trimesh 4.9.0


pip install trimesh

  Latest version

Released: Oct 22, 2025


Meta
Author: Michael Dawson-Haggerty
Requires Python: >=3.8

Classifiers

Development Status
  • 4 - Beta

License
  • OSI Approved :: MIT License

Programming Language
  • Python
  • Python :: 3.8
  • Python :: 3.9
  • Python :: 3.10
  • Python :: 3.11
  • Python :: 3.12

Natural Language
  • English

Topic
  • Scientific/Engineering
  • Multimedia :: Graphics
  • Multimedia :: Graphics :: 3D Modeling

trimesh


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Trimesh is a pure Python 3.8+ library for loading and using triangular meshes with an emphasis on watertight surfaces. The goal of the library is to provide a full featured and well tested Trimesh object which allows for easy manipulation and analysis, in the style of the Polygon object in the Shapely library.

The API is mostly stable, but this should not be relied on and is not guaranteed: install a specific version if you plan on deploying something using trimesh.

Pull requests are appreciated and responded to promptly! If you'd like to contribute, here is an up to date list of potential enhancements although things not on that list are also welcome. Here's a quick development and contributing guide.

Basic Installation

Keeping trimesh easy to install is a core goal, thus the only hard dependency is numpy. Installing other packages adds functionality but is not required. For the easiest install with just numpy, pip can generally install trimesh cleanly on Windows, Linux, and OSX:

pip install trimesh

The minimal install can load many supported formats (STL, PLY, GLTF/GLB) into numpy arrays. More functionality is available when soft dependencies are installed. This includes things like convex hulls (scipy), graph operations (networkx), faster ray queries (embreex), vector path handling (shapely and rtree), XML formats like 3DXML/XAML/3MF (lxml), preview windows (pyglet), faster cache checks (xxhash), etc. To install trimesh with the soft dependencies that generally install cleanly on Linux (x86_64), MacOS (ARM), and Windows (x86_64) using pip:

pip install trimesh[easy]

If you are supporting a different platform or are freezing your dependencies we recommend you do not use the extras (i.e. depend on trimesh scipy versus trimesh[easy].) Further information is available in the advanced installation documentation.

Quick Start

Here is an example of loading a mesh from file and colorizing its faces. Here is a nicely formatted ipython notebook version of this example. Also check out the cross section example.

import numpy as np
import trimesh

# attach to logger so trimesh messages will be printed to console
trimesh.util.attach_to_log()

# mesh objects can be created from existing faces and vertex data
mesh = trimesh.Trimesh(vertices=[[0, 0, 0], [0, 0, 1], [0, 1, 0]],
                       faces=[[0, 1, 2]])

# by default, Trimesh will do a light processing, which will
# remove any NaN values and merge vertices that share position
# if you want to not do this on load, you can pass `process=False`
mesh = trimesh.Trimesh(vertices=[[0, 0, 0], [0, 0, 1], [0, 1, 0]],
                       faces=[[0, 1, 2]],
                       process=False)

# some formats represent multiple meshes with multiple instances
# the loader tries to return the datatype which makes the most sense
# which will for scene-like files will return a `trimesh.Scene` object.
# if you *always* want a straight `trimesh.Trimesh` you can ask the
# loader to "force" the result into a mesh through concatenation
mesh = trimesh.load('models/CesiumMilkTruck.glb', force='mesh')

# mesh objects can be loaded from a file name or from a buffer
# you can pass any of the kwargs for the `Trimesh` constructor
# to `trimesh.load`, including `process=False` if you would like
# to preserve the original loaded data without merging vertices
# STL files will be a soup of disconnected triangles without
# merging vertices however and will not register as watertight
mesh = trimesh.load('../models/featuretype.STL')

# is the current mesh watertight?
mesh.is_watertight

# what's the euler number for the mesh?
mesh.euler_number

# the convex hull is another Trimesh object that is available as a property
# lets compare the volume of our mesh with the volume of its convex hull
print(mesh.volume / mesh.convex_hull.volume)

# since the mesh is watertight, it means there is a
# volumetric center of mass which we can set as the origin for our mesh
mesh.vertices -= mesh.center_mass

# what's the moment of inertia for the mesh?
mesh.moment_inertia

# if there are multiple bodies in the mesh we can split the mesh by
# connected components of face adjacency
# since this example mesh is a single watertight body we get a list of one mesh
mesh.split()

# facets are groups of coplanar adjacent faces
# set each facet to a random color
# colors are 8 bit RGBA by default (n, 4) np.uint8
for facet in mesh.facets:
    mesh.visual.face_colors[facet] = trimesh.visual.random_color()

# preview mesh in an opengl window if you installed pyglet and scipy with pip
mesh.show()

# transform method can be passed a (4, 4) matrix and will cleanly apply the transform
mesh.apply_transform(trimesh.transformations.random_rotation_matrix())

# axis aligned bounding box is available
mesh.bounding_box.extents

# a minimum volume oriented bounding box also available
# primitives are subclasses of Trimesh objects which automatically generate
# faces and vertices from data stored in the 'primitive' attribute
mesh.bounding_box_oriented.primitive.extents
mesh.bounding_box_oriented.primitive.transform

# show the mesh appended with its oriented bounding box
# the bounding box is a trimesh.primitives.Box object, which subclasses
# Trimesh and lazily evaluates to fill in vertices and faces when requested
# (press w in viewer to see triangles)
(mesh + mesh.bounding_box_oriented).show()

# bounding spheres and bounding cylinders of meshes are also
# available, and will be the minimum volume version of each
# except in certain degenerate cases, where they will be no worse
# than a least squares fit version of the primitive.
print(mesh.bounding_box_oriented.volume,
      mesh.bounding_cylinder.volume,
      mesh.bounding_sphere.volume)

Features

  • Import meshes from binary/ASCII STL, Wavefront OBJ, ASCII OFF, binary/ASCII PLY, GLTF/GLB 2.0, 3MF, XAML, 3DXML, etc.
  • Import and export 2D or 3D vector paths from/to DXF or SVG files
  • Import geometry files using the GMSH SDK if installed (BREP, STEP, IGES, INP, BDF, etc)
  • Export meshes as binary STL, binary PLY, ASCII OFF, OBJ, GLTF/GLB 2.0, COLLADA, etc.
  • Export meshes using the GMSH SDK if installed (Abaqus INP, Nastran BDF, etc)
  • Preview meshes using pyglet or in- line in jupyter/marimo notebooks using three.js
  • Automatic hashing of numpy arrays for change tracking using MD5, zlib CRC, or xxhash
  • Internal caching of computed values validated from hashes
  • Calculate face adjacencies, face angles, vertex defects, etc.
  • Calculate cross sections, i.e. the slicing operation used in 3D printing
  • Slice meshes with one or multiple arbitrary planes and return the resulting surface
  • Split mesh based on face connectivity using networkx, graph-tool, or scipy.sparse
  • Calculate mass properties, including volume, center of mass, moment of inertia, principal components of inertia vectors and components
  • Repair simple problems with triangle winding, normals, and quad/tri holes
  • Convex hulls of meshes
  • Compute rotation/translation/tessellation invariant identifier and find duplicate meshes
  • Determine if a mesh is watertight, convex, etc.
  • Uniformly sample the surface of a mesh
  • Ray-mesh queries including location, triangle index, etc.
  • Boolean operations on meshes (intersection, union, difference) using Manifold3D or Blender Note that mesh booleans in general are usually slow and unreliable
  • Voxelize watertight meshes
  • Volume mesh generation (TETgen) using Gmsh SDK
  • Smooth watertight meshes using laplacian smoothing algorithms (Classic, Taubin, Humphrey)
  • Subdivide faces of a mesh
  • Approximate minimum volume oriented bounding boxes for meshes
  • Approximate minimum volume bounding spheres
  • Calculate nearest point on mesh surface and signed distance
  • Determine if a point lies inside or outside of a well constructed mesh using signed distance
  • Primitive objects (Box, Cylinder, Sphere, Extrusion) which are subclassed Trimesh objects and have all the same features (inertia, viewers, etc)
  • Simple scene graph and transform tree which can be rendered (pyglet window, three.js in a jupyter/marimo notebook, pyrender) or exported.
  • Many utility functions, like transforming points, unitizing vectors, aligning vectors, tracking numpy arrays for changes, grouping rows, etc.

Viewer

Trimesh includes an optional pyglet based viewer for debugging and inspecting. In the mesh view window, opened with mesh.show(), the following commands can be used:

  • mouse click + drag rotates the view
  • ctl + mouse click + drag pans the view
  • mouse wheel zooms
  • z returns to the base view
  • w toggles wireframe mode
  • c toggles backface culling
  • g toggles an XY grid with Z set to lowest point
  • a toggles an XYZ-RGB axis marker between: off, at world frame, or at every frame and world, and at every frame
  • f toggles between fullscreen and windowed mode
  • m maximizes the window
  • q closes the window

If called from inside a jupyter or marimo notebook, mesh.show() displays an in-line preview using three.js to display the mesh or scene. For more complete rendering (PBR, better lighting, shaders, better off-screen support, etc) pyrender is designed to interoperate with trimesh objects.

Projects Using Trimesh

You can check out the Github network for things using trimesh. A select few:

  • Nvidia's kaolin for deep learning on 3D geometry.
  • Cura, a popular slicer for 3D printing.
  • Berkeley's DexNet4 and related ambidextrous.ai work with robotic grasp planning and manipulation.
  • Kerfed's Kerfed's Engine for analyzing assembly geometry for manufacturing.
  • MyMiniFactory's P2Slice for preparing models for 3D printing.
  • pyrender A library to render scenes from Python using nice looking PBR materials.
  • urdfpy Load URDF robot descriptions in Python.
  • moderngl-window A helper to create GL contexts and load meshes.
  • vedo Visualize meshes interactively (see example gallery).
  • FSLeyes View MRI images and brain data.

Which Mesh Format Should I Use?

Quick recommendation: GLB or PLY. Every time you replace OBJ with GLB an angel gets its wings.

If you want things like by-index faces, instancing, colors, textures, etc, GLB is a terrific choice. GLTF/GLB is an extremely well specified modern format that is easy and fast to parse: it has a JSON header describing data in a binary blob. It has a simple hierarchical scene graph, a great looking modern physically based material system, support in dozens-to-hundreds of libraries, and a John Carmack endorsment. Note that GLTF is a large specification, and trimesh only supports a subset of features: loading basic geometry is supported, NOT supported are fancier things like animations, skeletons, etc.

In the wild, STL is perhaps the most common format. STL files are extremely simple: it is basically just a list of triangles. They are robust and are a good choice for basic geometry. Binary PLY files are a good step up, as they support indexed faces and colors.

Wavefront OBJ is also pretty common: unfortunately OBJ doesn't have a widely accepted specification so every importer and exporter implements things slightly differently, making it tough to support. It also allows unfortunate things like arbitrary sized polygons, has a face representation which is easy to mess up, references other files for materials and textures, arbitrarily interleaves data, and is slow to parse. Give GLB or PLY a try as an alternative!

How can I cite this library?

A question that comes up pretty frequently is how to cite the library. A quick BibTex recommendation:

@software{trimesh,
	author = {{Dawson-Haggerty et al.}},
	title = {trimesh},
	url = {https://trimesh.org/},
	version = {3.2.0},
	date = {2019-12-8},
}

Containers

If you want to deploy something in a container that uses trimesh automated debian:slim-bullseye based builds with trimesh and most dependencies are available on Docker Hub with image tags for latest, git short hash for the commit in main (i.e. trimesh/trimesh:0c1298d), and version (i.e. trimesh/trimesh:3.5.27):

docker pull trimesh/trimesh

Here's an example of how to render meshes using LLVMpipe and XVFB inside a container.

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2.35.43 Dec 02, 2018
2.35.42 Dec 01, 2018
2.35.41 Dec 01, 2018
2.35.40 Nov 29, 2018
2.35.39 Nov 28, 2018
2.35.38 Nov 28, 2018
2.35.37 Nov 27, 2018
2.35.36 Nov 25, 2018
2.35.35 Nov 25, 2018
2.35.34 Nov 24, 2018
2.35.33 Nov 22, 2018
2.35.32 Nov 21, 2018
2.35.30 Nov 15, 2018
2.35.29 Nov 15, 2018
2.35.28 Nov 13, 2018
2.35.27 Nov 13, 2018
2.35.26 Nov 10, 2018
2.35.25 Nov 09, 2018
2.35.24 Nov 07, 2018
2.35.23 Nov 07, 2018
2.35.21 Nov 05, 2018
2.35.18 Nov 03, 2018
2.35.17 Nov 01, 2018
2.35.15 Oct 31, 2018
2.35.14 Oct 31, 2018
2.35.13 Oct 26, 2018
2.35.12 Oct 26, 2018
2.35.11 Oct 26, 2018
2.35.10 Oct 22, 2018
2.35.9 Oct 22, 2018
2.35.7 Oct 19, 2018
2.35.6 Oct 18, 2018
2.35.5 Oct 14, 2018
2.35.4 Oct 14, 2018
2.35.3 Oct 13, 2018
2.35.2 Oct 09, 2018
2.35.1 Oct 07, 2018
2.35.0 Oct 07, 2018
2.34.16 Oct 06, 2018
2.34.15 Oct 06, 2018
2.34.14 Oct 05, 2018
2.34.13 Oct 04, 2018
2.34.12 Oct 04, 2018
2.34.9 Oct 04, 2018
2.34.8 Oct 03, 2018
2.34.7 Oct 02, 2018
2.34.4 Oct 02, 2018
2.34.3 Oct 02, 2018
2.34.2 Oct 01, 2018
2.33.43 Sep 28, 2018
2.33.42 Sep 28, 2018
2.33.41 Sep 26, 2018
2.33.40 Sep 25, 2018
2.33.39 Sep 23, 2018
2.33.38 Sep 23, 2018
2.33.37 Sep 19, 2018
2.33.36 Sep 19, 2018
2.33.34 Sep 15, 2018
2.33.33 Sep 15, 2018
2.33.30 Sep 12, 2018
2.33.29 Sep 11, 2018
2.33.28 Sep 11, 2018
2.33.27 Sep 10, 2018
2.33.26 Sep 08, 2018
2.33.25 Sep 07, 2018
2.33.23 Sep 06, 2018
2.33.22 Sep 06, 2018
2.33.21 Sep 06, 2018
2.33.19 Sep 05, 2018
2.33.18 Sep 05, 2018
2.33.17 Sep 04, 2018
2.33.15 Sep 03, 2018
2.33.14 Sep 03, 2018
2.33.12 Sep 03, 2018
2.33.11 Sep 03, 2018
2.33.7 Sep 02, 2018
2.33.4 Aug 31, 2018
2.33.3 Aug 28, 2018
2.33.2 Aug 28, 2018
2.33.1 Aug 28, 2018
2.33.0 Aug 28, 2018
2.32.13 Aug 27, 2018
2.32.11 Aug 26, 2018
2.32.10 Aug 23, 2018
2.32.8 Aug 20, 2018
2.32.6 Aug 20, 2018
2.32.5 Aug 14, 2018
2.32.4 Aug 14, 2018
2.32.3 Aug 11, 2018
2.32.1 Aug 09, 2018
2.32.0 Aug 07, 2018
2.31.54 Aug 06, 2018
2.31.52 Aug 05, 2018
2.31.51 Aug 05, 2018
2.31.50 Aug 03, 2018
2.31.49 Aug 02, 2018
2.31.48 Aug 01, 2018
2.31.47 Aug 01, 2018
2.31.46 Jul 30, 2018
2.31.45 Jul 30, 2018
2.31.44 Jul 30, 2018
2.31.43 Jul 28, 2018
2.31.42 Jul 26, 2018
2.31.39 Jul 25, 2018
2.31.38 Jul 23, 2018
2.31.37 Jul 23, 2018
2.31.36 Jul 21, 2018
2.31.34 Jul 21, 2018
2.31.33 Jul 20, 2018
2.31.32 Jul 20, 2018
2.31.31 Jul 20, 2018
2.31.29 Jul 20, 2018
2.31.28 Jul 20, 2018
2.31.27 Jul 20, 2018
2.31.26 Jul 18, 2018
2.31.25 Jul 11, 2018
2.31.24 Jul 09, 2018
2.31.23 Jul 09, 2018
2.31.22 Jul 08, 2018
2.31.21 Jul 08, 2018
2.31.20 Jul 06, 2018
2.31.19 Jul 06, 2018
2.31.18 Jul 06, 2018
2.31.17 Jul 04, 2018
2.31.16 Jul 04, 2018
2.31.15 Jun 30, 2018
2.31.14 Jun 30, 2018
2.31.13 Jun 30, 2018
2.31.12 Jun 29, 2018
2.31.11 Jun 29, 2018
2.31.9 Jun 27, 2018
2.31.8 Jun 26, 2018
2.31.7 Jun 25, 2018
2.31.6 Jun 24, 2018
2.31.5 Jun 24, 2018
2.31.4 Jun 24, 2018
2.31.2 Jun 23, 2018
2.31.1 Jun 23, 2018
2.30.62 Jun 20, 2018
2.30.61 Jun 20, 2018
2.30.58 Jun 19, 2018
2.30.57 Jun 18, 2018
2.30.55 Jun 17, 2018
2.30.54 Jun 15, 2018
2.30.53 Jun 15, 2018
2.30.52 Jun 14, 2018
2.30.51 Jun 14, 2018
2.30.50 Jun 13, 2018
2.30.49 Jun 13, 2018
2.30.46 Jun 11, 2018
2.30.45 Jun 11, 2018
2.30.44 Jun 11, 2018
2.30.43 Jun 08, 2018
2.30.42 Jun 08, 2018
2.30.41 Jun 08, 2018
2.30.40 Jun 08, 2018
2.30.39 Jun 06, 2018
2.30.38 Jun 06, 2018
2.30.37 Jun 05, 2018
2.30.36 Jun 05, 2018
2.30.35 Jun 04, 2018
2.30.33 Jun 04, 2018
2.30.32 Jun 04, 2018
2.30.31 Jun 04, 2018
2.30.30 May 31, 2018
2.30.28 May 30, 2018
2.30.27 May 30, 2018
2.30.26 May 30, 2018
2.30.25 May 30, 2018
2.30.22 May 30, 2018
2.30.21 May 28, 2018
2.30.20 May 28, 2018
2.30.18 May 28, 2018
2.30.16 May 22, 2018
2.30.14 May 18, 2018
2.30.11 May 15, 2018
2.30.9 May 10, 2018
2.30.8 May 09, 2018
2.30.2 May 08, 2018
2.30.1 May 08, 2018
2.29.32 May 07, 2018
2.29.30 May 05, 2018
2.29.28 May 02, 2018
2.29.27 Apr 30, 2018
2.29.26 Apr 28, 2018
2.29.25 Apr 27, 2018
2.29.24 Apr 27, 2018
2.29.22 Apr 24, 2018
2.29.21 Apr 24, 2018
2.29.20 Apr 23, 2018
2.29.19 Apr 23, 2018
2.29.18 Apr 23, 2018
2.29.17 Apr 21, 2018
2.29.16 Apr 19, 2018
2.29.14 Apr 18, 2018
2.29.12 Apr 17, 2018
2.29.10 Apr 16, 2018
2.29.9 Apr 13, 2018
2.29.8 Apr 12, 2018
2.29.7 Apr 12, 2018
2.29.5 Apr 11, 2018
2.29.4 Apr 11, 2018
2.29.3 Apr 11, 2018
2.29.2 Apr 11, 2018
2.29.1 Apr 10, 2018
2.29.0 Apr 09, 2018
2.28.32 Apr 05, 2018
2.28.31 Apr 04, 2018
2.28.30 Apr 02, 2018
2.28.29 Mar 29, 2018
2.28.28 Mar 29, 2018
2.28.27 Mar 29, 2018
2.28.26 Mar 28, 2018
2.28.25 Mar 28, 2018
2.28.24 Mar 28, 2018
2.28.23 Mar 27, 2018
2.28.22 Mar 26, 2018
2.28.20 Mar 25, 2018
2.28.19 Mar 25, 2018
2.28.18 Mar 25, 2018
2.28.16 Mar 23, 2018
2.28.14 Mar 23, 2018
2.28.13 Mar 23, 2018
2.28.12 Mar 22, 2018
2.28.11 Mar 22, 2018
2.28.9 Mar 22, 2018
2.28.8 Mar 21, 2018
2.28.7 Mar 21, 2018
2.28.3 Mar 19, 2018
2.27.0 Mar 15, 2018
2.26.24 Mar 12, 2018
2.26.23 Mar 12, 2018
2.26.22 Mar 11, 2018
2.26.18 Mar 06, 2018
2.26.17 Mar 06, 2018
2.26.16 Mar 01, 2018
2.26.15 Feb 28, 2018
2.26.13 Feb 28, 2018
2.26.12 Feb 23, 2018
2.26.11 Feb 22, 2018
2.26.10 Feb 21, 2018
2.26.9 Feb 18, 2018
2.26.8 Feb 16, 2018
2.26.7 Feb 16, 2018
2.26.6 Feb 16, 2018
2.26.5 Feb 14, 2018
2.26.4 Feb 14, 2018
2.26.3 Feb 14, 2018
2.26.2 Feb 13, 2018
2.26.1 Feb 10, 2018
2.26.0 Feb 09, 2018
2.25.5 Feb 06, 2018
2.25.4 Feb 06, 2018
2.25.3 Feb 05, 2018
2.25.2 Feb 02, 2018
2.25.1 Feb 02, 2018
2.24.18 Feb 01, 2018
2.24.17 Jan 31, 2018
2.24.16 Jan 30, 2018
2.24.15 Jan 30, 2018
2.24.14 Jan 30, 2018
2.24.12 Jan 30, 2018
2.24.10 Jan 30, 2018
2.24.9 Jan 25, 2018
2.24.8 Jan 24, 2018
2.24.4 Jan 24, 2018
2.24.3 Jan 23, 2018
2.24.2 Jan 22, 2018
2.22.27 Jan 16, 2018
2.22.26 Jan 12, 2018
2.22.25 Jan 10, 2018
2.22.24 Jan 10, 2018
2.22.23 Jan 10, 2018
2.22.22 Jan 10, 2018
2.22.14 Jan 07, 2018
2.22.13 Jan 07, 2018
2.22.11 Jan 05, 2018
2.22.10 Jan 04, 2018
2.22.9 Jan 04, 2018
2.22.8 Jan 04, 2018
2.22.6 Jan 03, 2018
2.22.5 Dec 31, 2017
2.22.4 Dec 30, 2017
2.22.3 Dec 27, 2017
2.22.0 Dec 22, 2017
2.21.36 Dec 22, 2017
2.21.34 Dec 19, 2017
2.21.33 Dec 18, 2017
2.21.31 Dec 17, 2017
2.21.30 Dec 15, 2017
2.21.29 Dec 15, 2017
2.21.28 Dec 15, 2017
2.21.27 Dec 15, 2017
2.21.26 Dec 14, 2017
2.21.25 Dec 14, 2017
2.21.24 Dec 14, 2017
2.21.23 Dec 14, 2017
2.21.22 Dec 14, 2017
2.21.21 Dec 14, 2017
2.21.20 Dec 13, 2017
2.21.18 Dec 11, 2017
2.21.17 Dec 10, 2017
2.21.16 Dec 09, 2017
2.21.15 Dec 06, 2017
2.21.14 Dec 06, 2017
2.21.13 Dec 06, 2017
2.21.12 Dec 06, 2017
2.21.11 Dec 05, 2017
2.21.10 Dec 04, 2017
2.21.9 Dec 02, 2017
2.21.7 Dec 02, 2017
2.21.6 Dec 01, 2017
2.21.5 Dec 01, 2017
2.21.4 Nov 30, 2017
2.21.3 Nov 29, 2017
2.21.1 Nov 29, 2017
2.21.0 Nov 26, 2017
2.20.29 Nov 21, 2017
2.20.28 Nov 21, 2017
2.20.26 Nov 21, 2017
2.20.25 Nov 20, 2017
2.20.24 Nov 20, 2017
2.20.23 Nov 20, 2017
2.20.21 Nov 15, 2017
2.20.20 Nov 13, 2017
2.20.19 Nov 13, 2017
2.20.18 Nov 13, 2017
2.20.17 Nov 12, 2017
2.20.16 Nov 11, 2017
2.20.15 Nov 11, 2017
2.20.14 Nov 10, 2017
2.20.12 Nov 09, 2017
2.20.11 Nov 07, 2017
2.20.10 Nov 03, 2017
2.20.8 Oct 27, 2017
2.20.7 Oct 27, 2017
2.20.6 Oct 23, 2017
2.20.5 Oct 21, 2017
2.20.2 Oct 14, 2017
2.20.1 Oct 14, 2017
2.19.6 Oct 11, 2017
2.19.4 Oct 10, 2017
2.19.3 Oct 09, 2017
2.19.2 Oct 09, 2017
2.19.1 Oct 09, 2017
2.18.6 Oct 03, 2017
2.18.5 Oct 03, 2017
2.18.4 Oct 03, 2017
2.18.3 Oct 03, 2017
2.18.1 Oct 03, 2017
2.18.0 Oct 03, 2017
2.17.0 Sep 30, 2017
2.16.3 Sep 29, 2017
2.16.1 Sep 29, 2017
2.16.0 Sep 28, 2017
2.15.1 Sep 20, 2017
2.14.20 Sep 05, 2017
2.14.17 Aug 27, 2017
2.14.16 Aug 27, 2017
2.14.15 Aug 27, 2017
2.14.14 Aug 27, 2017
2.14.13 Aug 24, 2017
2.14.12 Aug 22, 2017
2.14.10 Aug 12, 2017
2.14.9 Aug 07, 2017
2.14.8 Aug 05, 2017
2.14.7 Aug 04, 2017
2.14.5 Aug 03, 2017
2.14.4 Jul 24, 2017
2.14.2 Jul 18, 2017
2.13.15 Jul 06, 2017
2.13.14 Jul 04, 2017
2.13.13 Jul 04, 2017
2.13.12 Jun 27, 2017
2.13.11 Jun 19, 2017
2.13.10 Jun 19, 2017
2.13.9 Jun 16, 2017
2.13.8 Jun 10, 2017
2.13.7 Jun 10, 2017
2.13.5 Jun 10, 2017
2.13.4 Jun 06, 2017
2.13.3 Jun 02, 2017
2.13.2 Jun 02, 2017
2.13.1 May 29, 2017
2.12.2 May 29, 2017
2.12.0 May 28, 2017
2.11.1 May 27, 2017
2.11.0 May 22, 2017
2.10.18 May 17, 2017
2.10.17 May 16, 2017
2.10.16 May 15, 2017
2.10.14 May 14, 2017
2.10.13 May 09, 2017
2.10.12 Apr 27, 2017
2.10.11 Apr 27, 2017
2.10.10 Apr 24, 2017
2.10.9 Apr 24, 2017
2.10.8 Apr 12, 2017
2.10.6 Apr 11, 2017
2.10.5 Apr 09, 2017
2.10.4 Apr 02, 2017
2.10.3 Apr 01, 2017
2.10.1 Mar 28, 2017
2.10.0 Mar 25, 2017
2.9.4 Mar 20, 2017
2.9.3 Mar 18, 2017
2.9.2 Mar 18, 2017
2.8.5 Mar 12, 2017
2.8.4 Mar 12, 2017
2.8.3 Mar 11, 2017
2.8.2 Mar 11, 2017
2.8.1 Mar 11, 2017
2.8.0 Mar 11, 2017
2.7.24 Mar 06, 2017
2.7.22 Mar 05, 2017
2.7.21 Mar 05, 2017
2.7.20 Mar 05, 2017
2.7.18 Mar 02, 2017
2.7.16 Mar 01, 2017
2.7.15 Feb 27, 2017
2.7.14 Feb 25, 2017
2.7.12 Feb 25, 2017
2.7.11 Feb 24, 2017
2.7.10 Feb 23, 2017
2.7.8 Feb 23, 2017
2.7.7 Feb 22, 2017
2.7.6 Feb 20, 2017
2.7.5 Feb 20, 2017
2.7.4 Feb 18, 2017
2.7.3 Feb 18, 2017
2.7.2 Feb 17, 2017
2.7.0 Feb 16, 2017
2.6.2 Feb 15, 2017
2.5.36 Feb 13, 2017
2.5.35 Feb 12, 2017
2.5.34 Jan 29, 2017
2.5.33 Jan 26, 2017
2.5.32 Jan 21, 2017
2.5.31 Jan 19, 2017
2.5.30 Jan 18, 2017
2.5.28 Jan 14, 2017
2.5.27 Jan 12, 2017
2.5.26 Jan 12, 2017
2.5.25 Jan 08, 2017
2.5.24 Jan 08, 2017
2.5.23 Jan 08, 2017
2.5.22 Jan 07, 2017
2.5.21 Jan 06, 2017
2.5.20 Jan 06, 2017
2.5.19 Jan 06, 2017
2.5.18 Jan 04, 2017
2.5.17 Jan 03, 2017
2.5.15 Jan 03, 2017
2.5.14 Jan 02, 2017
2.5.12 Dec 31, 2016
2.5.11 Dec 31, 2016
2.5.10 Dec 31, 2016
2.5.9 Dec 30, 2016
2.5.8 Dec 30, 2016
2.5.7 Dec 26, 2016
2.5.6 Dec 24, 2016
2.5.5 Dec 24, 2016
2.4.6 Dec 21, 2016
2.4.4 Dec 19, 2016
2.4.1 Dec 19, 2016
2.3.13 Dec 11, 2016
2.3.12 Dec 09, 2016
2.3.11 Dec 09, 2016
2.3.10 Dec 07, 2016
2.3.9 Nov 29, 2016
2.3.8 Nov 27, 2016
2.3.7 Nov 23, 2016
2.3.6 Nov 20, 2016
2.3.5 Nov 18, 2016
2.3.3 Nov 16, 2016
2.3.2 Nov 16, 2016
2.3.0 Nov 13, 2016
2.2.17 Nov 12, 2016
2.2.16 Nov 11, 2016
2.2.15 Nov 03, 2016
2.2.14 Oct 31, 2016
2.2.13 Oct 31, 2016
2.2.12 Oct 29, 2016
2.2.11 Oct 14, 2016
2.2.10 Oct 12, 2016
2.2.9 Oct 12, 2016
2.2.8 Oct 10, 2016
2.2.7 Oct 04, 2016
2.2.6 Oct 02, 2016
2.2.5 Oct 01, 2016
2.2.4 Oct 01, 2016
2.2.2 Sep 30, 2016
2.2.1 Sep 22, 2016
2.2.0 Sep 22, 2016
2.1.15 Sep 21, 2016
2.1.14 Sep 20, 2016
2.1.13 Sep 19, 2016
2.1.12 Sep 16, 2016
2.1.11 Sep 15, 2016
2.1.10 Sep 15, 2016
2.1.9 Sep 15, 2016
2.1.8 Sep 15, 2016
2.1.7 Sep 15, 2016
2.1.6 Sep 12, 2016
2.1.5 Sep 10, 2016
2.1.4 Sep 09, 2016
2.1.3 Sep 09, 2016
2.1.2 Sep 07, 2016
2.1.1 Sep 07, 2016
2.0.8 Sep 03, 2016
2.0.7 Sep 02, 2016
2.0.6 Sep 01, 2016
2.0.5 Sep 01, 2016
2.0.4 Aug 31, 2016
2.0.3 Aug 30, 2016
2.0.2 Aug 29, 2016
2.0.1 Aug 28, 2016
1.16.1 Aug 27, 2016
1.16.0 Aug 25, 2016
1.15.16 Aug 20, 2016
1.15.15 Aug 18, 2016
1.15.14 Aug 14, 2016
1.15.13 Aug 09, 2016
1.15.12 Aug 07, 2016
1.15.11 Aug 06, 2016
1.15.10 Aug 06, 2016
1.15.9 Jul 30, 2016
1.15.8 Jul 16, 2016
1.15.7 Jul 16, 2016
1.15.6 Jul 14, 2016
1.15.5 Jul 11, 2016
1.15.4 Jul 04, 2016
1.15.3 Jul 04, 2016
1.15.1 Jul 04, 2016
1.15.0 Jul 02, 2016
1.14.20 Jun 28, 2016
1.14.19 Jun 27, 2016
1.14.18 Jun 26, 2016
1.14.14 Jun 25, 2016
1.14.13 Jun 25, 2016
1.14.12 Jun 24, 2016
1.14.11 Jun 13, 2016
1.14.10 Jun 11, 2016
1.14.9 Jun 06, 2016
1.14.8 Jun 05, 2016
1.14.7 Jun 04, 2016
1.14.6 Jun 04, 2016
1.14.5 May 29, 2016
1.14.4 May 23, 2016
1.14.3 May 21, 2016
1.14.2 May 19, 2016
1.14.1 May 15, 2016
1.14.0 May 14, 2016
1.13.1 May 11, 2016
1.13.0 May 09, 2016
1.12.13 Apr 25, 2016
1.12.12 Apr 24, 2016
1.12.11 Apr 23, 2016
1.12.10 Apr 22, 2016
1.12.9 Apr 20, 2016
1.12.8 Apr 13, 2016
1.12.7 Apr 03, 2016
1.12.6 Apr 02, 2016
1.12.5 Mar 31, 2016
1.12.4 Mar 31, 2016
1.12.3 Mar 26, 2016
1.12.2 Mar 24, 2016
1.12.1 Mar 18, 2016
1.12.0 Mar 17, 2016
1.11.16 Mar 17, 2016
1.11.15 Mar 15, 2016
1.11.12 Mar 07, 2016
1.11.11 Mar 04, 2016
1.11.10 Mar 03, 2016
1.11.9 Mar 01, 2016
1.11.8 Feb 23, 2016
1.11.7 Feb 21, 2016
1.11.6 Feb 21, 2016
1.11.5 Feb 17, 2016
1.11.4 Feb 16, 2016
1.11.3 Feb 15, 2016
1.11.2 Feb 13, 2016
1.11.1 Feb 13, 2016
1.11.0 Feb 13, 2016
1.10.1 Feb 11, 2016
1.10.0 Feb 10, 2016
1.9.22 Feb 07, 2016
1.9.21 Feb 04, 2016
1.9.20 Jan 31, 2016
1.9.19 Jan 24, 2016
1.9.18 Jan 23, 2016
1.9.17 Jan 23, 2016
1.9.16 Jan 17, 2016
1.9.15 Jan 13, 2016
1.9.14 Jan 11, 2016
1.9.13 Jan 10, 2016
1.9.12 Jan 10, 2016
1.9.11 Jan 10, 2016
1.9.10 Jan 10, 2016
1.9.7 Dec 02, 2015

Wheel compatibility matrix

Platform Python 3
any

Files in release

Extras:
Dependencies:
numpy (>=1.20)