Add a Config Field#

Every TOML knob in HydroModPy is backed by a Pydantic v2 model with ConfigDict(extra="forbid"). This page describes how to add a new field to an existing section, or how to add a brand-new section.

Find the right model#

Sections live close to the package they configure:

TOML section

Pydantic model

File

[workflow]

WorkflowConfig

hydromodpy/config/hydromodpy_config.py

[workspace]

WorkspaceConfig

hydromodpy/core/workspace/config.py

[geographic]

GeographicConfig

hydromodpy/spatial/geographic/geographic_config.py

[domain]

DomainConfig

hydromodpy/spatial/domain/domain_config.py

[data]

DataManagersConfig

hydromodpy/data/data_managers_config.py

[flow]

FlowConfig

hydromodpy/physics/flow/flow_config.py

[transport]

TransportConfig

hydromodpy/physics/transport/transport_config.py

[simulation]

SimulationConfig

hydromodpy/simulation/planning/config.py

[solver]

SolverConfig

hydromodpy/solver/base/solver_config.py

[modflownwt]

ModflowConfig

hydromodpy/solver/modflow_nwt/nwt.py

[modflow6]

Modflow6Config

hydromodpy/solver/modflow6/modflow6_config.py

[display]

DisplayConfig

hydromodpy/display/config.py

[persistence]

PersistenceConfig

hydromodpy/core/config_kit/persistence.py

[analysis]

AnalysisConfig

hydromodpy/analysis/config.py

[overview]

OverviewConfig

hydromodpy/display/overview/config.py

[mesh_catchment]

MeshCatchmentConfig

hydromodpy/spatial/mesh/config.py

[calibration]

CalibrationConfig

hydromodpy/calibration/config.py

Pydantic invariants#

Every model in HydroModPy must:

  • inherit from HydroModelBase (or a model that does);

  • declare model_config = ConfigDict(extra="forbid");

  • use Annotated for unit-bearing fields (see below);

  • carry a Profile annotation on every field;

  • ship a Field(..., description="...") and at least one example for documented fields.

Pick a unit type#

Quantitative fields use the unit aliases declared in hydromodpy/core/units/types.py:

Alias

Canonical unit

Use for

Length

m

Lengths, distances, depths

Area

m²

Surfaces

Volume

m³

Volumes

Time

s

Durations

FlowRate

m³/s

Discharges

Velocity

m/s

Fluxes, recharge rates

HydraulicConductivity

m/s

K

SpecificStorage

1/m

Ss

SpecificYield

dimensionless

Sy

Dimensionless

dimensionless

Pure ratios

Bare numbers are interpreted in the canonical SI unit; users can also pass strings such as "50 m" or "0.36 m/h" and Pydantic will auto-convert.

Pick a Profile#

hydromodpy/core/config_kit/profile.py declares three visibility levels:

class Profile(IntEnum):
    USER = 1     # hydrogeologist: physics, paths, project I/O
    DEV = 2      # developer: tolerances, backends, cache
    EXPERT = 3   # MODFLOW / Boussinesq / pint internals

Default to Profile.USER. Demote to DEV or EXPERT only when the field is genuinely irrelevant for non-developer users.

Template generation, JSON Schema export, and frontend forms all respect the chosen Profile.

Add a field to an existing section#

# hydromodpy/physics/flow/flow_config.py
from typing import Annotated
from pydantic import Field
from hydromodpy.core.config_kit.profile import Profile
from hydromodpy.core.units import HydraulicConductivity


class FlowConfig(ProcessSpatialConfig):
    # ... existing fields ...

    k_aquifer: Annotated[HydraulicConductivity, Profile.USER] = Field(
        default=1e-5,
        description="Aquifer hydraulic conductivity (canonical: m/s).",
        examples=[1e-4, "0.36 m/h"],
    )

In TOML, both forms work:

[flow]
k_aquifer = 1e-4         # interpreted as m/s
# or
k_aquifer = "0.36 m/h"   # auto-converted to m/s

Tracked input files#

If the field carries a path, annotate it with InputFile from hydromodpy/core/tracking/input_file.py:

from hydromodpy.core.tracking.input_file import InputFile

dem_path: Annotated[Path, InputFile(role="dem", category="data", portable=True)] = ...

The reproducibility manifest will list the file, its canonical path, and its SHA-256 automatically.

Cross-field validators#

Use @field_validator(mode="before") for normalisation (parse-then-validate) and @model_validator(mode="after") for cross-field invariants. Keep them small and explicit.

Add a brand-new section#

  1. Create the Pydantic model in the appropriate package.

  2. Add the field to HydroModPyConfig in hydromodpy/config/hydromodpy_config.py (typically as Annotated[NewConfig | None, Profile.USER] = None).

  3. If a launcher should dispatch on the new section, wire it through hydromodpy/cli/workflows.py (or the equivalent dispatcher).

  4. Refresh the JSON Schema export with hmp schema export --output ./schema/ and commit the diff if the project pins generated artefacts.

Tests to add#

  • Unit under tests/unit/config/ for accept / reject cases (extra fields rejected, units parsed, validators raised on bad combos).

  • Integration if the field changes the dispatched workflow.

Run hmp config check <toml> to validate any candidate TOML against the new model.

Pitfalls flagged by the layer matrix#

  • The Pydantic model lives in the same layer as the package it configures. Do not move it to config/: config/ is the root composition only.

  • schema/ and config/ may both import any other layer; new cross-edges should still be justified.

  • Generated TOML templates and JSON Schema exports must stay in sync with the source models. Re-run the export after every field addition.

See also#

On this page