feat: add a2a-python SUT code generation

[jmesnil]

Add a Python code emitter that generates a runnable SUT project from Gherkin scenarios using the a2a-python SDK, mirroring the existing a2a-java pipeline.

New files:

• codegen/python_emitter.py — maps Actions to TaskUpdater API calls
• codegen/a2a-python/*.j2 — Jinja2 templates (sut_agent.py, pyproject.toml)
• tests/unit/codegen/test_python_emitter.py — 6 unit tests
• sut/a2a-python/ — generated SUT project (16 scenarios)

Modified:

• codegen/generator.py — register a2a-python emitter
• Makefile — add codegen-a2a-python-sut target
• AGENTS.md — document new emitter and commands
• .gitignore — scope a2a-python ignore to root only

TCK result: 76.5% compatibility (remaining failures are SDK-level).

[gemini-code-assist]

Summary of Changes

Hello, I'm Gemini Code Assist¹! I'm currently reviewing this pull request and will post my feedback shortly. In the meantime, here's a summary to help you and other reviewers quickly get up to speed!

This pull request significantly expands the A2A TCK's code generation capabilities by introducing a Python-based System Under Test (SUT) pipeline. This new feature allows for the automatic generation of runnable Python SUT projects from Gherkin scenarios, directly mirroring the existing Java SUT generation. The primary impact is enabling comprehensive conformance testing against the a2a-python SDK, ensuring broader compatibility and validation of the A2A specification across different language implementations.

Highlights

• New Python Code Emitter: Introduced a new Python code emitter to generate System Under Test (SUT) projects for the a2a-python SDK, mirroring the existing Java pipeline.
• Jinja2 Templates for Python SUT: Added Jinja2 templates (sut_agent.py.j2, pyproject.toml.j2) to facilitate the generation of the a2a-python SUT project structure and agent logic.
• Unit Tests for Python Emitter: Included comprehensive unit tests for the new Python code emitter to ensure its correctness and reliability.
• Build System and Documentation Updates: Integrated the a2a-python emitter into the code generation pipeline, updated the Makefile with a new build target, and documented the new capabilities in AGENTS.md.

Changelog

• .gitignore
  • Updated ignore rules to specifically target root-level a2a-python and a2a-java-sdk directories.
• AGENTS.md
  • Documented the new python_emitter.py and its associated Jinja2 templates.
  • Added the sut/a2a-python/ directory to the project structure description.
  • Included the new make codegen-a2a-python-sut command.
• Makefile
  • Added codegen-a2a-python-sut to the .PHONY list.
  • Defined a new codegen-a2a-python-sut target to generate the Python SUT.
• codegen/generator.py
  • Imported emit_python_project from the new python_emitter.
  • Registered a2a-python as a target emitter, mapping it to emit_python_project.

Activity

• Initial commit introducing the Python SUT code generation feature.

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[gemini-code-assist]

Code Review

This pull request introduces a Python code emitter for generating an a2a-python SUT, which is a great addition mirroring the existing Java pipeline. The implementation is well-structured, with clear separation of concerns between parsing, model definition, and code generation. The new emitter is properly integrated with the build system and documented.

My main feedback is to modernize the asyncio server startup logic in the generated sut_agent.py file. The current implementation uses asyncio.get_event_loop(), which is deprecated. I've provided a suggestion to refactor this using asyncio.run(), which is the recommended approach for Python 3.7+ and will make the generated code more robust and future-proof.

[jmesnil]

/gemini review

[gemini-code-assist]

Code Review

This pull request introduces a significant feature: a Python code emitter for generating a runnable SUT project from Gherkin scenarios, mirroring the existing Java pipeline. The implementation is well-structured, including the core emitter logic, Jinja2 templates, unit tests, and documentation. My review identifies a potential bug in the code generation for DataPartDef which could result in syntax errors in the generated code. I have also provided a suggestion to improve a command in the documentation to follow best practices. Overall, this is a strong contribution.