def __init__(self, mode="F"):
self._mode = mode
config = load_config()
self._sensor_type = config[
'temp_sensor_type'] if 'temp_sensor_type' in config else None
self.init_fail = True
def load_from_config(self):
''' loads the configuration for this unit '''
json_dic = load_config()
self.controller = json_dic['controller']
self._red_pin = json_dic['red_pin'] if 'red_pin' in json_dic else None
self._green_pin = json_dic['green_pin'] if 'green_pin' in json_dic else None
self._blue_pin = json_dic['blue_pin'] if 'blue_pin' in json_dic else None
def __init__(self, mode="F", time_delay=20):
super().__init__(mode)
self._time_delay = time_delay
self._sensor_type = 'DHT11'
config = load_config()
self.therm_pin = int(config['DHT11_pin'])
self.init_fail = False
self._last_called = time()
self._temp = self._get_temp()
def set_thermometer(self, mode="F"):
''' sets up the thermometer '''
config = load_config()
sensor_type = config[
'temp_sensor_type'] if 'temp_sensor_type' in config else None
# dht11 sensor
if sensor_type.lower() == 'dht11' and bool(sensor_type):
self.thermometer = DHT11(mode)
# ds18b20
elif sensor_type.lower() == 'ds18b20' and bool(sensor_type):
self.thermometer = DS18B20(mode)
# all others
else:
self.thermometer = Thermometer(mode)
def __init__(self,
latitude,
longitude,
radius=SEARCH_RADIUS,
min_price=3,
max_price=4,
asset_id=None):
self.base_url = 'https://maps.googleapis.com/maps/api/place/nearbysearch/json?'
self.latitude = latitude
self.longitude = longitude
self.radius = radius
self.min_price = min_price
self.max_price = max_price
self.asset_id = asset_id
# Retrieve Google API key from secrets file
sec_config = load_config(SECRET_PATH)
self.g_key = sec_config['google_key']
def runner(args):
configs = load_config(args.config)
project_configs = configs['PROJECT']
model_configs = configs['MODEL']
train_configs = configs['TRAIN']
test_configs = configs['TEST']
train_dataset_configs = configs['TRAIN_DATASET']
test_dataset_configs = configs['TEST_DATASET']
input_size = train_dataset_configs[
'input_size'] if args.train else test_dataset_configs['input_size']
if train_dataset_configs['channels'] == 3:
base_transforms = transforms.Compose([
transforms.Resize((input_size, input_size)),
transforms.ToTensor()
]) # ,
# transforms.Normalize(mean=train_dataset_configs['mean'], std=train_dataset_configs['std'])])
elif train_dataset_configs['channels'] == 1:
base_transforms = transforms.Compose([
transforms.Resize((input_size, input_size)),
transforms.ToTensor()
]) # ,
# transforms.Normalize(mean=[sum(train_dataset_configs['mean']) / len(train_dataset_configs['mean'])],
# std=[sum(train_dataset_configs['std']) / len(train_dataset_configs['std'])])])
train_datasets = Fusion_Datasets(train_dataset_configs, base_transforms)
test_datasets = Fusion_Datasets(test_dataset_configs, base_transforms)
model = eval(model_configs['model_name'])(model_configs)
print('Model Para:', count_parameters(model))
if train_configs['resume'] != 'None':
checkpoint = torch.load(train_configs['resume'])
model.load_state_dict(checkpoint['model'].state_dict())
if args.train:
train(model, train_datasets, test_datasets, configs)
if args.test:
test(model, test_datasets, configs, load_weight_path=True)
def __init__(self, key_name=None):
self._key_name = key_name
if key_name:
json_dic = load_config()
self._hashed_key = json_dic[key_name]
'session': session}
if not first:
time.sleep(3, 59)
first = False
run_cl_job(**kwargs_pass)
print('Completed job {}'.format(hood))
# TODO: Add random wait
if __name__ == "__main__":
config = load_config(CONFIG_PATH)
cl_config = config['scrapers']['craigslist']
# DB Setup. Create an engine to store data at specified path
# By default SQLite expects one thread, but multithread is supported:
# https://docs.sqlalchemy.org/en/13/dialects/sqlite.html
engine = create_engine(config['db_path'], echo=True,
connect_args={'check_same_thread': False})
Session = sessionmaker(bind=engine)
session = Session()
# Job Scheduler
# scheduler = BackgroundScheduler() #executors=executors)
sched = BlockingScheduler()
kwargs_pass = {'config': cl_config,
def one_step(path=''):
load_config(path)
init()
setup()
deploy()
def deploy(path=''):
load_config(path)
deploy_project()
def setup(path=''):
load_config(path)
setup_project()
setup_web_app()
def init(path=''):
load_config(path)
init_machine()
def config(path=''):
load_config(path)
log('load_config:' + str(env['load_config']) + " in the task->'config()'")
def create_super_user(path=''):
load_config(path)
with cd(env.django_project_root):
virtenvsudo('python manage.py createsuperuser')
def test_util_load_scraper_config(self):
""" Confirm that injested config contains 'db_path' """
config_in = cu.load_config(self.base_config_path)
self.assertTrue('db_path' in config_in.keys())