apache_beam.runners.interactive.testing.test_cache_manager module

class apache_beam.runners.interactive.testing.test_cache_manager.InMemoryCache

Bases: apache_beam.runners.interactive.cache_manager.CacheManager

A cache that stores all PCollections in an in-memory map.

This is only used for checking the pipeline shape. This can’t be used for running the pipeline isn’t shared between the SDK and the Runner.

exists(*labels)

read(*labels, **args)

write(value, *labels)

save_pcoder(pcoder, *labels)

load_pcoder(*labels)

cleanup()

source(*labels)

sink(labels, is_capture=False)

size(*labels)

clear(*labels)

Clears the cache entry of the given labels and returns True on success.

Parameters:

• value – An encodable (with corresponding PCoder) value
• *labels – List of labels for PCollection instance

is_latest_version(version, *labels)

Returns if the given version number is the latest.

class apache_beam.runners.interactive.testing.test_cache_manager.NoopSink(label=None)

Bases: apache_beam.transforms.ptransform.PTransform

expand(pcoll)

annotations() → Dict[str, Union[bytes, str, google.protobuf.message.Message]]

default_label()

default_type_hints()

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: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
}

Return type:Dict[str, Any]

classmethod from_runner_api(proto, context)

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)

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)

label

pipeline = None

classmethod register_urn(urn, parameter_type, constructor=None)

runner_api_requires_keyed_input()

side_inputs = ()

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

to_runner_api_parameter(unused_context)

to_runner_api_pickled(unused_context)

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.

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

with_output_types(type_hint)

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

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

class apache_beam.runners.interactive.testing.test_cache_manager.FileRecordsBuilder(tag=None)

Bases: object

add_element(element, event_time_secs)

advance_watermark(watermark_secs)

advance_processing_time(delta_secs)

build()