schrodinger.application.transforms.baseconfig module

class schrodinger.application.transforms.baseconfig.PTransformWithConfig(**kwargs)

Bases: PTransform

Base class for PTransforms that use Pydantic models for configuration.

Subclasses should define a class variable config_class pointing to a Pydantic BaseModel class. The constructor will automatically create an instance of this config class and store it as self.config.

Example usage:

class MyTransformConfig(BaseModel):
    multiplier: float

class MyTransform(PTransformWithConfig):
    config_class = MyTransformConfig

    def expand(self, pcoll):
        # Access configuration via self.config
        return pcoll | beam.Map(lambda x: x * self.config.multiplier)

config_class: Type[BaseModel] = None

__init__(**kwargs)

Initialize the transform with configuration.

All keyword arguments are passed to the config_class constructor to create a validated configuration instance stored as self.config.

Parameters:

kwargs – Configuration parameters for the config_class

Raises:

• AttributeError – If config_class is not defined on the subclass

• ValidationError – If the configuration parameters are invalid

classmethod from_config(config_instance: BaseModel)

display_data() → Dict[str, Any]

Return display data for the transform based on the configuration.

Automatically generates display data from all fields in the config, converting values to strings for display purposes.

Returns:

Dictionary of configuration data for display