otp.state.dynamic_tick#
- dynamic_tick()#
Can be used only in per-tick script function to define a dynamic tick local variable.
Dynamic ticks can be used with some methods of all tick sequences.
- Return type
onetick.py.static
value with tick object.
Examples
>>> def fun(tick): ... t = otp.dynamic_tick() ... t['X'] = tick['SUM']
- class _DynamicTick(name)#
This tick type allow to add and update fields dynamically. This tick can be inserted to all tick sequences.
- property schema#
- add_field(name, value)#
Add field with name and value to the tick.
- copy_fields(tick_object, field_names)#
Copy fields with field_names from other tick_object. Fields not listed in the field_names argument of the function will be removed from tick.
- get_datetime_value(field_name, check_schema=True)#
Get value of the datetime
field_name
of the tick.- Parameters
field_name (str,
otp.Operation
) – String field name or operation which returns field name.check_schema (bool) – Check that
field_name
exists in tick’s schema and its type is datetime. In some cases you may want to disable this behaviour, for example, when tick sequence is updated dynamically in different branches of per-tick script. In this case onetick-py can’t deduce iffield_name
exists in schema or has the same type.
- Return type
Examples
>>> def another_query(): ... t = otp.Ticks(X=['a', 'b', 'c']) ... t['TS'] = t['TIMESTAMP'] + otp.Milli(1) ... return t >>> def fun(tick): ... for t in tick.state_vars['LIST']: ... tick['TS'] = t.get_datetime_value('TS') >>> data = otp.Tick(A=1) >>> data.state_vars['LIST'] = otp.state.tick_list(otp.eval(another_query)) >>> data = data.script(fun)
>>> otp.run(data) Time A TS 0 2003-12-01 1 2003-12-01 00:00:00.003
- get_double_value(field_name, check_schema=True)#
Get value of the double
field_name
of the tick.- Parameters
field_name (str,
otp.Operation
) – String field name or operation which returns field name.check_schema (bool) – Check that
field_name
exists in tick’s schema and its type is float. In some cases you may want to disable this behaviour, for example, when tick sequence is updated dynamically in different branches of per-tick script. In this case onetick-py can’t deduce iffield_name
exists in schema or has the same type.
- Return type
Examples
>>> def another_query(): ... return otp.Ticks(X=[1.1, 2.2, 3.3]) >>> def fun(tick): ... tick['SUM'] = 0 ... for t in tick.state_vars['LIST']: ... tick['SUM'] += t.get_double_value('X') >>> data = otp.Tick(A=1) >>> data.state_vars['LIST'] = otp.state.tick_list(otp.eval(another_query)) >>> data = data.script(fun)
>>> otp.run(data) Time A SUM 0 2003-12-01 1 6.6
- get_long_value(field_name, dtype=int, check_schema=True)#
Get value of the long
field_name
of the tick.- Parameters
field_name (str,
otp.Operation
) – String field name or operation which returns field name.dtype (type) – Type to set for output operation. Should be set if value is integer’s subclass, e.g. short or byte. Default: int
check_schema (bool) – Check that
field_name
exists in tick’s schema and its type is int. In some cases you may want to disable this behaviour, for example, when tick sequence is updated dynamically in different branches of per-tick script. In this case onetick-py can’t deduce iffield_name
exists in schema or has the same type.
- Return type
Examples
>>> def another_query(): ... return otp.Ticks(X=[1, 2, 3]) >>> def fun(tick): ... tick['SUM'] = 0 ... for t in tick.state_vars['LIST']: ... tick['SUM'] += t.get_long_value('X') >>> data = otp.Tick(A=1) >>> data.state_vars['LIST'] = otp.state.tick_list(otp.eval(another_query)) >>> data = data.script(fun)
>>> otp.run(data) Time A SUM 0 2003-12-01 1 6
- get_string_value(field_name, dtype=str, check_schema=True)#
Get value of the string
field_name
of the tick.- Parameters
field_name (str,
otp.Operation
) – String field name or operation which returns field name.dtype (type) – Type to set for output operation. Should be set if value is string’s subclass, e.g. otp.varstring. Default: str
check_schema (bool) – Check that
field_name
exists in tick’s schema and its type is str. In some cases you may want to disable this behaviour, for example, when tick sequence is updated dynamically in different branches of per-tick script. In this case onetick-py can’t deduce iffield_name
exists in schema or has the same type.
- Return type
Examples
>>> def another_query(): ... return otp.Ticks(X=['a', 'b', 'c']) >>> def fun(tick): ... for t in tick.state_vars['LIST']: ... tick['S'] = t.get_string_value('X') >>> data = otp.Tick(A=1) >>> data.state_vars['LIST'] = otp.state.tick_list(otp.eval(another_query)) >>> data = data.script(fun)
>>> otp.run(data) Time A S 0 2003-12-01 1 c
- get_value(field_name)#
Get value of the
field_name
of the tick.Examples
>>> def another_query(): ... return otp.Ticks(X=[1.1, 2.2, 3.3]) >>> def fun(tick): ... tick['SUM'] = 0 ... for t in tick.state_vars['LIST']: ... tick['SUM'] += t.get_value('X') >>> data = otp.Tick(A=1) >>> data.state_vars['LIST'] = otp.state.tick_list(otp.eval(another_query)) >>> data = data.script(fun)
>>> otp.run(data) Time A SUM 0 2003-12-01 1 6.6
- Return type
- set_datetime_value(field_name, value, check_schema=True)#
Set
value
of the datetimefield_name
of the tick.- Parameters
field_name (str,
otp.Operation
) – String field name or operation which returns field name.value (int, float, str,
otp.Operation
) – Value to set or operation which return such value.check_schema (bool) – Check that
field_name
exists in tick’s schema and its type is the same as the type ofvalue
. In some cases you may want to disable this behaviour, for example, when tick sequence is updated dynamically in different branches of per-tick script. In this case onetick-py can’t deduce iffield_name
exists in schema or has the same type.
Examples
>>> def another_query(): ... t = otp.Ticks(X=['a', 'b', 'c']) ... t['TS'] = t['TIMESTAMP'] + otp.Milli(1) ... return t >>> def fun(tick): ... for t in tick.state_vars['LIST']: ... t.set_datetime_value('TS', otp.config['default_start_time']) >>> data = otp.Tick(A=1) >>> data.state_vars['LIST'] = otp.state.tick_list(otp.eval(another_query)) >>> data = data.script(fun)
>>> data = data.state_vars['LIST'].dump() >>> otp.run(data) Time X TS 0 2003-12-01 00:00:00.000 a 2003-12-01 1 2003-12-01 00:00:00.001 b 2003-12-01 2 2003-12-01 00:00:00.002 c 2003-12-01
- set_double_value(field_name, value, check_schema=True)#
Set
value
of the doublefield_name
of the tick.- Parameters
field_name (str,
otp.Operation
) – String field name or operation which returns field name.value (float,
otp.Operation
) – Double value to set or operation which return such value.check_schema (bool) – Check that
field_name
exists in tick’s schema and its type is the same as the type ofvalue
. In some cases you may want to disable this behaviour, for example, when tick sequence is updated dynamically in different branches of per-tick script. In this case onetick-py can’t deduce iffield_name
exists in schema or has the same type.
Examples
>>> def another_query(): ... return otp.Ticks(A=[1, 2, 3], X=[1.1, 2.2, 3.3]) >>> def fun(tick): ... for t in tick.state_vars['LIST']: ... t.set_double_value('X', 1.1) >>> data = otp.Tick(A=1) >>> data.state_vars['LIST'] = otp.state.tick_list(otp.eval(another_query)) >>> data = data.script(fun)
>>> data = data.state_vars['LIST'].dump() >>> otp.run(data) Time A X 0 2003-12-01 00:00:00.000 1 1.1 1 2003-12-01 00:00:00.001 2 1.1 2 2003-12-01 00:00:00.002 3 1.1
- set_long_value(field_name, value, check_schema=True)#
Set
value
of the longfield_name
of the tick.- Parameters
field_name (str,
otp.Operation
) – String field name or operation which returns field name.value (int,
otp.Operation
) – Long value to set or operation which return such value.check_schema (bool) – Check that
field_name
exists in tick’s schema and its type is the same as the type ofvalue
. In some cases you may want to disable this behaviour, for example, when tick sequence is updated dynamically in different branches of per-tick script. In this case onetick-py can’t deduce iffield_name
exists in schema or has the same type.
Examples
>>> def another_query(): ... return otp.Ticks(A=[1, 2, 3], X=[1, 2, 3]) >>> def fun(tick): ... for t in tick.state_vars['LIST']: ... t.set_long_value('X', 1) >>> data = otp.Tick(A=1) >>> data.state_vars['LIST'] = otp.state.tick_list(otp.eval(another_query)) >>> data = data.script(fun)
>>> data = data.state_vars['LIST'].dump() >>> otp.run(data) Time A X 0 2003-12-01 00:00:00.000 1 1 1 2003-12-01 00:00:00.001 2 1 2 2003-12-01 00:00:00.002 3 1
- set_string_value(field_name, value, check_schema=True)#
Set
value
of the stringfield_name
of the tick.- Parameters
field_name (str,
otp.Operation
) – String field name or operation which returns field name.value (str,
otp.Operation
) – String value to set or operation which return such value.check_schema (bool) – Check that
field_name
exists in tick’s schema and its type is the same as the type ofvalue
. In some cases you may want to disable this behaviour, for example, when tick sequence is updated dynamically in different branches of per-tick script. In this case onetick-py can’t deduce iffield_name
exists in schema or has the same type.
Examples
>>> def another_query(): ... return otp.Ticks(A=[1, 2, 3], X=['a', 'b', 'c']) >>> def fun(tick): ... for t in tick.state_vars['LIST']: ... t.set_string_value('X', 'a') >>> data = otp.Tick(A=1) >>> data.state_vars['LIST'] = otp.state.tick_list(otp.eval(another_query)) >>> data = data.script(fun)
>>> data = data.state_vars['LIST'].dump() >>> otp.run(data) Time A X 0 2003-12-01 00:00:00.000 1 a 1 2003-12-01 00:00:00.001 2 a 2 2003-12-01 00:00:00.002 3 a
- set_value(field_name, value)#
Set
value
of thefield_name
of the tick.- Parameters
field_name (str,
otp.Operation
) – String field name or operation which returns field name.value (int,
otp.Operation
) – Datetime value to set or operation which return such value.
Examples
>>> def another_query(): ... return otp.Ticks(A=[1, 2, 3], X=[1.1, 2.2, 3.3]) >>> def fun(tick): ... for t in tick.state_vars['LIST']: ... t.set_value('X', 0.0) >>> data = otp.Tick(A=1) >>> data.state_vars['LIST'] = otp.state.tick_list(otp.eval(another_query)) >>> data = data.script(fun)
>>> data = data.state_vars['LIST'].dump() >>> otp.run(data) Time A X 0 2003-12-01 00:00:00.000 1 0.0 1 2003-12-01 00:00:00.001 2 0.0 2 2003-12-01 00:00:00.002 3 0.0