U-Boot’s suite of Python tools—including buildman, patman, and binman—are critical parts of our development workflow. However, like any long-lived software project, technical debt accumulates. Buildman in particular was written a while ago, without much use of pylint and has grown significantly over the years. The accumulated pylint warnings, inconsistent naming conventions, and a monolithic structure make maintenance somewhat difficult.
On the other hand, cleaning up Python code is error-prone and not a lot of fun! A few recent series (board, general, builderthead and test.py) has shown a different path: extensive use of AI as a co-developer to accelerate the cleanup.
The Problem: Entropy
The buildman code has several issues typical of older Python codebases:
- Monolithic Class: The
TestBuildclass had become a dumping ground for all tests, making it hard to navigate. - Legacy Formatting: Reliance on
%string formatting instead of modern f-strings. - PEP 8 Violations: A mix of
CamelCaseandsnake_casemethod names, missing docstrings, and indentation inconsistencies. - Pylint Noise: A high volume of warnings that obscured actual logic errors.
The AI Advantage
Refactoring code to fix style issues is often tedious and error-prone. For this series, we used Claude Opus 4.5 to handle the heavy lifting. The AI was particularly effective at:
- Mechanical Translations: Converting hundreds of lines from
%formatting to f-strings and renaming variables fromCamelCasetosnake_caseto match PEP 8 standards. - Logic Extraction: Helping to identify seams in the code where the massive
TestBuildclass could be split into logical components. - Docstring Generation: Analyzing test methods and generating accurate, compliant docstrings where they were missing.
By offloading these tasks, we can focus on the architectural decisions while the AI handled the syntax updates. Each commit in the series carries a Co-developed-by tag, acknowledging the AI’s contribution to the code generation.
Most importantly, this clean-up can be largely a background task. In between other work, switch back to the clean-up terminal every now and then and spend a few minutes looking at what was done and deciding what to do next.
Key Architectural Improvements
The most significant change in the latest series is the decomposition of the TestBuild class.
Previously, TestBuild handled everything from output parsing to toolchain management. Now it is split into focused classes:
TestBuildBase: Common setup and teardown logic.TestBuildOutput: Tests specific to summary display and error formatting.TestBuildBoards: Tests regarding board selection logic.TestBuildConfig: Tests for Kconfig manipulation.TestBuildMisc: Process limits and other edge cases.
This separation of concerns makes the tests easier to read and understand.
The other series linked have adopted a similar approach – splitting code into separate functions to make it easier to read and maintain.
AI coding tools have a clear advantage in refactoring. They can fairly reliably extract code into functions and make other adjustments that are beyond a mere ‘refactor’ tool in VS Code or Eclipse, for example. It is also easy to go back to an earlier commit in the series to bring in a change, then continue the rebase and have the AI deal with merge conflicts.
Conclusion
This cleanup so far brings most of the buildman code into full pylint compliance (with some pragmatic disable-directives where necessary). It serves as a good example of how AI tools can be leveraged to modernize legacy infrastructure code in the U-Boot project, turning a multi-day refactoring slog into a manageable, efficient process.
