Simple library to make working with STL files (and 3D objects in general) fast and easy.
Due to all operations heavily relying on numpy this is one of the fastest STL editing libraries for Python available.
To report a security vulnerability, please use the Tidelift security contact. Tidelift will coordinate the fix and disclosure.
If you encounter any issues, make sure you report them here. Be sure to search for existing issues however. Many issues have been covered before. While this project uses numpy as it's main dependency, it is not in any way affiliated to the numpy project or the NumFocus organisation.
- The source: https://github.com/WoLpH/numpy-stl
- Project page: https://pypi.python.org/pypi/numpy-stl
- Reporting bugs: https://github.com/WoLpH/numpy-stl/issues
- Documentation: http://numpy-stl.readthedocs.org/en/latest/
- My blog: https://wol.ph/
- numpy any recent version
- python-utils version 1.6 or greater
pip install numpy-stl
After installing the package, you should be able to run the following commands similar to how you can run pip.
$ stl2bin your_ascii_stl_file.stl new_binary_stl_file.stl
$ stl2ascii your_binary_stl_file.stl new_ascii_stl_file.stl
$ stl your_ascii_stl_file.stl new_binary_stl_file.stlContributions are always welcome. Please view the guidelines to get started: https://github.com/WoLpH/numpy-stl/blob/develop/CONTRIBUTING.rst
import numpy
from stl import mesh
# Using an existing stl file:
your_mesh = mesh.Mesh.from_file('some_file.stl')
# Or creating a new mesh (make sure not to overwrite the `mesh` import by
# naming it `mesh`):
VERTICE_COUNT = 100
data = numpy.zeros(VERTICE_COUNT, dtype=mesh.Mesh.dtype)
your_mesh = mesh.Mesh(data, remove_empty_areas=False)
# The mesh normals (calculated automatically)
your_mesh.normals
# The mesh vectors
your_mesh.v0, your_mesh.v1, your_mesh.v2
# Accessing individual points (concatenation of v0, v1 and v2 in triplets)
assert (your_mesh.points[0][0:3] == your_mesh.v0[0]).all()
assert (your_mesh.points[0][3:6] == your_mesh.v1[0]).all()
assert (your_mesh.points[0][6:9] == your_mesh.v2[0]).all()
assert (your_mesh.points[1][0:3] == your_mesh.v0[1]).all()
your_mesh.save('new_stl_file.stl')Plotting using matplotlib is equally easy:
from stl import mesh
from mpl_toolkits import mplot3d
from matplotlib import pyplot
# Create a new plot
figure = pyplot.figure()
axes = figure.add_subplot(projection='3d')
# Load the STL files and add the vectors to the plot
your_mesh = mesh.Mesh.from_file('tests/stl_binary/HalfDonut.stl')
axes.add_collection3d(mplot3d.art3d.Poly3DCollection(your_mesh.vectors))
# Auto scale to the mesh size
scale = your_mesh.points.flatten()
axes.auto_scale_xyz(scale, scale, scale)
# Show the plot to the screen
pyplot.show()import pathlib
import stl
path = pathlib.Path('tests/3mf/Moon.3mf')
# Load the 3MF file
for m in stl.Mesh.from_3mf_file(path):
# Do something with the mesh
print('mesh', m)Note that this is still experimental and may not work for all 3MF files. Additionally it only allows reading 3mf files, not writing them.
from stl import mesh
import math
import numpy
# Create 3 faces of a cube
data = numpy.zeros(6, dtype=mesh.Mesh.dtype)
# Top of the cube
data['vectors'][0] = numpy.array([[0, 1, 1],
[1, 0, 1],
[0, 0, 1]])
data['vectors'][1] = numpy.array([[1, 0, 1],
[0, 1, 1],
[1, 1, 1]])
# Front face
data['vectors'][2] = numpy.array([[1, 0, 0],
[1, 0, 1],
[1, 1, 0]])
data['vectors'][3] = numpy.array([[1, 1, 1],
[1, 0, 1],
[1, 1, 0]])
# Left face
data['vectors'][4] = numpy.array([[0, 0, 0],
[1, 0, 0],
[1, 0, 1]])
data['vectors'][5] = numpy.array([[0, 0, 0],
[0, 0, 1],
[1, 0, 1]])
# Since the cube faces are from 0 to 1 we can move it to the middle by
# substracting .5
data['vectors'] -= .5
# Generate 4 different meshes so we can rotate them later
meshes = [mesh.Mesh(data.copy()) for _ in range(4)]
# Rotate 90 degrees over the Y axis
meshes[0].rotate([0.0, 0.5, 0.0], math.radians(90))
# Translate 2 points over the X axis
meshes[1].x += 2
# Rotate 90 degrees over the X axis
meshes[2].rotate([0.5, 0.0, 0.0], math.radians(90))
# Translate 2 points over the X and Y points
meshes[2].x += 2
meshes[2].y += 2
# Rotate 90 degrees over the X and Y axis
meshes[3].rotate([0.5, 0.0, 0.0], math.radians(90))
meshes[3].rotate([0.0, 0.5, 0.0], math.radians(90))
# Translate 2 points over the Y axis
meshes[3].y += 2
# Optionally render the rotated cube faces
from matplotlib import pyplot
from mpl_toolkits import mplot3d
# Create a new plot
figure = pyplot.figure()
axes = figure.add_subplot(projection='3d')
# Render the cube faces
for m in meshes:
axes.add_collection3d(mplot3d.art3d.Poly3DCollection(m.vectors))
# Auto scale to the mesh size
scale = numpy.concatenate([m.points for m in meshes]).flatten()
axes.auto_scale_xyz(scale, scale, scale)
# Show the plot to the screen
pyplot.show()from stl import mesh
import math
import numpy
# Create 3 faces of a cube
data = numpy.zeros(6, dtype=mesh.Mesh.dtype)
# Top of the cube
data['vectors'][0] = numpy.array([[0, 1, 1],
[1, 0, 1],
[0, 0, 1]])
data['vectors'][1] = numpy.array([[1, 0, 1],
[0, 1, 1],
[1, 1, 1]])
# Front face
data['vectors'][2] = numpy.array([[1, 0, 0],
[1, 0, 1],
[1, 1, 0]])
data['vectors'][3] = numpy.array([[1, 1, 1],
[1, 0, 1],
[1, 1, 0]])
# Left face
data['vectors'][4] = numpy.array([[0, 0, 0],
[1, 0, 0],
[1, 0, 1]])
data['vectors'][5] = numpy.array([[0, 0, 0],
[0, 0, 1],
[1, 0, 1]])
# Since the cube faces are from 0 to 1 we can move it to the middle by
# substracting .5
data['vectors'] -= .5
cube_back = mesh.Mesh(data.copy())
cube_front = mesh.Mesh(data.copy())
# Rotate 90 degrees over the X axis followed by the Y axis followed by the
# X axis
cube_back.rotate([0.5, 0.0, 0.0], math.radians(90))
cube_back.rotate([0.0, 0.5, 0.0], math.radians(90))
cube_back.rotate([0.5, 0.0, 0.0], math.radians(90))
cube = mesh.Mesh(numpy.concatenate([
cube_back.data.copy(),
cube_front.data.copy(),
]))
# Optionally render the rotated cube faces
from matplotlib import pyplot
from mpl_toolkits import mplot3d
# Create a new plot
figure = pyplot.figure()
axes = figure.add_subplot(projection='3d')
# Render the cube
axes.add_collection3d(mplot3d.art3d.Poly3DCollection(cube.vectors))
# Auto scale to the mesh size
scale = cube_back.points.flatten()
axes.auto_scale_xyz(scale, scale, scale)
# Show the plot to the screen
pyplot.show()import numpy as np
from stl import mesh
# Define the 8 vertices of the 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]])
# Define the 12 triangles composing the cube
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]])
# Create the mesh
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],:]
# Write the mesh to file "cube.stl"
cube.save('cube.stl')import numpy as np
from stl import mesh
# Using an existing closed stl file:
your_mesh = mesh.Mesh.from_file('some_file.stl')
volume, cog, inertia = your_mesh.get_mass_properties()
print("Volume = {0}".format(volume))
print("Position of the center of gravity (COG) = {0}".format(cog))
print("Inertia matrix at expressed at the COG = {0}".format(inertia[0,:]))
print(" {0}".format(inertia[1,:]))
print(" {0}".format(inertia[2,:]))import math
import stl
from stl import mesh
import numpy
# find the max dimensions, so we can know the bounding box, getting the height,
# width, length (because these are the step size)...
def find_mins_maxs(obj):
minx = obj.x.min()
maxx = obj.x.max()
miny = obj.y.min()
maxy = obj.y.max()
minz = obj.z.min()
maxz = obj.z.max()
return minx, maxx, miny, maxy, minz, maxz
def translate(_solid, step, padding, multiplier, axis):
if 'x' == axis:
items = 0, 3, 6
elif 'y' == axis:
items = 1, 4, 7
elif 'z' == axis:
items = 2, 5, 8
else:
raise RuntimeError('Unknown axis %r, expected x, y or z' % axis)
# _solid.points.shape == [:, ((x, y, z), (x, y, z), (x, y, z))]
_solid.points[:, items] += (step * multiplier) + (padding * multiplier)
def copy_obj(obj, dims, num_rows, num_cols, num_layers):
w, l, h = dims
copies = []
for layer in range(num_layers):
for row in range(num_rows):
for col in range(num_cols):
# skip the position where original being copied is
if row == 0 and col == 0 and layer == 0:
continue
_copy = mesh.Mesh(obj.data.copy())
# pad the space between objects by 10% of the dimension being
# translated
if col != 0:
translate(_copy, w, w / 10., col, 'x')
if row != 0:
translate(_copy, l, l / 10., row, 'y')
if layer != 0:
translate(_copy, h, h / 10., layer, 'z')
copies.append(_copy)
return copies
# Using an existing stl file:
main_body = mesh.Mesh.from_file('ball_and_socket_simplified_-_main_body.stl')
# rotate along Y
main_body.rotate([0.0, 0.5, 0.0], math.radians(90))
minx, maxx, miny, maxy, minz, maxz = find_mins_maxs(main_body)
w1 = maxx - minx
l1 = maxy - miny
h1 = maxz - minz
copies = copy_obj(main_body, (w1, l1, h1), 2, 2, 1)
# I wanted to add another related STL to the final STL
twist_lock = mesh.Mesh.from_file('ball_and_socket_simplified_-_twist_lock.stl')
minx, maxx, miny, maxy, minz, maxz = find_mins_maxs(twist_lock)
w2 = maxx - minx
l2 = maxy - miny
h2 = maxz - minz
translate(twist_lock, w1, w1 / 10., 3, 'x')
copies2 = copy_obj(twist_lock, (w2, l2, h2), 2, 2, 1)
combined = mesh.Mesh(numpy.concatenate([main_body.data, twist_lock.data] +
[copy.data for copy in copies] +
[copy.data for copy in copies2]))
combined.save('combined.stl', mode=stl.Mode.ASCII) # save as ASCII
- When speedups are enabled the STL name is automatically converted to lowercase.
