@codemod/python-maintainability-audit-bundle
Run a coordinated Python maintainability audit across framework usage, async patterns, collection checks, class structure, logging, tests, web handlers, data tooling, and machine-learning code quality.
The bundle invokes focused child codemods so teams can collect findings and metrics from a single workflow before planning targeted cleanup. The workflow uses independent nodes so compatible child codemods can be scheduled concurrently by the runner.
The bundle requires filesystem access because the Django URL/signature analyzer resolves project-local URL modules and views across files.
Included Codemods
@codemod/beautifulsoup-deprecated-method-usage@0.1.2@codemod/beautifulsoup-explicit-parser@0.1.2@codemod/bs4-raw-html-tag-insertion-audit@0.1.2@codemod/detect-deeply-nested-python-fstrings@0.1.2@codemod/detect-torch-empty-list-init@0.1.2@codemod/django-explicit-view-url-params@0.1.2@codemod/django-render-locals-usage@0.1.2@codemod/fastapi-dependencies-use-annotated@0.1.2@codemod/fastapi-file-upload-form-validation@0.1.2@codemod/fastapi-redundant-response-model@0.1.2@codemod/fastapi-router-prefix-init@0.1.2@codemod/flask-post-query-param-usage@0.1.1@codemod/pydantic-optional-explicit-defaults@0.1.2@codemod/pyspark-complex-column-expression-miner@0.1.1@codemod/pyspark-duplicate-dataframe-columns@0.1.2@codemod/python-async-resource-context-usage@0.1.1@codemod/python-async-sleep-zero-checkpoints@0.1.1@codemod/python-component-rename-directive-audit@0.1.1@codemod/python-dict-membership-via-keys@0.1.2@codemod/python-duplicate-base-class-inheritance@0.1.2@codemod/python-duplicate-class-field-defs@0.1.1@codemod/python-empty-membership-tests@0.1.2@codemod/python-enumerate-unpack-usage@0.1.2@codemod/python-exception-assertion-miner@0.1.2@codemod/python-fastapi-generic-route-decorators@0.1.2@codemod/python-gratuitous-boolean-expressions@0.1.1@codemod/python-inconsistent-tuple-return-arity@0.1.2@codemod/python-interface-architecture-drift@0.1.2@codemod/python-logging-best-practices-audit@0.1.2@codemod/python-long-sleep-forever@0.1.2@codemod/python-prefix-suffix-or-chains@0.1.2@codemod/pytorch-no-inline-module-instantiation@0.1.2@codemod/pytorch-stable-numeric-op-usage@0.1.2@codemod/safe-python-http-header-access@0.1.1
Output
Each child codemod emits its own findings and stable metrics. Use the combined output to prioritize maintainability cleanup across high-risk Python code before planning targeted transformations.
License
MIT