def supported_games():
output = ""
for game in config:
if game != "fallback":
output += "\t {game!s}".format(game=game)
if game is not config.keys()[len(config) - 1]:
output += "\n"
return output
def create_app_for_manager(config_name=None):
print "app config name: %s\n" % config_name
if config_name is not None:
if config_name in config.keys():
pass
else:
print "Wrong app config name: %s. Use default instead." % config_name
config_name = 'default'
else:
config_name = 'default'
app = create_app(config_name)
return app
def create_app(config_name):
app = Flask(__name__)
if not config_name in config:
raise ValueError("Invalid FLASK_CONFIG, choose one of %s" %
str.join(',', config.keys()))
app.config.from_object(config[config_name])
config[config_name].init_app(app)
from .api_1_0 import api as api_1_0_blueprint
app.register_blueprint(api_1_0_blueprint, url_prefix='/api/1.0')
from .ui import ui
app.register_blueprint(ui)
return app
def create_app(config_name):
app = Flask(__name__, static_folder='dashboard/dist')
if not config_name in config:
raise ValueError("Invalid FLASK_CONFIG, choose one of %s" %
str.join(', ', config.keys()))
app.config.from_object(config[config_name])
config[config_name].init_app(app)
from .api_1_0 import api as api_1_0_blueprint
app.register_blueprint(api_1_0_blueprint, url_prefix='/api/1.0')
from .dashboard import dashboard
app.register_blueprint(dashboard)
from .docs import docs
app.register_blueprint(docs, url_prefix='/docs')
Bower(app)
return app
def sub_cb(topic, message):
print((topic, message))
topic = topic.decode()
message = message.decode().strip("\"' ")
print((topic, message))
command = topic.split('/')[-1].strip("\"' ")
print("command: ", command)
if (command == "reboot"):
# Reboot command
if (message == "yes"):
mqttSend("Reboot command received. Rebooting...")
machine.reset()
else:
mqttSend("Reboot command received but the message is not as expected so ignore. Message: " + message)
elif (command == "save"):
if (message == "yes"):
mqttSend("Save current configuration into file.")
saveConfig()
else:
mqttSend("Save command received but the message is not as expected so ignore. Message: " + message)
# Check if received command is known as a configuration name
elif (command in config.keys()):
key = command
newValue = message
oldValue = config[key]
if (newValue == ""):
mqttSend("{key} = {oldValue}".format(key = key, oldValue = oldValue))
else:
config[key] = newValue
mqttSend("{key} has been updated to {newValue} from {oldValue}".format(key = key, oldValue = oldValue, newValue = newValue))
saveConfig()
else:
# Unknown command
mqttSend("Unknown command: {command}. Ignore.".format(command = command))
def filter(event):
'''Required filter() function that evaluates the lambda event'''
''' evaluate the lambda event data and return:
- None to abort ec2 execution
- list containing True and an optional list of values to
pass to the user_data '''
print("ec2_lambda received {}".format(event))
subject = event['Records'][0]['Sns']['Subject']
message = event['Records'][0]['Sns']['Message']
# if testfolder exists, use it.
if 'filter_testfolder' in config.keys():
message = config['filter_testfolder']
if not _check_prefix_in_bucket(message, config['custom_s3bucket']):
return(None)
if subject == 'TeslaCam Upload':
return([message])
else:
print("'Subject did not match 'TeslaCam Upload'")
return(None)
# Packages
import yaml
import boto3
# For pushover
import pushover
import os
# for identifying video file created
import re
from botocore.exceptions import ClientError
import time
# Force a few defaults in case the values aren't specified
for value in ['custom_pushover_token', 'custom_pushover_key']:
if value not in config.keys():
config[value] = None
# The functions below should be entirely rewritten based upn the
# particular lambda deployment and use case.
#
# filter(): evaluate the event data passed in to the lambda to
# 1) determine if the ec2 should launch and to 2) return back a list
# of values that can be used to format the ec2 user_data.
# Return: None if the ec2 should not launch or a list of values todo
# use as substitutions in user_data
#
# pre_process()
#
# launched_actions()
#
import mandrill
import logging
import sys
import os
application = Flask(__name__)
# FIXME set url prefix for celery tasks
application.register_blueprint(blueprint_app)
application.register_blueprint(blueprint_api, url_prefix='/api')
logger = logging.getLogger(__name__)
# update config from yaml dict
for key in config.keys():
application.config.update(key=config[key])
# write logs to a file for production
if config['DEBUG'] is not True:
from logging.handlers import RotatingFileHandler
file_handler = RotatingFileHandler('python.log', maxBytes=1024 * 1024 * 100, backupCount=20)
file_handler.setLevel(logging.ERROR)
formatter = logging.Formatter("%(asctime)s - %(name)s - %(levelname)s - %(message)s")
file_handler.setFormatter(formatter)
application.logger.addHandler(file_handler)
# if the upload folder doesn't exist we've just started the application.
if not os.path.exists(config['UPLOAD_FOLDER']):
logger.error("upload folder didn't exist, creating it now")
try:
from slacker import Slacker
from config import config
API_KEY = None
CHANNEL = None
slacker = None
if 'slack' in config.keys():
API_KEY = config['slack']['API_KEY']
CHANNEL = config['slack']['CHANNEL']
slacker = Slacker(API_KEY)
def post_slack(
_str=None,
file_title=None,
file_path=None,
image_url=None,
channel=None,
):
print('post_slack', _str)
if slacker is None:
print('slacker is None')
return
if channel is None:
channel = CHANNEL
if file_path:
slacker.files.upload(
file_path,
def train(device_ids, device) :
#if training stopped suddenly, resume
if config['resume']:
state = torch.load(os.path.join(config['@root'], config['@save'], config['@checkpoint'], config['version']+'.pth'))
if sum([str(config[key])==str(state['config'][key]) for key in config.keys() if key != 'resume']) != (len(config)-1):
print('Error : resume with different config')
print([(config[key], state['config'][key])
for key in config.keys() if str(config[key]) != str(state['config'][key]) and key !='resume'])
raise
folds = range(state['fold'], config['#fold']+1)
epochs = range(state['epoch']+1, config['#epoch']+1)
logger.debug('Resume {} : starts from Fold[{}/{}] Epoch[{}/{}]'.format(
config['version'], state['fold'], config['#fold'], state['epoch']+1, config['#epoch']))
#if not resume then fresh start
else :
folds = range(1, config['#fold']+1)
epochs = range(1, config['#epoch']+1)
#Cross-validation
fold_best_metric = []
for fold in folds:
#bring Dataset
train_loader = Dataloader(split='train', fold=fold)
val_loader = Dataloader(split='val', fold=fold)
#define Model
model = nn.DataParallel(config['model'](config['#class']), device_ids=device_ids)
model.to(device)
if config['resume'] and fold == folds[0] : model.load_state_dict(state['model_state'])
optimizer = config['optimizer'](model.parameters(), lr=config['lr'])
if config['resume'] and fold == folds[0] : optimizer.load_state_dict(state['optimizer_state'])
criterion = config['criterion']()
#check performance with model of random initialization
metric = run(fold=fold, epoch=-1, grad=False, model=model, optimizer=optimizer,
criterion=criterion, loader=val_loader, device=device)
logger.info('Random check {} | Fold[{}/{}] \n Metric {}'.format(
' val ', fold, config['#fold'], metric))
patience = 0
best_metric = {key:-1 for key in config['metric']}
for epoch in epochs :
#train
model, optimizer, metric = run(fold=fold, epoch=epoch, grad=True, model=model, optimizer=optimizer,
criterion=criterion, loader=train_loader, device=device)
logger.info('{} | Fold[{}/{}] Epoch[{}/{}] \n Metric {}'.format(
'train', fold, config['#fold'], epoch, config['#epoch'], metric))
#validate
metric = run(fold=fold, epoch=epoch, grad=False, model=model, optimizer=optimizer,
criterion=criterion, loader=val_loader, device=device)
logger.info('{} | Fold[{}/{}] Epoch[{}/{}] \n Metric {}'.format(
' val ', fold, config['#fold'], epoch, config['#epoch'], metric))
#update te best performance
if metric[config['decision_metric']] > best_metric[config['decision_metric']] :
best_metric = metric
save_model(checkpoint=False, fold=fold, epoch=epoch, metric=metric, model=model, optimizer=optimizer)
logger.debug('Fold[{}/{}] Epoch[{}/{}] Model saved'.format(
fold, config['#fold'], epoch, config['#epoch']))
patience = 0
else :
patience += 1
#early stopping
if patience == config['patience']:
logger.debug('Stopped early at Epoch {}'.format(epoch))
break
if epoch % config['checkpoint_term'] == 0:
save_model(checkpoint=True, fold=fold, epoch=epoch, metric=metric, model=model, optimizer=optimizer)
if config['#fold'] == 2:
break
if config['resume']:
epochs = range(1, config['#epoch']+1)
fold_best_metric.append(best_metric)
logger.info(' -------------------- END OF TRAIN -------------------- ')
#print performance
for key in config['metric']:
avg_metric=sum([best_metric[key] for best_metric in fold_best_metric])/len(fold_best_metric)
logger.info('{} | Avg {} : {}'.format('val', key, avg_metric))
#test
if config['test']:
test_loader = Dataloader(split='test', fold=0)
metric_list = []
for fold in range(1, config['#fold']+1):
path = os.path.join(config['@root'], config['@save'], config['@best_model'], config['version'], str(fold)+'.pth')
state = torch.load(path)
model.load_state_dict(state['model_state'])
optimizer.load_state_dict(state['optimizer_state'])
metric = run(fold=fold, epoch=epoch, grad=False, model=model, optimizer=optimizer,
criterion=criterion, loader=test_loader, device=device)
logger.info('{} | Fold[{}/{}] \n Metric {}'.format(
'test ', fold, config['#fold'], metric))
metric_list.append(metric)
for key in config['metric']:
avg_metric=sum([metric[key] for metric in metric_list])/len(metric_list)
logger.info('{} | Avg {} : {}'.format('test', key, avg_metric))
import time
import os
import logging
from lib.diskmapper import DiskMapper
from config import config
logger = logging.getLogger('disk_mapper_daemon')
hdlr = logging.FileHandler('/var/log/disk_mapper.log')
formatter = logging.Formatter('%(asctime)s %(process)d %(thread)d %(filename)s %(lineno)d %(levelname)s %(message)s')
hdlr.setFormatter(formatter)
logger.addHandler(hdlr)
logger.setLevel(logging.INFO)
poll_interval = 5
if "params" in config.keys():
if "log_level" in config["params"].keys():
log_level = config["params"]["log_level"]
if log_level == "info":
logger.setLevel(logging.INFO)
elif log_level == "error":
logger.setLevel(logging.ERROR)
elif log_level == "debug":
logger.setLevel(logging.DEBUG)
if poll_interval in config["params"].keys():
poll_interval = config["params"]["poll_interval"]
def is_daemon_stopped():
if not os.path.exists("/var/run/disk_mapper.lock"):
logger.info("=== Disk Mapper Stopped ===")
book={}
while True:
logging.info(url)
title,content,next_url=getall(url)
print next_url
#如果一切正常，把它标记为正常页面
if content!=None and next_url!=None:
normal_url=url
#如果下一页为空使用最近的正常页面,如果不是空的话继续下一页
if next_url==None:
url=normal_url
else:
url=next_url
#这个页面可能是目录,主要为了防止目录中出现"下一章"
if next_url.find('index')>0:
url=normal_url
if content!=None:
book=addchapter(book,bookname,title,content)
for _CreatTime,_Title,_Content in book[bookname]:
file=open('a.txt','a')
file.write(_Content.encode('gbk'))
print _Title
if url==normal_url:
config[bookname]=[url]
yamlwrite(config)
return
for bookname in config.keys():
for url in config[bookname]:
run(bookname,url)
import logging
import httplib
import base64
import subprocess
from signal import SIGSTOP, SIGCONT
from config import config
from cgi import parse_qs
logger = logging.getLogger('disk_mapper')
hdlr = logging.FileHandler('/var/log/disk_mapper.log')
formatter = logging.Formatter('%(asctime)s %(process)d %(thread)d %(filename)s %(lineno)d %(levelname)s %(message)s')
hdlr.setFormatter(formatter)
logger.addHandler(hdlr)
logger.setLevel(logging.INFO)
if "params" in config.keys() and "log_level" in config["params"].keys():
log_level = config["params"]["log_level"]
if log_level == "info":
logger.setLevel(logging.INFO)
elif log_level == "error":
logger.setLevel(logging.ERROR)
elif log_level == "debug":
logger.setLevel(logging.DEBUG)
def acquire_lock(lock_file):
lockfd = open(lock_file, 'w')
fcntl.flock(lockfd.fileno(), fcntl.LOCK_EX)
return lockfd
def release_lock(fd):
fcntl.flock(fd.fileno(), fcntl.LOCK_UN)
from models import blueprint_app
from config import config
import mandrill
import logging
import sys
import os
application = Flask(__name__)
# FIXME set url prefix for celery tasks
application.register_blueprint(blueprint_app)
application.register_blueprint(blueprint_api, url_prefix='/api')
logger = logging.getLogger(__name__)
# update config from yaml dict
for key in config.keys():
application.config.update(key=config[key])
# write logs to a file for production
if config['DEBUG'] is not True:
from logging.handlers import RotatingFileHandler
file_handler = RotatingFileHandler('python.log',
maxBytes=1024 * 1024 * 100,
backupCount=20)
file_handler.setLevel(logging.ERROR)
formatter = logging.Formatter(
"%(asctime)s - %(name)s - %(levelname)s - %(message)s")
file_handler.setFormatter(formatter)
application.logger.addHandler(file_handler)
# if the upload folder doesn't exist we've just started the application.
