jupyter-python-tutor
Python Tutor–style step-by-step code visualization directly inside JupyterLab 4.x and Notebook 7 cells.
Quick Start
pip install jupyter-python-tutor
In a Jupyter cell:
%load_ext jupyter_python_tutor
Then use the %%tutor cell magic:
%%tutor
x = 3
y = x + 4
print(y)
An interactive trace appears below the cell — drag the slider to navigate through execution, see variable values change at each line, with SVG arrows from frame variables to heap objects (like Python Tutor).
Features
- Interactive slider navigation — drag the slider (or use ◀ ▶ buttons / ← → arrow keys) to scrub through execution steps
- SVG pointer arrows — arrows from frame variables to heap objects, like OPT_Mentor / Python Tutor
- Single-step view — only the current step is shown (not all steps stacked)
- Call stack visualization — global frame + local frames with line numbers
- Heap objects — lists, dicts, class instances, functions, and other objects shown as boxes with arrows pointing to them
- Resizable columns — drag the vertical dividers between code / variables / objects to resize; double-click a divider to collapse/expand
- Auto-height — iframe height follows the tallest column content (no fixed height, no internal scroll)
- AST-based variable filtering — only variables used by the traced code are shown (no IPython internals, no contamination from other cells)
- stdout capture —
print()output is displayed per step - functools.wraps-safe — functions show their true name (
__code__.co_name), not the wrapper's__name__ - Trusted notebook support — renders fully (with JS, CSS, arrows) in trusted notebooks;
jupyter trust notebook.ipynbafter execution - Works with Notebook 7 — compatible with the new Jupyter Notebook 7 (JupyterLab-based)
- Pure Python — no compiled extensions, works in CPython 3.8+
Options
%%tutor --max-steps 1000 # Limit trace steps (default: 5000)
%%tutor --raw # Output trace as JSON instead of HTML
%%tutor --height 400 # Set minimum widget height (default: 500)
Examples
Loops
%%tutor
total = 0
for i in range(5):
total += i
print(f"Sum: {total}")
Functions with recursion
%%tutor
def factorial(n):
if n <= 1:
return 1
return n * factorial(n - 1)
result = factorial(4)
print(result)
Classes and inheritance
%%tutor
class Animal:
def __init__(self, name):
self.name = name
def speak(self):
return f"{self.name} says hello"
class Dog(Animal):
def speak(self):
return f"{self.name} barks"
d = Dog("Rex")
print(d.speak())
How It Works
-
Tracing: The
%%tutormagic compiles the cell code and executes it undersys.settrace(). At each line/call/return event, a snapshot of all local and global variables is captured. AST analysis (ast.parse) extracts the set of names the traced code touches, so only code-relevant variables are shown (filtering out IPython internals and variables from other cells). -
Rendering: The trace steps are rendered as a complete HTML page inside an
<iframe srcdoc="...">. This bypasses JupyterLab 4's HTML sanitizer (which strips<script>,<style>,<button>,<input>, etc. from untrusted output). In trusted notebooks, the iframe renders with full CSS + JavaScript — enabling slider navigation, SVG arrows, draggable dividers, and auto-height. -
Arrows: SVG paths are computed at render time from the bounding boxes of pointer boxes (in frame variables) to heap objects. Arrows redraw on slider navigation, column resize, and window resize.
-
JupyterLab 4 compatibility: JupyterLab 4's HTML sanitizer (DOMPurify) strips JavaScript and external URLs from untrusted notebooks. The iframe
srcdocapproach bypasses this entirely in trusted notebooks. Runjupyter trust your_notebook.ipynbafter executing cells with%%tutorto ensure the visualization renders correctly.
Limitations
- Trusted notebooks required for full rendering (arrows, slider, dividers). Untrusted notebooks will show a stripped-down version.
sys.settrace()adds overhead — very long loops will be slow; use--max-stepsto limit- Threads are not traced (only the main thread)
License
MIT
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