tft_beam.experimental.PTransformAnalyzer

A PTransform analyzer's base class which provides a temp dir if needed.

tft_beam.experimental.PTransformAnalyzer()

base_temp_dir

label

Methods

annotations

annotations() -> Dict[str, Union[bytes, str, message.Message]]

default_label

default_label()

default_type_hints

default_type_hints()

display_data

display_data()

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 :class:DisplayDataItem for values that have more data (e.g. short value, label, url); or a :class: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 }

expand

expand(
    input_or_inputs: InputT
) -> OutputT

from_runner_api

@classmethod
from_runner_api(
    proto, context
)

get_resource_hints

get_resource_hints()

get_type_hints

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

get_windowing(
    inputs
)

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

infer_output_type(
    unused_input_type
)

register_urn

@classmethod
register_urn(
    urn, parameter_type, constructor=None
)

runner_api_requires_keyed_input

runner_api_requires_keyed_input()

to_runner_api

to_runner_api(
    context, has_parts=False, **extra_kwargs
)

to_runner_api_parameter

to_runner_api_parameter(
    unused_context
)

to_runner_api_pickled

to_runner_api_pickled(
    unused_context
)

type_check_inputs

type_check_inputs(
    pvalueish
)

type_check_inputs_or_outputs

type_check_inputs_or_outputs(
    pvalueish, input_or_output
)

type_check_outputs

type_check_outputs(
    pvalueish
)

with_input_types

with_input_types(
    input_type_hint
)

Annotates the input type of a :class: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 :class:~apache_beam.typehints.typehints.TypeConstraint.

Raises
TypeError If input_type_hint is not a valid type-hint. See :obj:apache_beam.typehints.typehints.validate_composite_type_param() for further details.

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

with_output_types

with_output_types(
    type_hint
)

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

Args
type_hint type

An instance of an allowed built-in type, a custom class, or a :class:~apache_beam.typehints.typehints.TypeConstraint.

Raises
TypeError If type_hint is not a valid type-hint. See :obj:~apache_beam.typehints.typehints.validate_composite_type_param() for further details.

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

with_resource_hints

with_resource_hints(
    **kwargs
)

Adds resource hints to the :class: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 :mod:apache_beam.transforms.resources for a list of known hints.

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

__or__

__or__(
    right
)

Used to compose PTransforms, e.g., ptransform1 | ptransform2.

__ror__

__ror__(
    left, label=None
)

Used to apply this PTransform to non-PValues, e.g., a tuple.

__rrshift__

__rrshift__(
    label
)

pipeline None
side_inputs ()