def __init__(self, args):
"""Constructor of the winservice."""
win32serviceutil.ServiceFramework.__init__(self, args)
self.hWaitStop = win32event.CreateEvent(None, 0, 0, None)
socket.setdefaulttimeout(60)
logger.init_logging()
self.app = None
def main():
ltype = 'basic'
ext = None
if len(sys.argv) >= 2:
ltype = sys.argv[1]
result = re.match('.+\.(.+)$', ltype)
if result:
ext = result.group(1)
if ltype == 'basic':
log = logger.init_basic(fname='simple.log')
elif ltype == 'simple':
log = logger.init_logging()
elif ltype == 'rot':
log = logger.init_logging(rotate_size=1000)
elif ltype == 'trot':
# log = logger.init_logging(rotate_interval=5)
log = logger.init_logging(rotate_seconds=30)
elif ltype == 'code':
log = logger.init_logging(err_file="err.log")
elif ext == 'yml':
log = logger.init_logging_yaml(ltype)
elif ext == 'ini':
log = logger.init_logging_ini(ltype)
else:
print("invalid arg "+ ltype)
return 1
print("got here ")
log.warning("BEGINS")
log.debug('debug ')
log.info("some info")
log.warning("we might have a problem")
log.error("something bad")
sample.func1()
logger.list_handlers()
print(f"wrote: {logger.log_file}")
return 0
def __init__(self):
"""
init初始化
"""
# 清理旧日志
clear_log(AIRTEST_LOG)
# 设置日志目录
set_logdir(AIRTEST_LOG)
# 初始化日志
init_logging()
# 等待显示时间
self.timeout = ST.FIND_TIMEOUT
# airtest-api
self.api = api
self.poco = AndroidUiautomationPoco(use_airtest_input=True, screenshot_each_action=False)
self.UIObj = UIObjectProxy(poco=self.poco)
from aiohttp import web
from utils.logger import init_logging
from logging import info
from db.create_db import init_db
import config
import telegram
if __name__ == '__main__':
init_logging()
init_db()
info('Starting the bot')
telegram.bot.remove_webhook()
if config.dev_mode:
telegram.bot.polling()
else:
import webhook
telegram.bot.set_webhook(
url=config.webhook_url_base + config.webhook_url_path,
certificate=open(config.webhook_ssl_cert, 'r'))
info('Starting the webhook')
web.run_app(
webhook.hook,
host=config.webhook_listen,
port=config.webhook_port,
ssl_context=webhook.ssl_context,
)
def email(x):
automated_emails.auto_email(["*****@*****.**"],
subject="ERROR DETECTED: Recollect Data "
"Import/Ovewrite/Dataupload"
"Script",
text=str(x))
now = datetime.datetime.now().strftime('%Y%m%d_%H_Hours_%M_Mins_%S_Sec')
arcpy.env.overwriteOutput = 1
arcpy.Delete_management("in_memory")
out_direct = r"\\Apexgis\GIS\recollect_appdata"
pub_db = r"C:\Users\Jlong\AppData\Roaming\ESRI\Desktop10.5\ArcCatalog\APEXPUBLISHER_jlong.sde"
arcpy.env.workspace = pub_db
log = logger.init_logging(r"\\Apexgis\GIS\recollect_appdata\logfiles",
"RecollectDataUpload")
log.info("Initializing Log:%s" % log)
success_msg = "---SUCCESSFUL EXECUTION---"
fail_msg = "---FAILURE---"
try:
par_csv = None
if len(glob.glob(
r'\\Apexgis\GIS\recollect_appdata\csv_download\*.csv')) > 1:
print "There should only be the most current CSV file in the directory"
log.warning(
"More than 1 CSV detected in csv_download network directory")
else:
print "Current Recollect Parcels CSV detected"
par_csv = glob.glob(
r'\\Apexgis\GIS\recollect_appdata\csv_download\*.csv')[0]
import sys
from utils import shell
from utils import logger
from monitor.cluster_monitor import DbClusterMonitor
if __name__ == '__main__':
logger.init_logging()
config_loaded = False
config = {}
while not config_loaded:
config_loaded, config = shell.load_config_ini()
app = DbClusterMonitor(config)
sys.exit(app.start())
import argparse
import traceback
import concurrent.futures
from backoffice.crawler.cdc import CdcCrawler
from utils.crawler import _NEW_RUMOR, _OLD_RUMOR, _FAILED, fetch_latest_create_date_of_rumor
from utils.logger import init_logging, logger
from utils.settings import Settings
from models.aws.ddb.rumor_model import RumorModel
setting = Settings(_env_file='config/env')
init_logging(setting)
parser = argparse.ArgumentParser()
parser.add_argument("-d",
"--date",
help="To crawler content from date",
default=None,
type=str)
parser.add_argument("-u",
"--update",
help="To update rumor content by re-crawlering",
default=False,
type=bool,
action=argparse.BooleanOptionalAction)
args = parser.parse_args()
def parsing_work(crawler, rumor_info):
try:
fetched = False
def main():
parser = argparse.ArgumentParser()
parser.add_argument('--root_dir')
parser.add_argument('--train_path', default='raw/rawtext/train.bioes.txt')
parser.add_argument('--dev_path', default='raw/rawtext/valid.bioes.txt')
parser.add_argument('--test_path', default='raw/rawtext/test.bioes.txt')
parser.add_argument('--embedding_type',
choices=['senna', 'glove', 'sskip', 'polyglot'],
default='glove')
parser.add_argument('--embedding_path',
default='raw/embedd/glove.6B.100d.txt')
parser.add_argument('--ngpu', type=int, default=1)
parser.add_argument('--gpu_id', type=int, default=0)
parser.add_argument('--load_checkpoint',
action='store_true',
default=False)
parser.add_argument('--load_checkpoint_path')
parser.add_argument('--model_name',
choices=['RNNT', 'NCRFT'],
default='RNNT')
parser.add_argument('--checkpoint_path', default='checkpoints')
parser.add_argument('--tmp_path')
parser.add_argument('--decode_mode',
choices=['greedy', 'beam'],
default='greedy')
parser.add_argument('--loss', choices=['local-joint', 'local-separate', 'global-joint-normal', \
'global-joint-logsoftmax', 'global-separate-normal', 'global-separate-logsoftmax'])
args = parser.parse_args()
os.environ["CUDA_VISIBLE_DEVICES"] = "%d" % (args.gpu_id)
logger, args.root_dir = init_logging('log-%s' % args.model_name,
time.time())
dataset = CoNLL03_Dataset(args.train_path, [args.dev_path, args.test_path],
logger)
dataset.read_embedding(args.embedding_type, args.embedding_path)
print("Create Alphabets...")
alphabet_path = os.path.join(args.root_dir, 'alphabet')
dataset.create_alphabets(alphabet_path, max_vocabulary_size=50000)
args.checkpoint_path = os.path.join(args.root_dir, 'checkpoint')
os.makedirs(args.checkpoint_path)
args.tmp_path = os.path.join(args.root_dir, 'tmp')
os.makedirs(args.tmp_path)
writer = CoNLL03Writer(dataset._word_alphabet, dataset._char_alphabet, dataset._pos_alphabet, \
dataset._chunk_alphabet, dataset._ner_alphabet)
with open(os.path.join(args.checkpoint_path, 'args.json'), 'w') as f:
json.dump(vars(args), f)
if args.model_name == 'RNNT':
trainer = RNNT_Trainer(args, dataset, logger, writer)
elif args.model_name == 'NCRFT':
trainer = NCRFT_Trainer(args, dataset, logger, writer)
trainer.train()
def run(hps="teeny", port=29500, **kwargs):
#from jukebox.utils.dist_utils import setup_dist_from_mpi
from utils.dist_utils import setup_dist_from_mpi
rank, local_rank, device = setup_dist_from_mpi(port=port)
hps = setup_hparams(hps, kwargs)
hps.ngpus = dist.get_world_size()
hps.argv = " ".join(sys.argv)
hps.bs_sample = hps.nworkers = hps.bs
# Setup dataset
data_processor = DataProcessor(hps)
# Setup models
vqvae = make_vqvae(hps, device)
print_once(f"Parameters VQVAE:{count_parameters(vqvae)}")
if hps.prior:
prior = make_prior(hps, vqvae, device)
print_once(f"Parameters Prior:{count_parameters(prior)}")
model = prior
else:
model = vqvae
# Setup opt, ema and distributed_model.
opt, shd, scalar = get_optimizer(model, hps)
ema = get_ema(model, hps)
distributed_model = get_ddp(model, hps)
logger, metrics = init_logging(hps, local_rank, rank)
logger.iters = model.step
# 手直し=======================================================================
print("start epoch=", hps.curr_epoch)
print("end epoch=", hps.epochs)
print("epoch length=", len(range(hps.curr_epoch, hps.epochs)))
#==============================================================================
# Run training, eval, sample
for epoch in range(hps.curr_epoch, hps.epochs):
# 手直し=======================================================================
print(datetime.datetime.now(), " epoch=", epoch)
#==============================================================================
metrics.reset()
data_processor.set_epoch(epoch)
if hps.train:
train_metrics = train(distributed_model, model, opt, shd, scalar,
ema, logger, metrics, data_processor, hps)
train_metrics['epoch'] = epoch
if rank == 0:
print(
'Train', ' '.join([
f'{key}: {val:0.4f}'
for key, val in train_metrics.items()
]))
dist.barrier()
if hps.test:
if ema: ema.swap()
test_metrics = evaluate(distributed_model, model, logger, metrics,
data_processor, hps)
test_metrics['epoch'] = epoch
if rank == 0:
print(
'Ema', ' '.join([
f'{key}: {val:0.4f}'
for key, val in test_metrics.items()
]))
dist.barrier()
if ema: ema.swap()
dist.barrier()