视觉画布设计
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analyze-codebase-workflow【文档与办公】Analyze an arbitrary codebase to auto-detect workflows, data pipelines, and file dependencies using putior's put_auto() engine. Produces an annotation plan that maps detected I/O patterns to source files across 30+ supported languages with 902 auto-detection patterns. Use when onboarding onto an unfamiliar codebase to understand data flow, starting p…
独立 GitHub 快照 · 自动分类 · 以原作者文档为准
Survey repo → auto-detect data flows, file I/O, script deps → structured annotation plan for manual refinement.
annotate-source-filesIdentify src files + langs → what putior can analyze.
library(putior)
# List all supported languages and their extensions
list_supported_languages()
list_supported_languages(detection_only = TRUE) # Only languages with auto-detection
# Get supported extensions
exts <- get_supported_extensions()
File listing → repo composition:
# Count files by extension in the target directory
find /path/to/repo -type f | sed 's/.*\.//' | sort | uniq -c | sort -rn | head -20
→ File extensions in repo + counts. Map against get_supported_extensions() → coverage.
If err: No files match supported → putior can't auto-detect. Check if lang supported but non-standard ext.
Per detected lang → verify auto-detect pattern available.
# Check which languages have auto-detection patterns (18 languages, 902 patterns)
detection_langs <- list_supported_languages(detection_only = TRUE)
cat("Languages with auto-detection:\n")
print(detection_langs)
# Get pattern counts for specific languages found in the repo
for (lang in c("r", "python", "javascript", "sql", "dockerfile", "makefile")) {
patterns <- get_detection_patterns(lang)
cat(sprintf("%s: %d input, %d output, %d dependency patterns\n",
lang,
length(patterns$input),
length(patterns$output),
length(patterns$dependency)
))
}
→ Pattern counts printed. R 124, Python 159, JS 71, etc.
If err: No patterns → supports manual only, not auto. Plan manual annotations.
Execute put_auto() → discover workflow elements.
# Full auto-detection
workflow <- put_auto("./src/",
detect_inputs = TRUE,
detect_outputs = TRUE,
detect_dependencies = TRUE
)
# Exclude build scripts and test helpers from scanning
workflow <- put_auto("./src/",
detect_inputs = TRUE,
detect_outputs = TRUE,
detect_dependencies = TRUE,
exclude = c("build-", "test_helper")
)
# View detected workflow nodes
print(workflow)
# Check node count
cat(sprintf("Detected %d workflow nodes\n", nrow(workflow)))
Large repos → analyze subdirs incrementally:
# Analyze specific subdirectories
etl_workflow <- put_auto("./src/etl/")
api_workflow <- put_auto("./src/api/")
→ Df w/ id, label, input, output, source_file cols. Row = detected step.
If err: Empty → src may lack recognizable I/O patterns. Try workflow <- put_auto("./src/", log_level = "DEBUG") → see scanned + matched.
Visualize auto-detected → assess coverage + gaps.
# Generate diagram from auto-detected workflow
cat(put_diagram(workflow, theme = "github"))
# With source file info for traceability
cat(put_diagram(workflow, show_source_info = TRUE))
# Save to file for review
writeLines(put_diagram(workflow, theme = "github"), "workflow-auto.md")
→ Mermaid flowchart, detected nodes + data flow edges. Meaningful fn/file labels.
If err: Disconnected nodes → auto-detect found I/O but couldn't infer connections. Normal — matching output → input filenames. Annotation plan next step fills.
Generate plan → what found + what needs manual.
# Generate annotation suggestions
put_generate("./src/", style = "single")
# For multiline style (more readable for complex workflows)
put_generate("./src/", style = "multiline")
# Copy suggestions to clipboard for easy pasting
put_generate("./src/", output = "clipboard")
Doc plan w/ coverage assessment:
## Annotation Plan
### Auto-Detected (no manual work needed)
- `src/etl/extract.R` — 3 inputs, 2 outputs detected
- `src/etl/transform.py` — 1 input, 1 output detected
### Needs Manual Annotation
- `src/api/handler.js` — Language supported but no I/O patterns matched
- `src/config/setup.sh` — Only 12 shell patterns; complex logic missed
### Not Supported
- `src/legacy/process.f90` — Fortran not in detection languages
### Recommended Connections
- extract.R output `data.csv` → transform.py input `data.csv` (auto-linked)
- transform.py output `clean.parquet` → load.R input (needs annotation)
→ Clear plan: auto-detected vs manual, specific recs per file.
If err: put_generate() no out → verify path correct + has supported src files.
put_auto() no err on targetput_diagram() produces valid Mermaidput_generate() produces suggestions for detected filesput_auto(".") → includes node_modules/, .git/, venv/. Target specific src dirs.detect_dependencies = TRUE catches source(), import, require() → links scripts. Disable → lose cross-file connections..R vs .r, .jsx vs .js) may not detect. Use get_comment_prefix(). Extensionless Dockerfile, Makefile supported via filename match.install-putior — prereqannotate-source-files — next: add manualgenerate-workflow-diagram — final after annotationconfigure-putior-mcp — MCP tools for interactive