What Programming Language Is Used in the Code-Review-Graph Project?

The code-review-graph project is implemented primarily in Python.

This open-source repository, maintained by tirth8205, provides a Python-based tool for analyzing code repositories and generating interactive visualizations of code review patterns and call graphs. While the tool can analyze source code written in multiple languages—including Java, C++, and PHP—the implementation that drives these analyses is written entirely in Python.

Primary Language: Python

The code-review-graph repository is a Python codebase from top to bottom. This is immediately evident from several structural elements in the repository:

• The project uses a pyproject.toml file at the root level, which declares Python packaging metadata, build system requirements, and runtime dependencies.
• All source modules reside under the code_review_graph/ package directory and use the .py extension.
• The test suite consists of pytest files in tests/*.py, demonstrating Python-native testing practices.

You can verify this yourself by examining the repository structure:

# Clone and inspect the repository

git clone https://github.com/tirth8205/code-review-graph.git
cd code-review-graph

# Check for Python files

find . -name "*.py" | head -10

This will reveal Python files throughout the codebase, including code_review_graph/wiki.py, code_review_graph/visualization.py, and numerous test files.

Key Python Source Files

Understanding which files contain the core logic helps when extending or debugging the project.

Configuration: pyproject.toml

Located at the repository root, pyproject.toml serves as the project manifest. It specifies:

• Python version requirements
• Build backend (likely setuptools or hatchling)
• Runtime dependencies such as networkx, gitpython, and visualization libraries

This file is the standard for modern Python packaging, replacing the older setup.py approach.

Core Module: code_review_graph/wiki.py

The wiki.py module implements the core extraction logic. It parses source code repositories—regardless of their original programming language—and generates structured documentation or wikis. Functions in this module handle:

• Repository traversal via GitPython
• AST parsing for supported languages
• Markdown generation for documentation output

Visualization: code_review_graph/visualization.py

The visualization.py module provides HTML/D3-based rendering capabilities. It transforms the internal graph representation into interactive web visualizations that can be viewed in browsers or Jupyter notebooks.

Test Suite: tests/

The tests/ directory contains pytest files such as test_python_reachability.py. These exercise the Python implementation against sample repositories, ensuring correctness of graph construction and traversal algorithms.

How to Use the Python Library

Below are practical examples of interacting with code-review-graph from Python code.

Creating a Graph from a Local Repository

from code_review_graph import CodeReviewGraph

# Initialize the graph with the path to a git repository

graph = CodeReviewGraph(repo_path="path/to/your/repo")

# Run the analysis (parses files, builds the call-graph, etc.)

graph.build()

# Export the graph as JSON

graph.export_json("graph.json")

The CodeReviewGraph class in code_review_graph/__init__.py serves as the main entry point. Its build() method orchestrates the parsing pipeline, while export_json() serializes results for downstream consumption.

Visualizing in a Jupyter Notebook

from code_review_graph.visualization import GraphVisualizer
import json

# Load the JSON graph generated earlier

with open("graph.json") as f:
    data = json.load(f)

# Render an interactive HTML view

viz = GraphVisualizer(data)
viz.render()  # displays an interactive D3-based graph

The GraphVisualizer class wraps D3.js visualization logic, generating self-contained HTML that renders directly in notebook cells or browser tabs.

Using the Command-Line Interface

# Install the package (if not already installed)

pip install .

# Run the CLI to analyze a repository and generate a wiki

code-review-graph generate-wiki --repo path/to/repo --output docs/wiki

The CLI entry point is defined in pyproject.toml and maps to a Python function that invokes the same CodeReviewGraph and wiki modules demonstrated above.

Language Analysis Capabilities vs. Implementation Language

A common point of confusion: code-review-graph analyzes code in many languages, but is itself written in Python.

Aspect	Implementation	Target of Analysis
Primary language	Python	N/A
Parseable languages	Via tree-sitter/plugins	Java, C++, PHP, Python, etc.
Output formats	Python-generated	JSON, HTML, Markdown

The multi-language analysis capability comes from abstract syntax tree (AST) parsers—likely tree-sitter or similar libraries—that the Python code orchestrates. The graph algorithms (reachability, centrality, community detection) are implemented using NetworkX, a Python library for complex network analysis.

Summary

• code-review-graph is a Python project based on its pyproject.toml, .py source files, and pytest test suite.
• Core modules include code_review_graph/wiki.py for extraction and code_review_graph/visualization.py for rendering.
• The tool can be used as a Python library or via a CLI, both backed by the same Python implementation.
• While the implementation language is Python, the tool analyzes repositories containing Java, C++, PHP, and other languages.

Frequently Asked Questions

Are there any dependencies on other programming languages?

The runtime dependencies are Python packages only—networkx for graph algorithms, gitpython for repository access, and D3.js for frontend visualization (delivered as static JavaScript, not requiring a separate runtime). No compiled extensions or foreign language interpreters are required to execute the core tool.

What Python version is required?

While the exact minimum version is specified in pyproject.toml, modern Python packaging standards typically require Python 3.8 or higher. Check the requires-python field in that file for the definitive constraint.

Can I extend the tool to support additional languages?

Yes. The modular architecture in code_review_graph/wiki.py suggests that language-specific parsers are pluggable. Adding support for a new language would involve implementing an AST parser callable from Python—tree-sitter grammars are the likely integration point.

Is the visualization purely Python-based?

The visualization pipeline is Python-based: visualization.py generates HTML and JavaScript. The actual rendering uses D3.js, a JavaScript library, but this is bundled or injected by the Python code. No manual JavaScript coding is required to use the feature.

{
  "mcpServers": {
    "instagit": {
      "command": "npx",
      "args": ["-y", "instagit@latest"]
    }
  }
}