Skip to main content

Python bindings for CGAL - Computational Geometry Algorithms Library

Project description

pycglib — CGAL Python Bindings

Python bindings for CGAL — Computational Geometry Algorithms Library, powered by pybind11.

⚠️ Work in Progress: This package is currently in active development and not intended for public use yet. API may change without notice.

What is CGAL?

CGAL (Computational Geometry Algorithms Library) is a powerful C++ library that provides efficient and reliable algorithms for computational geometry. It covers a wide range of topics including triangulations, mesh generation, spatial searching, boolean operations, and much more. It is widely used in robotics, GIS, computer graphics, and scientific computing.

What is Python?

Python is one of the most popular programming languages in the world, known for its simplicity, readability, and a rich ecosystem of libraries for data science, machine learning, and engineering.

Why Python for CGAL?

CGAL is written in C++, which makes it fast but harder to access for many developers and researchers who work primarily in Python. By wrapping CGAL using pybind11, pycglib brings the full power of CGAL's geometry algorithms to Python — no C++ knowledge required. This makes computational geometry accessible to a much wider audience.


Installation

Prerequisites

  • Python 3.10 to 3.13 (64-bit)
  • Windows x86-64, Linux (glibc 2.28+), or macOS 15.0 (Sequoia)+
  • pip 21.0 or later

Install via pip

pip install pycglib

Verify Installation

Run the following snippet to confirm pycglib is installed and working correctly:

import pycglib as pg

a = (0, 0)
b = (3, 4)
result = pg.squared_distance(a, b)
print(result)  # Expected output: 25.0

If you see 25.0, your installation is successful!


Supported Platforms

Platform Supported
Windows x86-64
Linux (glibc 2.28+)
macOS 15.0+ (ARM64)
Windows 32-bit
Alpine Linux (musllinux)
macOS < 15.0

Supported Python Versions

Python Version Supported
3.10
3.11
3.12
3.13
< 3.10 or > 3.13

Links

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

If you're not sure about the file name format, learn more about wheel file names.

pycglib-0.1.28-cp313-cp313-win_amd64.whl (131.6 kB view details)

Uploaded CPython 3.13Windows x86-64

pycglib-0.1.28-cp313-cp313-manylinux_2_28_x86_64.whl (666.5 kB view details)

Uploaded CPython 3.13manylinux: glibc 2.28+ x86-64

pycglib-0.1.28-cp313-cp313-macosx_15_0_arm64.whl (546.0 kB view details)

Uploaded CPython 3.13macOS 15.0+ ARM64

pycglib-0.1.28-cp312-cp312-win_amd64.whl (131.6 kB view details)

Uploaded CPython 3.12Windows x86-64

pycglib-0.1.28-cp312-cp312-manylinux_2_28_x86_64.whl (666.5 kB view details)

Uploaded CPython 3.12manylinux: glibc 2.28+ x86-64

pycglib-0.1.28-cp312-cp312-macosx_15_0_arm64.whl (546.0 kB view details)

Uploaded CPython 3.12macOS 15.0+ ARM64

pycglib-0.1.28-cp311-cp311-win_amd64.whl (130.5 kB view details)

Uploaded CPython 3.11Windows x86-64

pycglib-0.1.28-cp311-cp311-manylinux_2_28_x86_64.whl (666.0 kB view details)

Uploaded CPython 3.11manylinux: glibc 2.28+ x86-64

pycglib-0.1.28-cp311-cp311-macosx_15_0_arm64.whl (545.9 kB view details)

Uploaded CPython 3.11macOS 15.0+ ARM64

pycglib-0.1.28-cp310-cp310-win_amd64.whl (129.9 kB view details)

Uploaded CPython 3.10Windows x86-64

pycglib-0.1.28-cp310-cp310-manylinux_2_28_x86_64.whl (664.6 kB view details)

Uploaded CPython 3.10manylinux: glibc 2.28+ x86-64

pycglib-0.1.28-cp310-cp310-macosx_15_0_arm64.whl (544.8 kB view details)

Uploaded CPython 3.10macOS 15.0+ ARM64

File details

Details for the file pycglib-0.1.28-cp313-cp313-win_amd64.whl.

File metadata

  • Download URL: pycglib-0.1.28-cp313-cp313-win_amd64.whl
  • Upload date:
  • Size: 131.6 kB
  • Tags: CPython 3.13, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.13.7

File hashes

Hashes for pycglib-0.1.28-cp313-cp313-win_amd64.whl
Algorithm Hash digest
SHA256 094b15fa0101d49c7786f4d2ec708d0bead3b0404333e47a6d466167f31e5fe5
MD5 f53cff26f487ea6d4455fee3cf371ffd
BLAKE2b-256 14e5216a217184849f0dd0bf39f8897b409197779040256b869f1a9760774c76

See more details on using hashes here.

File details

Details for the file pycglib-0.1.28-cp313-cp313-manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for pycglib-0.1.28-cp313-cp313-manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 c68dd39c23ea96bf64ff3cc2c593a448b7ed714dd0ab027249c4115c3766b10f
MD5 be02470b2a1520d7e5bec4c318defd6b
BLAKE2b-256 0dc7b14abdbf774011ac54164c2063252901aedc71d24f23298fa9bca981df26

See more details on using hashes here.

File details

Details for the file pycglib-0.1.28-cp313-cp313-macosx_15_0_arm64.whl.

File metadata

File hashes

Hashes for pycglib-0.1.28-cp313-cp313-macosx_15_0_arm64.whl
Algorithm Hash digest
SHA256 b331e6eba5d213d8a510f762eb3a206ca97559c7026a019d371ca098e3b9bff7
MD5 c63cf141bfced56297e817a06f7f97e9
BLAKE2b-256 87d0b53c1bd3dad1a979576bed8e2068b93157f9a08efafbc985b7be16008c0d

See more details on using hashes here.

File details

Details for the file pycglib-0.1.28-cp312-cp312-win_amd64.whl.

File metadata

  • Download URL: pycglib-0.1.28-cp312-cp312-win_amd64.whl
  • Upload date:
  • Size: 131.6 kB
  • Tags: CPython 3.12, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.13.7

File hashes

Hashes for pycglib-0.1.28-cp312-cp312-win_amd64.whl
Algorithm Hash digest
SHA256 9c0a47937972bdba9c8ea0f90f61ffc3af8f256eacca48842705bfbf9183c8bb
MD5 8aeac5bdb1e264b63860fe6bd53e9a2f
BLAKE2b-256 8a250123cb3099bb58247e04a7db72ef19085e00ee7d996040630392113cdd51

See more details on using hashes here.

File details

Details for the file pycglib-0.1.28-cp312-cp312-manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for pycglib-0.1.28-cp312-cp312-manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 6758d150f3fe4b8f69387bc29942879852e274a12ac32ae558d83893c2efc1b5
MD5 e31b342cc436de656996e2828ca1ac83
BLAKE2b-256 0ade9ea099cf2d51d33dcc76ea0e6e62f26d1ef374a3ac6cf3729611e9321ccd

See more details on using hashes here.

File details

Details for the file pycglib-0.1.28-cp312-cp312-macosx_15_0_arm64.whl.

File metadata

File hashes

Hashes for pycglib-0.1.28-cp312-cp312-macosx_15_0_arm64.whl
Algorithm Hash digest
SHA256 383807c4e2d06aee9b0108d20c3a81a531859beb0c983c83a0360c7e20129cbb
MD5 e99734c948964f5b2ce2e7b9f733b4e6
BLAKE2b-256 98e16a3016400e3576166ee522a1839b9fdee3f183bd7f0600ee1970ed6386a7

See more details on using hashes here.

File details

Details for the file pycglib-0.1.28-cp311-cp311-win_amd64.whl.

File metadata

  • Download URL: pycglib-0.1.28-cp311-cp311-win_amd64.whl
  • Upload date:
  • Size: 130.5 kB
  • Tags: CPython 3.11, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.13.7

File hashes

Hashes for pycglib-0.1.28-cp311-cp311-win_amd64.whl
Algorithm Hash digest
SHA256 15c0a74b63ce244d77cd43de0044ffa3b0623b1081c7b0d30e9fa38b550af43c
MD5 2defc7707f232b134ac1f7eaa00a39f5
BLAKE2b-256 864c180ad4ad73ab83d28a3b8b1a4fdea6d6e4d5f5909649668d2c83c94aaa02

See more details on using hashes here.

File details

Details for the file pycglib-0.1.28-cp311-cp311-manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for pycglib-0.1.28-cp311-cp311-manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 d38ac9b333b72d12c8bf47984d93a2109c5e701e8682c1fdeb7317ff4128f0b5
MD5 b5340650308cfdb821d679304ded92a1
BLAKE2b-256 a30f7ed11c3dc0b10430db133551e9bda8ab7261a752df6a02eb4c7abf4cd3b6

See more details on using hashes here.

File details

Details for the file pycglib-0.1.28-cp311-cp311-macosx_15_0_arm64.whl.

File metadata

File hashes

Hashes for pycglib-0.1.28-cp311-cp311-macosx_15_0_arm64.whl
Algorithm Hash digest
SHA256 bdda0c99b9986a8a9a79ba54ad1896fa606f4a93c500940cdb4c2f75788c24ff
MD5 6bd21d17611459e3ab8a246f7b1c2dbc
BLAKE2b-256 331cbda7fc34093e9186c83e7b1d0d7ce743ffff26ded22bd2dc85b4f86a8990

See more details on using hashes here.

File details

Details for the file pycglib-0.1.28-cp310-cp310-win_amd64.whl.

File metadata

  • Download URL: pycglib-0.1.28-cp310-cp310-win_amd64.whl
  • Upload date:
  • Size: 129.9 kB
  • Tags: CPython 3.10, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.13.7

File hashes

Hashes for pycglib-0.1.28-cp310-cp310-win_amd64.whl
Algorithm Hash digest
SHA256 32f58b6fec48bac294d497087d2518a71ec70383d2e687388efa942fa525fb33
MD5 f8bee6c6783dafe3cf68a507b38ee7fb
BLAKE2b-256 582dc4e489225603580cf5fb6386aeb6837fb4c1962df0ad99bd97e7e04c5cd2

See more details on using hashes here.

File details

Details for the file pycglib-0.1.28-cp310-cp310-manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for pycglib-0.1.28-cp310-cp310-manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 5d352ea6b43f0d3254397d68f3e737437509889639396f3ccc5695bca84e8250
MD5 0e708c4be9a347b9d6414171ff8f487b
BLAKE2b-256 d88fd108421404cb1e1f2945f0c10042b1ba2f6fe1b4e0695585b460984a7616

See more details on using hashes here.

File details

Details for the file pycglib-0.1.28-cp310-cp310-macosx_15_0_arm64.whl.

File metadata

File hashes

Hashes for pycglib-0.1.28-cp310-cp310-macosx_15_0_arm64.whl
Algorithm Hash digest
SHA256 4d97cacbd424c8111c28823febc49855f141c80f2ea5ca419b0c8c8a3c377b74
MD5 099e2196af201acadf029d18a64678bd
BLAKE2b-256 9170a7d770ebf7f6009ece32462ce33d93ba540141dfcf98ef396fabb6a290ae

See more details on using hashes here.

Supported by

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