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Markdown dependency analyzer โ€” extract all dependencies, generate diagrams and charts

Project description

mdflow

AI Cost Tracking

PyPI Version Python License AI Cost Human Time Model

  • ๐Ÿค– LLM usage: $0.4500 (3 commits)
  • ๐Ÿ‘ค Human dev: ~$200 (2.0h @ $100/h, 30min dedup)

Generated on 2026-05-03 using openrouter/qwen/qwen3-coder-next


Markdown dependency analyzer โ€” extract all dependencies, generate diagrams and charts.

mdflow parses Markdown files and extracts every possible structural element: headings, links, fenced code blocks (including markpact:* embedded file references), list items, TOON/YAML quality sections, and document metadata. It then generates Mermaid diagrams, HTML reports, and Markdown summaries.


What it extracts

Element Details
Headings Full H1โ€“H6 hierarchy, anchor slugs
Links [text](href) โ€” classified as internal / external / anchor / image
Code blocks Language, content, line range, markpact:type path=... metadata
List items Depth, parent heading, clean text
TOON sections ALERTS, REFACTOR, HOTSPOTS, HEALTH, NEXT, RISKS, PIPELINESโ€ฆ
Document metadata ## Metadata key/value lists
Cross-doc dependencies Links between files, markpact embedded file paths

Generated outputs

Output Description
{stem}_report.html Self-contained HTML report with all diagrams (Mermaid.js)
{stem}_report.md Markdown summary with inline Mermaid
{stem}_heading_mindmap.mermaid Mindmap of heading hierarchy
{stem}_section_flow.mermaid Section flowchart with code/link annotations
{stem}_code_pie.mermaid Pie chart of code blocks by language
{stem}_markpact_graph.mermaid Graph of embedded file references
{stem}_alerts_graph.mermaid TOON alerts & refactor tasks flowchart
{stem}_workflow.mermaid DOQL workflow steps diagram
dependency_graph.html Cross-document dependency graph (directory scan)

Installation

# Clone or copy the mdflow/ directory, then:
pip install -e .
# No mandatory dependencies โ€” pure stdlib.

Usage

Python API

from mdflow import MdFlow

flow = MdFlow()

# โ”€โ”€ Single file โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€
doc = flow.parse("SUMR.md")

print(doc.title)                        # "Ze ลบrรณdeล‚"
print(len(doc.headings))               # 24
print([ts.name for ts in doc.toon_sections])  # ['HEALTH', 'REFACTOR', ...]
print(doc.metadata)                    # {'name': 'redsl', 'version': '1.2.45', ...}

# Access markpact embedded file references
for cb in doc.markpact_blocks:
    print(f"markpact:{cb.markpact_type}  path={cb.markpact_path}")

# Get TOON quality metrics
metrics = flow.toon_metrics(doc)
print(metrics["health"])               # {'cc_mean': 20.0, 'critical': 7}
print(metrics["refactors"][:3])        # list of refactor tasks

# Get all Mermaid diagrams as strings (no files written)
diagrams = flow.diagrams(doc)
print(diagrams["section_flow"])        # flowchart TD ...

# Generate reports to disk
flow.report(doc, "output/")            # writes HTML + MD + .mermaid files

# โ”€โ”€ Directory scan โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€
docs, graph = flow.scan("docs/", "output/")
print(f"{len(docs)} files, {len(graph.edges)} dependency edges")

CLI

# Analyze a single file
mdflow analyze SUMR.md --output output/

# Select formats
mdflow analyze SUMR.md --format html,md

# Scan a directory
mdflow scan docs/ --output output/

# Print a specific Mermaid diagram to stdout
mdflow diagram SUMR.md --diagram section_flow
mdflow diagram SUMR.md --diagram list        # list available diagrams

# Write diagram to file
mdflow diagram SUMR.md --diagram alerts_graph -o alerts.mermaid

Examples

The examples/ directory contains comprehensive usage examples:

  • basic_usage.py - Basic parsing and report generation
  • advanced_analysis.py - Structure analysis, code inventory, TOON metrics
  • directory_scan.py - Scanning multiple files and dependency graphs
  • custom_diagrams.py - Working with diagrams programmatically
  • cli_usage.sh - CLI usage examples

Run examples from the project root:

python examples/basic_usage.py
python examples/advanced_analysis.py
python examples/directory_scan.py
python examples/custom_diagrams.py
bash examples/cli_usage.sh

See examples/README.md for detailed documentation.


Architecture

mdflow/
โ”œโ”€โ”€ __init__.py         โ† MdFlow faรงade (high-level API)
โ”œโ”€โ”€ models.py           โ† Data classes: MdDocument, DependencyGraph, โ€ฆ
โ”œโ”€โ”€ parser.py           โ† Core Markdown parser (stdlib only)
โ”œโ”€โ”€ analyzers/
โ”‚   โ””โ”€โ”€ __init__.py     โ† DependencyAnalyzer, StructureAnalyzer,
โ”‚                          CodeInventoryAnalyzer, ToonAnalyzer
โ”œโ”€โ”€ generators/
โ”‚   โ”œโ”€โ”€ __init__.py
โ”‚   โ”œโ”€โ”€ mermaid.py      โ† All Mermaid diagram generators
โ”‚   โ”œโ”€โ”€ html.py         โ† Self-contained HTML report
โ”‚   โ””โ”€โ”€ markdown.py     โ† Markdown summary report
โ””โ”€โ”€ cli.py              โ† argparse CLI entry point

Supported TOON sections

mdflow recognises these TOON section names inside toon / yaml code blocks and in blocks tagged markpact:analysis:

ALERTS ยท REFACTOR ยท HOTSPOTS ยท HEALTH ยท NEXT ยท RISKS ยท PIPELINES ยท DUPLICATES ยท WARNINGS ยท MODULES ยท EVOLUTION ยท COUPLING


Extension points

  • Custom extractor: subclass or monkey-patch MdParser
  • Custom diagram: call flow.diagrams(doc) and extend the mermaid module
  • Graphviz output: install graphviz Python package and use DependencyGraph data directly

License

Licensed under Apache-2.0.

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