本文整理汇总了Python中twilio.rest.Client.create方法的典型用法代码示例。如果您正苦于以下问题：Python Client.create方法的具体用法？Python Client.create怎么用？Python Client.create使用的例子？那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类twilio.rest.Client的用法示例。
在下文中一共展示了Client.create方法的1个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: __init__
# 需要导入模块: from twilio.rest import Client [as 别名]
# 或者: from twilio.rest.Client import create [as 别名]
class RedisMatching:
def __init__(self, config):
self.db = Redis(host=config['host'], port=config['port'], db=config['db'], decode_responses=True)
self.msg_client = Client(config['account_sid'], config['auth_token']).messages
self.msg_sender = config['sender']
def set_userdata(self, user_data):
user_data['timestamp'] = int(time())
return self.db.hmset(user_data['phone_numb'], user_data)
def get_userdata(self, user_name):
return self.db.hgetall(user_name)
def get_all_user(self):
return self.db.keys()
def remove_userdata(self, user_name):
return self.db.delete(user_name)
def send_message(self, phone_numb, message):
phone_numb = '+82'+phone_numb[1:]
result = self.msg_client.create(to=phone_numb,
from_=self.msg_sender,
body=message
)
return result
def initialize(self):
for key in self.get_all_user():
self.db.delete(key)
def match_user(self):
def make_food_vector(user_data):
food_vector = [ int(user_data['cutlet']),
int(user_data['hamburger']),
int(user_data['noodle']),
int(user_data['korean_food']) ]
return food_vector
def make_message_text(target_name, user_data, similarity=0):
if user_data['gender'] == 'male' : user_data['gender'] = '남'
elif user_data['gender'] == 'female' : user_data['gender'] = '여'
text ='%s님, 혼밥러 매칭완료!\n\n상대 : %s님\n연락처 : %s\n성별 : %s\n유사도 : %0.2f' \
%(target_name, user_data['user_name']
, user_data['phone_numb'], user_data['gender']
, similarity*100)
return text
while(len(self.get_all_user()) >= 2):
user_list = self.get_all_user()
user_data_list = list(map(self.get_userdata, user_list))
user_data_list = [[user_data['timestamp'], user_data] for user_data in user_data_list]
user_data_list = [user_data[1] for user_data in sorted(user_data_list)]
print(user_data_list)
target_user = user_data_list[0]
target_vec = make_food_vector(target_user)
similarity_list = []
for user_data in user_data_list[1:]:
user_vec = make_food_vector(user_data)
similarity = RedisMatching.cosine_similarity(target_vec, user_vec)
similarity_list.append( (similarity, user_data) )
max_val = max(similarity_list)
print(max_val)
text = make_message_text(target_user['user_name'], max_val[1], max_val[0])
self.send_message(target_user['phone_numb'], text)
print(text)
text = make_message_text(max_val[1]['user_name'], target_user, max_val[0])
self.send_message(max_val[1]['phone_numb'], text)
print(text)
# self.remove_userdata(target_user['phone_numb'])
# self.remove_userdata(max_val[1]['phone_numb'])
return True
@staticmethod
def cvt_unit_vec(vector):
scalar = math.sqrt(sum([i*i for i in vector]))
return [idx/scalar for idx in vector]
@staticmethod
def cosine_similarity(a, b):
a = RedisMatching.cvt_unit_vec(a)
b = RedisMatching.cvt_unit_vec(b)
return sum([i*j for i,j in zip(a, b)])
@staticmethod
def custom_similarity(a, b):
# a = RedisMatching.cvt_unit_vec(a)
# b = RedisMatching.cvt_unit_vec(b)
c = [i-j for i,j in zip(a, b)]
c = [i*i for i in c]
return 300 - math.sqrt(sum(c))