本文整理汇总了Python中sqlalchemy.types.Date方法的典型用法代码示例。如果您正苦于以下问题:Python types.Date方法的具体用法?Python types.Date怎么用?Python types.Date使用的例子?那么, 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sqlalchemy.types
的用法示例。
在下文中一共展示了types.Date方法的15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: get_type
# 需要导入模块: from sqlalchemy import types [as 别名]
# 或者: from sqlalchemy.types import Date [as 别名]
def get_type(data_type):
type_map = {
"bytes": types.LargeBinary,
"boolean": types.Boolean,
"date": types.Date,
"datetime": types.DateTime,
"double": types.Numeric,
"text": types.String,
"keyword": types.String,
"integer": types.Integer,
"half_float": types.Float,
"geo_point": types.String,
# TODO get a solution for nested type
"nested": types.String,
# TODO get a solution for object
"object": types.BLOB,
"long": types.BigInteger,
"float": types.Float,
"ip": types.String,
}
type_ = type_map.get(data_type)
if not type_:
logger.warning(f"Unknown type found {data_type} reverting to string")
type_ = types.String
return type_
示例2: fields_map
# 需要导入模块: from sqlalchemy import types [as 别名]
# 或者: from sqlalchemy.types import Date [as 别名]
def fields_map(self, field_type):
if field_type == "primary":
return ID(stored=True, unique=True)
type_map = {
'date': types.Date,
'datetime': types.DateTime,
'boolean': types.Boolean,
'integer': types.Integer,
'float': types.Float
}
if isinstance(field_type, str):
field_type = type_map.get(field_type, types.Text)
if not isinstance(field_type, type):
field_type = field_type.__class__
if issubclass(field_type, (types.DateTime, types.Date)):
return DATETIME(stored=True, sortable=True)
elif issubclass(field_type, types.Integer):
return NUMERIC(stored=True, numtype=int)
elif issubclass(field_type, types.Float):
return NUMERIC(stored=True, numtype=float)
elif issubclass(field_type, types.Boolean):
return BOOLEAN(stored=True)
return TEXT(stored=True, analyzer=self.analyzer, sortable=False)
示例3: test_python_type
# 需要导入模块: from sqlalchemy import types [as 别名]
# 或者: from sqlalchemy.types import Date [as 别名]
def test_python_type(self):
eq_(types.Integer().python_type, int)
eq_(types.Numeric().python_type, decimal.Decimal)
eq_(types.Numeric(asdecimal=False).python_type, float)
eq_(types.LargeBinary().python_type, util.binary_type)
eq_(types.Float().python_type, float)
eq_(types.Interval().python_type, datetime.timedelta)
eq_(types.Date().python_type, datetime.date)
eq_(types.DateTime().python_type, datetime.datetime)
eq_(types.String().python_type, str)
eq_(types.Unicode().python_type, util.text_type)
eq_(types.Enum("one", "two", "three").python_type, str)
assert_raises(
NotImplementedError, lambda: types.TypeEngine().python_type
)
示例4: test_conn_execute
# 需要导入模块: from sqlalchemy import types [as 别名]
# 或者: from sqlalchemy.types import Date [as 别名]
def test_conn_execute(self, connection):
from sqlalchemy.sql.expression import FunctionElement
from sqlalchemy.ext.compiler import compiles
class myfunc(FunctionElement):
type = Date()
@compiles(myfunc)
def compile_(elem, compiler, **kw):
return compiler.process(func.current_date())
x = connection.execute(func.current_date()).scalar()
y = connection.execute(func.current_date().select()).scalar()
z = connection.scalar(func.current_date())
q = connection.scalar(myfunc())
assert (x == y == z == q) is True
示例5: test_extract_expression
# 需要导入模块: from sqlalchemy import types [as 别名]
# 或者: from sqlalchemy.types import Date [as 别名]
def test_extract_expression(self, connection):
meta = self.metadata
table = Table("test", meta, Column("dt", DateTime), Column("d", Date))
meta.create_all(connection)
connection.execute(
table.insert(),
{
"dt": datetime.datetime(2010, 5, 1, 12, 11, 10),
"d": datetime.date(2010, 5, 1),
},
)
rs = connection.execute(
select([extract("year", table.c.dt), extract("month", table.c.d)])
)
row = rs.first()
assert row[0] == 2010
assert row[1] == 5
rs.close()
示例6: _compare_type_affinity
# 需要导入模块: from sqlalchemy import types [as 别名]
# 或者: from sqlalchemy.types import Date [as 别名]
def _compare_type_affinity(self, other):
return other._type_affinity in (sqltypes.DateTime, sqltypes.Date)
示例7: fields_map
# 需要导入模块: from sqlalchemy import types [as 别名]
# 或者: from sqlalchemy.types import Date [as 别名]
def fields_map(self, field_type):
if field_type == "primary":
return {'type': 'keyword'}
type_map = {
'date': types.Date,
'datetime': types.DateTime,
'boolean': types.Boolean,
'integer': types.Integer,
'float': types.Float,
'binary': types.Binary
}
if isinstance(field_type, str):
field_type = type_map.get(field_type, types.Text)
if not isinstance(field_type, type):
field_type = field_type.__class__
if issubclass(field_type, (types.DateTime, types.Date)):
return {'type': 'date'}
elif issubclass(field_type, types.Integer):
return {'type': 'long'}
elif issubclass(field_type, types.Float):
return {'type': 'float'}
elif issubclass(field_type, types.Boolean):
return {'type': 'boolean'}
elif issubclass(field_type, types.Binary):
return {'type': 'binary'}
return {'type': 'string'}
# https://medium.com/@federicopanini/elasticsearch-6-0-removal-of-mapping-types-526a67ff772
示例8: test_should_date_convert_string
# 需要导入模块: from sqlalchemy import types [as 别名]
# 或者: from sqlalchemy.types import Date [as 别名]
def test_should_date_convert_string():
assert get_field(types.Date()).type == graphene.String
示例9: import_jq_stock_info
# 需要导入模块: from sqlalchemy import types [as 别名]
# 或者: from sqlalchemy.types import Date [as 别名]
def import_jq_stock_info(chain_param=None, refresh=False):
""" 获取全市场股票代码及名称
"""
table_name = TABLE_NAME
logging.info("更新 %s 开始", table_name)
# has_table = engine_md.has_table(table_name)
param_list = [
('jq_code', String(20)),
('display_name', String(20)),
('name', String(20)),
('start_date', Date),
('end_date', Date),
]
# 设置 dtype
dtype = {key: val for key, val in param_list}
# 数据提取
# types: list: 用来过滤securities的类型, list元素可选:
# 'stock', 'fund', 'index', 'futures', 'etf', 'lof', 'fja', 'fjb'。types为空时返回所有股票, 不包括基金,指数和期货
# date: 日期, 一个字符串或者 [datetime.datetime]/[datetime.date] 对象,
# 用于获取某日期还在上市的股票信息. 默认值为 None, 表示获取所有日期的股票信息
stock_info_all_df = get_all_securities()
stock_info_all_df.index.rename('jq_code', inplace=True)
stock_info_all_df.reset_index(inplace=True)
logging.info('%s stock data will be import', stock_info_all_df.shape[0])
data_count = bunch_insert_on_duplicate_update(
stock_info_all_df, table_name, engine_md, dtype=dtype,
myisam_if_create_table=True, primary_keys=['jq_code'], schema=config.DB_SCHEMA_MD)
logging.info("更新 %s 完成 存量数据 %d 条", table_name, data_count)
# 更新 map 表
update_from_info_table(table_name)
示例10: import_info_table
# 需要导入模块: from sqlalchemy import types [as 别名]
# 或者: from sqlalchemy.types import Date [as 别名]
def import_info_table(type_name, insert_db=True) -> pd.DataFrame:
"""
调用 get_all_securities 获取指定 type 的信息
type: 'stock', 'fund', 'index', 'futures', 'etf', 'lof', 'fja', 'fjb'。types为空时返回所有股票, 不包括基金,指数和期货
:param type_name:
:return:
"""
table_name = f'jq_{type_name}_info'
logger.info("更新 %s 开始", table_name)
# has_table = engine_md.has_table(table_name)
param_list = [
('jq_code', String(20)),
('display_name', String(20)),
('name', String(20)),
('start_date', Date),
('end_date', Date),
]
# 设置 dtype
dtype = {key: val for key, val in param_list}
# 数据提取
# types: list: 用来过滤securities的类型, list元素可选:
# 'stock', 'fund', 'index', 'futures', 'etf', 'lof', 'fja', 'fjb'。types为空时返回所有股票, 不包括基金,指数和期货
# date: 日期, 一个字符串或者 [datetime.datetime]/[datetime.date] 对象,
# 用于获取某日期还在上市的股票信息. 默认值为 None, 表示获取所有日期的股票信息
stock_info_all_df = get_all_securities(types=type_name)
stock_info_all_df.index.rename('jq_code', inplace=True)
stock_info_all_df.reset_index(inplace=True)
if insert_db:
logger.info('%s 数据将被导入', stock_info_all_df.shape[0])
data_count = bunch_insert_p(stock_info_all_df, table_name=table_name, dtype=dtype, primary_keys=['jq_code'])
logger.info("更新 %s 完成 存量数据 %d 条", table_name, data_count)
return stock_info_all_df
示例11: import_jq_trade_date
# 需要导入模块: from sqlalchemy import types [as 别名]
# 或者: from sqlalchemy.types import Date [as 别名]
def import_jq_trade_date(chain_param=None):
"""
插入股票日线数据到最近一个工作日-1。
如果超过 BASE_LINE_HOUR 时间,则获取当日的数据
:return:
"""
logger.info("更新 %s 开始", TABLE_NAME)
# 判断表是否已经存在
has_table = engine_md.has_table(TABLE_NAME)
if has_table:
trade_day_max = execute_scalar(f'SELECT max(trade_date) FROM {TABLE_NAME}', engine_md)
trade_date_list = get_trade_days(start_date=(trade_day_max + timedelta(days=1)),
end_date=(date.today() + timedelta(days=366)))
else:
trade_date_list = get_all_trade_days()
date_count = len(trade_date_list)
if date_count == 0:
logger.info("没有更多的交易日数据可被导入")
return
logger.info("%d 条交易日数据将被导入", date_count)
trade_date_df = pd.DataFrame({'trade_date': trade_date_list})
bunch_insert_on_duplicate_update(trade_date_df, TABLE_NAME, engine_md,
dtype={'trade_date': Date},
myisam_if_create_table=True,
primary_keys=['trade_date'], schema=config.DB_SCHEMA_MD)
logger.info('%d 条交易日数据导入 %s 完成', date_count, TABLE_NAME)
示例12: save_future_daily_df_list
# 需要导入模块: from sqlalchemy import types [as 别名]
# 或者: from sqlalchemy.types import Date [as 别名]
def save_future_daily_df_list(data_df_list):
"""将期货历史数据保存的数据库"""
data_df_count = len(data_df_list)
if data_df_count > 0:
logger.info('merge data with %d df', data_df_count)
data_df = pd.concat(data_df_list)
data_count = data_df.shape[0]
data_df.to_sql('ifind_future_daily', engine_md, if_exists='append', index=False,
dtype={
'ths_code': String(20),
'time': Date,
'preClose': String(20),
'open': DOUBLE,
'high': DOUBLE,
'low': DOUBLE,
'close': DOUBLE,
'volume': DOUBLE,
'amount': DOUBLE,
'avgPrice': DOUBLE,
'change': DOUBLE,
'changeRatio': DOUBLE,
'preSettlement': DOUBLE,
'settlement': DOUBLE,
'change_settlement': DOUBLE,
'chg_settlement': DOUBLE,
'openInterest': DOUBLE,
'positionChange': DOUBLE,
'amplitude': DOUBLE,
})
logger.info("更新 wind_future_daily 结束 %d 条记录被更新", data_count)
else:
logger.info("更新 wind_future_daily 结束 0 条记录被更新")
示例13: import_tushare_stock_info
# 需要导入模块: from sqlalchemy import types [as 别名]
# 或者: from sqlalchemy.types import Date [as 别名]
def import_tushare_stock_info(chain_param=None, refresh=False):
""" 获取全市场股票代码及名称
"""
table_name = 'tushare_stock_info'
logging.info("更新 %s 开始", table_name)
has_table = engine_md.has_table(table_name)
tushare_indicator_param_list = [
('ts_code', String(20)),
('symbol', String(20)),
('name', String(40)),
('area', String(100)),
('industry', String(200)),
('fullname', String(100)),
('enname', String(200)),
('market', String(100)),
('exchange', String(20)),
('curr_type', String(20)),
('list_status', String(20)),
('list_date', Date),
('delist_date', Date),
('is_hs', String(20)),
]
# # 获取列属性名,以逗号进行分割 "ipo_date,trade_code,mkt,exch_city,exch_eng"
param = ",".join([key for key, _ in tushare_indicator_param_list])
# 设置 dtype
dtype = {key: val for key, val in tushare_indicator_param_list}
dtype['ts_code'] = String(20)
# 数据提取
stock_info_all_df = pro.stock_basic(exchange='',
fields='ts_code,symbol,name,area,industry,fullname,enname,market,exchange,curr_type,list_status,list_date,delist_date,is_hs,is_hs,is_hs')
logging.info('%s stock data will be import', stock_info_all_df.shape[0])
data_count = bunch_insert_on_duplicate_update(
stock_info_all_df, table_name, engine_md, dtype=dtype,
myisam_if_create_table=True, primary_keys=['ts_code'], schema=config.DB_SCHEMA_MD)
logging.info("更新 %s 完成 存量数据 %d 条", table_name, data_count)
# 更新 code_mapping 表
# update_from_info_table(table_name)
示例14: fresh_tushare_stock_fund_holdings
# 需要导入模块: from sqlalchemy import types [as 别名]
# 或者: from sqlalchemy.types import Date [as 别名]
def fresh_tushare_stock_fund_holdings(year, quarter):
table_name = 'tushare_stock_fund_holdings'
logging.info("更新 %s 表%s年%s季度基金持股信息开始", table_name, year, quarter)
has_table = engine_md.has_table(table_name)
tushare_fund_holdings_indicator_param_list = [
('ts_code', String(20)),
('sec_name', String(20)),
('end_date', Date),
('nums', DOUBLE),
('nlast', DOUBLE),
('count', DOUBLE),
('clast', DOUBLE),
('amount', DOUBLE),
('ratio', DOUBLE),
]
tushare_fund_holdings_dtype = {key: val for key, val in tushare_fund_holdings_indicator_param_list}
data_df_list, data_count, all_data_count, = [], 0, 0
data_df = invoke_fund_holdings(year, quarter)
ts_code_list = []
for i in data_df.code:
if i[0] == '6':
sh = i + '.SH'
ts_code_list.append(sh)
else:
sz = i + '.SZ'
ts_code_list.append(sz)
data_df.code = ts_code_list
data_df = data_df.rename(columns={'code': 'ts_code', 'name': 'sec_name', 'date': 'end_date'})
bunch_insert_on_duplicate_update(data_df, table_name, engine_md, tushare_fund_holdings_dtype)
logging.info("%s年%s季度 %s 更新 %d 条基金持股信息", year, quarter, table_name, all_data_count)
示例15: fund_nav_df_2_sql
# 需要导入模块: from sqlalchemy import types [as 别名]
# 或者: from sqlalchemy.types import Date [as 别名]
def fund_nav_df_2_sql(table_name, fund_nav_df, engine_md, is_append=True):
col_name_param_list = [
('NAV_DATE', Date),
('NAV', DOUBLE),
('NAV_ACC', DOUBLE),
]
col_name_dic = {col_name.upper(): col_name.lower() for col_name, _ in col_name_param_list}
dtype = {col_name.lower(): val for col_name, val in col_name_param_list}
dtype['wind_code'] = String(200)
dtype['trade_date'] = Date
# print('reorg dfnav data[%d, %d]' % fund_nav_df.shape)
try:
fund_nav_df['NAV_DATE'] = pd.to_datetime(fund_nav_df['NAV_DATE']).apply(lambda x: x.date())
except Exception as exp:
logger.exception(str(fund_nav_df['NAV_DATE']))
return None
trade_date_s = pd.to_datetime(fund_nav_df.index)
trade_date_latest = trade_date_s.max().date()
fund_nav_df['trade_date'] = trade_date_s
fund_nav_df.rename(columns=col_name_dic, inplace=True)
# fund_nav_df['trade_date'] = trade_date_s
fund_nav_df.set_index(['wind_code', 'trade_date'], inplace=True)
fund_nav_df.reset_index(inplace=True)
# action_str = 'append' if is_append else 'replace'
# print('df--> sql fundnav table if_exists="%s"' % action_str)
bunch_insert_on_duplicate_update(fund_nav_df, table_name, engine_md, dtype=dtype)
# fund_nav_df.to_sql(table_name, engine_md, if_exists=action_str, index_label=['wind_code', 'trade_date'],
# dtype={
# 'wind_code': String(200),
# 'nav_date': Date,
# 'trade_date': Date,
# }) # , index=False
logger.info('%d data inserted', fund_nav_df.shape[0])
return trade_date_latest