Structural, not textual.
The LST preserves formatting and intent while resolving symbols, imports, types, and relationships across modules and repositories.
Language support Python
Coordinate Python changes across every repo on a semantic model.
Upgrade Python runtimes, modernize deprecated APIs, manage pyproject.toml dependencies, and remediate CVEs. Built on the Lossless Semantic Tree, governed end-to-end.
Why Python at Moderne
A semantic model of Python, not a regex pass.
Code is modeled structurally and semantically rather than treated as text. Recipes execute against that model, applying consistent changes across many Python repositories.
Governed execution.
Recipes deliver changes as reviewable pull requests within your existing CI/CD pipelines. Transformations are auditable and reversible.
Cross-language coordination.
A single campaign can span Python, Java, and JavaScript or TypeScript. Align dependencies and pair API changes with their Python consumers in one run.
What you can migrate
What ships today.
Python is shipped under the same LST engine as Java and C#. The categories below cover the recipes available now.
Python migration coverage is growing. More concrete version-to-version paths are landing this quarter.
Python runtime upgrades
Upgrade Python runtimes across repositories. Recipes flag deprecated APIs and unsafe usage patterns introduced between runtime versions.
pyproject.toml management
Add, change, or remove dependencies in pyproject.toml. Upgrade direct and transitive dependencies across the repository estate.
CVE remediation
Identify vulnerable Python dependencies and unsafe usage patterns across repos. Remediate at portfolio scale on the same review workflow as application code.
Deprecated API modernization
Standardize language features and runtime behavior. Recipes surface deprecated APIs and risky constructs introduced over time.
Import restructuring
Restructure imports across modules consistently. Operates on the semantic model, not a text pass.
Symbol and pattern audit
Surface symbol usage and architectural patterns across Python systems. Audit framework and library adoption portfolio-wide.
Moderne helps keep our codebases cleaner, safer, and easier to evolve. It is a major unlock for teams that want to spend more time shipping and less time maintaining.
How it works
Three steps, every language.
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Ingest the LST.
Moderne parses every Python file across every repo into a Lossless Semantic Tree. Types, symbols, imports, comments, and formatting are preserved.
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Run the recipe.
Recipes execute against the LST. Dependency updates, API modernization, and CVE patches apply deterministically across every affected file.
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Review and merge.
Reviewable pull requests open across every repo touched. Your team merges. Moderne tracks coverage across Python alongside the rest of the estate.
Questions
Python transformation, answered.
Python code modernization at enterprise scale refers to coordinating large-scale changes across many Python repositories, such as upgrading Python runtimes, updating deprecated APIs, aligning dependencies, and remediating security vulnerabilities.
Enterprises safely apply large-scale Python code changes by using semantic code analysis and deterministic automation rather than manual refactoring or AI-generated text edits.
Semantic code analysis for Python means analyzing Python code using a structural, type-attributed model rather than treating code as plain text.
AST-based Python refactoring tools operate on syntax trees but often lose higher-level semantic context, such as symbol resolution, dependency relationships, and behavioral intent.
Enterprises upgrade Python versions across many repositories by analyzing deprecated APIs, runtime compatibility, and dependency constraints using semantic automation.
Enterprises coordinate Python changes across multiple repositories by executing portfolio-wide change initiatives that analyze impact across repositories, apply consistent transformations, and deliver changes as reviewable pull requests.
Get started
Run Python changes on the same engine as Java.
Recipes lock in the change. Future runtime upgrades and CVE patches run on the same engine, on the same review workflow.