Time Series Store¶

TimeSeriesStore provides access to time series data from different backends. All TimeSeriesStore implementations provide this methods, to see details on a concrete Store usage go to Stores Backends

class kisters.water.time_series.core.time_series_store.TimeSeriesStore¶

Bases: abc.ABC

create_time_series(path: str, display_name: str, attributes: Mapping = None, params: Mapping[str, Any] = None) → kisters.water.time_series.core.time_series.TimeSeries¶

Create an empty time series.

Parameters:	path – The time series path. display_name – The time series name to display. attributes – The metadata of the time series. params – The additional parameters, which are passed to the backend.

create_time_series_from(copy_from: kisters.water.time_series.core.time_series.TimeSeries, **kwargs) → kisters.water.time_series.core.time_series.TimeSeries¶

Create a time series as a copy from another existing time series e.g. from another system. This function only copies meta data and only if the underlaying backend supports it.

Parameters:	copy_from – The time series object to be copied.

get_by_filter(ts_filter: str, params: Mapping[str, Any] = None) → Iterable[kisters.water.time_series.core.time_series.TimeSeries]¶

Get the time series list by filter.

Parameters:	ts_filter – time series path or filter. params – the additional parameters, which are passed to the backend.
Returns:	The list of the found TimeSeries objects.

Examples

store.get_by_filter("W7AgentTest/20004/S/*")

get_by_id(ts_id: Union[int, str, Iterable[int], Iterable[str]], params: Mapping[str, Any] = None) → Union[kisters.water.time_series.core.time_series.TimeSeries, Iterable[kisters.water.time_series.core.time_series.TimeSeries]]¶

Get the time series by id.

Parameters:	ts_id – List of ids or single id. params – The additional parameters, which are passed to the backend.
Returns:	The time series or a list of time series if ts_id is a list.

Examples

store.get_by_id(4711)
store.get_by_id([4711, 4712])

get_by_path(path: str, params: Mapping[str, Any] = None) → kisters.water.time_series.core.time_series.TimeSeries¶

Get the time series by path.

Parameters:	path – The full qualified time series path. params – The additional parameters, which are passed to the backend.
Returns:	The TimeSeries object.

Examples

store.get_by_path("W7AgentTest/20003/S/cmd")

get_entity(entity_path: str = None, entity_id: int = None, **kwargs) → kisters.water.time_series.core.entity.Entity¶

Retrieve a single Entity from the backend.

Basic implementation is given based on get_entity_list, but it is recommended to overwrite this method based on the backend specifications. :param entity_path: The entity path. :param entity_id: The entity id. :param **kwargs: Additional arguments dependent on the backend.

Returns:	The matching Entity.

get_entity_list(entity_filter: str = None, entities_id: Iterable[int] = None, **kwargs) → Iterable[kisters.water.time_series.core.entity.Entity]¶

Retrieve a list of entities from the backend.

The behaviour depends totally on the backend implementation, this should decide if both entity_filter and entities_id arguments can be given and how they behave if both are given. As a rule of thumb if both arguments are given a double filter should be applied. :param entity_filter: The entity filter. :param entities_id: A list of entities id. :param **kwargs: Additional arguments dependent on the backend.

Returns:	The list of Entity objects.

get_time_series(**kwargs)¶

get_time_series_list(**kwargs)¶

read_data_frames(ts_list: Iterable[kisters.water.time_series.core.time_series.TimeSeries], start: Union[str, datetime.datetime] = None, end: Union[str, datetime.datetime] = None, params: Mapping = None, t0: datetime.datetime = None, dispatch_info: str = None, member: str = None) → Mapping[kisters.water.time_series.core.time_series.TimeSeries, pandas.core.frame.DataFrame]¶

Read multiple time series as data frames.

Note: TimeSeriesStore provides a default unoptimized implementation. Override this method if your store can provide a more efficient bulk read method.

write_data_frames(ts_list: Iterable[kisters.water.time_series.core.time_series.TimeSeries], data_frames: Iterable[pandas.core.frame.DataFrame], start: Union[datetime.datetime, Iterable] = None, end: Union[datetime.datetime, Iterable] = None, t0: Union[datetime.datetime, Iterable] = None, dispatch_info: Iterable = None, member: Iterable = None)¶

Write multiple data frames to time series

Note: Override this method if your store can provide a better implementation to bulk write data frames.

write_time_series(ts: kisters.water.time_series.core.time_series.TimeSeries, start: datetime.datetime = None, end: datetime.datetime = None, auto_create: bool = False) → kisters.water.time_series.core.time_series.TimeSeries¶

Write a single time series to the time series back end for the given time range.

Parameters:	ts – The time series to write. start – The starting date from which data will be written. end – The ending date until which data will be written. auto_create – Create the time series if not exists in the back end.

Examples

ts = store1.get_by_id(47122)
store2.write_time_series(ts)

write_time_series_list(ts_list: Iterable[kisters.water.time_series.core.time_series.TimeSeries], start: datetime.datetime = None, end: datetime.datetime = None, auto_create: bool = False)¶

Write a time series list to the back end for the given time range.

Parameters:	ts_list – The time series list. start – The starting date from which data will be written. end – The ending date until which data will be written. auto_create – Create the time series if not exists in the back end.

Examples

ts_list = store1.get_by_filter('W7AgentTest/2000*')
store2.write_time_series_list(ts_list, datetime(2001, 1, 1), datetime(2002, 1, 1))