schrodinger.application.transforms.starter module

Starter code with a basic transform and pipeline to demonstrate how to use Beam.

If this is your first time writing a PTransform, please consider reading through the Beam style guide:

Usage:

$SCHRODINGER/run seam_example.py starter

See the unit tests for this example to see how to test your PTransforms.

class schrodinger.application.transforms.starter.CarbonCount(label: Optional[str] = None)

Bases: apache_beam.typehints.decorators.WithTypeHints, apache_beam.transforms.display.HasDisplayData, Generic[apache_beam.transforms.ptransform.InputT, apache_beam.transforms.ptransform.OutputT]

A PTransform that counts the number of carbon atoms in each molecule in the input PCollection.

This could also be accomplished by just using a ParDo, i.e.

CarbonCount = beam.ParDo(_CarbonCountDoFn())

But per the style guide, we expose our PTransform as a composite transform.

Expose every major data-parallel task accomplished by your library as a composite PTransform. This allows the structure of the transform to evolve transparently to the code that uses it: e.g. something that started as a ParDo can become a more complex transform over time.

https://beam.apache.org/contribute/ptransform-style-guide/#exposing-a-ptransform-vs-something-else

expand(molecule_pcoll)
__init__(label: Optional[str] = None) → None
annotations() → Dict[str, Union[bytes, str, google.protobuf.message.Message]]
default_label() → str
default_type_hints()
display_data() → dict

Returns the display data associated to a pipeline component.

It should be reimplemented in pipeline components that wish to have static display data.

Returns:

Dict[str, Any]: A dictionary containing key:value pairs. The value might be an integer, float or string value; a DisplayDataItem for values that have more data (e.g. short value, label, url); or a HasDisplayData instance that has more display data that should be picked up. For example:

{
  'key1': 'string_value',
  'key2': 1234,
  'key3': 3.14159265,
  'key4': DisplayDataItem('apache.org', url='http://apache.org'),
  'key5': subComponent
}
classmethod from_runner_api(proto: Optional[beam_runner_api_pb2.PTransform], context: PipelineContext) → Optional[PTransform]
get_resource_hints() → Dict[str, bytes]
get_type_hints()

Gets and/or initializes type hints for this object.

If type hints have not been set, attempts to initialize type hints in this order: - Using self.default_type_hints(). - Using self.__class__ type hints.

get_windowing(inputs: Any) → Windowing

Returns the window function to be associated with transform’s output.

By default most transforms just return the windowing function associated with the input PCollection (or the first input if several).

infer_output_type(unused_input_type)
property label
pipeline: Optional[Pipeline] = None
classmethod register_urn(urn, parameter_type, constructor=None)
runner_api_requires_keyed_input()
side_inputs: Sequence[pvalue.AsSideInput] = ()
to_runner_api(context: PipelineContext, has_parts: bool = False, **extra_kwargs: Any) → beam_runner_api_pb2.FunctionSpec
to_runner_api_parameter(unused_context: PipelineContext) → Tuple[str, Optional[Union[message.Message, bytes, str]]]
to_runner_api_pickled(unused_context: PipelineContext) → Tuple[str, bytes]
type_check_inputs(pvalueish)
type_check_inputs_or_outputs(pvalueish, input_or_output)
type_check_outputs(pvalueish)
with_input_types(input_type_hint)

Annotates the input type of a PTransform with a type-hint.

Args:
input_type_hint (type): An instance of an allowed built-in type, a custom

class, or an instance of a TypeConstraint.

Raises:
TypeError: If input_type_hint is not a valid type-hint.

See apache_beam.typehints.typehints.validate_composite_type_param() for further details.

Returns:

PTransform: A reference to the instance of this particular PTransform object. This allows chaining type-hinting related methods.

with_output_types(type_hint)

Annotates the output type of a PTransform with a type-hint.

Args:
type_hint (type): An instance of an allowed built-in type, a custom class,

or a TypeConstraint.

Raises:
TypeError: If type_hint is not a valid type-hint. See

validate_composite_type_param() for further details.

Returns:

PTransform: A reference to the instance of this particular PTransform object. This allows chaining type-hinting related methods.

with_resource_hints(**kwargs) → apache_beam.transforms.ptransform.PTransform

Adds resource hints to the PTransform.

Resource hints allow users to express constraints on the environment where the transform should be executed. Interpretation of the resource hints is defined by Beam Runners. Runners may ignore the unsupported hints.

Args:

**kwargs: key-value pairs describing hints and their values.

Raises:
ValueError: if provided hints are unknown to the SDK. See

apache_beam.transforms.resources for a list of known hints.

Returns:

PTransform: A reference to the instance of this particular PTransform object.