def __init__(self):
super().__init__()
self.config = ConfigHelper()
self.model = self.config.get_broker_config(type(self).__name__.upper())
self.main_words = [
"acciones", "fondos", "cedears", "bonos", "total var. $"
]
def process(hive_cmd_env):
# 1.1 load model selectors and models' conf
model_confs = ConfigHelper.load_config(
os.path.join(os.path.dirname(__file__), 'conf', 'model_selectors_and_models.yaml'))
model_selector = model_confs.get('model_selector')
models = model_confs.get('models')
# 1.2 load recmd requirement's conf
requirements = ConfigHelper.load_config(os.path.join(os.path.dirname(__file__), 'conf', 'recmd_requirement.yaml'))
# 1.3 load recmd score items
score_params = ConfigHelper.load_config(os.path.join(os.path.dirname(__file__), 'conf', 'score_params.yaml'))
# 2 get model key bu running model selector
if model_selector:
recmd_model_key = get_recmd_model_key_by_running_model_selector(requirements, model_selector)
else:
recmd_model_key = 'default'
# 3 get model by recmd key and run model
if models:
recmd_result = get_recmd_result_by_running_models(hive_cmd_env, requirements, score_params,
models, recmd_model_key)
else:
raise
return recmd_result
def main():
data_dir = join(dirname(dirname(abspath(__file__))), 'train', 'data',
'normal')
# generate src/tgt tables
src_vocab_set, tgt_vocab_set = set(), set()
with open(join(data_dir, 'train.en'), 'r') as f:
for line in f:
words = line.split()
for word in words:
src_vocab_set.add(word)
with open(join(data_dir, 'train.fr'), 'r') as f:
for line in f:
words = line.split()
for word in words:
tgt_vocab_set.add(word)
# write to config
cfg = ConfigHelper()
cfg.set_value('Others', 'normal_src_vocab_size', len(src_vocab_set) + 3)
cfg.set_value('Others', 'normal_tgt_vocab_size', len(tgt_vocab_set) + 3)
print('normal_src_vocab_size: {}'.format(len(src_vocab_set) + 3))
print('normal_tgt_vocab_size: {}'.format(len(tgt_vocab_set) + 3))
# write to src/tgt vocab file
fw = open(join(data_dir, 'vocab.en'), 'w')
write_header(fw)
for vocab in list(src_vocab_set):
fw.write('{}\n'.format(vocab))
fw.close()
fw = open(join(data_dir, 'vocab.fr'), 'w')
write_header(fw)
for vocab in list(tgt_vocab_set):
fw.write('{}\n'.format(vocab))
fw.close()
print('generate normal vocab files successfully!')
def create_database():
if not os.path.exists('./database.db'):
print("Create a database\n")
database.create_all()
sleep(0.1)
file_name = "products_79936.json"
if not os.path.exists(file_name):
# Download of mock database
Process.run(
'curl https://servicespub.prod.api.aws.grupokabum.com.br/descricao/v1/descricao/produto/79936 >> %s'
% file_name)
## Save database ##
# Read $filename
config_file = './%s' % file_name
config_helper = ConfigHelper(config_file)
config = config_helper.load_config()
# Read only products of config
config = config['familia']['produtos']
for data in config:
product = ProductModel(**data)
try:
# Save products in database
product.save_product()
sleep(0.01)
except:
print({"message": "An error ocurred trying to create product."},
500) # Internal Server Error
def get_connection_info():
ci = namedtuple("ConnectionInfo", "dbhost, dbport, dbuser, dbpass, dbname")
config = ConfigHelper()
ci.dbhost = config.get_config("DB_HOST")
ci.dbport = config.get_config("DB_PORT")
ci.dbuser = config.get_config("DB_USER")
ci.dbpass = config.get_config("DB_PASS")
ci.dbname = config.get_config("DB_NAME")
return ci
def test_get_recmd_model_key(self):
requirement = ConfigHelper.load_config(
'E:\\PythonProject\\Work\\work_3\\dake_recommendation\\conf\\recmd_requirement.yaml'
)
model_selector = ConfigHelper.load_config(
'E:\\PythonProject\\Work\\work_3\\dake_recommendation\\conf\\model_selectors_and_models.yaml'
).get('model_selector')
results = ['md5_model_0001', 'md5_model_0002']
self._list_in(get_recmd_model_key_by_running_model_selector(requirement, model_selector), results)
class BullMarkets(ChromeHelper):
def __init__(self):
super().__init__()
self.config = ConfigHelper()
self.model = self.config.get_broker_config(type(self).__name__.upper())
self.main_words = [
"acciones", "fondos", "cedears", "bonos", "total var. $"
]
def login(self, login_model: LoginModel, url: str):
"""
:param login_model:
:param url:
:return:
"""
config = self.config.get_all_config("BULLMARKETS")
self.browser.get(url)
self.browser.execute_script(config["script_modal"])
time.sleep(5)
username = self.browser.find_element_by_id(
login_model.username_element)
password = self.browser.find_element_by_id(
login_model.password_element)
username.send_keys(login_model.username)
password.send_keys(login_model.password)
time.sleep(5)
self.browser.execute_script(config["script_login"])
def get_data(self):
"""
:return:
"""
self.login(self.model, "https://bullmarketbrokers.com/")
time.sleep(10)
rows = self.get_rows_table("tbody_accountBrief")
response = {}
main_words_word = ''
for row in rows:
tds: list = list(
filter(None,
[x.text for x in row.find_elements_by_tag_name("td")]))
if self.main_words.count(tds[0].lower()) > 0:
main_words_word = tds[0]
response[main_words_word] = {}
response["total"] = tds[1:len(tds)]
continue
response[main_words_word][tds[0]] = []
for i in range(1, len(tds)):
response[main_words_word][tds[0]].append(tds[i])
return response
def test_get_value(self, mock_path_exists):
mock_path_exists.return_value = True
read_data = """{"key":"value"}"""
mo = mock_open(read_data=read_data)
with patch('utils.config_helper.open', mo):
config = ConfigHelper()
self.assertEqual(
config.get_config("key"), "value",
"""Is is not finding the correct
key-value config""")
def get_registration_info(self):
file = 'config.xml'
config_helper = ConfigHelper(file)
config = ConfigData()
ret = config_helper.init_root()
if ret:
config_helper.parse(config)
self.txt_registration_info.setText(config._qds_id)
else:
QMessageBox.information(self, '提示', '配置文件config.xml出错')
def get_authorize(self):
file = 'config.xml'
config_helper = ConfigHelper(file)
config = ConfigData()
ret = config_helper.init_root()
if ret:
config_helper.parse(config)
self.txt_access_key.setText(config._access_key)
self.txt_secret_key.setText(config._secret_key)
else:
QMessageBox.information(self, '提示', '配置文件config.xml出错')
def __init__(self):
config = ConfigHelper()
self.bucket = config.get_config("GCP_BUCKET")
self.account = config.get_config("GOOGLE_APPLICATION_CREDENTIALS")
# all these values are necessary
if not self.bucket or not self.account:
raise Exception("""The GCP_BUCKET or GOOGLE_APPLICATION_CREDENTIALS
are not set and there is not a .dspreview.json file in the user's
home folder, please provide one of them.""")
# make sure they are the same
os.environ["GOOGLE_APPLICATION_CREDENTIALS"] = self.account
self._service = None
def test_with_invalid_file(self, mock_path_exists):
mock_path_exists.return_value = True
read_data = "{..."
mo = mock_open(read_data=read_data)
with patch('utils.config_helper.open', mo):
with self.assertRaises(Exception):
ConfigHelper()
def test_rescore(self):
col_name = ['id', 'name', 'age', 'money']
recmd_results_without_score = pd.read_csv(
'E:\\PythonProject\\Work\\work_3\\dake_recommendation\\test\\test_1.txt', encoding='utf-8', names=col_name,
sep=' ')
score_params = ConfigHelper.load_config('E:\\PythonProject\\Work\\work_3\\dake_recommendation\\conf\\tmp.yaml')
model_params = {}
print rescore(recmd_results_without_score, score_params, model_params)
def set_params(self):
period = self.cbx_period.currentText().strip()
ema_fast = self.txt_ema_fast.toPlainText().strip()
ema_slow = self.txt_ema_slow.toPlainText().strip()
open_offset = self.txt_open_offset.toPlainText().strip()
open_interval = self.txt_open_interval.toPlainText().strip()
stop_earning_offset = self.txt_stop_earning_offset.toPlainText().strip(
)
stop_loss_offset = self.txt_stop_loss_offset.toPlainText().strip()
level_rate = self.txt_level_rate.toPlainText().strip()
max_number = self.txt_max_num.toPlainText().strip()
file = 'config.xml'
config_helper = ConfigHelper(file)
config_to_save = ConfigData()
ret = config_helper.init_root()
if ret:
config_helper.parse(config_to_save)
config_to_save._period = period
config_to_save._ema_fast = ema_fast
config_to_save._ema_slow = ema_slow
config_to_save._open_offset = open_offset
config_to_save._open_interval = open_interval
config_to_save._stop_earning_offset = stop_earning_offset
config_to_save._level_rate = level_rate
config_to_save._max_open_number = max_number
config_helper.save(config_to_save)
else:
QMessageBox.information(self, '提示', '配置文件config.xml出错')
def test_with_valid_file(self, mock_path_exists):
mock_path_exists.return_value = True
read_data = """{"key":"value"}"""
mo = mock_open(read_data=read_data)
with patch('utils.config_helper.open', mo):
try:
ConfigHelper()
except Exception:
self.fail("""It shouldn't raise an exception since
we are feeding a valid file""")
def set_logging(log_folder_path, log_level):
# set log file path
log_config = ConfigHelper.load_config(os.path.join(os.path.dirname(__file__), 'conf', 'log.yaml'))
log_file_name = 'log'
if not os.path.exists(log_folder_path):
os.makedirs(log_folder_path)
log_file_path = os.path.join(log_folder_path, log_file_name)
log_config['handlers']['file_handler']['filename'] = log_file_path
log_config['handlers']['file_handler']['level'] = log_level
logging.config.dictConfig(log_config)
def process(hive_cmd_env):
# read conf 2: download from hive
hive_calculate_and_download = ConfigHelper.load_config(
os.path.join(os.path.dirname(__file__), 'conf', 'hive_calculate_and_download.yaml')
)
for hql_number, hql_detail in hive_calculate_and_download.items():
# download files from hive after calculate
download_file_from_hive(
hive_cmd_env, hql_detail.get('hql'), hql_detail.get('hql_date_diff'),
hql_detail.get('data_store_path'), hql_detail.get('update_mode')
)
def get_params(self):
file = 'config.xml'
config_helper = ConfigHelper(file)
config = ConfigData()
global g_config
g_config = config
ret = config_helper.init_root()
if ret:
config_helper.parse(config)
self.cbx_period.setCurrentText(config._period)
self.txt_ema_fast.setText(config._ema_fast)
self.txt_ema_slow.setText(config._ema_slow)
self.txt_open_offset.setText(config._open_offset)
self.txt_open_interval.setText(config._open_interval)
self.txt_stop_earning_offset.setText(config._stop_earning_offset)
self.txt_stop_loss_offset.setText("0")
self.txt_level_rate.setText(config._level_rate)
self.txt_max_num.setText(config._max_open_number)
else:
QMessageBox.information(self, '提示', '配置文件config.xml出错')
def set_logging(error_log_config_file_path, error_log_folder_path,
error_log_level):
if not os.path.exists(error_log_folder_path):
os.makedirs(error_log_folder_path)
# set log file path and level
# log_config = ConfigHelper.load_config(os.path.join(os.path.dirname(__file__), "conf", "log.yaml"))
log_config = ConfigHelper.load_config(error_log_config_file_path)
log_config["handlers"]["file_handler"]["filename"] = os.path.join(
error_log_folder_path, "logs")
log_config["handlers"]["file_handler"]["level"] = error_log_level
logging.config.dictConfig(log_config)
def process(hive_cmd_env):
# read conf 1: download from hive
hive_calculate_and_download = ConfigHelper.load_config(
os.path.join(os.path.dirname(__file__), 'conf', 'hive_calculate_and_download.yaml')
)
for hql_number, hql_detail in hive_calculate_and_download.items():
# download files from hive after calculate
download_file_from_hive(
hive_cmd_env, hql_detail.get('hql'), hql_detail.get('data_store_path')
)
# read conf 2: wrap to json and upload
wrap_to_json_and_upload_to_es = ConfigHelper.load_config(
os.path.join(os.path.dirname(__file__), 'conf', 'wrap_to_json_and_upload_to_es.yaml')
)
for file_number, process_detail in wrap_to_json_and_upload_to_es.items():
# wrap the downloaded files to json
json_schema_path, json_file_path = wrap_to_json(
process_detail.get('schema_path'), process_detail.get('data_path'),
process_detail.get('index_name'), process_detail.get('type_name')
)
# and then upload them to it
upload_to_es(process_detail.get('index_name'), json_schema_path, json_file_path)
def process(args_config_file_path):
args_config = ConfigHelper.load_config(args_config_file_path)
# 1. get training or testing mode:
is_training = args_config["is_training"]
# 2. get middle result log dir params
middle_result_log_dir_params = args_config["middle_result_log_dir_params"]
# 3. get model params:
model_params = args_config["model_params"]
# 4. get running params from and run your model
training_params = args_config["training_params"]
testing_params = args_config["testing_params"]
# step 1. get dirname pattern
pattern, default_pattern = middle_result_log_dir_params[
"pattern"], middle_result_log_dir_params["default_pattern"]
if pattern is None or len(pattern) == 0:
pattern = default_pattern
# step 2. get and generate middle result log dir
if is_training:
# get middle result log dir automatically from config args under training mode
tensorboard_dir, model_dir = genarate_middle_result_log_dir(
args_config_file_path,
middle_result_log_dir_params["tensorboard_dir"],
middle_result_log_dir_params["model_dir"],
middle_result_log_dir_params["note_dir"],
middle_result_log_dir_params["self_increasing_mode"]
and is_training, pattern)
training_params.update({"tensorboard_dir": tensorboard_dir})
training_params.update({"model_dir": model_dir})
# step 3. todo: train or test your model
if is_training:
set_up_visiable_gpu(training_params.get("gpu_num"),
training_params.get("gpu_device_num"))
model_handler = ModelHandler(model_params)
model_handler.train(training_params)
else:
set_up_visiable_gpu(testing_params.get("gpu_num"),
testing_params.get("gpu_device_num"))
model_handler = ModelHandler(model_params)
model_handler.test(testing_params)
def save_registration_info(self):
registration_info = self.txt_registration_info.toPlainText().strip()
if not registration_info:
QMessageBox.information(self, '提示', '注册信息不完整')
return
file = 'config.xml'
config_helper = ConfigHelper(file)
config_to_save = ConfigData()
ret = config_helper.init_root()
if ret:
config_helper.parse(config_to_save)
config_to_save._qds_id = registration_info
config_helper.save(config_to_save)
QMessageBox.information(self, '提示', '信息已保存, 重启软件生效')
else:
QMessageBox.information(self, '警告', '配置文件config.xml出错')
def set_authorize(self):
access_key = self.txt_access_key.toPlainText().strip()
secret_key = self.txt_secret_key.toPlainText().strip()
if not access_key or not secret_key:
QMessageBox.information(self, '提示', '信息不完整')
return
file = 'config.xml'
config_helper = ConfigHelper(file)
config_to_save = ConfigData()
ret = config_helper.init_root()
if ret:
config_helper.parse(config_to_save)
config_to_save._access_key = access_key
config_to_save._secret_key = secret_key
config_helper.save(config_to_save)
QMessageBox.information(self, '提示', '信息已保存，重启软件生效')
else:
QMessageBox.information(self, '提示', '配置文件config.xml出错')
def __enter__(self):
try:
config = ConfigHelper()
credentials = pika.PlainCredentials(config.get_config("MQ_USER"),
config.get_config("MQ_PASS"))
host = config.get_config("MQ_HOST")
port = config.get_config("MQ_PORT")
vhost = config.get_config("MQ_VHOST")
self.queue = config.get_config("MQ_QUEUE")
parameters = pika.ConnectionParameters(host=host,
port=port,
virtual_host=vhost,
credentials=credentials)
self.connection = pika.BlockingConnection(parameters)
self.channel = self.connection.channel()
self.channel.queue_declare(queue=self.queue, durable=True)
except Exception as err:
logger.exception(err)
raise Exception("""It was not possible to connect to the MQ,
please check the connection information""")
return self
from model import NMTModel
from helpers.misc_helper import create_hparams
from helpers.input_helper import get_infer_input, get_input
from helpers.vocab_helper import create_idx2vocab_tables, create_vocab2idx_tables
from helpers.evaluation_helper import compute_bleu
sys.path.append(dirname(dirname(abspath(__file__))))
from utils.config_helper import ConfigHelper
flags = tf.flags
logging = tf.logging
logging.set_verbosity(tf.logging.INFO)
CHECKPOINT_BASENAME = 'model.ckpt'
cfg = ConfigHelper()
hparams = create_hparams(cfg)
def _run_training():
data_dir = join(dirname(abspath(__file__)), 'data')
# vocab files
src_vocab_file = join(data_dir, hparams.vocab_prefix + '.' + hparams.src)
tgt_vocab_file = join(data_dir, hparams.vocab_prefix + '.' + hparams.tgt)
src_vocab2idx_table, tgt_vocab2idx_table = create_vocab2idx_tables(
src_vocab_file, tgt_vocab_file, hparams.share_vocab)
src_idx2vocab_table, tgt_idx2vocab_table = create_idx2vocab_tables(
src_vocab_file, tgt_vocab_file, hparams.share_vocab)
# train files
train_src_file = join(data_dir, hparams.train_prefix + '.' + hparams.src)
train_tgt_file = join(data_dir, hparams.train_prefix + '.' + hparams.tgt)
from utils.register import Register
logging.basicConfig(level=logging.DEBUG, # 控制台打印的日志级别
filename='qds.log',
filemode='w', ##模式，有w和a，w就是写模式，每次都会重新写日志，覆盖之前的日志
# a是追加模式，默认如果不写的话，就是追加模式
format='%(asctime)s : %(message)s'
# '%(asctime)s - %(pathname)s[line:%(lineno)d] - %(levelname)s: %(message)s'
# 日志格式
)
URL = 'https://api.btcgateway.pro'
file = 'config.xml'
config_helper = ConfigHelper(file)
config = ConfigData()
ret = config_helper.init_root()
if ret:
config_helper.parse(config)
else:
logging.debug("Error, please check file {0}".format(file))
sys.exit(-1)
ACCESS_KEY = config._access_key
SECRET_KEY = config._secret_key
dm = ReliableHuobiDM(URL, ACCESS_KEY, SECRET_KEY)
# 1min, 5min, 15min, 30min, 60min,4hour,1day, 1mon
period = config._period
