leaf_engine.adapt.context

Submodules

Classes

AdaptActionContext

AdaptConsolidatedNetworkActionContext

AdaptDataContext

AdaptETLContext

AdaptExplorerContext

AdaptNetworkContext

AdaptObservationContext

AdaptSyntheticRateContext

Context

DataSource

Package Contents

class leaf_engine.adapt.context.AdaptActionContext(int_rt: Callable[[], pandas.DataFrame], int_tri: Callable[[], pandas.DataFrame], leaf_rt: Callable[[], pandas.DataFrame], ext_rt: Callable[[], pandas.DataFrame], ext_tri: Callable[[], pandas.DataFrame], leaf_tri: Callable[[], pandas.DataFrame], int_cm: Callable[[], pandas.DataFrame], ext_cm: Callable[[], pandas.DataFrame], leaf_cm: Callable[[], pandas.DataFrame], shorty: Callable[[], pandas.DataFrame], leaf_shorty: Callable[[], pandas.DataFrame], flex_daily_price: Callable[[], pandas.DataFrame], flex_daily_performance: Callable[[], pandas.DataFrame], flex_weekly_price: Callable[[], pandas.DataFrame], flex_uncommitted_price: Callable[[], pandas.DataFrame])

Bases: leaf_engine.adapt.context.context.Context

Parameters:
class leaf_engine.adapt.context.AdaptConsolidatedNetworkActionContext(actions: Callable[[], pandas.DataFrame])

Bases: leaf_engine.adapt.context.context.Context

Parameters:

actions (Callable[[], pandas.DataFrame]) –

class leaf_engine.adapt.context.AdaptDataContext(equip_class_ships: Callable[[], pandas.DataFrame], markets: Callable[[], pandas.DataFrame], lanes: Callable[[], pandas.DataFrame], db_lanes: Callable[[], pandas.DataFrame], lane_equip_class_annual_volume: Callable[[], pandas.DataFrame], lane_equip_class_recent_rpm: Callable[[], pandas.DataFrame], company_id: int, company_name: str, batch_date: str, equipment_class: str, dat_fuel: float, db_key: str, run_type: dict, incl_record_types: list[str], leaf_company_ids: list[int])

Bases: leaf_engine.adapt.context.context.Context

Parameters:
class leaf_engine.adapt.context.AdaptETLContext(ships: Callable[[], pandas.DataFrame], markets: Callable[[], pandas.DataFrame], db_lanes: Callable[[], pandas.DataFrame], company_id: int, batch_date: str, company_name: str, equipment_class: str, db_key: str, minimum_lane_miles: int, oa_daily_params: Dict, oa_dow_params: Dict, oa_weekly_params: Dict, leaf_company_ids: list[int])

Bases: leaf_engine.adapt.context.context.Context

Parameters:

  • ships (Callable[[], pandas.DataFrame]) –

  • markets (Callable[[], pandas.DataFrame]) –

  • db_lanes (Callable[[], pandas.DataFrame]) –

  • company_id (int) –

  • batch_date (str) –

  • company_name (str) –

  • equipment_class (str) –

  • db_key (str) –

  • minimum_lane_miles (int) –

  • oa_daily_params (Dict) –

  • oa_dow_params (Dict) –

  • oa_weekly_params (Dict) –

  • leaf_company_ids (list[int]) –

class leaf_engine.adapt.context.AdaptExplorerContext(lane_summary: Callable[[], pandas.DataFrame], lane_daily_volume: Callable[[], pandas.DataFrame], lane_detail_volume: Callable[[], pandas.DataFrame], lane_daily_spend: Callable[[], pandas.DataFrame], lane_scac_daily_volume: Callable[[], pandas.DataFrame], lane_scac_spend: Callable[[], pandas.DataFrame], lane_weekly_scac_spend: Callable[[], pandas.DataFrame], lane_quick_ref: Callable[[], pandas.DataFrame])

Bases: leaf_engine.adapt.context.context.Context

Parameters:
class leaf_engine.adapt.context.AdaptNetworkContext(int_rt: Callable[[], pandas.DataFrame], ext_rt: Callable[[], pandas.DataFrame], leaf_rt: Callable[[], pandas.DataFrame], int_tri: Callable[[], pandas.DataFrame], ext_tri: Callable[[], pandas.DataFrame], leaf_tri: Callable[[], pandas.DataFrame], int_cm: Callable[[], pandas.DataFrame], ext_cm: Callable[[], pandas.DataFrame], leaf_cm: Callable[[], pandas.DataFrame], shorty: Callable[[], pandas.DataFrame], leaf_shorty: Callable[[], pandas.DataFrame])

Bases: leaf_engine.adapt.context.context.Context

Parameters:
class leaf_engine.adapt.context.AdaptObservationContext(contract_rate_spread: Callable[[], pandas.DataFrame], spot_exposure: Callable[[], pandas.DataFrame], market_rate_variance: Callable[[], pandas.DataFrame], carrier_churn: Callable[[], pandas.DataFrame], daily_pattern: Callable[[], pandas.DataFrame], weekly_pattern: Callable[[], pandas.DataFrame], should_be_flex: Callable[[], pandas.DataFrame])

Bases: leaf_engine.adapt.context.context.Context

Parameters:
class leaf_engine.adapt.context.AdaptSyntheticRateContext(lane_rates: Callable[[], pandas.DataFrame], market_rates: Callable[[], pandas.DataFrame], dat_fuel: float)

Bases: leaf_engine.adapt.context.context.Context

Parameters:
class leaf_engine.adapt.context.Context(sources: Dict[str, DataSource], params: dict)
Parameters:
__getstate__()
__setstate__(state)
static from_pkl(filename)
load(load_sources=None, validate=True)
sources() → Dict[str, str]
Return type:

Dict[str, str]

to_pkl(filename)
validate(validate_sources=None)
_sources
data: Dict[str, pandas.DataFrame]
params
pickled = False
class leaf_engine.adapt.context.DataSource(schema: pandera.DataFrameSchema, source: Callable[[], pandas.DataFrame])
Parameters:

  • schema (pandera.DataFrameSchema) –

  • source (Callable[[], pandas.DataFrame]) –

load(validate=True) → pandas.DataFrame
Return type:

pandas.DataFrame

validate()
_data
schema
source