numpy-stl 4.0.0

Library to make reading, writing and modifying both binary and ascii STL files easy.

A fast library for reading, writing, and modifying STL files, powered by NumPy. Every mesh operation uses vectorized array math for speed.

Stanford Dragon — 871,414 triangles loaded in 0.63s, rendered with matplotlib

Quick Start

pip install numpy-stl

from stl import mesh

# Load an STL file (auto-detects binary/ASCII)
your_mesh = mesh.Mesh.from_file('model.stl')

# Inspect
print(f'{len(your_mesh)} triangles')
print(f'Bounding box: {your_mesh.min_} to {your_mesh.max_}')

# Save
your_mesh.save('output.stl')

Features

• Read and write binary and ASCII STL files
• Read PLY and 3MF files (3MF is experimental, read-only)
• Mesh operations: rotate, translate, transform (4x4 matrix)
• Properties: surface area, volume, center of gravity, inertia tensor, convexity
• Combine multiple meshes by concatenating data arrays
• CLI tools: stl, stl2ascii, stl2bin for format conversion
• Fast: all operations backed by NumPy vectorized math

Supported Formats

Format	Read	Write	Notes
STL (binary)	✅	✅	Auto-detected on load
STL (ASCII)	✅	✅	~5x faster with optional speedups
PLY	✅	✅	Binary and ASCII; from_ply_file / save_ply
3MF	✅	—	Experimental; from_3mf_file

Requirements & Compatibility

• Python: 3.10+
• NumPy: 1.24+ (installed automatically)
• Platforms: Linux, macOS, Windows
• Optional: numpy-stl[fast] for the Cython ASCII speedups (see below)

Performance / Optional Speedups

numpy-stl is fast out of the box. For even faster ASCII STL I/O, install the optional Cython speedups:

pip install numpy-stl[fast]

This installs the speedups package, a compiled C extension for ASCII parsing. The library works identically without it -- pure Python is the default.

Benchmark

ASCII STL read performance — ~5x faster with the speedups C extension, consistent across data sizes (median of 5 runs):

Facets	Pure Python	Speedups	Factor
10,000	36 ms	7 ms	5.1x
100,000	0.36 s	73 ms	4.9x
871,414	3.10 s	0.59 s	5.2x
1,000,000	3.60 s	0.73 s	4.9x

Note: Results will vary by hardware. Run the benchmark yourself: python benchmarks/benchmark_ascii_read.py

Usage Examples

Creating a Mesh from Scratch

import numpy as np
from stl import mesh

# Define vertices and faces of a cube
vertices = np.array([
    [-1, -1, -1], [+1, -1, -1], [+1, +1, -1], [-1, +1, -1],
    [-1, -1, +1], [+1, -1, +1], [+1, +1, +1], [-1, +1, +1],
])
faces = np.array([
    [0, 3, 1], [1, 3, 2], [0, 4, 7], [0, 7, 3],
    [4, 5, 6], [4, 6, 7], [5, 1, 2], [5, 2, 6],
    [2, 3, 6], [3, 7, 6], [0, 1, 5], [0, 5, 4],
])

cube = mesh.Mesh(np.zeros(faces.shape[0], dtype=mesh.Mesh.dtype))
for i, f in enumerate(faces):
    for j in range(3):
        cube.vectors[i][j] = vertices[f[j], :]

cube.save('cube.stl')

Rotating and Translating

import math
from stl import mesh

m = mesh.Mesh.from_file('model.stl')
m.rotate([0, 0, 1], math.radians(90))
m.translate([10, 0, 0])
m.save('transformed.stl')

Mass Properties

from stl import mesh

m = mesh.Mesh.from_file('closed_model.stl')
volume, cog, inertia = m.get_mass_properties()
print(f'Volume: {volume:.4f}')
print(f'Center of gravity: {cog}')

Combining Meshes

import numpy as np
from stl import mesh

m1 = mesh.Mesh.from_file('part1.stl')
m2 = mesh.Mesh.from_file('part2.stl')
combined = mesh.Mesh(np.concatenate([m1.data, m2.data]))
combined.save('combined.stl')

Plotting with Matplotlib

import math
from stl import mesh
from mpl_toolkits import mplot3d
from matplotlib import pyplot

figure = pyplot.figure(figsize=(8, 6))
axes = figure.add_subplot(projection='3d')

dragon = mesh.Mesh.from_ply_file('dragon_vrip.ply')
dragon.rotate([1, 0, 0], math.radians(-90))

axes.add_collection3d(
    mplot3d.art3d.Poly3DCollection(dragon.vectors)
)

scale = dragon.points.flatten()
axes.auto_scale_xyz(scale, scale, scale)
pyplot.show()

API Cheatsheet

Assumes import math, import numpy as np, from stl import mesh, and from stl import Mode (for the ASCII save).

Task	Call
Load (auto-detect)	mesh.Mesh.from_file('m.stl')
Load PLY	mesh.Mesh.from_ply_file('m.ply')
Load 3MF (experimental)	list(mesh.Mesh.from_3mf_file('m.3mf'))
Save (auto/format)	m.save('out.stl')
Save as ASCII	m.save('out.stl', mode=Mode.ASCII)
Save PLY	m.save_ply('out.ply')
Rotate (axis, radians)	m.rotate([0, 0, 1], math.radians(90))
Translate	m.translate([x, y, z])
Transform (4x4 matrix)	m.transform(matrix)
Bounding box	m.min_, m.max_
Mass properties	volume, cog, inertia = m.get_mass_properties()
With density	vol, mass, cog, inertia = m.get_mass_properties_with_density(d)
Combine meshes	mesh.Mesh(np.concatenate([a.data, b.data]))

CLI Tools

# Convert ASCII to binary
stl2bin input.stl output.stl

# Convert binary to ASCII
stl2ascii input.stl output.stl

# Auto-detect and convert
stl input.stl output.stl

Documentation

Full documentation is available at numpy-stl.readthedocs.io.

Contributing

Contributions are welcome! See CONTRIBUTING.md for the development setup guide.

Links

• Source code
• PyPI
• Bug reports
• Documentation
• Changelog

License

BSD-3-Clause