otp.eval#

eval(query, symbol=None, start=None, end=None, **kwargs)#

Creates an object with query with saved parameters that can be used later.

It can be used to:

return a list of symbols for which the main query will be executed (multistage queries). Note that in this case query must return ticks with column SYMBOL_NAME.
return some value dynamically to be used in other places in the main query. Note that in this case query must return only single tick.

Note that only constant expressions are allowed in query parameters, they must not depend on ticks.

Parameters

query (onetick.py.Source, onetick.py.query or function) – source or query to evaluate. If function, then it must return onetick.py.Source or onetick.py.query. Parameter with name symbol and parameters specified in kwargs will be propagated to this function. Parameter from kwargs must be specified in function signature, but parameter symbol may be omitted if it is not used.
symbol (_SymbolParamSource) – symbol parameter that will be used by query as a symbol. If the function is used as a query, parameter symbol can be defined in function signature and used in source operations.
start (meta field (MetaFields) or symbol param (_SymbolParamColumn)) – start time with which query will be executed. By default the start time for evaluated query is inherited from the main query.
end (meta field (MetaFields) or symbol param (_SymbolParamColumn)) – end time with which query will be executed. By default the end time for evaluated query is inherited from the main query.
kwargs (str, int, meta fields (MetaFields) or symbol params (_SymbolParamColumn)) – or join_with_query() parameters parameters that will be passed to query. If the function is used as a query, parameters specified in kwargs must be defined in function signature and can be used in source operations.

Examples

Use otp.eval to be passed as symbols when running the query:

>>> def fsq():
...     symbols = otp.Ticks(SYMBOL_NAME=['AAPL', 'AAP'])
...     return symbols
>>> main = otp.DataSource(db='NYSE_TAQ', tick_type='TRD', date=otp.dt(2022, 3, 1))
>>> main['SYMBOL_NAME'] = main.Symbol.name
>>> main = otp.merge([main], symbols=otp.eval(fsq))
>>> otp.run(main)
                     Time  PRICE  SIZE SYMBOL_NAME
0 2022-03-01 00:00:00.000   1.30   100        AAPL
1 2022-03-01 00:00:00.000  45.37     0         AAP
2 2022-03-01 00:00:00.001   1.40    10        AAPL
3 2022-03-01 00:00:00.001  45.41     0         AAP
4 2022-03-01 00:00:00.002   1.40    50        AAPL

Use otp.eval as filter:

>>> def get_filter(a, b):
...     return otp.Tick(WHERE=f'X >= {a} and X < {b}', OTHER_FIELD='X')
>>> data = otp.Ticks(X=[1, 2, 3])
>>> data, _ = data[otp.eval(get_filter, a=0, b=2)['WHERE']]
>>> otp.run(data)
        Time  X
0 2003-12-01  1

Use otp.eval with meta fields:

>>> def filter_by_tt(tick_type):
...     res = otp.Ticks({
...         'TICK_TYPE': ['TRD', 'QTE'],
...         'WHERE': ['PRICE>=1.4', 'ASK_PRICE>=1.4']
...     })
...     res, _ = res[res['TICK_TYPE'] == tick_type]
...     return res.drop(['TICK_TYPE'])
>>> t = otp.DataSource('NYSE_TAQ::TRD')
>>> t, _ = t[otp.eval(filter_by_tt, tick_type=t['_TICK_TYPE'])]
>>> otp.run(t, start=otp.dt(2022, 3, 1), end=otp.dt(2022, 3, 2))
                     Time  PRICE  SIZE
0 2022-03-01 00:00:00.001    1.4    10
1 2022-03-01 00:00:00.002    1.4    50