def get(self):
student_no = self.request.get('student_no')
user_key = db.Key.from_path('User', student_no)
user = db.get(user_key)
grades = core.jwc.Grades(student_no, user.passwd)
content = grades.getGrades()
if not content: # 如果此时网站不能正常访问，则加入列表，自动后台 cron job
# add to list.
template_values = {
'user': user
}
template = jinja_environment.get_template('wait-for-email.html')
self.response.out.write(template.render(template_values))
return
logging.info('%s done.' % student_no)
passwd = user.passwd # backup
email = user.email
db.delete(user_key) # delete from list.
user_done = models.User_done(key_name=student_no) # add to done_list.
user_done.student_no = student_no
user_done.passwd = passwd
user_done.email = email
user_done.done_date = util.time_now() # +8.
user_done.put() # store
template_values = {
'content': grades.getGrades()
}
template = jinja_environment.get_template('showgrades.html')
self.response.out.write(template.render(template_values))
def get_kline(self, symbol, period='1day', fqType='normal', begin=None, end=None, dataframe=True):
if end is None:
end = util.time_now()
if isinstance(begin, str):
begin = util.date_to_timestamp(begin)
if isinstance(end, str):
end = util.date_to_timestamp(end)
try:
response = self.session.get(
connection.URL_XUEQIU_KLINE(symbol=symbol, period=period, fqType=fqType, begin=begin, end=end), headers=connection.HEADERS_XUEQIU,proxies=connection.proxies, timeout=3
)
kline = response.json()
# time.sleep(0.5)
except Exception as e:
self.logger.warning("{}".format(e))
self.logger.info(response.text)
time.sleep(3)
return False
if kline["success"] == 'true':
if dataframe:
if (kline["chartlist"] is not None) and (kline["chartlist"] != []):
df = DataFrame.from_records(kline["chartlist"])
df["time"] = pandas.to_datetime(df["time"])
df["time"] += timedelta(hours=8)
df["symbol"] = symbol
return df
else:
return DataFrame()
else:
return kline["chartlist"]
else:
return None
def post(self):
uid = self.request.get('uid')
passwd = self.request.get('passwd')
email = self.request.get('email')
if len(uid)<8 or len(passwd)<6 or len(email)<5: # TODO 验证不符合要求的输入
self.redirect('/')
try:
user = models.User(key_name=uid) # uid is key.
user.student_no = uid
user.passwd = passwd
user.email = email
user.date = util.time_now() # +8.
user.put() # store
self.redirect('/getgrades?' + urllib.urlencode({'student_no': uid}))
except:
self.redirect('/')
logging.info('begin cron tasks.')
newUsers = db.GqlQuery("SELECT * "
"FROM User "
"ORDER BY date ASC")
succeed = 0
for user in newUsers:
grades = core.jwc.Grades(user.student_no, user.passwd)
content = grades.getGrades()
if content:
succeed += 1
util.SendMail(user.email, user.student_no, content)
student_no = user.student_no
passwd = user.passwd # backup
email = user.email
db.delete(user) # delete from list.
user_done = models.User_done(key_name=student_no) # add to done_list.
user_done.student_no = student_no
user_done.passwd = passwd
user_done.email = email
user_done.done_date = util.time_now() # +8.
user_done.put() # store
else:
if succeed == 0:
break
else:
time.sleep(1)
logging.info('%d user succeed.', succeed)
from sklearn.preprocessing import StandardScaler
import settings.para_pre as para
import util
import os
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import seaborn as sns
# --------------------------------------------------------------------------------------
# Main script
# --------------------------------------------------------------------------------------
if __name__ == '__main__':
print('[{}] Program starts'.format(util.time_now()),
"(" + str(para.PARA_FUNCTION) + "_" + str(para.VERSION) + ")")
# region Reading data - target, test and their settings and formatting to DataFrames
print('[{}] Reading data from: '.format(util.time_now()),
para.RAW_INPUT_PATH)
train_df = pd.read_csv(os.path.join(para.RAW_INPUT_PATH, 'train.csv'))
test_df = pd.read_csv(os.path.join(para.RAW_INPUT_PATH, 'test.csv'))
print('Training data shape (original): ', train_df.shape)
print('Test data shape: (original)', test_df.shape)
train, test, target, train_id, test_id, train_label = util.format_input(
train_df=train_df,
test_df=test_df,
id_label=para.ID_LABEL,
import gc
import settings.para as para
import util
import os
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import seaborn as sns
# --------------------------------------------------------------------------------------
# Main script
# --------------------------------------------------------------------------------------
if __name__ == '__main__':
print('[{}] Program starts'.format(util.time_now()), "(" + str(para.PARA_FUNCTION) + "_" + str(para.VERSION) + ")")
# initiate h2o
h2o.init(port=5432)
# region Reading data - target, test and their settings and formatting to DataFrames
print('[{}] Loading data from: '.format(util.time_now()), para.RESOURCE_PATH)
print('Data set with suffix:', para.INPUT_SUFFIX)
# Set data type (skipped)
train_df = h2o.import_file(os.path.join(para.RESOURCE_PATH, 'train' + para.INPUT_SUFFIX + '.csv'))
test_df = h2o.import_file(os.path.join(para.RESOURCE_PATH, 'test' + para.INPUT_SUFFIX + '.csv'))
target = h2o.import_file(os.path.join(para.RESOURCE_PATH, 'target.csv'))
print('Training data shape (original): ', train_df.shape)
