Skip to main content

Convert STEP files to GLB using OpenCASCADE

Project description

cascadio

A Python library which uses OpenCASCADE to convert STEP files to a GLB file which can quickly be loaded by trimesh and other libraries.

The primary effort here is build and packaging using the wonderful work done recently on scikit-build-core and cibuildwheel. The goal is to produce wheels that don't require users to build OpenCASCADE themselves.

This is not intended to be a full binding of OpenCASCADE like OCP or PythonOCC. Rather it is intended to be an easy minimal way to load boundary representation files into a triangulated scene in Python. There are a few options for loading STEP geometry in the open-source ecosystem: GMSH, FreeCAD, etc. However nearly all of them use OpenCASCADE under the hood as it is pretty much the only open-source BREP kernel.

Install

The primary goal of this project is building wheels so vanilla pip can be used:

pip install cascadio

Currently this works on non-MUSL flavors of Linux, Windows x64, and MacOS x64+ARM. You can check PyPi for current platforms.

:warning: :warning: :warning: :warning:

PyPI has a size limit, and each release of this is large! We will not be keeping every release on PyPi (i.e. if we run out of space we delete versions) so be very careful pinning the version!

We'll keep the following versions as "LTS" style releases on PyPi:

pip install cascadio==0.0.13

Motivation

A lot of analysis can be done on triangulated surface meshes that doesn't need the analytical surfaces from a STEP or BREP file.

Contributing

Developed on Linux which should build wheels locally with docker:

# this doesn't cache the OCCT build unfortunately.
# It would be nice if it did! You could do it by building OCCT
# in the manylinux images and then passing the new tag to CIBW
CIBW_BUILD="cp312-manylinux_x86_64" cibuildwheel --platform linux

Or, if you want to develop that will only work in your local environment for development:

# just run the `before-all` from pyproject.toml which is approximatly:
cd upstream/OCCT
cmake -G Ninja -DCMAKE_BUILD_TYPE=Release \
      -DUSE_RAPIDJSON:BOOL="ON" \
      -D3RDPARTY_RAPIDJSON_INCLUDE_DIR="../rapidjson/include" .
ninja
mv lin64/gcc/lib .

Then pip install . will build and install locally. Make sure to point LD_LIBRARY_PATH=upstream/OCCT/lin64/gcc/lib or wherever you put the libraries.

Future Work

Pull requests welcome!

  • Add passable parameters for options included in the RWGLTF writer.
  • use in-memory data for input and output, i.e. stepReader.ReadStream() instead of a file name. Ideally the Python function signature would be:
    • convert_to_glb(data: bytes, file_type: str, **parameters) -> bytes
    • Currently using file names because it's easier.
  • Support IGES
    • Investigate using OpenCASCADE "Advanced Data Exchange" for Parasolid .x_b/.x_t and JT .jt support.

Project details


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

cascadio-0.0.16-pp310-pypy310_pp73-win_amd64.whl (13.7 MB view details)

Uploaded PyPyWindows x86-64

cascadio-0.0.16-pp310-pypy310_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (25.5 MB view details)

Uploaded PyPymanylinux: glibc 2.17+ x86-64

cascadio-0.0.16-pp310-pypy310_pp73-manylinux_2_17_i686.manylinux2014_i686.whl (26.1 MB view details)

Uploaded PyPymanylinux: glibc 2.17+ i686

cascadio-0.0.16-pp310-pypy310_pp73-macosx_11_0_arm64.whl (19.8 MB view details)

Uploaded PyPymacOS 11.0+ ARM64

cascadio-0.0.16-pp310-pypy310_pp73-macosx_10_15_x86_64.whl (22.4 MB view details)

Uploaded PyPymacOS 10.15+ x86-64

cascadio-0.0.16-pp39-pypy39_pp73-win_amd64.whl (13.7 MB view details)

Uploaded PyPyWindows x86-64

cascadio-0.0.16-pp39-pypy39_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (25.5 MB view details)

Uploaded PyPymanylinux: glibc 2.17+ x86-64

cascadio-0.0.16-pp39-pypy39_pp73-manylinux_2_17_i686.manylinux2014_i686.whl (26.1 MB view details)

Uploaded PyPymanylinux: glibc 2.17+ i686

cascadio-0.0.16-pp39-pypy39_pp73-macosx_11_0_arm64.whl (19.8 MB view details)

Uploaded PyPymacOS 11.0+ ARM64

cascadio-0.0.16-pp39-pypy39_pp73-macosx_10_15_x86_64.whl (22.4 MB view details)

Uploaded PyPymacOS 10.15+ x86-64

cascadio-0.0.16-pp38-pypy38_pp73-win_amd64.whl (13.7 MB view details)

Uploaded PyPyWindows x86-64

cascadio-0.0.16-pp38-pypy38_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (25.5 MB view details)

Uploaded PyPymanylinux: glibc 2.17+ x86-64

cascadio-0.0.16-pp38-pypy38_pp73-manylinux_2_17_i686.manylinux2014_i686.whl (26.1 MB view details)

Uploaded PyPymanylinux: glibc 2.17+ i686

cascadio-0.0.16-pp38-pypy38_pp73-macosx_11_0_arm64.whl (19.8 MB view details)

Uploaded PyPymacOS 11.0+ ARM64

cascadio-0.0.16-pp38-pypy38_pp73-macosx_10_9_x86_64.whl (22.4 MB view details)

Uploaded PyPymacOS 10.9+ x86-64

cascadio-0.0.16-pp37-pypy37_pp73-win_amd64.whl (13.7 MB view details)

Uploaded PyPyWindows x86-64

cascadio-0.0.16-pp37-pypy37_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (25.5 MB view details)

Uploaded PyPymanylinux: glibc 2.17+ x86-64

cascadio-0.0.16-pp37-pypy37_pp73-manylinux_2_17_i686.manylinux2014_i686.whl (26.1 MB view details)

Uploaded PyPymanylinux: glibc 2.17+ i686

cascadio-0.0.16-pp37-pypy37_pp73-macosx_10_9_x86_64.whl (22.4 MB view details)

Uploaded PyPymacOS 10.9+ x86-64

cascadio-0.0.16-cp313-cp313-win_amd64.whl (13.6 MB view details)

Uploaded CPython 3.13Windows x86-64

cascadio-0.0.16-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (25.5 MB view details)

Uploaded CPython 3.13manylinux: glibc 2.17+ x86-64

cascadio-0.0.16-cp313-cp313-manylinux_2_17_i686.manylinux2014_i686.whl (26.1 MB view details)

Uploaded CPython 3.13manylinux: glibc 2.17+ i686

cascadio-0.0.16-cp313-cp313-macosx_11_0_arm64.whl (19.8 MB view details)

Uploaded CPython 3.13macOS 11.0+ ARM64

cascadio-0.0.16-cp313-cp313-macosx_10_13_x86_64.whl (22.4 MB view details)

Uploaded CPython 3.13macOS 10.13+ x86-64

cascadio-0.0.16-cp312-cp312-win_amd64.whl (13.6 MB view details)

Uploaded CPython 3.12Windows x86-64

cascadio-0.0.16-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (25.5 MB view details)

Uploaded CPython 3.12manylinux: glibc 2.17+ x86-64

cascadio-0.0.16-cp312-cp312-manylinux_2_17_i686.manylinux2014_i686.whl (26.1 MB view details)

Uploaded CPython 3.12manylinux: glibc 2.17+ i686

cascadio-0.0.16-cp312-cp312-macosx_11_0_arm64.whl (19.8 MB view details)

Uploaded CPython 3.12macOS 11.0+ ARM64

cascadio-0.0.16-cp312-cp312-macosx_10_13_x86_64.whl (22.4 MB view details)

Uploaded CPython 3.12macOS 10.13+ x86-64

cascadio-0.0.16-cp311-cp311-win_amd64.whl (13.6 MB view details)

Uploaded CPython 3.11Windows x86-64

cascadio-0.0.16-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (25.5 MB view details)

Uploaded CPython 3.11manylinux: glibc 2.17+ x86-64

cascadio-0.0.16-cp311-cp311-manylinux_2_17_i686.manylinux2014_i686.whl (26.1 MB view details)

Uploaded CPython 3.11manylinux: glibc 2.17+ i686

cascadio-0.0.16-cp311-cp311-macosx_11_0_arm64.whl (19.8 MB view details)

Uploaded CPython 3.11macOS 11.0+ ARM64

cascadio-0.0.16-cp311-cp311-macosx_10_9_x86_64.whl (22.4 MB view details)

Uploaded CPython 3.11macOS 10.9+ x86-64

cascadio-0.0.16-cp310-cp310-win_amd64.whl (13.6 MB view details)

Uploaded CPython 3.10Windows x86-64

cascadio-0.0.16-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (25.5 MB view details)

Uploaded CPython 3.10manylinux: glibc 2.17+ x86-64

cascadio-0.0.16-cp310-cp310-manylinux_2_17_i686.manylinux2014_i686.whl (26.1 MB view details)

Uploaded CPython 3.10manylinux: glibc 2.17+ i686

cascadio-0.0.16-cp310-cp310-macosx_11_0_arm64.whl (19.8 MB view details)

Uploaded CPython 3.10macOS 11.0+ ARM64

cascadio-0.0.16-cp310-cp310-macosx_10_9_x86_64.whl (22.4 MB view details)

Uploaded CPython 3.10macOS 10.9+ x86-64

cascadio-0.0.16-cp39-cp39-win_amd64.whl (13.6 MB view details)

Uploaded CPython 3.9Windows x86-64

cascadio-0.0.16-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (25.5 MB view details)

Uploaded CPython 3.9manylinux: glibc 2.17+ x86-64

cascadio-0.0.16-cp39-cp39-manylinux_2_17_i686.manylinux2014_i686.whl (26.1 MB view details)

Uploaded CPython 3.9manylinux: glibc 2.17+ i686

cascadio-0.0.16-cp39-cp39-macosx_11_0_arm64.whl (19.8 MB view details)

Uploaded CPython 3.9macOS 11.0+ ARM64

cascadio-0.0.16-cp39-cp39-macosx_10_9_x86_64.whl (22.4 MB view details)

Uploaded CPython 3.9macOS 10.9+ x86-64

cascadio-0.0.16-cp38-cp38-win_amd64.whl (13.7 MB view details)

Uploaded CPython 3.8Windows x86-64

cascadio-0.0.16-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (25.5 MB view details)

Uploaded CPython 3.8manylinux: glibc 2.17+ x86-64

cascadio-0.0.16-cp38-cp38-manylinux_2_17_i686.manylinux2014_i686.whl (26.1 MB view details)

Uploaded CPython 3.8manylinux: glibc 2.17+ i686

cascadio-0.0.16-cp38-cp38-macosx_11_0_arm64.whl (19.8 MB view details)

Uploaded CPython 3.8macOS 11.0+ ARM64

cascadio-0.0.16-cp38-cp38-macosx_10_9_x86_64.whl (22.4 MB view details)

Uploaded CPython 3.8macOS 10.9+ x86-64

cascadio-0.0.16-cp37-cp37m-win_amd64.whl (13.7 MB view details)

Uploaded CPython 3.7mWindows x86-64

cascadio-0.0.16-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (25.5 MB view details)

Uploaded CPython 3.7mmanylinux: glibc 2.17+ x86-64

cascadio-0.0.16-cp37-cp37m-manylinux_2_17_i686.manylinux2014_i686.whl (26.1 MB view details)

Uploaded CPython 3.7mmanylinux: glibc 2.17+ i686

cascadio-0.0.16-cp37-cp37m-macosx_10_9_x86_64.whl (22.4 MB view details)

Uploaded CPython 3.7mmacOS 10.9+ x86-64

File details

Details for the file cascadio-0.0.16-pp310-pypy310_pp73-win_amd64.whl.

File metadata

File hashes

Hashes for cascadio-0.0.16-pp310-pypy310_pp73-win_amd64.whl
Algorithm Hash digest
SHA256 23209d1ae22375c9f931cd84ba801d5e456b8c220d8806fc13507b753e4684b4
MD5 f95e452b5a3db41db77b5e6d02c56104
BLAKE2b-256 bc7c1e0a6a03e0daf225c6e7b01d3b636fa2260606f781a1e05c6663f015da14

See more details on using hashes here.

File details

Details for the file cascadio-0.0.16-pp310-pypy310_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for cascadio-0.0.16-pp310-pypy310_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 a93721381bab801e3867062bde1df704a71aebfef3683699dab60002a6ad25da
MD5 d1c268c89f931c6edeac08eb3c8464f2
BLAKE2b-256 9a90288eb02524a0740f705744a5e49a33f7f60f63c032011fa30a4461cb9712

See more details on using hashes here.

File details

Details for the file cascadio-0.0.16-pp310-pypy310_pp73-manylinux_2_17_i686.manylinux2014_i686.whl.

File metadata

File hashes

Hashes for cascadio-0.0.16-pp310-pypy310_pp73-manylinux_2_17_i686.manylinux2014_i686.whl
Algorithm Hash digest
SHA256 00378d4901fb49d2641590bc5452eaf8a6f07ec9c2ecdc6398f726446a85175a
MD5 52f3fe21d4da3dfc560d0cc36ff6ccc8
BLAKE2b-256 005a712be86ad47c7f8ea433e569e7c25de3677a95a3ad884732ca4cb266b756

See more details on using hashes here.

File details

Details for the file cascadio-0.0.16-pp310-pypy310_pp73-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for cascadio-0.0.16-pp310-pypy310_pp73-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 a3aae6d47d3a3fd3ac486e99071bbf5eaa72478b17d905df65c90594cd17a83e
MD5 a6c5c82ea1fa133d03c5b686acf0cd2d
BLAKE2b-256 be69a31bd6d3327aa3b549e3de77e902beb3f4b6723453f7c6d263b32c509af5

See more details on using hashes here.

File details

Details for the file cascadio-0.0.16-pp310-pypy310_pp73-macosx_10_15_x86_64.whl.

File metadata

File hashes

Hashes for cascadio-0.0.16-pp310-pypy310_pp73-macosx_10_15_x86_64.whl
Algorithm Hash digest
SHA256 b116be4693ee6d230fc09f7f8ea662b0f95241acc7ac94aedd4e4ddbdd2b2c2e
MD5 6d55353c4355cd4f84fe2bd018308b9e
BLAKE2b-256 ee8989be5c3490b510fe7182bb0a430fa7b139184f8f4088f83e6e27fb7ee55b

See more details on using hashes here.

File details

Details for the file cascadio-0.0.16-pp39-pypy39_pp73-win_amd64.whl.

File metadata

File hashes

Hashes for cascadio-0.0.16-pp39-pypy39_pp73-win_amd64.whl
Algorithm Hash digest
SHA256 fb75cdee6368677d78e34cc63b04fbe68d7c6da7a9592c72916be4009cf43ed7
MD5 a2f5baa075905c0172a552be3f33a180
BLAKE2b-256 31d55872e484a2a61700fd9bd586186ec0413188f3ce66aa8905579e60342f8c

See more details on using hashes here.

File details

Details for the file cascadio-0.0.16-pp39-pypy39_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for cascadio-0.0.16-pp39-pypy39_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 85a39e8a633b679fd05b380e106502540890ea5f05f975d1d4b5fd6265ce9d10
MD5 a0db3640e862793672542df901a6561e
BLAKE2b-256 bbc3c6f258d4acdf85a2b35a39953dc701a4bf96f54c563b95d7987715da96ff

See more details on using hashes here.

File details

Details for the file cascadio-0.0.16-pp39-pypy39_pp73-manylinux_2_17_i686.manylinux2014_i686.whl.

File metadata

File hashes

Hashes for cascadio-0.0.16-pp39-pypy39_pp73-manylinux_2_17_i686.manylinux2014_i686.whl
Algorithm Hash digest
SHA256 8a7666a7c1bd89a6c33b6bd12e2f56d6bfc11aa4df5b730c866bf4dbc110a736
MD5 098d3f04c255b91a5e3642361ff95127
BLAKE2b-256 fd3f7d21de25f089153242dab46f156965098406b892b436285f7d9734d19703

See more details on using hashes here.

File details

Details for the file cascadio-0.0.16-pp39-pypy39_pp73-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for cascadio-0.0.16-pp39-pypy39_pp73-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 a7ceb57428ad2005b09e669ba0e39a79c77ab7e7a639923defd228e9db0b4825
MD5 5ebeb976f14890d208c32516ae4c887b
BLAKE2b-256 edfb44aedda042dd5093f5189d0514adaed94e441cb1913d213528971af6d378

See more details on using hashes here.

File details

Details for the file cascadio-0.0.16-pp39-pypy39_pp73-macosx_10_15_x86_64.whl.

File metadata

File hashes

Hashes for cascadio-0.0.16-pp39-pypy39_pp73-macosx_10_15_x86_64.whl
Algorithm Hash digest
SHA256 6b813fc1c53a1e99bdd1c485f17e9ed8180bde4bbb1fee3a862ef11bc0a67d4c
MD5 6d102624f3cb889e1bc127d010a473fa
BLAKE2b-256 509dbb82af8e04e51bc1e5831197ff9ecb2591fcd11d9e1219c39e5b84855c7a

See more details on using hashes here.

File details

Details for the file cascadio-0.0.16-pp38-pypy38_pp73-win_amd64.whl.

File metadata

File hashes

Hashes for cascadio-0.0.16-pp38-pypy38_pp73-win_amd64.whl
Algorithm Hash digest
SHA256 a7128725613056877883a252ccd2e982b1380582d43aca0c723c887e97aaafe5
MD5 d95f783ca0e4472864c11a293438da18
BLAKE2b-256 0e317e088603429d88ff4ec540e29275a5af6a2e650629d58813e6eb5dc4cb05

See more details on using hashes here.

File details

Details for the file cascadio-0.0.16-pp38-pypy38_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for cascadio-0.0.16-pp38-pypy38_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 d62d80e2cfa994007841bcaa1714ab492e2d543bec2dd9078aaf7e088cf5ea45
MD5 92f71f40c5a625e07c84515c64e4bc20
BLAKE2b-256 19d4c4e06acab66c5a17dedc55f3540b2a6e1aab677f2ed48685ea73126bf63a

See more details on using hashes here.

File details

Details for the file cascadio-0.0.16-pp38-pypy38_pp73-manylinux_2_17_i686.manylinux2014_i686.whl.

File metadata

File hashes

Hashes for cascadio-0.0.16-pp38-pypy38_pp73-manylinux_2_17_i686.manylinux2014_i686.whl
Algorithm Hash digest
SHA256 35d87b1832e79f1b7e3364a0bbb590ec5cfdd8ae76c60aa085ffbae1b77d347a
MD5 5963921de9d15e654d48ae466297694e
BLAKE2b-256 5e1dcc6578dc4285992c2987a83a830bf44a6531d1bf9143b5cbe691fbbe2b7b

See more details on using hashes here.

File details

Details for the file cascadio-0.0.16-pp38-pypy38_pp73-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for cascadio-0.0.16-pp38-pypy38_pp73-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 8d92ad3f2e054c7f3acb5d5e9c1b996a607276343e23377902bc03a0f4843eec
MD5 ed31393cdeef728d327822fbce4dad43
BLAKE2b-256 53fd444e33506ee3b6ed3b9ea64b801c9b42f1852f6d2f83e0f9f792c30ff139

See more details on using hashes here.

File details

Details for the file cascadio-0.0.16-pp38-pypy38_pp73-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for cascadio-0.0.16-pp38-pypy38_pp73-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 b49f314ae9325f4c5c4698e1169344a0a50ac5d450d97a2e5b59ed8c41e9dcf6
MD5 eaa3d8f65336b6c12883b37b11029703
BLAKE2b-256 225abd64903e7e4525f20cc81fb6fc67567422ba9dd13d06823ca8e41cf91484

See more details on using hashes here.

File details

Details for the file cascadio-0.0.16-pp37-pypy37_pp73-win_amd64.whl.

File metadata

File hashes

Hashes for cascadio-0.0.16-pp37-pypy37_pp73-win_amd64.whl
Algorithm Hash digest
SHA256 bb1be08c0be5f7c5a1a993a508039b6995960caa90681042b1749bed676be0f4
MD5 15a70288a9bf8e4a252d17dc7101797d
BLAKE2b-256 1b494415e3cf762f0339b8f1ef4763cf8afa513386ed883cee2ad7b829eb3eda

See more details on using hashes here.

File details

Details for the file cascadio-0.0.16-pp37-pypy37_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for cascadio-0.0.16-pp37-pypy37_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 6e82b8dc4bb26d17151d1ad05610409d6c094029c1ad7ec19ac34114452b53a7
MD5 6571bea9829ad7c157103b56c028da8f
BLAKE2b-256 278c1865118a94bafcfb1fbdeb5d1fa9fce1e81e22123563b3f6738e620f6cd0

See more details on using hashes here.

File details

Details for the file cascadio-0.0.16-pp37-pypy37_pp73-manylinux_2_17_i686.manylinux2014_i686.whl.

File metadata

File hashes

Hashes for cascadio-0.0.16-pp37-pypy37_pp73-manylinux_2_17_i686.manylinux2014_i686.whl
Algorithm Hash digest
SHA256 cdf7f979b460fe927c55c436360de24dcd58918512b2e2c57c082269ca2ef24e
MD5 6590bcddf1e9abd88b96f6541ff3b4bb
BLAKE2b-256 beeef819df011964a7cb9c304043e134c53d274c48158c043316ed1b7ee49082

See more details on using hashes here.

File details

Details for the file cascadio-0.0.16-pp37-pypy37_pp73-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for cascadio-0.0.16-pp37-pypy37_pp73-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 a09f31344a126870f8151822af4b34cfb9a2641e73111e21c56250333b98325a
MD5 bf6ce5356b07b13fa23f76192246944c
BLAKE2b-256 7a91b0fb210c81aec5fa6814868a4a9be51d6ad8922485761f2db5d1baa9f2ad

See more details on using hashes here.

File details

Details for the file cascadio-0.0.16-cp313-cp313-win_amd64.whl.

File metadata

  • Download URL: cascadio-0.0.16-cp313-cp313-win_amd64.whl
  • Upload date:
  • Size: 13.6 MB
  • Tags: CPython 3.13, Windows x86-64
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/4.0.2 CPython/3.11.11

File hashes

Hashes for cascadio-0.0.16-cp313-cp313-win_amd64.whl
Algorithm Hash digest
SHA256 3827bcaae0a753edc83874d15dc07228409e50707e55e27df04edd38f4fa5bca
MD5 847816e82ea7136eb5c0008ed0ef96f3
BLAKE2b-256 8cba31e91d4fe9e764a638d1990ef2737ae2e559980e51bbb1746e9acba3e440

See more details on using hashes here.

File details

Details for the file cascadio-0.0.16-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for cascadio-0.0.16-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 2d4be983ce648381ec6bd85d82110d6238ab8bf422b28effe3fed3318b9dbc7d
MD5 cb84cc45fbd9bc4de2f6e777fec788e0
BLAKE2b-256 5f12f748b9d1ff911f8dceeaca316e3dbad8b6b9893c28d07014fd3ef17ff7d0

See more details on using hashes here.

File details

Details for the file cascadio-0.0.16-cp313-cp313-manylinux_2_17_i686.manylinux2014_i686.whl.

File metadata

File hashes

Hashes for cascadio-0.0.16-cp313-cp313-manylinux_2_17_i686.manylinux2014_i686.whl
Algorithm Hash digest
SHA256 4710b37c65cfebfe7557b68686f1c4c2a899cb7c233534b5d45049c025a1e9a2
MD5 3f55a46c06ef64396f9d3c98d9a5146f
BLAKE2b-256 9741a735dee195271ed058ee70d8744e055295f6772cb0b6a0291873fdebea1e

See more details on using hashes here.

File details

Details for the file cascadio-0.0.16-cp313-cp313-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for cascadio-0.0.16-cp313-cp313-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 b1564bd2c55a742db42bb8c36092c8685477dd6c12a2c7a0ec4ab6348d048f8f
MD5 d1394f6991342c553d5e7ab6cda162bf
BLAKE2b-256 9a8d948efab566ca60509e0caa301a642d7828e23a6ce545ac0c1f885f2e5475

See more details on using hashes here.

File details

Details for the file cascadio-0.0.16-cp313-cp313-macosx_10_13_x86_64.whl.

File metadata

File hashes

Hashes for cascadio-0.0.16-cp313-cp313-macosx_10_13_x86_64.whl
Algorithm Hash digest
SHA256 67ddf6c4cbf31205a6e0a41c4946be7e01d601eeeca32a261fe60724750e53be
MD5 d4294dcaa6cefced688151a1b0b76213
BLAKE2b-256 68c170303c72ac07db08ca07d3265756410517571890da1eefdb961cd15f1e60

See more details on using hashes here.

File details

Details for the file cascadio-0.0.16-cp312-cp312-win_amd64.whl.

File metadata

  • Download URL: cascadio-0.0.16-cp312-cp312-win_amd64.whl
  • Upload date:
  • Size: 13.6 MB
  • Tags: CPython 3.12, Windows x86-64
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/4.0.2 CPython/3.11.11

File hashes

Hashes for cascadio-0.0.16-cp312-cp312-win_amd64.whl
Algorithm Hash digest
SHA256 0c79ec8fcda24ac3b99823effe0c968fcf38ebc5d0ae0601546d9623eea3f70d
MD5 1c62145bd35c6eef2ed0cd6b4eb674b0
BLAKE2b-256 58a2ee03bb2b3f5486da865bcb26af3428aadf368d3b9c524190f6511cbefb93

See more details on using hashes here.

File details

Details for the file cascadio-0.0.16-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for cascadio-0.0.16-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 e58b6b8b19da2bb9eb8637b4da90aec46f7850e5abc73a7f6cf862703fbfde03
MD5 b07ce87871627a0a6e60230e004c602e
BLAKE2b-256 89c36f2486ebe36ae23b08655edf505da858a2a0910d160239986ad21a4cce05

See more details on using hashes here.

File details

Details for the file cascadio-0.0.16-cp312-cp312-manylinux_2_17_i686.manylinux2014_i686.whl.

File metadata

File hashes

Hashes for cascadio-0.0.16-cp312-cp312-manylinux_2_17_i686.manylinux2014_i686.whl
Algorithm Hash digest
SHA256 c89011a637dbea7920013f19d4f293b50640a4c4fa652437b603d843bc16c54e
MD5 6f8295bb8945f9e2d2209e45865c4700
BLAKE2b-256 a77c3e4b77a11f92c430f068d3e2a4fe92a876c2750adf2f43d64511dc319970

See more details on using hashes here.

File details

Details for the file cascadio-0.0.16-cp312-cp312-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for cascadio-0.0.16-cp312-cp312-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 2a7b23d659386851b7a12192b7cbc88d076bd3cb0526f8a885e08d67410d8b69
MD5 39b85b06d2dcf8a8ea9fca14bc7b9d7c
BLAKE2b-256 b6adec7afb616c46f994cb5abdea1062e6b63c88e7c18a18ca3092a0d0c16444

See more details on using hashes here.

File details

Details for the file cascadio-0.0.16-cp312-cp312-macosx_10_13_x86_64.whl.

File metadata

File hashes

Hashes for cascadio-0.0.16-cp312-cp312-macosx_10_13_x86_64.whl
Algorithm Hash digest
SHA256 c62f203aa3fabb22aa222c521eff5e87a224d535c629c66cb0f5868428b2b971
MD5 99aa371ec42952d1ccfd9b7f50f22a36
BLAKE2b-256 30d29015072e0cbbef9f9f03200334102eddb3eda2b531c0c6a27de8d0170a16

See more details on using hashes here.

File details

Details for the file cascadio-0.0.16-cp311-cp311-win_amd64.whl.

File metadata

  • Download URL: cascadio-0.0.16-cp311-cp311-win_amd64.whl
  • Upload date:
  • Size: 13.6 MB
  • Tags: CPython 3.11, Windows x86-64
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/4.0.2 CPython/3.11.11

File hashes

Hashes for cascadio-0.0.16-cp311-cp311-win_amd64.whl
Algorithm Hash digest
SHA256 dda43a9688c710ea707a5e3dc4995cd83873a749f7804f216cda3410bc2ec452
MD5 e41eed6885ec4e66aaa21bcab149b522
BLAKE2b-256 3acd377e1e3e3e08967aaa7516119f094780e56b42c8f579a05f914064ac94ac

See more details on using hashes here.

File details

Details for the file cascadio-0.0.16-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for cascadio-0.0.16-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 2d5883c7cd127a47f0a9f006ed32d709bcb013d4cd95e66cd174218780e72353
MD5 f75ae818710d759411ee13572e247ad1
BLAKE2b-256 81bc9987d8b3184415b51f5a31f886f4958550923f65daa5c347907ac68ca222

See more details on using hashes here.

File details

Details for the file cascadio-0.0.16-cp311-cp311-manylinux_2_17_i686.manylinux2014_i686.whl.

File metadata

File hashes

Hashes for cascadio-0.0.16-cp311-cp311-manylinux_2_17_i686.manylinux2014_i686.whl
Algorithm Hash digest
SHA256 2ec9672515b48672de4da8bdc13e40d008d1a5ff53dd87efdb78f8147d54bdda
MD5 bfb2a6be0655e41cdf11ee38316744ce
BLAKE2b-256 b12ae2166ca78a33200215dba1a52c4c55f38d2ccde153d38601c315eb9da289

See more details on using hashes here.

File details

Details for the file cascadio-0.0.16-cp311-cp311-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for cascadio-0.0.16-cp311-cp311-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 b7d5ebc0b6df8cbe885490bda9d95f6beb014ef653e2778f5bc42243548f6c97
MD5 47bf255fb2da370091dae97e0bbf8d47
BLAKE2b-256 86c2bdf621e765ece3bd78dd423ee48cc5831a73b77c0303335a751a9b2f7d42

See more details on using hashes here.

File details

Details for the file cascadio-0.0.16-cp311-cp311-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for cascadio-0.0.16-cp311-cp311-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 d1a803e0a8b3153d236109b8fcf71bb0814f06572d5a84691ef54f70cd3299be
MD5 051397365cd64bc9b6c68ce6cbb98439
BLAKE2b-256 890ef50218b9255363a625dc5d06eab1717fb7966f5f56b3b1b98d795d552aee

See more details on using hashes here.

File details

Details for the file cascadio-0.0.16-cp310-cp310-win_amd64.whl.

File metadata

  • Download URL: cascadio-0.0.16-cp310-cp310-win_amd64.whl
  • Upload date:
  • Size: 13.6 MB
  • Tags: CPython 3.10, Windows x86-64
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/4.0.2 CPython/3.11.11

File hashes

Hashes for cascadio-0.0.16-cp310-cp310-win_amd64.whl
Algorithm Hash digest
SHA256 29185c6744b35c7bfaaa339974fa67f3364f12b78a7c1d712846a61347388883
MD5 e453ab9104b070eba4d9f0e84a2bc136
BLAKE2b-256 67273c0941f9c8eeba95bc764225e766616c867c963560e92280035d512088f0

See more details on using hashes here.

File details

Details for the file cascadio-0.0.16-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for cascadio-0.0.16-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 1ae41a1112d1bde2f556e919794de7b8fc0a296107425cdeb83f9af38b745b52
MD5 0018d85f2878295bc3c2fd7033d3849d
BLAKE2b-256 916d9e05d7dab2a96577d0596f2037563e564be9eef415f5e534085b6220962a

See more details on using hashes here.

File details

Details for the file cascadio-0.0.16-cp310-cp310-manylinux_2_17_i686.manylinux2014_i686.whl.

File metadata

File hashes

Hashes for cascadio-0.0.16-cp310-cp310-manylinux_2_17_i686.manylinux2014_i686.whl
Algorithm Hash digest
SHA256 e6c1527f5564d416f72f02a9ccd4f25b0e1b32ab75c3e282ac54112aea2258eb
MD5 3c1d6ef5e279c4fc64ee7d3ce5ae56ae
BLAKE2b-256 67832fd4bb0bf258ab2e7694503f14b384d6367c75d95d4c3b3c58f3deb30227

See more details on using hashes here.

File details

Details for the file cascadio-0.0.16-cp310-cp310-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for cascadio-0.0.16-cp310-cp310-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 35d98b99165c92bd42cb946c3a0967b278ae15e743884bcc7e8938a6314d6284
MD5 e6ec3995e3d21c8be85f8d868ee95239
BLAKE2b-256 e8611803061271e5b0166d4db120cfe78d9d3bb45b0f88f473105a2f9f044c9b

See more details on using hashes here.

File details

Details for the file cascadio-0.0.16-cp310-cp310-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for cascadio-0.0.16-cp310-cp310-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 36eb4fa0a6c95faacf306c720e0ea508e0fd1cacbc2941f3112aaaad1dd002c5
MD5 6ec24b1520b885bc58c94a2d0d6c88c1
BLAKE2b-256 242f86c201f4423a45dd151eb89147a2311c3aa274461950a46dc6d37bd4d13b

See more details on using hashes here.

File details

Details for the file cascadio-0.0.16-cp39-cp39-win_amd64.whl.

File metadata

  • Download URL: cascadio-0.0.16-cp39-cp39-win_amd64.whl
  • Upload date:
  • Size: 13.6 MB
  • Tags: CPython 3.9, Windows x86-64
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/4.0.2 CPython/3.11.11

File hashes

Hashes for cascadio-0.0.16-cp39-cp39-win_amd64.whl
Algorithm Hash digest
SHA256 e07f6ce55a48c20602ee2ab6ad89ae8b06ee12b2337f5f98491e8054420c8101
MD5 82a9a39f1a156612ebcfee791b0c00d1
BLAKE2b-256 266d5bf6cdf37da64d031cc76eaa97a4fc17ca59407266bf97336caf2f343d82

See more details on using hashes here.

File details

Details for the file cascadio-0.0.16-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for cascadio-0.0.16-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 81f80f1fef7ade49884ed7434ead4dede576d58f909caadded801baba86878d5
MD5 842a74267b93c0e417d1ac1817250953
BLAKE2b-256 65f3bb056fd86e03ca5c8e6f201e324afeb288125120045fe9b822e9fc801283

See more details on using hashes here.

File details

Details for the file cascadio-0.0.16-cp39-cp39-manylinux_2_17_i686.manylinux2014_i686.whl.

File metadata

File hashes

Hashes for cascadio-0.0.16-cp39-cp39-manylinux_2_17_i686.manylinux2014_i686.whl
Algorithm Hash digest
SHA256 5b1d7b81096eb2e5a06753f869298cadca59c1597f8d6819cf265726da5471cc
MD5 3ff155df73daa141c8a665740e1836c3
BLAKE2b-256 9714aaa8d1b686053c63f62631d628a80adc5e8159e5cefe2e025511ffbfd788

See more details on using hashes here.

File details

Details for the file cascadio-0.0.16-cp39-cp39-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for cascadio-0.0.16-cp39-cp39-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 61cb95f4f87393bda85a9df45f81aa413dc334dff54f5bf95a5f50b9f847c1b1
MD5 34856b9c48637f25e0b44cfe241082e6
BLAKE2b-256 e6bfc16967c71281fc427819253507a92e43a9408d286f39b06c4ffb3699c384

See more details on using hashes here.

File details

Details for the file cascadio-0.0.16-cp39-cp39-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for cascadio-0.0.16-cp39-cp39-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 6c2f1abbcb9cb55655a89a036702687b0d6e447bbeb4481549c2182b190e334b
MD5 aca58ea43e4d4123fb366e64c0026382
BLAKE2b-256 e41ddc9c2b55abab8459221e4e285747f26fd3da4e6ce6dd9101c550d13bfe9e

See more details on using hashes here.

File details

Details for the file cascadio-0.0.16-cp38-cp38-win_amd64.whl.

File metadata

  • Download URL: cascadio-0.0.16-cp38-cp38-win_amd64.whl
  • Upload date:
  • Size: 13.7 MB
  • Tags: CPython 3.8, Windows x86-64
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/4.0.2 CPython/3.11.11

File hashes

Hashes for cascadio-0.0.16-cp38-cp38-win_amd64.whl
Algorithm Hash digest
SHA256 cf7f8900bc5855672dd81ba6fdcc3fb304bbafeef47a9e282baa936f61c8ad9f
MD5 f2ebaf57417ca4764efdcd25ae4a2be2
BLAKE2b-256 0a2838d3e755bdd0fcc548eb4d47b944c4a63609c5aa177105982aebefa60dde

See more details on using hashes here.

File details

Details for the file cascadio-0.0.16-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for cascadio-0.0.16-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 d9e2f290c86729e94542fa8c079fe56eb8f90d48214fd6c7b2cceb029d93bcd5
MD5 a31a8c828a87e4d101132767ea520ca0
BLAKE2b-256 840fbe35b06196db0e72fc0e76bfb4ad08422733672f30e39eec9a4f4984a508

See more details on using hashes here.

File details

Details for the file cascadio-0.0.16-cp38-cp38-manylinux_2_17_i686.manylinux2014_i686.whl.

File metadata

File hashes

Hashes for cascadio-0.0.16-cp38-cp38-manylinux_2_17_i686.manylinux2014_i686.whl
Algorithm Hash digest
SHA256 9efe40d17b3121bd7299e64622316cc8eccefdd2c09efc3901fad738c55b88da
MD5 52a4d01c489b9312aa636bbf217f1c5c
BLAKE2b-256 5b147310673ba6e615564ae43531cb3764269caee9dc1b6b43e4df6228f77117

See more details on using hashes here.

File details

Details for the file cascadio-0.0.16-cp38-cp38-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for cascadio-0.0.16-cp38-cp38-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 1b33b0e6f7ca426cf8a650b541ccf1e2df21cfffd556e615201f4d0a150fbb21
MD5 b32855aa0dc12a5c3921f148815891b9
BLAKE2b-256 e3e349cd99c7a2db8ea87fe9e5709889cc240b81dd7ab27b1f3cde2197a8b257

See more details on using hashes here.

File details

Details for the file cascadio-0.0.16-cp38-cp38-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for cascadio-0.0.16-cp38-cp38-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 b963436ce240ebcd68e2e5cb3b15a313366e1bfc549a01b8c8308888dec5a45a
MD5 210c726246aa80ff066247dd7c952364
BLAKE2b-256 624e214fa8c964538a3d21762d483fd2bb8ad928f6bd82cb3702b1e041d08e1c

See more details on using hashes here.

File details

Details for the file cascadio-0.0.16-cp37-cp37m-win_amd64.whl.

File metadata

  • Download URL: cascadio-0.0.16-cp37-cp37m-win_amd64.whl
  • Upload date:
  • Size: 13.7 MB
  • Tags: CPython 3.7m, Windows x86-64
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/4.0.2 CPython/3.11.11

File hashes

Hashes for cascadio-0.0.16-cp37-cp37m-win_amd64.whl
Algorithm Hash digest
SHA256 263f9d195b7c66c59591d3226d3992794bf3d79661d33b9145f4edb3f7c90c48
MD5 a25e43850bf993078c388b7a0d93a8db
BLAKE2b-256 7cb7b5774dc1ef2e59fefb0f381b5e719936befe4851b18b66cb1b9de5ffe569

See more details on using hashes here.

File details

Details for the file cascadio-0.0.16-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for cascadio-0.0.16-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 c7b3b93bbc11406c6d4d970cbebde387666f79556a49f24c11a2d09731f07473
MD5 97d1f62b71b6ea460a5199e2e9b13c48
BLAKE2b-256 f424917ac25a2780be6fc31e9ffcfffc524c0cbe18c9cdcfc245de8524c8f8eb

See more details on using hashes here.

File details

Details for the file cascadio-0.0.16-cp37-cp37m-manylinux_2_17_i686.manylinux2014_i686.whl.

File metadata

File hashes

Hashes for cascadio-0.0.16-cp37-cp37m-manylinux_2_17_i686.manylinux2014_i686.whl
Algorithm Hash digest
SHA256 9e00b777532c03a2cf95ba7a12ecc7fb022636aeeb755bd9d6312b3b8169472e
MD5 950a810ac364453abf8e6e511874aece
BLAKE2b-256 69bcffc174a37a55dd9d33e8097b880d2dbfac0e263c12654671cd81b205fb52

See more details on using hashes here.

File details

Details for the file cascadio-0.0.16-cp37-cp37m-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for cascadio-0.0.16-cp37-cp37m-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 691b9d908cd26a22f18c9713984987601e3309ebdf3a2db2f58ccf8f929e6e38
MD5 abf258e5314c331c13b910ffb47a3ea9
BLAKE2b-256 aa352c18076c3ca15f1c1b2bb011b8686d2f96dd8364f32d4db0fff36d4ec2cf

See more details on using hashes here.

Supported by

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