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def QA_SU_save_stock_xdxr(engine, client=DATABASE):
"""save stock_xdxr
Arguments:
engine {[type]} -- [description]
Keyword Arguments:
client {[type]} -- [description] (default: {DATABASE})
"""
engine = select_save_engine(engine)
engine.QA_SU_save_stock_xdxr(client=client) |
def QA_SU_save_stock_block(engine, client=DATABASE):
"""save stock_block
Arguments:
engine {[type]} -- [description]
Keyword Arguments:
client {[type]} -- [description] (default: {DATABASE})
"""
engine = select_save_engine(engine)
engine.QA_SU_save_stock_block(client=client) |
def select_save_engine(engine, paralleled=False):
'''
select save_engine , tushare ts Tushare 使用 Tushare 免费数据接口， tdx 使用通达信数据接口
:param engine: 字符串Str
:param paralleled: 是否并行处理；默认为False
:return: sts means save_tushare_py or stdx means save_tdx_py
'''
if engine in ['tushare', 'ts', 'Tushare']:... |
def QA_fetch_stock_day(code, start, end, format='numpy', frequence='day', collections=DATABASE.stock_day):
"""'获取股票日线'
Returns:
[type] -- [description]
感谢@几何大佬的提示
https://docs.mongodb.com/manual/tutorial/project-fields-from-query-results/#return-the-specified-fields-and-the-id-field-on... |
def QA_fetch_stock_min(code, start, end, format='numpy', frequence='1min', collections=DATABASE.stock_min):
'获取股票分钟线'
if frequence in ['1min', '1m']:
frequence = '1min'
elif frequence in ['5min', '5m']:
frequence = '5min'
elif frequence in ['15min', '15m']:
frequence = '15min'
... |
def QA_fetch_stock_list(collections=DATABASE.stock_list):
'获取股票列表'
return pd.DataFrame([item for item in collections.find()]).drop('_id', axis=1, inplace=False).set_index('code', drop=False) |
def QA_fetch_etf_list(collections=DATABASE.etf_list):
'获取ETF列表'
return pd.DataFrame([item for item in collections.find()]).drop('_id', axis=1, inplace=False).set_index('code', drop=False) |
def QA_fetch_index_list(collections=DATABASE.index_list):
'获取指数列表'
return pd.DataFrame([item for item in collections.find()]).drop('_id', axis=1, inplace=False).set_index('code', drop=False) |
def QA_fetch_stock_terminated(collections=DATABASE.stock_terminated):
'获取股票基本信息 , 已经退市的股票列表'
# 🛠todo 转变成 dataframe 类型数据
return pd.DataFrame([item for item in collections.find()]).drop('_id', axis=1, inplace=False).set_index('code', drop=False) |
def QA_fetch_stock_basic_info_tushare(collections=DATABASE.stock_info_tushare):
'''
purpose:
tushare 股票列表数据库
code,代码
name,名称
industry,所属行业
area,地区
pe,市盈率
outstanding,流通股本(亿)
totals,总股本(亿)
totalAssets,总资产(万)
liquidAssets,流动资产
... |
def QA_fetch_stock_full(date, format='numpy', collections=DATABASE.stock_day):
'获取全市场的某一日的数据'
Date = str(date)[0:10]
if QA_util_date_valid(Date) is True:
__data = []
for item in collections.find({
"date_stamp": QA_util_date_stamp(Date)}, batch_size=10000):
__data... |
def QA_fetch_index_min(
code,
start, end,
format='numpy',
frequence='1min',
collections=DATABASE.index_min):
'获取股票分钟线'
if frequence in ['1min', '1m']:
frequence = '1min'
elif frequence in ['5min', '5m']:
frequence = '5min'
elif frequence in ['15min... |
def QA_fetch_future_min(
code,
start, end,
format='numpy',
frequence='1min',
collections=DATABASE.future_min):
'获取股票分钟线'
if frequence in ['1min', '1m']:
frequence = '1min'
elif frequence in ['5min', '5m']:
frequence = '5min'
elif frequence in ['15m... |
def QA_fetch_future_list(collections=DATABASE.future_list):
'获取期货列表'
return pd.DataFrame([item for item in collections.find()]).drop('_id', axis=1, inplace=False).set_index('code', drop=False) |
def QA_fetch_ctp_tick(code, start, end, frequence, format='pd', collections=DATABASE.ctp_tick):
"""仅供存储的ctp tick使用
Arguments:
code {[type]} -- [description]
Keyword Arguments:
format {str} -- [description] (default: {'pd'})
collections {[type]} -- [description] (default: {DATABASE.... |
def QA_fetch_stock_xdxr(code, format='pd', collections=DATABASE.stock_xdxr):
'获取股票除权信息/数据库'
code = QA_util_code_tolist(code)
data = pd.DataFrame([item for item in collections.find(
{'code': {'$in': code}}, batch_size=10000)]).drop(['_id'], axis=1)
data['date'] = pd.to_datetime(data['date'])
... |
def QA_fetch_quotations(date=datetime.date.today(), db=DATABASE):
'获取全部实时5档行情的存储结果'
try:
collections = db.get_collection(
'realtime_{}'.format(date))
data = pd.DataFrame([item for item in collections.find(
{}, {"_id": 0}, batch_size=10000)])
return data.assign(dat... |
def QA_fetch_account(message={}, db=DATABASE):
"""get the account
Arguments:
query_mes {[type]} -- [description]
Keyword Arguments:
collection {[type]} -- [description] (default: {DATABASE})
Returns:
[type] -- [description]
"""
collection = DATABASE.account
return ... |
def QA_fetch_risk(message={}, params={"_id": 0, 'assets': 0, 'timeindex': 0, 'totaltimeindex': 0, 'benchmark_assets': 0, 'month_profit': 0}, db=DATABASE):
"""get the risk message
Arguments:
query_mes {[type]} -- [description]
Keyword Arguments:
collection {[type]} -- [description] (default... |
def QA_fetch_user(user_cookie, db=DATABASE):
"""
get the user
Arguments:
user_cookie : str the unique cookie_id for a user
Keyword Arguments:
db: database for query
Returns:
list --- [ACCOUNT]
"""
collection = DATABASE.account
return [res for res in collection... |
def QA_fetch_strategy(message={}, db=DATABASE):
"""get the account
Arguments:
query_mes {[type]} -- [description]
Keyword Arguments:
collection {[type]} -- [description] (default: {DATABASE})
Returns:
[type] -- [description]
"""
collection = DATABASE.strategy
retur... |
def QA_fetch_lhb(date, db=DATABASE):
'获取某一天龙虎榜数据'
try:
collections = db.lhb
return pd.DataFrame([item for item in collections.find(
{'date': date}, {"_id": 0})]).set_index('code', drop=False).sort_index()
except Exception as e:
raise e |
def QA_fetch_financial_report(code, report_date, ltype='EN', db=DATABASE):
"""获取专业财务报表
Arguments:
code {[type]} -- [description]
report_date {[type]} -- [description]
Keyword Arguments:
ltype {str} -- [description] (default: {'EN'})
db {[type]} -- [description] (default: {DAT... |
def QA_fetch_stock_divyield(code, start, end=None, format='pd', collections=DATABASE.stock_divyield):
'获取股票日线'
#code= [code] if isinstance(code,str) else code
# code checking
code = QA_util_code_tolist(code)
if QA_util_date_valid(end):
__data = []
cursor = collections.find({
... |
def QA_SU_save_stock_day(client=DATABASE, ui_log=None, ui_progress=None):
'''
save stock_day
保存日线数据
:param client:
:param ui_log: 给GUI qt 界面使用
:param ui_progress: 给GUI qt 界面使用
:param ui_progress_int_value: 给GUI qt 界面使用
'''
stock_list = QA_fetch_get_stock_list().code.unique().tolist... |
def QA_SU_save_stock_week(client=DATABASE, ui_log=None, ui_progress=None):
"""save stock_week
Keyword Arguments:
client {[type]} -- [description] (default: {DATABASE})
"""
stock_list = QA_fetch_get_stock_list().code.unique().tolist()
coll_stock_week = client.stock_week
coll_stock_week.... |
def QA_SU_save_stock_xdxr(client=DATABASE, ui_log=None, ui_progress=None):
"""[summary]
Keyword Arguments:
client {[type]} -- [description] (default: {DATABASE})
"""
stock_list = QA_fetch_get_stock_list().code.unique().tolist()
# client.drop_collection('stock_xdxr')
try:
coll =... |
def QA_SU_save_stock_min(client=DATABASE, ui_log=None, ui_progress=None):
"""save stock_min
Keyword Arguments:
client {[type]} -- [description] (default: {DATABASE})
"""
stock_list = QA_fetch_get_stock_list().code.unique().tolist()
coll = client.stock_min
coll.create_index(
[
... |
def QA_SU_save_index_day(client=DATABASE, ui_log=None, ui_progress=None):
"""save index_day
Keyword Arguments:
client {[type]} -- [description] (default: {DATABASE})
"""
__index_list = QA_fetch_get_stock_list('index')
coll = client.index_day
coll.create_index(
[('code',
... |
def QA_SU_save_index_min(client=DATABASE, ui_log=None, ui_progress=None):
"""save index_min
Keyword Arguments:
client {[type]} -- [description] (default: {DATABASE})
"""
__index_list = QA_fetch_get_stock_list('index')
coll = client.index_min
coll.create_index(
[
('c... |
def QA_SU_save_stock_list(client=DATABASE, ui_log=None, ui_progress=None):
"""save stock_list
Keyword Arguments:
client {[type]} -- [description] (default: {DATABASE})
"""
client.drop_collection('stock_list')
coll = client.stock_list
coll.create_index('code')
try:
# 🛠todo ... |
def QA_SU_save_etf_list(client=DATABASE, ui_log=None, ui_progress=None):
"""save etf_list
Keyword Arguments:
client {[type]} -- [description] (default: {DATABASE})
"""
try:
QA_util_log_info(
'##JOB16 Now Saving ETF_LIST ====',
ui_log=ui_log,
ui_progre... |
def QA_SU_save_stock_block(client=DATABASE, ui_log=None, ui_progress=None):
"""save stock_block
Keyword Arguments:
client {[type]} -- [description] (default: {DATABASE})
"""
client.drop_collection('stock_block')
coll = client.stock_block
coll.create_index('code')
try:
QA_u... |
def QA_SU_save_stock_info(client=DATABASE, ui_log=None, ui_progress=None):
"""save stock_info
Keyword Arguments:
client {[type]} -- [description] (default: {DATABASE})
"""
client.drop_collection('stock_info')
stock_list = QA_fetch_get_stock_list().code.unique().tolist()
coll = client.s... |
def QA_SU_save_stock_transaction(
client=DATABASE,
ui_log=None,
ui_progress=None
):
"""save stock_transaction
Keyword Arguments:
client {[type]} -- [description] (default: {DATABASE})
"""
stock_list = QA_fetch_get_stock_list().code.unique().tolist()
coll = client.st... |
def QA_SU_save_option_commodity_day(
client=DATABASE,
ui_log=None,
ui_progress=None
):
'''
:param client:
:return:
'''
_save_option_commodity_cu_day(
client=client,
ui_log=ui_log,
ui_progress=ui_progress
)
_save_option_commodity_m_day(
... |
def QA_SU_save_option_commodity_min(
client=DATABASE,
ui_log=None,
ui_progress=None
):
'''
:param client:
:return:
'''
# 测试中发现， 一起回去，容易出现错误，每次获取一个品种后 ，更换服务ip继续获取 ？
_save_option_commodity_cu_min(
client=client,
ui_log=ui_log,
ui_progress=ui... |
def QA_SU_save_option_min(client=DATABASE, ui_log=None, ui_progress=None):
'''
:param client:
:return:
'''
option_contract_list = QA_fetch_get_option_contract_time_to_market()
coll_option_min = client.option_day_min
coll_option_min.create_index(
[("code",
pymongo.ASCENDING)... |
def QA_SU_save_option_day(client=DATABASE, ui_log=None, ui_progress=None):
'''
:param client:
:return:
'''
option_contract_list = QA_fetch_get_option_50etf_contract_time_to_market()
coll_option_day = client.option_day
coll_option_day.create_index(
[("code",
pymongo.ASCENDIN... |
def QA_SU_save_future_day(client=DATABASE, ui_log=None, ui_progress=None):
'''
save future_day
保存日线数据
:param client:
:param ui_log: 给GUI qt 界面使用
:param ui_progress: 给GUI qt 界面使用
:param ui_progress_int_value: 给GUI qt 界面使用
:return:
'''
future_list = [
item for item in QA_... |
def QA_SU_save_future_min(client=DATABASE, ui_log=None, ui_progress=None):
"""save future_min
Keyword Arguments:
client {[type]} -- [description] (default: {DATABASE})
"""
future_list = [
item for item in QA_fetch_get_future_list().code.unique().tolist()
if str(item)[-2:] in ['... |
def do_shell(self, arg):
"run a shell commad"
print(">", arg)
sub_cmd = subprocess.Popen(arg, shell=True, stdout=subprocess.PIPE)
print(sub_cmd.communicate()[0]) |
def QA_fetch_stock_min_adv(
code,
start, end=None,
frequence='1min',
if_drop_index=True,
# 🛠 todo collections 参数没有用到， 且数据库是固定的， 这个变量后期去掉
collections=DATABASE.stock_min):
'''
'获取股票分钟线'
:param code: 字符串str eg 600085
:param start: 字符串str 开始日期 eg 2011-01-01
... |
def QA_fetch_stock_day_full_adv(date):
'''
'返回全市场某一天的数据'
:param date:
:return: QA_DataStruct_Stock_day类 型数据
'''
# 🛠 todo 检查日期data参数
res = QA_fetch_stock_full(date, 'pd')
if res is None:
print("QA Error QA_fetch_stock_day_full_adv parameter date=%s call QA_fetch_stock_full return... |
def QA_fetch_index_day_adv(
code,
start, end=None,
if_drop_index=True,
# 🛠 todo collections 参数没有用到， 且数据库是固定的， 这个变量后期去掉
collections=DATABASE.index_day):
'''
:param code: code: 字符串str eg 600085
:param start: 字符串str 开始日期 eg 2011-01-01
:param end: 字符串str 结束日期 eg 2... |
def QA_fetch_index_min_adv(
code,
start, end=None,
frequence='1min',
if_drop_index=True,
collections=DATABASE.index_min):
'''
'获取股票分钟线'
:param code:
:param start:
:param end:
:param frequence:
:param if_drop_index:
:param collections:
:return:
... |
def QA_fetch_stock_list_adv(collections=DATABASE.stock_list):
'''
'获取股票列表'
:param collections: mongodb 数据库
:return: DataFrame
'''
stock_list_items = QA_fetch_stock_list(collections)
if len(stock_list_items) == 0:
print("QA Error QA_fetch_stock_list_adv call item for item in collectio... |
def QA_fetch_index_list_adv(collections=DATABASE.index_list):
'''
'获取股票列表'
:param collections: mongodb 数据库
:return: DataFrame
'''
index_list_items = QA_fetch_index_list(collections)
if len(index_list_items) == 0:
print("QA Error QA_fetch_index_list_adv call item for item in collectio... |
def QA_fetch_future_day_adv(
code,
start, end=None,
if_drop_index=True,
# 🛠 todo collections 参数没有用到， 且数据库是固定的， 这个变量后期去掉
collections=DATABASE.index_day):
'''
:param code: code: 字符串str eg 600085
:param start: 字符串str 开始日期 eg 2011-01-01
:param end: 字符串str 结束日期 eg ... |
def QA_fetch_future_min_adv(
code,
start, end=None,
frequence='1min',
if_drop_index=True,
collections=DATABASE.future_min):
'''
'获取股票分钟线'
:param code:
:param start:
:param end:
:param frequence:
:param if_drop_index:
:param collections:
:return... |
def QA_fetch_future_list_adv(collections=DATABASE.future_list):
'''
'获取股票列表'
:param collections: mongodb 数据库
:return: DataFrame
'''
future_list_items = QA_fetch_future_list()
if len(future_list_items) == 0:
print("QA Error QA_fetch_future_list_adv call item for item in collections.fi... |
def QA_fetch_stock_block_adv(code=None, blockname=None, collections=DATABASE.stock_block):
'''
返回板块 ❌
:param code:
:param blockname:
:param collections: 默认数据库 stock_block
:return: QA_DataStruct_Stock_block
'''
if code is not None and blockname is None:
# 返回这个股票代码所属的板块
dat... |
def QA_fetch_stock_realtime_adv(code=None,
num=1,
collections=DATABASE.get_collection('realtime_{}'.format(datetime.date.today()))):
'''
返回当日的上下五档, code可以是股票可以是list, num是每个股票获取的数量
:param code:
:param num:
:param collections: realtime_X... |
def QA_fetch_financial_report_adv(code, start, end=None, ltype='EN'):
"""高级财务查询接口
Arguments:
code {[type]} -- [description]
start {[type]} -- [description]
Keyword Arguments:
end {[type]} -- [description] (default: {None})
"""
if end is None:
return QA_DataStruct_Fi... |
def QA_fetch_stock_financial_calendar_adv(code, start="all", end=None, format='pd', collections=DATABASE.report_calendar):
'获取股票日线'
#code= [code] if isinstance(code,str) else code
end = start if end is None else end
start = str(start)[0:10]
end = str(end)[0:10]
# code checking
if start == '... |
def QA_fetch_get_tdxtraderecord(file):
"""
QUANTAXIS 读取历史交易记录 通达信 历史成交-输出-xlsfile--转换csvfile
"""
try:
with open('./20180606.csv', 'r') as f:
l = csv.reader(f)
data = [item for item in l]
res = pd.DataFrame(data[1:], columns=data[0])
return res
except:... |
def AROON(DataFrame, N=14):
"""阿隆指标
Arguments:
DataFrame {[type]} -- [description]
Keyword Arguments:
N {int} -- [description] (default: {14})
Returns:
[type] -- [description]
"""
ar_up, ar_down = talib.AROON(DataFrame.high.values, DataFrame.low.values, N)... |
def get_commission_coeff(self, code):
"""
当前无法区分是百分比还是按手数收费,不过可以拿到以后自行判断
"""
return max(self.get_code(code).get('commission_coeff_peramount'),
self.get_code(code).get('commission_coeff_pervol')) |
def import_trade(self, trade):
"""
trade是一个可迭代的list/generator
"""
for item in trade:
self.make_deal(item.code, item.datetime, item.amount,
item.towards, item.price.item.order_model, item.amount_model) |
def make_deal(self, code, datetime, amount=100, towards=ORDER_DIRECTION.BUY, price=0, order_model=ORDER_MODEL.MARKET, amount_model=AMOUNT_MODEL.BY_AMOUNT):
"""
这是一个一定会成交,并且立刻结转(及t+0)的交易入口
"""
self.account.receive_deal(self.backtest_broker.receive_order(QA_Event(order=self.account.send_or... |
def cancel(self):
"""撤单
Arguments:
amount {int} -- 撤单数量
"""
self.cancel_amount = self.amount - self.trade_amount
if self.trade_amount == 0:
# 未交易 直接订单全撤
self._status = ORDER_STATUS.CANCEL_ALL
else:
# 部分交易 剩余订单全撤
... |
def failed(self, reason=None):
"""失败订单(未成功创建入broker)
Arguments:
reason {str} -- 失败原因
"""
# 订单创建失败(如废单/场外废单/价格高于涨停价/价格低于跌停价/通讯失败)
self._status = ORDER_STATUS.FAILED
self.reason = str(reason) |
def trade(self, trade_id, trade_price, trade_amount, trade_time):
"""trade 状态
Arguments:
amount {[type]} -- [description]
"""
if self.status in [ORDER_STATUS.SUCCESS_PART, ORDER_STATUS.QUEUED]:
trade_amount = int(trade_amount)
trade_id = str(trade_id)... |
def to_otgdict(self):
"""{
"aid": "insert_order", # //必填, 下单请求
# //必填, 需要与登录用户名一致, 或为登录用户的子账户(例如登录用户为user1, 则报单 user_id 应当为 user1 或 user1.some_unit)
"user_id": account_cookie,
# //必填, 委托单号, 需确保在一个账号中不重复, 限长512字节
"or... |
def from_otgformat(self, otgOrder):
"""[summary]
Arguments:
otgOrder {[type]} -- [description]
{'seqno': 6,
'user_id': '106184',
'order_id': 'WDRB_QA01_FtNlyBem',
'exchange_id': 'SHFE',
'instrument_id': 'rb1905',
'direction': 'SELL',
... |
def from_dict(self, order_dict):
'''
从字段类型的字段 填充 对象的字段
:param order_dict: dict 类型
:return: self QA_Order
'''
try:
# QA_util_log_info('QA_ORDER CHANGE: from {} change to {}'.format(
# self.order_id, order['order_id']))
self.price = ... |
def insert_order(self, order):
'''
:param order: QA_Order类型
:return:
'''
#print(" *>> QAOrder!insert_order {}".format(order))
# QUEUED = 300 # queued 用于表示在order_queue中 实际表达的意思是订单存活 待成交
#order.status = ORDER_STATUS.QUEUED
# 🛠 todo 是为了速度快把order对象转换成 d... |
def pending(self):
'''
600 废单 未委托成功
200 委托成功,完全交易
203 委托成功,未完全成功
300 委托队列 待成交
400 已撤单
500 服务器撤单/每日结算
订单生成(100) -- 废单(600)
订单生成(100) -- 进入待成交队列(300) -- 完全成交(200) -- 每日结算(500)-- 死亡
订单生成(100) -- 进入待成交队列(300) -- 部分成交(203) -- 未成交(300) -- 每日结算(... |
def _QA_data_stock_to_fq(bfq_data, xdxr_data, fqtype):
'使用数据库数据进行复权'
info = xdxr_data.query('category==1')
bfq_data = bfq_data.assign(if_trade=1)
if len(info) > 0:
data = pd.concat(
[
bfq_data,
info.loc[bfq_data.index[0]:bfq_data.index[-1],
... |
def QA_data_stock_to_fq(__data, type_='01'):
def __QA_fetch_stock_xdxr(
code,
format_='pd',
collections=DATABASE.stock_xdxr
):
'获取股票除权信息/数据库'
try:
data = pd.DataFrame(
[item for item in collections.find({'code': code})]
... |
def get_response(self, statement=None, **kwargs):
"""
Return the bot's response based on the input.
:param statement: An statement object or string.
:returns: A response to the input.
:rtype: Statement
:param additional_response_selection_parameters: Parameters to pass ... |
def generate_response(self, input_statement, additional_response_selection_parameters=None):
"""
Return a response based on a given input statement.
:param input_statement: The input statement to be processed.
"""
Statement = self.storage.get_object('statement')
results... |
def learn_response(self, statement, previous_statement=None):
"""
Learn that the statement provided is a valid response.
"""
if not previous_statement:
previous_statement = statement.in_response_to
if not previous_statement:
previous_statement = self.get_... |
def serialize(self):
"""
:returns: A dictionary representation of the statement object.
:rtype: dict
"""
data = {}
for field_name in self.get_statement_field_names():
format_method = getattr(self, 'get_{}'.format(
field_name
), Non... |
def import_module(dotted_path):
"""
Imports the specified module based on the
dot notated import path for the module.
"""
import importlib
module_parts = dotted_path.split('.')
module_path = '.'.join(module_parts[:-1])
module = importlib.import_module(module_path)
return getattr(mo... |
def initialize_class(data, *args, **kwargs):
"""
:param data: A string or dictionary containing a import_path attribute.
"""
if isinstance(data, dict):
import_path = data.get('import_path')
data.update(kwargs)
Class = import_module(import_path)
return Class(*args, **data... |
def validate_adapter_class(validate_class, adapter_class):
"""
Raises an exception if validate_class is not a
subclass of adapter_class.
:param validate_class: The class to be validated.
:type validate_class: class
:param adapter_class: The class type to check against.
:type adapter_class:... |
def get_response_time(chatbot, statement='Hello'):
"""
Returns the amount of time taken for a given
chat bot to return a response.
:param chatbot: A chat bot instance.
:type chatbot: ChatBot
:returns: The response time in seconds.
:rtype: float
"""
import time
start_time = tim... |
def print_progress_bar(description, iteration_counter, total_items, progress_bar_length=20):
"""
Print progress bar
:param description: Training description
:type description: str
:param iteration_counter: Incremental counter
:type iteration_counter: int
:param total_items: total number it... |
def get_unit(self, ureg, unit_variations):
"""
Get the first match unit metric object supported by pint library
given a variation of unit metric names (Ex:['HOUR', 'hour']).
:param ureg: unit registry which units are defined and handled
:type ureg: pint.registry.UnitRegistry obj... |
def get_valid_units(self, ureg, from_unit, target_unit):
"""
Returns the firt match `pint.unit.Unit` object for from_unit and
target_unit strings from a possible variation of metric unit names
supported by pint library.
:param ureg: unit registry which units are defined and hand... |
def handle_matches(self, match):
"""
Returns a response statement from a matched input statement.
:param match: It is a valid matched pattern from the input statement
:type: `_sre.SRE_Match`
"""
response = Statement(text='')
from_parsed = match.group("from")
... |
def get_default_response(self, input_statement):
"""
This method is called when a logic adapter is unable to generate any
other meaningful response.
"""
from random import choice
if self.default_responses:
response = choice(self.default_responses)
els... |
def time_question_features(self, text):
"""
Provide an analysis of significant features in the string.
"""
features = {}
# A list of all words from the known sentences
all_words = " ".join(self.positive + self.negative).split()
# A list of the first word in each... |
def can_process(self, statement):
"""
Determines whether it is appropriate for this
adapter to respond to the user input.
"""
response = self.process(statement)
self.cache[statement.text] = response
return response.confidence == 1 |
def process(self, statement, additional_response_selection_parameters=None):
"""
Takes a statement string.
Returns the equation from the statement with the mathematical terms solved.
"""
from mathparse import mathparse
input_text = statement.text
# Use the resul... |
def get_recent_repeated_responses(chatbot, conversation, sample=10, threshold=3, quantity=3):
"""
A filter that eliminates possibly repetitive responses to prevent
a chat bot from repeating statements that it has recently said.
"""
from collections import Counter
# Get the most recent statement... |
def get_most_frequent_response(input_statement, response_list, storage=None):
"""
:param input_statement: A statement, that closely matches an input to the chat bot.
:type input_statement: Statement
:param response_list: A list of statement options to choose a response from.
:type response_list: li... |
def get_first_response(input_statement, response_list, storage=None):
"""
:param input_statement: A statement, that closely matches an input to the chat bot.
:type input_statement: Statement
:param response_list: A list of statement options to choose a response from.
:type response_list: list
... |
def get_random_response(input_statement, response_list, storage=None):
"""
:param input_statement: A statement, that closely matches an input to the chat bot.
:type input_statement: Statement
:param response_list: A list of statement options to choose a response from.
:type response_list: list
... |
def compare(self, statement_a, statement_b):
"""
Compare the two input statements.
:return: The percent of similarity between the text of the statements.
:rtype: float
"""
# Return 0 if either statement has a falsy text value
if not statement_a.text or not state... |
def compare(self, statement_a, statement_b):
"""
Compare the two input statements.
:return: The percent of similarity between the closest synset distance.
:rtype: float
"""
document_a = self.nlp(statement_a.text)
document_b = self.nlp(statement_b.text)
r... |
def compare(self, statement_a, statement_b):
"""
Return the calculated similarity of two
statements based on the Jaccard index.
"""
# Make both strings lowercase
document_a = self.nlp(statement_a.text.lower())
document_b = self.nlp(statement_b.text.lower())
... |
def get_statement_model(self):
"""
Return the class for the statement model.
"""
from chatterbot.conversation import Statement
# Create a storage-aware statement
statement = Statement
statement.storage = self
return statement |
def mongo_to_object(self, statement_data):
"""
Return Statement object when given data
returned from Mongo DB.
"""
Statement = self.get_model('statement')
statement_data['id'] = statement_data['_id']
return Statement(**statement_data) |
def filter(self, **kwargs):
"""
Returns a list of statements in the database
that match the parameters specified.
"""
import pymongo
page_size = kwargs.pop('page_size', 1000)
order_by = kwargs.pop('order_by', None)
tags = kwargs.pop('tags', [])
ex... |
def create(self, **kwargs):
"""
Creates a new statement matching the keyword arguments specified.
Returns the created statement.
"""
Statement = self.get_model('statement')
if 'tags' in kwargs:
kwargs['tags'] = list(set(kwargs['tags']))
if 'search_te... |
def create_many(self, statements):
"""
Creates multiple statement entries.
"""
create_statements = []
for statement in statements:
statement_data = statement.serialize()
tag_data = list(set(statement_data.pop('tags', [])))
statement_data['tags... |
def get_random(self):
"""
Returns a random statement from the database
"""
from random import randint
count = self.count()
if count < 1:
raise self.EmptyDatabaseException()
random_integer = randint(0, count - 1)
statements = self.statements... |
def add_tags(self, *tags):
"""
Add a list of strings to the statement as tags.
"""
self.tags.extend([
Tag(name=tag) for tag in tags
]) |
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