find-duplication

# Find Code Duplication Detect duplicated or near-duplicate code and suggest consolidation candidates. ## Rules - Report findings, do not refactor. Refactoring is a separate task. - Focus on production code (`ols/`). Skip test duplication unless explicitly asked. - Group findings by severity: exact duplicates first, then near-duplicates. - For each finding, state whether extraction is worth it or acceptable duplication. ## Step 1: Determine Scope Ask the user: - **Branch mode**: only files changed in the current branch vs main. - **Full mode**: scan the entire `ols/` directory. For branch mode: ```bash git diff --name-only origin/main -- 'ols/' | grep '\.py$' ``` For full mode, the target is `ols/`. ## Step 2: Run Pylint Duplicate Detection ```bash uv run pylint --disable=all --enable=duplicate-code --min-similarity-lines=6 <target files or directory> ``` Review output. Filter out false positives: - Import blocks (common imports are not duplication) - Pydantic model boilerplate (Field declarations) - Single-line patterns (logging, raises) ## Step 3: Semantic Duplication Search Pylint only catches textual similarity. Also look for: 1. **Similar function signatures** — functions with near-identical parameter lists doing similar work. 2. **Repeated error handling** — same try/except/log/return pattern across multiple files. 3. **Copy-pasted blocks** — search for distinctive string literals or variable names that appear in multiple files. ```bash rg "<distinctive pattern>" ols/ --type py -l ``` ## Step 4: Classify Findings For each duplicate found, classify: | Category | Action | |----------|--------| | **Extract** — identical logic in 3+ places | Recommend a shared helper | | **Parameterize** — same structure, different values | Recommend a common function with parameters | | **Acceptable** — similar but serving different domains | Note it, no action needed | | **Test-only** — repeated test setup/fixtures | Recommend shared fixture (only if user asked) | ## Step 5: Report For each finding: 1. Files and line ranges involved 2. What is duplicated (brief description) 3. Classification (extract / parameterize / acceptable) 4. Suggested location for shared code (if applicable) Summary: total findings, how many actionable, estimated lines saved.