nan_rows):
logger.info('\t\tNo Nans found in {}'.format(name))
return
logger.info(
'\t\tFound {} rows ({:.1f}%) and {} columns (out of {}) with Nans in {}'
.format(len(nan_rows), 100 * len(nan_rows) / len(data),
data.isnull().values.any(axis=0).sum(), len(data.columns),
name))
nan_counts = {}
for source, source_data in data.groupby('source'):
source_nans = {}
for column in source_data.columns:
col_nans = source_data[column].isnull().values.sum()
if col_nans:
source_nans[column] = col_nans
nan_counts[source] = source_nans
for k, v in nan_counts.items():
logger.error('\t\tFor source {}, found NaNs in {} columns:'.format(
k, len(v)))
for l, c in v.items():
logger.error('\t\t\t{:20} {:8} ({:.1f}%)'.format(
l, c, 100 * c / len(data)))
raise ValueError
def get_image_from_event(event):
content_type_header = event["headers"]["content-type"]
body = base64.b64decode(event["body"])
logger.info("Body Loaded")
picture = decoder.MultipartDecoder(body, content_type_header).parts[0]
filename = get_picture_filename(picture).replace('"', "")
return picture, filename
def filter_data(data,
msg,
keep_condition=None,
drop_indices=None,
keep_indices=None,
quiet_mode=False):
""" Filters a pandas data frame and logs the result with 'msg'. This runs in two modes,
either supply a condition under which data is to be *kept*, or supply a list of indices
to drop.
"""
n_before = len(data)
if drop_indices is not None:
assert keep_condition is None
assert keep_indices is None
data = data.drop(drop_indices)
elif keep_indices is not None:
assert keep_condition is None
assert drop_indices is None
data = data.loc[keep_indices]
else:
data = data[keep_condition]
n_after = len(data)
if not quiet_mode:
logger.info('\t\tRemoved {} data ({:.1f}%) which '.format(
n_before - n_after, 100 * (n_before - n_after) / n_before) + msg)
data.is_copy = False
return data
def get_session():
logger.info("Session route hit")
user_id = request.args.get("user_id")
response = UserController.get(user_id)
return response
def __save_dicts(self):
with open(self.save_path_w2i, 'w') as f:
json.dump(self.word2index, f)
with open(self.save_path_i2w, 'w') as f:
json.dump(self.index2word, f)
logger.info('Saved')
def start_command(update: Update, context: CallbackContext) -> None:
"""Sends a welcome message when the command /start is issued."""
user_info = update.effective_message.from_user
identifier = get_user(user_info)
logger.info(f"Bot started for user: {identifier}")
update.effective_message.reply_text(WELCOME_START_COMMAND)
def generate_template_information(movies_data: ByIMDb) -> DisplayMovieInformation:
logger.info('Generating template information.')
title = movies_data.title
year = movies_data.year
rating = f"{movies_data.rating} / 10"
runtime = f"{movies_data.runtime} minute(s)"
genres = movies_data.genres
youtube_trailer = movies_data.youtube_trailer
mpa_rating = movies_data.mpa_rating
large_cover_image = movies_data.large_cover_image
raw_torrents = movies_data.torrents
torrents = []
for torrent in raw_torrents:
torrent_url = torrent.torrent_url
quality = torrent.quality
raw_release_type = torrent.release_type
release_type = parse_release_type(raw_release_type)
health = f"{torrent.seeds} Seed(s) / {torrent.peers} Peer(s)"
size = HumanBytes.format(torrent.size_bytes, metric=True)
option = DisplayTorrentInformation(torrent_url, quality, release_type, health, size)
torrents.append(option)
result = DisplayMovieInformation(title, year, rating, runtime, genres, youtube_trailer, mpa_rating, large_cover_image, torrents)
return result
def echo(update: Update, context: CallbackContext) -> None:
"""Sends a message when the user sends a no command."""
user_info = update.effective_message.from_user
identifier = get_user(user_info)
logger.info(f"A no command has been sent from user: {identifier}")
update.effective_message.reply_text(WRONG_FORMAT_ECHO_COMMAND)
def register_jobs(jobs_config_path):
with open(jobs_config_path) as json_file:
config = json.load(json_file)
query_hashes = set()
for query in config['queries']:
frequency = query['frequency']
query_hash = query['query_hash']
if query_hash in query_hashes:
raise ValueError(
f"Query hash {query_hash} is duplicated, a same query can't be set multiple time"
)
query_hashes.add(query_hash)
frequency_number = int(frequency[:-1])
if frequency[-1] == 's':
schedule.every(frequency_number).seconds.do(
run_threaded, job, query_hash)
elif frequency[-1] == 'm':
schedule.every(frequency_number).minutes.do(
run_threaded, job, query_hash)
elif frequency[-1] == 'h':
schedule.every(frequency_number).hours.do(run_threaded, job,
query_hash)
else:
raise ValueError(
f'Config expect a frequency: <x>[s|m|h], got {frequency}')
if len(query_hashes) == 0:
raise ValueError('No query found')
next_run: datetime.timedelta = schedule.next_run() - datetime.datetime.now(
)
logger.info('Loaded %s queries with success, next run in %1.0f s',
len(query_hashes), next_run.total_seconds())
def prepare(self, region: SpliceRegion, ):
data = []
for i, f in enumerate(self.files):
with pyBigWig.open(f) as r:
try:
data.append(r.values(region.chromosome, region.start, region.end + 1))
except RuntimeError as e:
logger.warning(e)
logger.info("may be caused by the mismatch of chromosome")
if region.chromosome.startswith("chr"):
data.append(r.values(region.chromosome.replace("chr", ""), region.start, region.end + 1))
else:
data.append(r.values("chr" + region.chromosome, region.start, region.end + 1))
self.data = np.array(data)
if self.clustering and self.data.shape[0] > 1:
data = linkage(self.data, method=self.clustering_method, metric=self.distance_metric)
order = dendrogram(data, orientation='right')
self.data = self.data[order["leaves"], :]
if self.do_scale:
"""
y = (x – mean) / standard_deviation
"""
# b = (self.data.transpose() - np.mean(self.data, axis=1)) / np.std(self.data, axis=1)
# self.data = b.transpose()
self.data = zscore(self.data, axis=1)
pass
def say(bot, message, message_to_say=None):
logger.info(message)
if not message_to_say:
message_to_say = get_message(message)
if message_to_say:
send_functions[message_to_say.message_type](bot, message.chat.id,
message_to_say.value)
def get_title(quality: str, raw_title: str) -> str:
logger.info(f"Recovering title.")
index = raw_title.find(quality)
title = raw_title[0:index]
return title
def solve_puzzle(ctx):
"""
Solves a given puzzle
"""
puzzle = PuzzleUtils.load_puzzle(ctx.obj[PUZZLE_FILE_KEY])
puzzle.solve()
logger.info(puzzle.dump_grid())
def is_bam(infile: str) -> bool:
u"""
check if input file is bam or sam file
:param infile: path to input file
:return: Boolean
"""
try:
create = False
if not os.path.exists(infile + ".bai"):
create = True
elif os.path.getctime(infile + ".bai") < os.path.getctime(infile):
try:
os.remove(infile + ".bai")
create = True
except PermissionError as err:
logger.warn(err)
create = False
else:
try:
with pysam.AlignmentFile(infile) as r:
r.check_index()
except ValueError:
create = True
if create:
logger.info(f"Creating index for {infile}")
pysam.index(infile)
return True
except pysam.utils.SamtoolsError:
return False
def StopTorcs(containerID: str): # sourcery skip: merge-list-extend
logger.info(f"stopping torcs process on container {containerID}")
subprocess.Popen(
["docker", "exec", containerID, "pkill", "torcs"],
stdout=subprocess.DEVNULL,
stderr=subprocess.DEVNULL,
)