Skip to main content

WorkflowConfig

WorkflowConfig(
    **data: Any,
)
Main strategy configuration. Create a new model by parsing and validating input data from keyword arguments. Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model. self is explicitly positional-only to allow self as a field name.

Ancestors

  • pydantic.main.BaseModel

Class variables

  • meta: systematica.tools.schedulers.config.Meta: Metadata configuration.
  • loader: systematica.tools.schedulers.config.Loader: Loader specific configuration.
  • loader_params: Dict[str, Any]: Loader parameters.
  • model: systematica.tools.schedulers.config.Model: Model specific configuration.
  • model_params: Dict[str, Any]: Model parameters.
  • signal: systematica.tools.schedulers.config.Signal: Signal specific configuration.
  • portfolio: Dict[str, Any]: Portfolio specific configuration.
  • model_config: The type of the None singleton.

Static methods

from_template

from_template(
    path: pathlib._local.Path,
    template: str,
) ‑> systematica.tools.schedulers.config.WorkflowConfig
Get configuration from TOML file name. Parameters:
NameTypeDefaultDescription
pathPath--Path to the templates.
templatestr--The name of the strategy. It will load a toml file located in systematica/workflow/templates
Returns:
TypeDescription
ConfigValided Config instance.

from_all_templates

from_all_templates(
    path: pathlib._local.Path,
) ‑> Dict[str, systematica.tools.schedulers.config.WorkflowConfig]
Get configuration from TOML file name. Ignore test template. Parameters:
NameTypeDefaultDescription
pathPath--Path to the templates.
Returns:
TypeDescription
ConfigValidated Config instance.

Instance variables

  • params: Dict[str, Any]: All parameters needed to run scheduler.