Xournal++ Python Math Plugin

A powerful, cross-platform(macos and linux) Xournal++ plugin that lets you write multi-line Python code, solve complex equations using SymPy, and generate transparent Matplotlib graphs directly inside your Xournal++ documents.

Features

• Jupyter-like Multi-line Execution: Write multiple lines of Python code natively. The final expression or plot is automatically evaluated and rendered.
• Beautiful LaTeX Rendering: High-res, automatically formatted LaTeX math generation for SymPy output.
• Seamless Plotting: Native Matplotlib and SymPy plot support. Backgrounds are automatically forced to be transparent so they sit perfectly on your Xournal++ page.
• Auto-Environment Detection: The plugin dynamically scans your system (including Conda environments) to find a Python executable equipped with the necessary scientific libraries.
• Pre-loaded Libraries: No need to write imports. sp (SymPy), np (NumPy), plt (Matplotlib), scipy (SciPy), and common variables (x, y, z, t, a, b, c) are pre-imported automatically.

Requirements

Python Dependencies

The plugin requires a Python environment with the following packages installed:

pip install numpy scipy sympy matplotlib

(Conda environments are highly recommended and are prioritized during auto-detection).

System Dependencies

• macOS: Works out of the box (uses native AppleScript for clipboard handling).
• Linux: Requires xclip and xdotool to manipulate the clipboard and simulate the paste keystroke.

  sudo apt install xclip xdotool

Installation

1. Clone or download this repository.
2. Copy the entire repository folder into your Xournal++ plugins directory and name it python_math:
   • Linux: ~/.config/xournalpp/plugins/python_math
   • macOS: ~/.config/xournalpp/plugins/python_math
3. Open Xournal++, go to Plugin Manager, and enable the python_math plugin.
4. Restart Xournal++.

Usage

1. Press Ctrl + Shift + P inside Xournal++ to open the Python Math Evaluator window.
2. Type your Python code.
3. Press Cmd + Enter (macOS) or Ctrl + Enter (Linux), or click the "Run Code" button.
4. The result (equation or plot) will be automatically pasted onto your active page!

Example 1: Integration

sp.integrate(x**2 * sp.sin(x), x)

Example 2: Basic Algebra

sp.expand((x + y + z)**4)

Example 3: Plotting

t_vals = np.linspace(0, 4 * np.pi, 500)
wave1 = np.sin(t_vals)
wave2 = np.sin(1.1 * t_vals)
interference = wave1 + wave2

plt.figure(figsize=(8, 4))
plt.plot(t_vals, interference, color='crimson', linewidth=2,
label='Beat Frequency')
plt.fill_between(t_vals, interference, color='crimson', alpha=0.2)

plt.title("Wave Interference (Beats)", fontsize=16)
plt.grid(True, linestyle='--', alpha=0.6)
plt.legend()

Example 4: Series and Limits

sp.series(sp.sin(x),x)
sp.limit(sp.sin(x)/x,x,0)

Example 5: ODE

# No imports needed!
ode = sp.Eq(y.diff(x, x) + y, 0)
sp.dsolve(ode, y)

For more example see sympy and matplotlib tutorials.

Author

K.A.Rousan