jupyter-cpp-tutor

C++ step-by-step code visualization for JupyterLab 4.x and Notebook 7.

Uses GDB to trace C++ code execution and renders an interactive step-by-step visualization (like Python Tutor / OPT_Mentor) inside a Jupyter notebook cell.

Features

• %%cpptutor cell magic — write C++ code in a Python kernel cell, get instant visualization
• GDB-based tracing — compiles with g++ -g, traces with GDB's Python API
• Step-by-step navigation — slider + first/prev/next/last buttons
• Variable visualization — int, char, bool, float, pointers, arrays, structs
• Call stack — see function frames with parameters and locals
• Pointer arrows — SVG arrows from pointers to their targets
• Resizable panels — draggable dividers between code/frames/heap columns
• Iframe srcdoc — works in trusted JupyterLab 4 / Notebook 7 notebooks

Requirements

• g++ (with -g debug support)
• gdb (with Python scripting support — standard on Linux)
• A Python kernel (not a C++ kernel — tracing is done via GDB)
• JupyterLab 4.x or Notebook 7.x

Installation

pip install jupyter-cpp-tutor

Then load the extension in a notebook:

%load_ext jupyter_cpp_tutor

Or add to your ~/.ipython/profile_default/ipython_config.py:

c.InteractiveShellApp.extensions = ['jupyter_cpp_tutor']

Usage

Basic

%%cpptutor
int main() {
    int x = 1;
    int y = x + 2;
    int z = x * y;
    return 0;
}

Functions

%%cpptutor
int add(int a, int b) {
    return a + b;
}
int main() {
    int x = add(3, 4);
    return 0;
}

Pointers

%%cpptutor
int main() {
    int x = 42;
    int *p = &x;
    return 0;
}

Arrays

%%cpptutor
int main() {
    int arr[3] = {10, 20, 30};
    return 0;
}

Structs

%%cpptutor
struct Point {
    int x;
    int y;
};
int main() {
    Point p;
    p.x = 3;
    p.y = 4;
    return 0;
}

Loops

%%cpptutor
int main() {
    int sum = 0;
    for (int i = 1; i <= 3; i++) {
        sum += i;
    }
    return 0;
}

With cout output

%%cpptutor
#include <iostream>
int main() {
    std::cout << "Hello, C++!" << std::endl;
    int x = 42;
    std::cout << "x = " << x << std::endl;
    return 0;
}

Configuring the compiler

Set the C++ standard and extra compiler flags for the entire notebook:

%cpptutor_config --std c++20 --flags "-Wall -Wextra"

Or per-cell:

%%cpptutor --std c++20
consteval int sq(int n) { return n * n; }
int main() {
    constexpr int x = sq(5);
    return 0;
}

Show current settings or reset:

%cpptutor_config            # show current settings
%cpptutor_config --reset    # back to defaults (c++23, no extra flags)

Default: C++23, no extra flags. -g -O0 are always added for GDB debugging.

Writing code

You must write your own main() function. The magic does not auto-wrap your code — this ensures GDB line numbers map 1:1 to your source for accurate step highlighting.

Common #include headers (<iostream>, <string>, <vector>, <map>, <list>, <set>, <memory>) are added automatically if not already present. A #line 1 directive is injected so GDB reports line numbers matching your original source exactly.

If you forget main(), you'll get a clear error message reminding you.

How It Works

1. Standard #include headers are prepended (if not already present)
2. A #line 1 "user.cpp" directive ensures GDB line numbers match your source 1:1
3. The code is compiled with g++ -g -O0 -std=c++23
4. GDB runs in batch mode with a Python script that:
   • Sets breakpoints on main() and all user-defined functions
   • Steps through execution with next
   • At each step, captures variables (via GDB's block/symbol API)
   • Captures the call stack and heap objects (from new/malloc pointers)
5. The trace is rendered as an HTML iframe with srcdoc

License

MIT