otp.Source.add_fields_from_symbol_params#

Source.add_fields_from_symbol_params(*, prefix=None, inplace=False)#

Modifies the input time series by adding all symbol parameters (preserving original value types) as new fields to each tick.

Note

This OneTick EP returns arbitrary number of fields, so the source’s schema will not be updated automatically.

Parameters:

prefix (str) – If specified, it will be appended to each added tick field name with the following form: PREFIX.SYMBOL_PARAM_NAME
inplace (bool) – The flag controls whether operation should be applied inplace or not. If inplace=True, then it returns nothing. Otherwise method returns a new modified object.
self (Source)

Return type:

Source or None

Examples

Let’s create first-stage query with some symbol parameters first:

>>> symbols = otp.Tick(SYMBOL_NAME='AAPL', PARAM_1='HELLO', PARAM_2=12345, PARAM_3=1.2345)

Then add these symbol parameters as new fields:

>>> data = otp.Tick(A=1)
>>> data = data.add_fields_from_symbol_params()
>>> data = otp.merge([data], symbols=symbols)
>>> otp.run(data)
        Time  A PARAM_1  PARAM_2  PARAM_3
0 2003-12-01  1   HELLO    12345   1.2345

Note that source’s schema can’t be updated automatically in this case and need to be set manually in order to use new fields:

>>> data.schema.update(**{'PARAM_1': str, 'PARAM_2': int, 'PARAM_3': float})
>>> data['B'] = data['PARAM_2'] + 1
>>> otp.run(data)
        Time  A PARAM_1  PARAM_2  PARAM_3      B
0 2003-12-01  1   HELLO    12345   1.2345  12346

Parameter prefix can be used to add some prefix to the new fields:

>>> data = otp.Tick(A=1)
>>> data = data.add_fields_from_symbol_params(prefix='PREFIX')
>>> data = otp.merge([data], symbols=symbols)
>>> otp.run(data)
        Time  A PREFIX.PARAM_1  PREFIX.PARAM_2  PREFIX.PARAM_3
0 2003-12-01  1          HELLO           12345          1.2345