codemarp 0.1.1

Multi-level code architecture and relationship mapping

CodeMarp

Multi-level code architecture and relationship mapping

Understand a codebase like a map — zoom in, zoom out, follow the flow.

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The problem

Large codebases are hard to navigate. You open a file and you're already lost. You don't know what calls what, where things live, or what actually happens inside a function.

Documentation is outdated. Diagrams don't exist. The only way to understand the code is to read all of it.

CodeMarp takes a different approach: it builds the map for you.

What CodeMarp does

Given a Python repository, CodeMarp gives you three zoom levels:

Level	What you see
High	Module and package architecture — how things are organised
Mid	Function relationships — who calls what
Low	Control flow inside a function — what actually happens

Think of it as Google Maps for your codebase. Built entirely from static analysis — no runtime, no instrumentation.

Zoom out to see the city. Zoom in to see the streets. Zoom in further to see the building layout.

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Quickstart

Run CodeMarp on a Python repository:

codemarp analyze src --out out

This generates:

out/
  high_level.mmd
  mid_level.mmd
  graph.json

To zoom into one function:

codemarp analyze src --view low --focus codemarp.cli.main:analyze_command --out out

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Output

Every analysis produces:

out/
  high_level.mmd    # architecture graph
  mid_level.mmd     # function call graph
  low_level.mmd     # control flow (when using --view low)
  graph.json        # full graph data for tooling

• Mermaid (.mmd) — renders in GitHub, VS Code, Mermaid Live Editor
• JSON — for tooling, integrations, and future UI

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Install

For local development in this repo:

uv sync --extra dev

To install in a project environment:

uv pip install codemarp

Or with pip:

pip install codemarp

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Usage

Analyse a repo

codemarp analyze path/to/repo --out out

Point at the folder that contains your top-level package:

# flat layout: mypackage/ is at root
codemarp analyze .

# src layout: mypackage/ is inside src/
codemarp analyze src

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Views

Full (default)

See the entire graph — architecture + all function relationships.

codemarp analyze path/to/repo --view full --out out

Trace — what does this function call?

Follow a function forward through the call graph.

codemarp analyze path/to/repo \
  --view trace \
  --focus package.module:function_name \
  --max-depth 3 \
  --out out

Reverse — what calls this function?

Find every path that leads to a function.

codemarp analyze path/to/repo \
  --view reverse \
  --focus package.module:function_name \
  --max-depth 3 \
  --out out

Module — zoom into one module

Show the functions and internal relationships for a single module.

codemarp analyze path/to/repo \
  --view module \
  --module package.module_name \
  --out out

Low — what happens inside this function?

Build a control-flow graph for one function.

codemarp analyze path/to/repo \
  --view low \
  --focus package.module:function_name \
  --out out

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Typical workflow

1. codemarp analyze src --view full
   → understand the overall structure

2. codemarp analyze src --view module --module mypackage.core
   → inspect one area

3. codemarp analyze src --view trace --focus mypackage.core:run --max-depth 3
   → follow a specific entrypoint

4. codemarp analyze src --view low --focus mypackage.core:run
   → zoom into the logic

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Viewing the output

Mermaid files render automatically in:

• GitHub — renders Mermaid blocks directly in Markdown files
• Mermaid Live Editor — paste and share
• VS Code — with the Mermaid Preview extension

Yes, GitHub renders Mermaid blocks directly in Markdown, so the sample diagrams below should display in the repo README.

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Sample output

These examples were generated from the CodeMarp codebase itself.

High-level architecture

Command:

codemarp analyze src --view full --out samples/codemarp_full_out

Excerpt from samples/codemarp_full_out/high_level.mmd:

flowchart LR
    codemarp_analyzers["codemarp.analyzers"]
    codemarp_cli["codemarp.cli"]
    codemarp_errors(["codemarp.errors"])
    codemarp_exporters["codemarp.exporters"]
    codemarp_graph["codemarp.graph"]
    codemarp_parser["codemarp.parser"]
    codemarp_pipeline["codemarp.pipeline"]
    codemarp_views["codemarp.views"]
    codemarp_analyzers -->|imports| codemarp_graph
    codemarp_analyzers -->|imports| codemarp_parser
    codemarp_cli -->|imports| codemarp_analyzers
    codemarp_cli -->|imports| codemarp_errors
    codemarp_cli -->|imports| codemarp_pipeline
    codemarp_exporters -->|imports| codemarp_graph
    codemarp_exporters -->|imports| codemarp_analyzers
    codemarp_parser -->|imports| codemarp_errors
    codemarp_parser -->|imports| codemarp_graph
    codemarp_pipeline -->|imports| codemarp_graph
    codemarp_pipeline -->|imports| codemarp_views
    codemarp_pipeline -->|imports| codemarp_analyzers
    codemarp_pipeline -->|imports| codemarp_parser
    codemarp_pipeline -->|imports| codemarp_exporters
    codemarp_views -->|imports| codemarp_errors
    codemarp_views -->|imports| codemarp_graph

This is the zoomed-out package view: which parts of the project depend on which others.

Focused function trace

Command:

codemarp analyze src --focus codemarp.cli.main:analyze_command --out out

Excerpt from samples/codemarp_trace_out/mid_level.mmd:

flowchart LR
    codemarp_graph_models_GraphBundle_function_by_id["codemarp.graph.models:GraphBundle.function_by_id"]
    codemarp_views_subgraph_build_function_subgraph["codemarp.views.subgraph:build_function_subgraph"]
    codemarp_views_subgraph__filter_edges_for_nodes["codemarp.views.subgraph:_filter_edges_for_nodes"]
    codemarp_views_subgraph__modules_for_functions["codemarp.views.subgraph:_modules_for_functions"]
    codemarp_views_trace__build_call_adjacency["codemarp.views.trace:_build_call_adjacency"]
    codemarp_views_trace_trace_functions_forward["codemarp.views.trace:trace_functions_forward"]
    codemarp_views_trace_trace_function_view["codemarp.views.trace:trace_function_view"]
    codemarp_views_trace__validate_entrypoint["codemarp.views.trace:_validate_entrypoint"]
    codemarp_views_subgraph_build_function_subgraph -->|calls| codemarp_views_subgraph__modules_for_functions
    codemarp_views_subgraph_build_function_subgraph -->|calls| codemarp_views_subgraph__filter_edges_for_nodes
    codemarp_views_trace_trace_functions_forward -->|calls| codemarp_views_trace__validate_entrypoint
    codemarp_views_trace_trace_functions_forward -->|calls| codemarp_views_trace__build_call_adjacency
    codemarp_views_trace_trace_function_view -->|calls| codemarp_views_trace__validate_entrypoint
    codemarp_views_trace_trace_function_view -->|calls| codemarp_views_trace_trace_functions_forward
    codemarp_views_trace_trace_function_view -->|calls| codemarp_views_subgraph_build_function_subgraph
    codemarp_views_trace__validate_entrypoint -->|calls| codemarp_graph_models_GraphBundle_function_by_id

This is the focused mid-level view: starting from one function, you can follow the call chain it reaches.

Low-level control flow

Command:

codemarp analyze src --view low --focus codemarp.parser.python_parser:get_source --out out

Excerpt from samples/codemarp_low_out/low_level.mmd:

flowchart TD
    n1(["Start"]):::terminal
    n2{"encoding is None"}:::decision
    n3["get_best_encoding(...)"]:::statement
    n4["Merge"]:::merge
    n5{"errors is None"}:::decision
    n6["Assign"]:::statement
    n7["Merge"]:::merge
    n8(["Return"]):::terminal
    n9(["End"]):::terminal
    n1 --> n2
    n2 -->|True| n3
    n3 --> n4
    n2 -->|False| n4
    n4 --> n5
    n5 -->|True| n6
    n6 --> n7
    n5 -->|False| n7
    n7 --> n8
    n8 --> n9

    classDef decision fill:#fff3cd,stroke:#d4a017,color:#000;
    classDef statement fill:#f0f0f0,stroke:#aaa,color:#333;
    classDef terminal fill:#fde8e8,stroke:#c0392b,color:#000;
    classDef merge fill:#eef2ff,stroke:#7c8fdb,color:#000;
    classDef start fill:#e8f5e9,stroke:#2e7d32,color:#000;

This is the zoomed-in function view: branches, merges, and return flow inside a single function.

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Known limitations

CodeMarp is static analysis — it reads your code without running it.

Limitation	Workaround
Relative imports may produce sparse high-level graphs	Use --view module or --view trace instead
Method calls (self.method()) are conservatively handled	Some valid edges may be missing, but false positives are reduced
Dynamic dispatch is not tracked	Results reflect static structure only
Large full graphs can be hard to read	Use focused views — trace, module, reverse

These are honest limitations, not bugs. Focused views exist precisely because full graphs on real codebases get noisy.

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Roadmap

• Better call resolution (method dispatch, aliases)
• Graph filtering and noise reduction
• Tree-sitter migration → multi-language support
• JavaScript / TypeScript support
• Interactive web UI

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Philosophy

Useful before perfect. CodeMarp v0.1 is not exhaustive. It is correct for common cases and honest about where it isn't.

Readable before complete. A graph you can understand is more valuable than a graph that shows everything.

Static first. No runtime instrumentation. No code execution. Analysis runs anywhere.

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Status

• Python only (AST-based, tree-sitter planned)
• CLI-first
• v0.1.x — early but usable on real codebases

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Name

CodeMarp — sounds like "code map", because that's what it produces.

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Built to answer the question every developer asks when they open an unfamiliar codebase: where do I even start?