Schemas Module

Pydantic schemas for data validation in the catchment simulation package.

Provides strict runtime validation of simulation parameters and subcatchment data, ensuring physically meaningful values before any computation begins.

class catchment_simulation.schemas.SimulationMethodParams(*, method_name: Literal['simulate_percent_slope', 'simulate_area', 'simulate_width', 'simulate_percent_impervious', 'simulate_percent_zero_imperv', 'simulate_curb_length', 'simulate_n_imperv', 'simulate_n_perv', 'simulate_s_imperv', 'simulate_s_perv'], start: Annotated[float | None, Ge(ge=0)] = None, stop: Annotated[float | None, Ge(ge=0)] = None, step: Annotated[float | None, Gt(gt=0)] = None, catchment_name: Annotated[str, MinLen(min_length=1), MaxLen(max_length=100)])

Bases: BaseModel

Parameters for a single simulation run.

Range-based methods (e.g. simulate_area) require start, stop and step. Predefined methods (Manning’s n and depression storage) use literature values and do not accept range parameters.

PREDEFINED_METHODS: ClassVar[frozenset[str]] = frozenset({'simulate_n_imperv', 'simulate_n_perv', 'simulate_s_imperv', 'simulate_s_perv'})

catchment_name: str

method_name: Literal['simulate_percent_slope', 'simulate_area', 'simulate_width', 'simulate_percent_impervious', 'simulate_percent_zero_imperv', 'simulate_curb_length', 'simulate_n_imperv', 'simulate_n_perv', 'simulate_s_imperv', 'simulate_s_perv']

model_config = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

start: float | None

step: float | None

stop: float | None

validate_method_params() → SimulationMethodParams

class catchment_simulation.schemas.SimulationParams(*, start: Annotated[float, Ge(ge=0)], stop: Annotated[float, Ge(ge=0)], step: Annotated[float, Gt(gt=0)])

Bases: BaseModel

Validated parameters for a simulation range sweep.

Enforces that start <= stop and step > 0, replacing manual if checks with a declarative schema that raises ValidationError on bad input.

model_config = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

start: float

start_le_stop() → SimulationParams

step: float

stop: float

class catchment_simulation.schemas.SubcatchmentParams(*, area: Annotated[float, Gt(gt=0)], slope: Annotated[float, Gt(gt=0), Le(le=100)], imperviousness: Annotated[float, Ge(ge=0), Le(le=100)], width: Annotated[float, Gt(gt=0)], n_imperv: Annotated[float, Gt(gt=0)], n_perv: Annotated[float, Gt(gt=0)], s_imperv: Annotated[float, Ge(ge=0)], s_perv: Annotated[float, Ge(ge=0)], pct_zero: Annotated[float, Ge(ge=0), Le(le=100)])

Bases: BaseModel

Physical parameters of a single subcatchment.

All constraints reflect physically valid ranges used in SWMM modelling.

area: Annotated[float, Gt(gt=0)]

imperviousness: float

model_config = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

n_imperv: float

n_perv: float

pct_zero: float

s_imperv: float

s_perv: float

slope: float

width: Annotated[float, Gt(gt=0)]