otp.state.tick_sequence_tick#

class TickSequenceTick(name, owner=None)#

Tick object that can be accessed only in per-tick script. This object is a first per-tick script function argument. This object is the loop variable of for-cycle in the code of per-tick script when for-cycle is used on tick sequence. Also tick can be defined as static local variable.

Examples

>>> def another_query():
...     return otp.Ticks(X=[1, 2, 3])
>>> def fun(tick):
...     dyn_t = otp.dynamic_tick()
...     tick['SUM'] = 0
...     for t in tick.state_vars['LIST']:
...         tick['SUM'] += t.get_long_value('X')
...     dyn_t['X'] = tick['SUM']
>>> data = otp.Tick(A=1)
>>> data.state_vars['LIST'] = otp.state.tick_list(otp.eval(another_query))
>>> data = data.script(fun)
property schema: dict#
next()#

Moves to the next tick in the container.

prev()#

Moves to the previous tick in the container.

is_end()#

Checks if current tick is valid. If false tick can not be accessed.

copy(tick_object)#

Makes passed object to point on the same tick (passed object must be of the same type).

get_timestamp()#

Get timestamp of the tick.

Examples

>>> def another_query():
...     return otp.Ticks({'A': [1, 2, 3]})
>>> def fun(tick):
...    for t in tick.state_vars['LIST']:
...        tick['TS'] = t.get_timestamp()
>>> 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 00:00:00.002
Return type

onetick.py.core.column_operations.base.Operation

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
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 if field_name exists in schema or has the same type.

Return type

onetick.py.core.column_operations.base.Operation

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 if field_name exists in schema or has the same type.

Return type

onetick.py.core.column_operations.base.Operation

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 if field_name exists in schema or has the same type.

Return type

onetick.py.core.column_operations.base.Operation

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 if field_name exists in schema or has the same type.

Return type

onetick.py.core.column_operations.base.Operation

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
set_datetime_value(field_name, value, check_schema=True)#

Set value of the datetime field_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 of value. 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 if field_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 double field_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 of value. 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 if field_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 long field_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 of value. 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 if field_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 string field_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 of value. 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 if field_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 the field_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