sampo.pipeline#

Submodules#

Classes#
`InputPipeline`	Base class to build different pipeline, that help to use the framework
`DefaultInputPipeline`	Default pipeline, that help to use the framework
`PipelineType`	Generic enumeration.
`SchedulingPipeline`	-

class sampo.pipeline.InputPipeline#

Bases: abc.ABC

Base class to build different pipeline, that help to use the framework

abstract wg(wg: sampo.schemas.graph.WorkGraph | pandas.DataFrame | str, full_connection: bool = False, change_base_on_history: bool = False) → InputPipeline#

abstract contractors(contractors: list[sampo.schemas.contractor.Contractor] | pandas.DataFrame | str) → InputPipeline#

abstract name_mapper(name_mapper: sampo.utilities.task_name.NameMapper) → InputPipeline#

abstract landscape(landscape_config: sampo.schemas.landscape.LandscapeConfiguration) → InputPipeline#

abstract spec(spec: sampo.schemas.schedule_spec.ScheduleSpec) → InputPipeline#

Mandatory argument. Shows should graph be lag-optimized or not. If not defined, pipeline should search the best variant of this argument in result.

abstract work_estimator(work_estimator: sampo.schemas.time_estimator.WorkTimeEstimator) → InputPipeline#

abstract node_order(node_order: list[sampo.schemas.graph.GraphNode]) → InputPipeline#

abstract optimize_local(optimizer: sampo.scheduler.utils.local_optimization.OrderLocalOptimizer, area: range) → InputPipeline#

abstract schedule(scheduler: sampo.scheduler.base.Scheduler) → SchedulePipeline#

class sampo.pipeline.DefaultInputPipeline#

Bases: sampo.pipeline.base.InputPipeline

Default pipeline, that help to use the framework

wg(wg: sampo.schemas.graph.WorkGraph | pandas.DataFrame | str, is_wg_has_full_info_about_connections: bool = False, change_base_on_history: bool = False) → sampo.pipeline.base.InputPipeline#

Mandatory argument.

Parameters:

change_base_on_history – whether it is necessary to change project information based on connection history data
is_wg_has_full_info_about_connections – does the project information contain full details of the works
wg – the WorkGraph object for scheduling task

Returns:

the pipeline object

Mandatory argument.

Set landscape configuration

name_mapper(name_mapper: sampo.utilities.task_name.NameMapper) → sampo.pipeline.base.InputPipeline#: Set works’ name mapper :param name_mapper: :return:

history(history: pandas.DataFrame | str) → sampo.pipeline.base.InputPipeline#: Set historical data. Mandatory method, if work graph hasn’t info about links :param history: :return: