def test_multiple_ping(self):
subject = PingSensor()
with TemporaryDirectory() as d:
with ChangeToDir(d):
# when: multiple pings should be sent
subject.execute('1234', '8.8.8.8', {'method': PingSensor.MULTIPLE_PING_ID}, {'executable': RECORD_ARGS})
# then: the correct arguments are passed on the command line
args = arguments(d)
self.assertEqual(['-c', '3', '8.8.8.8'], args)
def test_ping_with_different_packet_size(self):
subject = PingSensor()
with TemporaryDirectory() as d:
with ChangeToDir(d):
# when: a single ping with a custom packet size should be sent
subject.execute('1234', '8.8.8.8',
{'method': PingSensor.SINGLE_PING_ID, 'size': 300},
{'executable': RECORD_ARGS})
# then: the correct arguments are passed on the command line
args = arguments(d)
self.assertEqual(['-c', '1', '-s', '300', '8.8.8.8'], args)
def eval_input(self, s):
namespace = {}
exec
PREEXEC in {}, namespace
def plot(f=None, **kwargs):
"""Plot functions. Not the same as SymPy's plot.
This plot function is specific to Gamma. It has the following syntax::
plot([x^2, x^3, ...])
or::
plot(y=x,y1=x^2,r=sin(theta),r1=cos(theta))
``plot`` accepts either a list of single-variable expressions to
plot or keyword arguments indicating expressions to plot. If
keyword arguments are used, the plot will be polar if the keyword
argument starts with ``r`` and will be an xy graph otherwise.
Note that Gamma will cut off plot values above and below a
certain value, and that it will **not** warn the user if so.
"""
pass
namespace.update({
'plot': plot, # prevent textplot from printing stuff
'help': lambda f: f
})
evaluator = Eval(namespace)
# change to True to spare the user from exceptions:
if not len(s):
return None
transformations = []
transformations.append(synonyms)
transformations.extend(standard_transformations)
transformations.extend((convert_xor, custom_implicit_transformation))
parsed = stringify_expr(s, {}, namespace, transformations)
try:
evaluated = eval_expr(parsed, {}, namespace)
except SyntaxError:
raise
except Exception as e:
raise ValueError(str(e))
input_repr = repr(evaluated)
namespace['input_evaluated'] = evaluated
return parsed, arguments(parsed, evaluator), evaluator, evaluated
def eval_input(self, s):
namespace = {}
exec PREEXEC in {}, namespace
def plot(f=None, **kwargs):
"""Plot functions. Not the same as SymPy's plot.
This plot function is specific to Gamma. It has the following syntax::
plot([x^2, x^3, ...])
or::
plot(y=x,y1=x^2,r=sin(theta),r1=cos(theta))
``plot`` accepts either a list of single-variable expressions to
plot or keyword arguments indicating expressions to plot. If
keyword arguments are used, the plot will be polar if the keyword
argument starts with ``r`` and will be an xy graph otherwise.
Note that Gamma will cut off plot values above and below a
certain value, and that it will **not** warn the user if so.
"""
pass
namespace.update({
'plot': plot, # prevent textplot from printing stuff
'help': lambda f: f
})
evaluator = Eval(namespace)
# change to True to spare the user from exceptions:
if not len(s):
return None
transformations = []
transformations.append(synonyms)
transformations.extend(standard_transformations)
transformations.extend((convert_xor, custom_implicit_transformation))
parsed = stringify_expr(s, {}, namespace, transformations)
try:
evaluated = eval_expr(parsed, {}, namespace)
except SyntaxError:
raise
except Exception as e:
raise ValueError(str(e))
input_repr = repr(evaluated)
namespace['input_evaluated'] = evaluated
return parsed, arguments(parsed, evaluator), evaluator, evaluated
def main():
args = arguments()
browser = args.browser
if browser.lower() == 'c' or browser.lower() == 'chrome':
driver = driver_chrome()
elif browser.lower() == 'f' or browser.lower() == 'firefox':
driver = driver_firefox()
print('\n-- RECLAME AQUI SCRAPER --')
file = args.file
id_page = args.id
pages = args.pages
conn, cursor = db_conn()
coletor = url_collector(driver, file, id_page, pages, conn, cursor)
scraper(driver, coletor, id_page, conn, cursor)
driver.quit()
def eval_input(self, s):
namespace = {}
exec PREEXEC in {}, namespace
evaluator = Eval(namespace)
# change to True to spare the user from exceptions:
if not len(s):
return None
transformations = []
transformations.append(synonyms)
transformations.extend(standard_transformations)
transformations.extend((convert_xor, custom_implicit_transformation))
local_dict = {
'plot': lambda *args: None # prevent textplot from printing stuff
}
global_dict = {}
exec 'from sympy import *' in global_dict
parsed = stringify_expr(s, local_dict, global_dict, transformations)
evaluated = eval_expr(parsed, local_dict, global_dict)
input_repr = repr(evaluated)
namespace['input_evaluated'] = evaluated
return parsed, arguments(parsed, evaluator), evaluator, evaluated
# print('\n'*5)
adam.zero_grad()
loss.backward()
for p in self.q.parameters():
p.grad.data.clamp_(-1., 1.)
adam.step()
self.update_counter += 1
if self.update_counter % self.target_net_update_freq == 0:
self.update_counter = 0
self.target.load_state_dict(self.q.state_dict())
args = utils.arguments()
bins = 2
env = BranchingTensorEnv(args.env, bins, 500_000, 500_000)
config = AgentConfig()
memory = ExperienceReplayMemory(config.memory_size)
agent = BranchingDQN(env.env.observation_space(), env.env.action_space(), bins,
config)
adam = optim.Adam(agent.q.parameters(), lr=config.lr)
s = env.reset()
ep_reward = 0.
recap = []
p_bar = tqdm(total=config.max_frames)
#!/usr/bin/env python
import argparse
from utils import Output, is_valid_user, arguments
from classes import Model
parser = argparse.ArgumentParser(description='Performs a data modeling pipeline',
usage='python model.py user password [OPTIONS]')
input_username, input_password, db_name, db_host = arguments(parser)
output = Output()
def model_data():
model = Model(input_username, input_password, db_name, db_host)
# Create course content similarity DataFrame
output.write('Create a course content similarity DataFrame')
output.warning('This process can take a long time')
output.start_spinner('Creating a course content similarity DataFrame')
try:
model.create_course_content_similarity_df()
output.spinner_success()
except Exception as err:
output.spinner_fail(str(err))
exit(1)
# Save courses content similarities to database
booking.rating = _host['rating']
booking.reviews = _host['evaluations']
session.add(booking)
session.commit()
logging.info(host)
except:
logging.error(_host)
logging.error("Exception occurred", exc_info=True)
except:
logging.error("Exception occurred", exc_info=True)
if __name__ == "__main__":
try:
args = arguments()
checkin = args['checkin']
checkout = args['checkout']
max_price = args['maxprice']
min_price = args['minprice']
num_pages = args['pages']
path = args['path']
host = args['host']
username = args['username']
password = args['password']
db = "hosts.db"
log_file = 'webscraping.log'
# logging.basicConfig(level=logging.WARNING, filename=os.path.join(path, log_file) , format='%(asctime)s :: %(message)s', datefmt='%Y-%m-%d %H:%M:%S', filemode='w+')
logging.basicConfig(level=logging.WARNING)