Fix #37736: Allow composite transforms to use implicit input chaining

[liferoad]

Issue

#37736

When using type: composite in Beam YAML, each sub-transform requires an explicit input, unlike type: chain which automatically passes the output of one transform to the next.

Fix

Modified expand_composite_transform() in sdks/python/apache_beam/yaml/yaml_transform.py to automatically chain sub-transforms when no explicit inputs/outputs are specified, similar to how chain type transforms work.

Testing

Added test_composite_implicit_input_chaining test case in yaml_transform_test.py to verify the fix.

[gemini-code-assist]

Summary of Changes

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This pull request significantly enhances the usability of Apache Beam's YAML composite transforms by introducing implicit input chaining. Previously, composite transforms required explicit input/output definitions for each sub-transform, which could be verbose. With this change, users can now define a sequence of sub-transforms within a composite without specifying inputs and outputs, and the system will automatically pass the output of one transform as the input to the next, streamlining the definition of complex pipelines.

Highlights

• Implicit Input Chaining for Composite Transforms: Enabled type: composite transforms in Beam YAML to automatically chain sub-transforms when no explicit inputs or outputs are specified, mirroring the behavior of type: chain transforms.
• expand_composite_transform Modification: Modified the expand_composite_transform function to detect the absence of explicit inputs/outputs and then programmatically set up implicit chaining between sub-transforms.
• New Test Case: Added test_composite_implicit_input_chaining to validate the correct functionality of the newly implemented implicit input chaining for composite transforms.
• Logging Refactor: Refactored direct logging calls in sdks/python/apache_beam/transforms/util.py to use a module-level _LOGGER instance for consistency.

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Changelog

• sdks/python/apache_beam/transforms/util.py
  • Introduced _LOGGER = logging.getLogger(name) at the module level.
  • Replaced all direct calls to logging.info, logging.warning, logging.debug, logging.error, and logging.critical with calls to _LOGGER.info, _LOGGER.warning, _LOGGER.debug, _LOGGER.error, and _LOGGER.critical respectively.
• sdks/python/apache_beam/yaml/yaml_transform.py
  • Added a new block of code within expand_composite_transform to handle implicit input chaining.
  • Checked if any sub-transform in the composite has explicit 'input' or 'output' keys.
  • If no explicit I/O is found, it iterates through original_transforms, setting the 'input' for subsequent transforms to the uuid of the preceding transform.
  • For the first transform, it handles the composite's overall input.
  • If new_transforms are created, the spec is updated, and an implicit 'output' is set for the composite based on the last sub-transform's uuid.
• sdks/python/apache_beam/yaml/yaml_transform_test.py
  • Added a new test method test_composite_implicit_input_chaining to YamlTransformTest.
  • This test defines a composite transform with two PyMap sub-transforms (Square and Increment) without explicit inputs, and asserts the correct chained output [2, 5, 10] for input [1, 2, 3].

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