otp.state.tick_list#
- tick_list(default_value=None, scope='query', schema=None)#
Defines a state tick list.
- Parameters
default_value (
eval query
) – Evaluated query to initialize tick list from.scope (str) – Scope for the state variable. Possible values are: query, branch, cross_symbol, all_inputs, all_outputs
Desired schema for the created tick list. If not passed, schema will be inherited from
default_value
. ifdefault_value
is not passed as well, schema will contain fields of the main Source object.If schema is passed as a list, it will select only these fields from the schema of
default_value
or main Source object.
- Return type
Examples
>>> def fsq(): ... return otp.Ticks(B=[1, 2, 3]) >>> data = otp.Tick(A=1) >>> data.state_vars['LIST'] = otp.state.tick_list(otp.eval(fsq)) >>> data = data.state_vars['LIST'].dump() >>> otp.run(data)[['B']] B 0 1 1 2 2 3
- class TickList(name, obj_ref, default_value, scope, schema=None, **kwargs)#
Represents a tick list. This class should only be created with
onetick.py.state.tick_list()
function and should be added to theonetick.py.Source.state_vars()
dictionary of theonetick.py.Source
and can be accessed only via this dictionary.Examples
>>> data = otp.Tick(A=1) >>> data.state_vars['LIST'] = otp.state.tick_list() >>> data = data.state_vars['LIST'].dump()
See also
- clear()#
Clear tick list. Can be used in per-tick script or on Source directly.
- inplace: bool
If
True
current source will be modified else modified copy will be returned. Makes sense only if used not in per-tick script.
- Returns
if
inplace
is False and method is not used in per-tick scriptthen returns
Source
copy.
Examples
Can be used in per-tick script:
>>> def fun(tick): ... tick.state_vars['LIST'].clear() >>> data = otp.Tick(A=1) >>> data.state_vars['LIST'] = otp.state.tick_list() >>> data = data.script(fun)
Can be used in source columns operations:
>>> data = otp.Tick(A=1) >>> data.state_vars['LIST'] = otp.state.tick_list(otp.eval(otp.Tick(A=1))) >>> data = data.state_vars['LIST'].clear()
>>> data = data.state_vars['LIST'].dump() >>> otp.run(data) Empty DataFrame Columns: [A, Time] Index: []
- push_back(tick_object)#
Add tick_object to the tick list. Can only be used in per-tick script.
Examples
>>> def fun(tick): ... tick.state_vars['LIST'].push_back(tick) >>> data = otp.Tick(A=1) >>> data.state_vars['LIST'] = otp.state.tick_list() >>> data = data.script(fun)
>>> data = data.state_vars['LIST'].dump() >>> otp.run(data) Time A 0 2003-12-01 1
- get_size()#
Get size of the tick list. Can be used in per-tick script or in Source operations directly.
Examples
Can be used in per-tick script:
>>> def fun(tick): ... tick['B'] = tick.state_vars['LIST'].get_size() >>> data = otp.Tick(A=1) >>> data.state_vars['LIST'] = otp.state.tick_list() >>> data = data.script(fun)
Can be used in source columns operations:
>>> data = otp.Tick(A=1) >>> data.state_vars['LIST'] = otp.state.tick_list() >>> data['B'] = data.state_vars['LIST'].get_size()
>>> otp.run(data) Time A B 0 2003-12-01 1 0
- Return type
- size()#
See also
- Return type
- sort(field_name, field_type=None)#
Sort the tick list in the ascending order over the specified field. Integer, float and datetime fields are supported for sorting. Implementation is per tick script which does a merge sort algorithm. Implemented algorithm is stable: it should not change the order of ticks with the same field value. Can only be used Source operations directly.
- Parameters
Examples
>>> def fun(tick): ... tick.state_vars['LIST'].push_back(tick) >>> data = otp.Ticks([ ... ['offset', 'VALUE'], ... [0, 2], ... [0, 3], ... [0, 1], ... ]) >>> data.state_vars['LIST'] = otp.state.tick_list() >>> data = data.script(fun) >>> data = data.agg(dict(NUM_TICKS=otp.agg.count()), bucket_time='end') >>> data = data.state_vars['LIST'].sort('VALUE', int) >>> data = data.state_vars['LIST'].dump()
>>> otp.run(data) Time VALUE 0 2003-12-01 1 1 2003-12-01 2 2 2003-12-01 3
- erase(tick_object)#
Remove tick_object from the tick list. Can only be used in per-tick script.
Examples
>>> def another_query(): ... return otp.Ticks(X=[1, 2]) >>> def fun(tick): ... for t in tick.state_vars['LIST']: ... if t['X'] == 1: ... tick.state_vars['LIST'].erase(t) >>> 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 0 2003-12-01 00:00:00.001 2
- dump(propagate_input_ticks=False, when_to_dump='first_tick', delimiter=None, added_field_name_suffix=None)#
Propagates all ticks from a given tick sequence upon the arrival of input tick.
Preserves original timestamps from tick list/deque, if they fall into query start/end time range, and for ticks before start time and after end time, timestamps are changed to start time and end time correspondingly.
- Parameters
propagate_input_ticks (bool) – Propagate input ticks or not.
when_to_dump (str) –
first_tick - Propagates once before input ticks. There must be at least one input tick.
before_tick - Propagates once before input ticks. Content will be propagated even if there are no input ticks.
delimiter ('tick', 'flag or None) –
This parameter specifies the policy for adding the delimiter field. The name of the additional field is “DELIMITER” +
added_field_name_suffix
. Possible options are:None - No additional field is added to propagated ticks.
’tick’ - An extra tick is created after the last tick. Also, an additional column is added to output ticks. The extra tick has values of all fields set to the defaults (0,NaN,””), except the delimiter field, which is set to string “D”. All other ticks have this field’s value set to empty string.
’flag’ - The delimiter field is appended to each output tick. The field’s value is empty for all ticks except the last tick of the tick sequence, which is string “D”.
added_field_name_suffix (str or None) – The suffix to add to the name of the additional field.
inplace (bool) – If
True
current source will be modified else modified copy will be returned
- Return type
if
inplace
is False then returnsSource
copy.
Examples
>>> def another_query(): ... return otp.Ticks(B=[1, 2, 3]) >>> data = otp.Tick(A=1) >>> data.state_vars['LIST'] = otp.state.tick_list(otp.eval(another_query)) >>> data = data.state_vars['LIST'].dump() >>> otp.run(data)[['B']] B 0 1 1 2 2 3
- modify_from_query(query, symbol=None, start=None, end=None, params=None, action='replace', where=None, output_field_name=None)#
Modifies a
state variable
by assigning it a value that was resulted from aquery
evaluation.- Parameters
query (callable, Source) –
Callable
query
should returnSource
. This object will be evaluated by OneTick (not python) for every tick. Note python code will be executed only once, so all python’s conditional expressions will be evaluated only once too.If
query
is aSource
object then it will be propagated as a query to OneTick.If state
var
is a primitive (not tick sequence), thenquery
must return only one tick, otherwise exception will be raised.symbol (str, Operation, dict, Source, or Tuple[Union[str, Operation], Union[dict, Source]]) –
Symbol name to use in
query
. In addition, symbol params can be passed along with symbol name.Symbol name can be passed as a string or as an
Operation
.Symbol parameters can be passed as a dictionary. Also, the main
Source
object, or the object containing a symbol parameter list, can be used as a list of symbol parameters.symbol
will be interpreted as a symbol name or as symbol parameters, depending on its type. You can pass both as a tuple.If symbol name is not passed, then symbol name from the main source is used.
start (datetime, Operation) – Start time to run the
query
. By default the start time of the main query is used.end (datetime, Operation) – End time to run the
query
. By default the end time of the main query is used.params (dict) – Mapping of the parameters’ names and their values for the
query
.Columns
can be used as a value.action (str) – Specifies whether all ticks should be erased before the query results are inserted into the tick set. Possible values are
update
andreplace
. For non-tick-sets, you can set theaction
only toreplace
; otherwise, an error is thrown.where (Operation) – Condition to filter ticks for which the result of the
query
will be joined.output_field_name (str) – Specifies the output field name for state variables of primitive types, in case if the query result contains multiple fields.
- Returns
Source with joined ticks from
query
- Return type
Source
Examples
Update simple state variable from query:
data = otp.Ticks(A=[1, 2, 3]) data.state_vars['VAR'] = 0 data.state_vars['VAR'] = 7 def fun(): return otp.Tick(X=123, Y=234) data = data.state_vars['VAR'].modify_from_query(fun, output_field_name='X', where=(data['A'] % 2 == 1)) data['X'] = data.state_vars['VAR'] df = otp.run(data) print(df)
Time A X 0 2003-12-01 00:00:00.000 1 123 1 2003-12-01 00:00:00.001 2 7 2 2003-12-01 00:00:00.002 3 123
Update tick sequence from query:
data = otp.Tick(A=1) data.state_vars['VAR'] = otp.state.tick_list() def fun(): return otp.Ticks(X=[123, 234]) data = data.state_vars['VAR'].modify_from_query(fun) data = data.state_vars['VAR'].dump() df = otp.run(data) print(df)
Time X 0 2003-12-01 00:00:00.000 123 1 2003-12-01 00:00:00.001 234
Passing parameters to the
query
:data = otp.Tick(A=1) data.state_vars['VAR'] = otp.state.tick_list() def fun(min_value): t = otp.Ticks(X=[123, 234]) t, _ = t[t['X'] > min_value] return t data = data.state_vars['VAR'].modify_from_query(fun, params={'min_value': 200}) data = data.state_vars['VAR'].dump() df = otp.run(data) print(df)
Time X 0 2003-12-01 00:00:00.001 234
See also
MODIFY_STATE_VAR_FROM_QUERY OneTick event processor