Skip to main content

A volume modeler computation-oriented. Include rendering bindings.

Project description


Volmdlr

A computations-oriented python VOLume MoDeLeR with STEP support for import and export

Description

Volmdlr is a python volume modeler used as a CAD platform. With it, you can easily create 3D models from python code. Check the examples to see what you can do with this library.

A casing is defined by a 2D contour formed with the primitive RoundedLineSegment2D. This contour is offset by the casing width.


A Sweep is pipes, created with Circle2D/Arc2D which is contained in a Contour2D. You have to create the neutral fiber, i.e., the pipe’s road, with the primitive RoundedLineSegment3D.


A polygon is defined out of points. Random points are sampled and the tested whether they are inside or outside the polygon. They are plotted with the Matplotlib binding MPLPlot with custom styles: - red if they are outside, - blue if they are inside


A 3D B-spline surface split by a 3D B-spline curve.


Features

  • Generate 2D and 3D geometries from python
  • Handles complexe geometries : B-spline curves and surfaces
  • Primitives provide computational tasks : distances, belonging, union, intersections, etc.
  • STEP/STL imports and exports
  • Geometries display in your web browser with babylon.js

User Installation

pip install volmdlr
# or
pip3 install volmdlr

Dev Installation

Before using Volmdlr, be sure to have a C/C++ compiler (not necessary on Linux).
N.B : With Windows you have to download one and allow it to read Python’s code.

First, clone the package. Then, enter the newly created volmdlr repository. Finally, develop the setup.py file, and you are good to go !

git clone https://github.com/Dessia-tech/volmdlr.git

cd volmdlr

python3 setup.py develop --user
# or whatever version you are using :
python3.x setup.py develop --user

Usage

See the script folder for examples

Documentation

https://documentation.dessia.tech/volmdlr/

License

100% opensource on LGPL license. See LICENSE for more details.

Team and contributors

The project leader is Wirajan Da Silva. Volmdlr is mainly developed by the dessia company as a part of its opensource SDK, but contributions are welcomed. See CONTRIBUTING.md for details

Project details


Release history Release notifications | RSS feed

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distributions

No source distribution files available for this release.See tutorial on generating distribution archives.

Built Distributions

volmdlr-0.15.2-pp310-pypy310_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (2.8 MB view details)

Uploaded PyPy manylinux: glibc 2.17+ x86-64

volmdlr-0.15.2-pp310-pypy310_pp73-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl (2.8 MB view details)

Uploaded PyPy manylinux: glibc 2.17+ i686 manylinux: glibc 2.5+ i686

volmdlr-0.15.2-pp310-pypy310_pp73-macosx_10_9_x86_64.whl (2.7 MB view details)

Uploaded PyPy macOS 10.9+ x86-64

volmdlr-0.15.2-pp39-pypy39_pp73-win_amd64.whl (3.1 MB view details)

Uploaded PyPy Windows x86-64

volmdlr-0.15.2-pp39-pypy39_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (2.8 MB view details)

Uploaded PyPy manylinux: glibc 2.17+ x86-64

volmdlr-0.15.2-pp39-pypy39_pp73-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl (2.8 MB view details)

Uploaded PyPy manylinux: glibc 2.17+ i686 manylinux: glibc 2.5+ i686

volmdlr-0.15.2-pp39-pypy39_pp73-macosx_10_9_x86_64.whl (2.7 MB view details)

Uploaded PyPy macOS 10.9+ x86-64

volmdlr-0.15.2-cp311-cp311-win_amd64.whl (3.2 MB view details)

Uploaded CPython 3.11 Windows x86-64

volmdlr-0.15.2-cp311-cp311-win32.whl (3.1 MB view details)

Uploaded CPython 3.11 Windows x86

volmdlr-0.15.2-cp311-cp311-musllinux_1_1_x86_64.whl (9.2 MB view details)

Uploaded CPython 3.11 musllinux: musl 1.1+ x86-64

volmdlr-0.15.2-cp311-cp311-musllinux_1_1_i686.whl (8.9 MB view details)

Uploaded CPython 3.11 musllinux: musl 1.1+ i686

volmdlr-0.15.2-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (8.7 MB view details)

Uploaded CPython 3.11 manylinux: glibc 2.17+ x86-64

volmdlr-0.15.2-cp311-cp311-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl (8.4 MB view details)

Uploaded CPython 3.11 manylinux: glibc 2.17+ i686 manylinux: glibc 2.5+ i686

volmdlr-0.15.2-cp311-cp311-macosx_10_9_x86_64.whl (2.9 MB view details)

Uploaded CPython 3.11 macOS 10.9+ x86-64

volmdlr-0.15.2-cp310-cp310-win_amd64.whl (3.2 MB view details)

Uploaded CPython 3.10 Windows x86-64

volmdlr-0.15.2-cp310-cp310-win32.whl (3.1 MB view details)

Uploaded CPython 3.10 Windows x86

volmdlr-0.15.2-cp310-cp310-musllinux_1_1_x86_64.whl (8.7 MB view details)

Uploaded CPython 3.10 musllinux: musl 1.1+ x86-64

volmdlr-0.15.2-cp310-cp310-musllinux_1_1_i686.whl (8.4 MB view details)

Uploaded CPython 3.10 musllinux: musl 1.1+ i686

volmdlr-0.15.2-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (8.2 MB view details)

Uploaded CPython 3.10 manylinux: glibc 2.17+ x86-64

volmdlr-0.15.2-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl (7.9 MB view details)

Uploaded CPython 3.10 manylinux: glibc 2.17+ i686 manylinux: glibc 2.5+ i686

volmdlr-0.15.2-cp310-cp310-macosx_10_9_x86_64.whl (2.9 MB view details)

Uploaded CPython 3.10 macOS 10.9+ x86-64

volmdlr-0.15.2-cp39-cp39-win_amd64.whl (3.2 MB view details)

Uploaded CPython 3.9 Windows x86-64

volmdlr-0.15.2-cp39-cp39-win32.whl (3.1 MB view details)

Uploaded CPython 3.9 Windows x86

volmdlr-0.15.2-cp39-cp39-musllinux_1_1_x86_64.whl (8.7 MB view details)

Uploaded CPython 3.9 musllinux: musl 1.1+ x86-64

volmdlr-0.15.2-cp39-cp39-musllinux_1_1_i686.whl (8.5 MB view details)

Uploaded CPython 3.9 musllinux: musl 1.1+ i686

volmdlr-0.15.2-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (8.3 MB view details)

Uploaded CPython 3.9 manylinux: glibc 2.17+ x86-64

volmdlr-0.15.2-cp39-cp39-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl (7.9 MB view details)

Uploaded CPython 3.9 manylinux: glibc 2.17+ i686 manylinux: glibc 2.5+ i686

volmdlr-0.15.2-cp39-cp39-macosx_10_9_x86_64.whl (2.9 MB view details)

Uploaded CPython 3.9 macOS 10.9+ x86-64

File details

Details for the file volmdlr-0.15.2-pp310-pypy310_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for volmdlr-0.15.2-pp310-pypy310_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 61806cf35317e0a52b2c49a670c8c4633b04f378e8c8380d612da3f55568d39a
MD5 16a1cb716e7b095bf621928ab25a6006
BLAKE2b-256 4b18359b65a3794d39d90209bcf375b93674ea676e51d3976bbf6a6a78a1c229

See more details on using hashes here.

File details

Details for the file volmdlr-0.15.2-pp310-pypy310_pp73-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl.

File metadata

File hashes

Hashes for volmdlr-0.15.2-pp310-pypy310_pp73-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl
Algorithm Hash digest
SHA256 c84d3d9521730355262f6905fb30c26057d50f8a95bb18172ac144d9c31ee118
MD5 75abdb1d4ac6819e09dc5a21843744c1
BLAKE2b-256 b25314ad004e8c1e07bb6576ce141e371aa358bf3445eed01da8e78dc733d110

See more details on using hashes here.

File details

Details for the file volmdlr-0.15.2-pp310-pypy310_pp73-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for volmdlr-0.15.2-pp310-pypy310_pp73-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 bc62bfc2403b3b1167ae50e3604b4ae080c749d9c9347de7719cd286cfb03bf3
MD5 1ad9f85ef8433dfea885e47c5a58b2f3
BLAKE2b-256 b84a6bf687c5acb552f1d5858bc1b555fa0891573a692d7ec5e4eb3cf4539e90

See more details on using hashes here.

File details

Details for the file volmdlr-0.15.2-pp39-pypy39_pp73-win_amd64.whl.

File metadata

File hashes

Hashes for volmdlr-0.15.2-pp39-pypy39_pp73-win_amd64.whl
Algorithm Hash digest
SHA256 21ba161c1d8d7fcba89677678e63bac5f583c486853b5fdae27fdc83ebd1b004
MD5 b81a77c56c4c01458e65e73f81d64dc3
BLAKE2b-256 a0af7fbb38368b1daa57dc0c68bdaadf90892ee2baf7b3f9d849f7387ea52e0c

See more details on using hashes here.

File details

Details for the file volmdlr-0.15.2-pp39-pypy39_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for volmdlr-0.15.2-pp39-pypy39_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 d472980291eefc219dac523a6a8624022390dfea6866edc1cd9451df0c2d8760
MD5 2034f79744ff047eacffb73eadbd4977
BLAKE2b-256 8f659875d87241fdcff3fabf93d3b2a11002c385f5428d8a3972111bc5556450

See more details on using hashes here.

File details

Details for the file volmdlr-0.15.2-pp39-pypy39_pp73-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl.

File metadata

File hashes

Hashes for volmdlr-0.15.2-pp39-pypy39_pp73-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl
Algorithm Hash digest
SHA256 64016805b9429107f172b7b95ab6348be97298a810bac0ee4af568cf4ec9c636
MD5 de5af709df687eae378b4c3907b33150
BLAKE2b-256 dbd601d0faf580b53473b233943918579a4889559b53115258702b17575d31bd

See more details on using hashes here.

File details

Details for the file volmdlr-0.15.2-pp39-pypy39_pp73-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for volmdlr-0.15.2-pp39-pypy39_pp73-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 5eecae4ff5834a008c8881d96a23f8c7cecbae6e22a2f535349cdb7eced448ad
MD5 c08349734b2f344d30e27181a9686897
BLAKE2b-256 90ccfffc81ea1cd915f5e768c83bdfa398e070ec40ec5950c503a6b3d2c7d21a

See more details on using hashes here.

File details

Details for the file volmdlr-0.15.2-cp311-cp311-win_amd64.whl.

File metadata

File hashes

Hashes for volmdlr-0.15.2-cp311-cp311-win_amd64.whl
Algorithm Hash digest
SHA256 4a2e24121eb5f169341dedcb102c6f20f212f655e6413313d83a5016ca2bd783
MD5 9deef5c380f10d9abe6c288b2a7057af
BLAKE2b-256 01b7a2301c46e6f62eeef210a2ac00194d2173ff90426a05cc7e4d47de0495c4

See more details on using hashes here.

File details

Details for the file volmdlr-0.15.2-cp311-cp311-win32.whl.

File metadata

  • Download URL: volmdlr-0.15.2-cp311-cp311-win32.whl
  • Upload date:
  • Size: 3.1 MB
  • Tags: CPython 3.11, Windows x86
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.9.18

File hashes

Hashes for volmdlr-0.15.2-cp311-cp311-win32.whl
Algorithm Hash digest
SHA256 923aa8ae4e6985809e588467ce90137924490f1791b0746a909dc9c3889c22d9
MD5 29017f361dcc4044c6eb09ae9da9f486
BLAKE2b-256 3576e8c1e31ebf17db78a246b3dd2eb7372841dfc7f83dd6380aa34c48a0a1da

See more details on using hashes here.

File details

Details for the file volmdlr-0.15.2-cp311-cp311-musllinux_1_1_x86_64.whl.

File metadata

File hashes

Hashes for volmdlr-0.15.2-cp311-cp311-musllinux_1_1_x86_64.whl
Algorithm Hash digest
SHA256 b39415780a73b1114b26b0916393f3ec5f7693ab0c18076a776fd7c76196adb0
MD5 697c6d07de81102d3a4ad8bf6def6d02
BLAKE2b-256 c53d2130ff5277375b211f87287d9d2a47f1d76a9480539b34104bddc9cf3be1

See more details on using hashes here.

File details

Details for the file volmdlr-0.15.2-cp311-cp311-musllinux_1_1_i686.whl.

File metadata

File hashes

Hashes for volmdlr-0.15.2-cp311-cp311-musllinux_1_1_i686.whl
Algorithm Hash digest
SHA256 93f1cab1d022cea0f93ea89b5314507498d27139a9fe3ec49cc83ef3515aae3f
MD5 c623ac668a19f56031a1d56172378d65
BLAKE2b-256 f15648cff4dc259438efa1212287391124fd29fb6548d3ba335bda2d2c1e24d9

See more details on using hashes here.

File details

Details for the file volmdlr-0.15.2-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for volmdlr-0.15.2-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 96889c1aba5e3265ff6d838cac5f08d9ae0d890bbad69c56553d0c7b73ec2153
MD5 f32ffceda6112ae391e28b21c143e030
BLAKE2b-256 d7170e29d67123da4f268ba91c9b8953d3c58efb4aa4e6da13c21be7b6336b5a

See more details on using hashes here.

File details

Details for the file volmdlr-0.15.2-cp311-cp311-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl.

File metadata

File hashes

Hashes for volmdlr-0.15.2-cp311-cp311-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl
Algorithm Hash digest
SHA256 760c45b1ff7f32066fadc4d6f0d090701d949c645ea27c665f21b09af00664e8
MD5 be7027dd0b9ba2a07bba5273814fdc01
BLAKE2b-256 d8d97a36b1bd4c45dd9c3a06681ffbda49b72cf16a8bb686168d1398ab24da21

See more details on using hashes here.

File details

Details for the file volmdlr-0.15.2-cp311-cp311-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for volmdlr-0.15.2-cp311-cp311-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 f98ef4cdaaf6297a0a59c213c84f9719c14aad21ddb81f20822945a0bc7f2db9
MD5 8a1f83e233f2b9f02f9265ee4046f456
BLAKE2b-256 9c3c05a2acb21e363c03e559598604b9f341473660778e37f0a78faf502f2943

See more details on using hashes here.

File details

Details for the file volmdlr-0.15.2-cp310-cp310-win_amd64.whl.

File metadata

File hashes

Hashes for volmdlr-0.15.2-cp310-cp310-win_amd64.whl
Algorithm Hash digest
SHA256 2023ede774dd33ccc3cb60e4abaeb227bbaa0d5e3d07834bc4e9b80ea5354310
MD5 accd79942ac3733979bb2825e5207fae
BLAKE2b-256 04e3abf250cdb30eed1b3f302b614dcc8c1b9ec2db32d76c24f72eba594115c4

See more details on using hashes here.

File details

Details for the file volmdlr-0.15.2-cp310-cp310-win32.whl.

File metadata

  • Download URL: volmdlr-0.15.2-cp310-cp310-win32.whl
  • Upload date:
  • Size: 3.1 MB
  • Tags: CPython 3.10, Windows x86
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.9.18

File hashes

Hashes for volmdlr-0.15.2-cp310-cp310-win32.whl
Algorithm Hash digest
SHA256 910dff3ce81776e1a412b2e0d22f97c3621ddab22d410c036520a82e994593a0
MD5 bc91753e3e9aa0caa502a7e7b16ccc53
BLAKE2b-256 64c49143d0687f7d3ae39cda9555fb22f3cd4566c3b3de3069d032f290c7b0d8

See more details on using hashes here.

File details

Details for the file volmdlr-0.15.2-cp310-cp310-musllinux_1_1_x86_64.whl.

File metadata

File hashes

Hashes for volmdlr-0.15.2-cp310-cp310-musllinux_1_1_x86_64.whl
Algorithm Hash digest
SHA256 88fe84b2b4966877d90aaed2cefc938798ef745a249499a51414b3188914ea26
MD5 ba1468f30e5564b6c82abaa9c7067a2a
BLAKE2b-256 732fef6e35c7cfe44cc5f54647b3bfc5f2e97f8496e8d07ca1f8c87c180768c5

See more details on using hashes here.

File details

Details for the file volmdlr-0.15.2-cp310-cp310-musllinux_1_1_i686.whl.

File metadata

File hashes

Hashes for volmdlr-0.15.2-cp310-cp310-musllinux_1_1_i686.whl
Algorithm Hash digest
SHA256 4ea5174ca03eb1c532825bb01a0f9fcd04c5b756ceeeadc4cf178a1a0d39d833
MD5 b97b0fe066f1e56063c63af309a9456e
BLAKE2b-256 baa4883de6f2460f8513b4162b656a73c0e8b4425ea4443076c54e16be809d9a

See more details on using hashes here.

File details

Details for the file volmdlr-0.15.2-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for volmdlr-0.15.2-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 4c3c9af4f945551de9d7fad671380b622c9a1807a5978cc8bb14c99956c96180
MD5 5afe30bc031922d3dfaa386bd542fa0e
BLAKE2b-256 bf038c3ebd989119125375465983abbd173ab3a21e71bd1de7fe69e88bb1dae2

See more details on using hashes here.

File details

Details for the file volmdlr-0.15.2-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl.

File metadata

File hashes

Hashes for volmdlr-0.15.2-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl
Algorithm Hash digest
SHA256 6f4b45421457b6fa50f473e3266155a17276ade811c68fb6a42eeb04b399525c
MD5 2c7342d72cf2bba6897b010e39067e72
BLAKE2b-256 66dc9da2e7d49bf2f12abddde365ef14de22c5eff43ab05653645fce03214265

See more details on using hashes here.

File details

Details for the file volmdlr-0.15.2-cp310-cp310-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for volmdlr-0.15.2-cp310-cp310-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 5c4b8a6b66a3b233a51be872e71651d4f689ee4cd9a19c401ccc085f2f30e49a
MD5 81e5abb78c3a440044ddb0ef4eff4b26
BLAKE2b-256 5358acd730065eefb5e77339ed5a19b0014fe72c9a81575f539b88d930f96835

See more details on using hashes here.

File details

Details for the file volmdlr-0.15.2-cp39-cp39-win_amd64.whl.

File metadata

  • Download URL: volmdlr-0.15.2-cp39-cp39-win_amd64.whl
  • Upload date:
  • Size: 3.2 MB
  • Tags: CPython 3.9, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.9.18

File hashes

Hashes for volmdlr-0.15.2-cp39-cp39-win_amd64.whl
Algorithm Hash digest
SHA256 a9420591beb97bb673b7de39800a092db49f730a12e354381db948ffd9b98e5f
MD5 01c2b82456ecb0cbd4699a4295f201c1
BLAKE2b-256 e268beb07009ba2cb9940abd67dd00b2d6ffaed04319c07a8edd3ac20a0b6fb0

See more details on using hashes here.

File details

Details for the file volmdlr-0.15.2-cp39-cp39-win32.whl.

File metadata

  • Download URL: volmdlr-0.15.2-cp39-cp39-win32.whl
  • Upload date:
  • Size: 3.1 MB
  • Tags: CPython 3.9, Windows x86
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.9.18

File hashes

Hashes for volmdlr-0.15.2-cp39-cp39-win32.whl
Algorithm Hash digest
SHA256 4f0023f163f351be8a61d76893589d260bf37df1aaf30ec880e3f0a9b69b2284
MD5 5ffc4fff1b35047407f107744b4ce225
BLAKE2b-256 bbdfa186f8161de31fcbd673b9c8ab9cfb286fd8b3419e79266987c0da1fbb4e

See more details on using hashes here.

File details

Details for the file volmdlr-0.15.2-cp39-cp39-musllinux_1_1_x86_64.whl.

File metadata

File hashes

Hashes for volmdlr-0.15.2-cp39-cp39-musllinux_1_1_x86_64.whl
Algorithm Hash digest
SHA256 7ed71e24f6404fe71ca9c9698c0507a5414809d6885786997d36e12ca2098615
MD5 3e3abc7c464b18c5335e0dd1bb8d37ba
BLAKE2b-256 1264c144bcd456cf7612a49ef829079fe6b6aeed76d07d6caff649bf6f364dcd

See more details on using hashes here.

File details

Details for the file volmdlr-0.15.2-cp39-cp39-musllinux_1_1_i686.whl.

File metadata

File hashes

Hashes for volmdlr-0.15.2-cp39-cp39-musllinux_1_1_i686.whl
Algorithm Hash digest
SHA256 5c113ef71e3858807378d5d0135968a31b1a0bb7754803aa8fd03cbef924c346
MD5 fb2402173d91af3991bfd0f597850379
BLAKE2b-256 a21b7a4c1adfa379868466b64aea0b5f87056feb96f7bcf12b7453823289135c

See more details on using hashes here.

File details

Details for the file volmdlr-0.15.2-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for volmdlr-0.15.2-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 88b39e2853567245f5100fa9568634daa54d68cadd7dfcaf5e4eccf93fd830b7
MD5 3b803e51f6938d70e8511547f048a420
BLAKE2b-256 8d1b8a748ed56e7aabfbbb5eb6e7c58b77417c4ef0b9c0417988995b2e34455a

See more details on using hashes here.

File details

Details for the file volmdlr-0.15.2-cp39-cp39-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl.

File metadata

File hashes

Hashes for volmdlr-0.15.2-cp39-cp39-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl
Algorithm Hash digest
SHA256 d342c62a05a4717d7fe6cab4f85eeee97e37735e2cb15aa7db63a77a10c91d0d
MD5 6c1aeaba0b864355ef300a6f1cb3a79c
BLAKE2b-256 8363ec4a60f262b13564e15cfe7e69ac63450f268290f9bc127a58936cbbab42

See more details on using hashes here.

File details

Details for the file volmdlr-0.15.2-cp39-cp39-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for volmdlr-0.15.2-cp39-cp39-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 b994498c5299832ce89274557fad8b4fe031b6c4ec32781758ba42c8f474d207
MD5 172fa5c8c0a8162ba217dcb69e10b041
BLAKE2b-256 7dc4bc08acbc3da1c3a0adafa7c48499095fd57623dff806d06e9f60fe8efec9

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page