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Write Python lecture code. Get an interactive viewer on GitHub Pages.

Project description

lectrace

Write Python lecture code. Get an interactive step-through viewer on GitHub Pages — automatically.

lectrace traces your Python code line by line using sys.settrace, captures variable state and rendered content at each step, and produces a static React app that lets anyone step through the execution with arrow keys. No Node.js, no configuration, no build step for the user — just Python.

Inspired by edtrace by Percy Liang.


Install

uv add lectrace
# or
pip install lectrace

Requires Python 3.11+. Zero mandatory dependencies — lectrace uses the standard library only. numpy, torch, and sympy are detected and rendered automatically if they are already installed in your environment.


A lecture file

A lecture is any .py file that imports from lectrace and defines a main() function:

# 01_binary_search.py
from lectrace import text, link

def binary_search(arr, target):
    lo, hi = 0, len(arr) - 1
    while lo <= hi:              # @inspect lo hi
        mid = (lo + hi) // 2    # @inspect mid
        if arr[mid] == target:
            return mid
        elif arr[mid] < target:
            lo = mid + 1
        else:
            hi = mid - 1
    return -1

def main():
    text("# Binary Search")
    text("Finds a target in a sorted array in $O(\\log n)$ time.")

    arr = [2, 5, 8, 12, 16, 23, 38, 42]  # @inspect arr
    result = binary_search(arr, 23)       # @inspect result

    text(f"Found 23 at index `{result}`")
    link(binary_search)   # click to jump to the function definition

Directives

Directives are inline comments that control tracing and display:

Directive Effect
# @inspect x y Show x and y in the variable panel after this line runs
# @clear x Remove x from the variable panel
# @stepover Execute this line as a single step — don't trace into any calls it makes
# @hide Run this line silently — never shown in the viewer

Rendering functions

Call these anywhere inside main() or any function it calls:

Function What it renders
text("# Heading") Markdown with LaTeX math ($...$ inline, $$...$$ display)
text("...", verbatim=True) Monospace, whitespace preserved
image("fig.png", width=400) Local file or remote URL (cached)
video("demo.mp4") Embedded video with controls
link(MyClass) Clickable jump to that class or function in the viewer
link(title="Paper", url="...", authors=["Smith"], date="2024") Reference card with hover metadata
plot({...}) Interactive Vega-Lite chart
note("speaker annotation") Presenter note, hidden until N is pressed
system_text(["python3", "--version"]) Shell command output as verbatim text

Custom type rendering

Implement __lectrace__ on any class to control how it appears in the variable panel:

class Node:
    def __init__(self, val, left=None, right=None):
        self.val = val
        self.left = left
        self.right = right

    def __lectrace__(self):
        return {
            "val": self.val,
            "left": self.left.val if self.left else None,
            "right": self.right.val if self.right else None,
        }

Without __lectrace__, nested objects show their full repr. With it, you control exactly what students see.


File naming

Pattern Behaviour
01_intro.py Lecture — appears in sidebar, traced and deployed
02_sorting.py Lecture — sidebar order follows alphabetical sort
_utils.py Helper — imported normally, never traced or shown

Number prefixes control sidebar order. Helper files starting with _ are ignored by lectrace entirely.

my-course/
  _data.py            ← shared data, ignored by lectrace
  01_intro.py         ← first in sidebar
  02_complexity.py    ← second
  03_sorting.py       ← third

CLI

lectrace serve                  # build + serve all lectures at http://localhost:7000
lectrace serve 01_intro.py      # serve a single file
lectrace build --output _site   # build static site for deployment
lectrace init                   # generate GitHub Actions workflow + lectrace.toml
lectrace run 01_intro.py        # execute and print trace stats (no server)

Deploy to GitHub Pages

lectrace init   # generates .github/workflows/lectrace.yml
git add .
git commit -m "add lectures"
git push

Enable GitHub Pages in your repo settings (Source: GitHub Actions). Every push to main rebuilds and redeploys automatically.


How it works

  • Tracersys.settrace intercepts every line of execution. At each step it captures the call stack, inspected variable values (serialized to JSON), and any pending renderings.
  • Serializer — converts Python values to JSON. Primitives are direct. Collections recurse. numpy/torch/sympy are imported lazily only when encountered.
  • Builder — discovers lecture files, runs each through the tracer, writes traces/*.json plus a traces/index.json manifest. Incremental: files are skipped if their SHA-256 hash hasn't changed.
  • Viewer — a pre-built React + TypeScript SPA bundled into lectrace/_static/ and shipped inside the pip package. Uses HashRouter so it works at any URL depth with zero configuration. Math via KaTeX, charts via Vega-Lite, syntax highlighting via highlight.js.

Documentation

Full documentation: https://praisegee.github.io/lectrace/

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