geochemistrypi package

Subpackages

Submodules

geochemistrypi.automation module

Versioned, fail-closed input automation for the existing interactive CLI.

exception AutomationContractError[source]

Bases: RuntimeError

Raised when machine-supplied CLI input is invalid or incomplete.

class AutomationInput(id: str, response: str)[source]

Bases: object

One ordered response identified independently from human prompt text.

id: str
response: str
class AutomationInputAdapter(plan: AutomationPlan, events_path: Path)[source]

Bases: object

Temporarily serve ordered inputs to the unchanged interactive workflow.

class AutomationPlan(schema_version: int, plan_name: str, inputs: Tuple[AutomationInput, ...])[source]

Bases: object

Strict automation request loaded by the CLI process.

inputs: Tuple[AutomationInput, ...]
classmethod load(path: Path) → AutomationPlan[source]
plan_name: str
schema_version: int
exception MissingAutomationInputError[source]

Bases: AutomationContractError

Raised when the workflow asks for an input that was not supplied.

exception UnusedAutomationInputError[source]

Bases: AutomationContractError

Raised when supplied inputs were not consumed by the workflow.

automation_input_adapter(plan_path: Path, events_path: Path) → AutomationInputAdapter[source]

Build the automation adapter without importing any scientific modules.

geochemistrypi.cli module

data_mining(data: str = <typer.models.OptionInfo object>, desktop: bool = <typer.models.OptionInfo object>, training: str = <typer.models.OptionInfo object>, application: str = <typer.models.OptionInfo object>, mlflow: bool = <typer.models.OptionInfo object>, automation_plan: str = <typer.models.OptionInfo object>, automation_events: str = <typer.models.OptionInfo object>, world_map_config: str = <typer.models.OptionInfo object>, tracking_root: str = <typer.models.OptionInfo object>, existing_experiment_id: str = <typer.models.OptionInfo object>) → None[source]

Implement the customized automated machine learning pipeline for geochemistry data mining.

datasets(source: str = <typer.models.OptionInfo object>, output: str = <typer.models.OptionInfo object>) → None[source]

List built-in and Desktop datasets without creating, copying, or modifying files.

main(version: bool = <typer.models.OptionInfo object>) → None[source]

Geochemistry Pi is an open-sourced highly automated machine learning Python framework for data-driven geochemistry discovery. It has the cores components of continous training, machine learning lifecycle management and model inference.

time_series(input_path: str = <typer.models.OptionInfo object>, bin_width: float = <typer.models.OptionInfo object>, iterations: int = <typer.models.OptionInfo object>, seed: int = <typer.models.OptionInfo object>, output_root: str = <typer.models.OptionInfo object>, experiment_name: str = <typer.models.OptionInfo object>, run_name: str = <typer.models.OptionInfo object>, sheet: str = <typer.models.OptionInfo object>, age_column: str = <typer.models.OptionInfo object>, maximum_age_column: str = <typer.models.OptionInfo object>, probability_column: str = <typer.models.OptionInfo object>, latitude_column: str = <typer.models.OptionInfo object>, longitude_column: str = <typer.models.OptionInfo object>, age_unit: str = <typer.models.OptionInfo object>, fit_curve: bool = <typer.models.OptionInfo object>, automation_plan: str = <typer.models.OptionInfo object>, automation_events: str = <typer.models.OptionInfo object>) → None[source]

Run reproducible subaerial-proportion Time Series analysis.

geochemistrypi.database module

exception DatabaseConfigurationError[source]

Bases: RuntimeError

Raised when database access is requested without a configured URL.

get_database_url() → str[source]

Return the configured database URL at the database access boundary.

get_db()[source]

Get a database session.

get_engine() → Engine[source]

Create or reuse the engine for the currently configured database URL.

get_session() → Session[source]

Create a database session after validating database configuration.

geochemistrypi.start_cli_pipeline module

geochemistrypi.start_dash_pipeline module

custom_openapi()[source]
initialize_database() → None[source]

Create database tables only when the API application starts.

async read_root()[source]

geochemistrypi.tracking module

Bounded, machine-readable access to the local MLflow tracking store.

exception TrackingStoreError[source]

Bases: ValueError

Raised when a tracking-store request is invalid or cannot be satisfied.

get_experiment(tracking_root: Path, experiment_id: str, maximum_runs: int = 50) → Dict[str, Any][source]

Return one active experiment and its newest bounded run summaries.

list_experiments(tracking_root: Path, maximum_experiments: int = 100) → Dict[str, Any][source]

List active experiments from one local store with a hard response bound.

require_experiment(tracking_root: Path, experiment_id: str, expected_name: str) → Dict[str, Any][source]

Resolve a stable experiment ID and reject output-name mismatches.

resolve_tracking_root(value: str) → Path[source]

Resolve one explicit absolute tracking root without accepting URI input.

tracking_uri(root: Path) → str[source]

Return the portable file URI understood by MLflow.

geochemistrypi.tracking_cli module

Private JSON bridge used by the separately installed MCP runtime.

main(argv: List[str] | None = None) → int[source]

Module contents