Code-Execution-Visualizer

Code Execution Visualizer is a Python tool for dynamic analysis of Python programs.
It executes code in an isolated environment (e.g., Docker), analyzes function and class calls, and generates visualizations such as:

• Sequence diagrams of function execution
• Heatmaps of executed lines
• Function and class dependency graphs

Designed for developers and students, it provides clear insights into program flow and execution behavior.

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Classes Overview

App

The main entry point of the application.

Responsibilities:

• Initializes the processing pipeline and sets the base path of the code repository.
• Runs the Processor to scan Python files and build a registry of functions, classes, and calls.
• Saves the dependency roadmap and file hashes to JSON.
• Uses VersionProcessor to compare with previous runs.
• Builds the execution graph using ExecutionChainBuildProcessor.
• Visualizes call chains with CallChainVisualizer.

Key Methods:

__init__(base_path: str)  # Sets the root directory for code scanning
run()  # Executes full pipeline: scanning, hashing, building execution chains, visualizing graphs

Processor

Handles static analysis of Python files and builds the foundational data for execution chains.

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Responsibilities

• Scans all .py files in the specified directory recursively.
• Parses each file’s Abstract Syntax Tree (AST) to extract functions, classes, and nested definitions.
• Builds registries of classes and functions (RegistryFile, RegistryClass) for later use.
• Analyzes imports to determine module dependencies.
• Tracks function calls across the codebase, even filling in missing file references.
• Generates a dependency roadmap that maps relationships between files, functions, and classes.

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Key Methods

__init__(base_path: Path)
# Initializes processor with the root path for code scanning

run() -> Tuple[DependencyRoadMap, dict]
# Executes the full processing pipeline:
# 1. Processes each Python file
# 2. Builds registries of classes and functions
# 3. Analyzes imports and calls
# 4. Maps functions/classes to files
# 5. Returns dependency roadmap and file hash dictionary

_process_single_file(py_file: Path, base_path: Path)
    -> Tuple[File, RegistryFile, Imports, Calls, str]
# Processes a single Python file:
# - Reads source code
# - Parses AST
# - Builds registry of classes/functions
# - Analyzes imports
# - Analyzes calls
# - Returns file metadata, registry, imports, calls, and raw source