Moderne has announced that its OpenRewrite code refactoring platform now supports Python, enabling organizations to modernize their systems, fix vulnerabilities, and run change initiatives over a larger proportion of their application and data infrastructure.
OpenRewrite is powered by the company’s Lossless Semantic Tree (LST), a code model that resolves symbols, tracks relationships, and preserves intent, allowing changes to be safely applied.
Previously, the LST supported Java, JavaScript, and TypeScript, but since Python is commonly used in AI and automation, the company felt it was important to add support for it as well. According to Moderne, this extends LST coverage from backend and frontend application code into the data and AI layer.
After the code is modeled by LST, developers can use recipes to execute changes in a repeatable way. The company already offers several out-of-the-box recipes for Python for various use cases, including upgrading to newer Python versions by modernizing deprecated APIs and patterns; adding, changing, or removing dependencies; finding, fixing, and upgrading direct and transitive dependencies across repositories; removing redundant constructs like unnecessary pass statements; and applying consistent formatting transformations.
“Agents can assist in identifying patterns or drafting transformations. Recipes provide the mechanism for applying those changes consistently within existing review and CI/CD workflows,” the company wrote in a blog post.
According to the company, “modern systems rarely evolve in isolation,” and a Java service might expose an API that is consumed by a Python integration, or a shared dependency might appear across backend services, frontend tooling, and Python automation scripts.
With the addition of Python, Moderne customers will now be able to coordinate their modernization efforts across a greater proportion of their codebases. For example, dependency upgrades can be coordinated across multiple languages using a single campaign, security remediations can be analyzed and applied together across different runtimes, and API changes in one service can be combined with updates in dependent Python systems.
“Modern software doesn’t stop at backend services or frontend applications. Python now sits alongside them powering data workflows, automation, integrations, and increasingly, AI-driven systems. Python now extends the same semantic execution model across the data, automation, and AI layers of modern systems. Analysis, migration, and coordinated change can extend into Python codebases without introducing new tooling or parallel processes,” the company wrote.
