Skip to main content

Bindings C++ avec pybind11 de Jerboa

Project description

Jerboapy

This project is a port of the Jerboa C++ implementation to Python. It is a pybind11 binding to the Jerboa C++ library, which is located in the jerboa-cpp directory. The goal of this project is to provide a Python interface for users who prefer to work in Python while leveraging the performance and capabilities of the Jerboa C++ library.

Currently it proves a 3D modeler (understanding that there is an alpha_3 links in their gmaps).

Installation

To install the required dependencies, run:

pip install jerboapy

Optional: 3D visualization and advanced features

If you want to use the 3D visualization features and advanced coordinate/color classes, install the extra ext:

pip install jerboapy[ext]

This will install additional dependencies for graphical display and advanced geometry. The extra ext enables:

  • 3D visualization (with PyVista and Trame)
  • The module jerboa_ext with:
    • Point3: class for 3D coordinates
    • Color4: class for RGBA color management

You can then use these classes for embedding coordinates and managing colors in your models.

Usage

Provide an example of how to use your project:

from jerboapy import *

# Example usage
modeler = Modeler3D()

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.

jerboapy-0.5rc394-cp314-cp314t-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl (2.8 MB view details)

Uploaded CPython 3.14tmanylinux: glibc 2.27+ x86-64manylinux: glibc 2.28+ x86-64

jerboapy-0.5rc394-cp314-cp314-win_amd64.whl (4.4 MB view details)

Uploaded CPython 3.14Windows x86-64

jerboapy-0.5rc394-cp314-cp314-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl (2.4 MB view details)

Uploaded CPython 3.14manylinux: glibc 2.27+ x86-64manylinux: glibc 2.28+ x86-64

jerboapy-0.5rc394-cp313-cp313t-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl (2.0 MB view details)

Uploaded CPython 3.13tmanylinux: glibc 2.27+ x86-64manylinux: glibc 2.28+ x86-64

jerboapy-0.5rc394-cp313-cp313-win_amd64.whl (3.2 MB view details)

Uploaded CPython 3.13Windows x86-64

jerboapy-0.5rc394-cp313-cp313-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl (1.6 MB view details)

Uploaded CPython 3.13manylinux: glibc 2.27+ x86-64manylinux: glibc 2.28+ x86-64

jerboapy-0.5rc394-cp312-cp312-win_amd64.whl (2.1 MB view details)

Uploaded CPython 3.12Windows x86-64

jerboapy-0.5rc394-cp312-cp312-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl (1.2 MB view details)

Uploaded CPython 3.12manylinux: glibc 2.27+ x86-64manylinux: glibc 2.28+ x86-64

jerboapy-0.5rc394-cp311-cp311-win_amd64.whl (1.1 MB view details)

Uploaded CPython 3.11Windows x86-64

jerboapy-0.5rc394-cp311-cp311-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl (812.5 kB view details)

Uploaded CPython 3.11manylinux: glibc 2.27+ x86-64manylinux: glibc 2.28+ x86-64

jerboapy-0.5rc394-cp310-cp310-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl (419.1 kB view details)

Uploaded CPython 3.10manylinux: glibc 2.27+ x86-64manylinux: glibc 2.28+ x86-64

jerboapy-0.5rc394-cp39-cp39-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl (3.6 MB view details)

Uploaded CPython 3.9manylinux: glibc 2.27+ x86-64manylinux: glibc 2.28+ x86-64

jerboapy-0.5rc394-cp38-cp38-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl (3.2 MB view details)

Uploaded CPython 3.8manylinux: glibc 2.27+ x86-64manylinux: glibc 2.28+ x86-64

File details

Details for the file jerboapy-0.5rc394-cp314-cp314t-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for jerboapy-0.5rc394-cp314-cp314t-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 1837195496a540d7f2ef04fc0a82cbb4c3778252cb8f50580c064d795f5cb53b
MD5 45b8b66a1388d6746059114e1787f9e9
BLAKE2b-256 183da5e6469dcd84ebf1d092f1d84fd7321a2710740b5131826f4286f816b9d1

See more details on using hashes here.

File details

Details for the file jerboapy-0.5rc394-cp314-cp314-win_amd64.whl.

File metadata

File hashes

Hashes for jerboapy-0.5rc394-cp314-cp314-win_amd64.whl
Algorithm Hash digest
SHA256 fee8b99e0643cf8153023453a10e9dea0c47b9e4ab1a74e1407161a0b0112418
MD5 c920468d82247934e5692c580598604a
BLAKE2b-256 1cb0c1e5208ede6b97d9ee5e630d4b4e535f4fb0a5797d82656e4670ad489ca0

See more details on using hashes here.

File details

Details for the file jerboapy-0.5rc394-cp314-cp314-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for jerboapy-0.5rc394-cp314-cp314-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 81b78585d63894ba6f6a789ccb4b49164ac0b3c7fe19d934047efa240b866386
MD5 7327b82b7cb98f331c0434a59e497be3
BLAKE2b-256 9e8032eae433d24d08109c6da8a10156fa670272a2a5a3a0be8bc24f681b8f1e

See more details on using hashes here.

File details

Details for the file jerboapy-0.5rc394-cp313-cp313t-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for jerboapy-0.5rc394-cp313-cp313t-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 b29a7377ec125fef13078d95926ea130b3b1d7c3cc1d53462cc57e127143f268
MD5 957c46a02e4353984957c26e451ae82b
BLAKE2b-256 e66ac2664484c7c39d7a1f30eabbf59c8b5fd96edb0261186a7158eb8165f2fe

See more details on using hashes here.

File details

Details for the file jerboapy-0.5rc394-cp313-cp313-win_amd64.whl.

File metadata

File hashes

Hashes for jerboapy-0.5rc394-cp313-cp313-win_amd64.whl
Algorithm Hash digest
SHA256 ab6fb5c01331934ec51731c553160a22715bc683325ba4b3aad6ea06e161bb83
MD5 f12f1ea2c5484f23f1c1b0f9d4e7b81c
BLAKE2b-256 4722adac756dd7e825fc52d289d34323c1c03a11dd4ee1516d7a4d064197cdd9

See more details on using hashes here.

File details

Details for the file jerboapy-0.5rc394-cp313-cp313-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for jerboapy-0.5rc394-cp313-cp313-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 1169522004d37975aa15471d073a1a919a282bd50056ca8a090b199e00a3e0d3
MD5 aebf176b84bd9c59f7bba17b67071c1b
BLAKE2b-256 e06b20081b26486ad0294ec56efe5c5ddc381e62d4647480ca2329b1a6620089

See more details on using hashes here.

File details

Details for the file jerboapy-0.5rc394-cp312-cp312-win_amd64.whl.

File metadata

File hashes

Hashes for jerboapy-0.5rc394-cp312-cp312-win_amd64.whl
Algorithm Hash digest
SHA256 45149cecd304f4cf5069ff165e8e83d9c5f84e7e7ce8575254bba5d79d772125
MD5 0656c871f9a6def207a6a05fd10c2230
BLAKE2b-256 f343ca277644818de35203931ce4e4c21156ed454eb930024af2c829386b2895

See more details on using hashes here.

File details

Details for the file jerboapy-0.5rc394-cp312-cp312-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for jerboapy-0.5rc394-cp312-cp312-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 00907c3f677df2f8084669285816e1eae979a0d4eee2b57d9f460c3697c1c776
MD5 c7a2421f123e2f9aaecdc7fb7b1f6fd6
BLAKE2b-256 a662533e48ec23e49a60555dafba3f3e0d818ef53fc388312c1900e04c100c4f

See more details on using hashes here.

File details

Details for the file jerboapy-0.5rc394-cp311-cp311-win_amd64.whl.

File metadata

File hashes

Hashes for jerboapy-0.5rc394-cp311-cp311-win_amd64.whl
Algorithm Hash digest
SHA256 1ce5a35e233a10eac568acad73c5012cfb43fe3735da71aa013999e2103bed2f
MD5 1f525f7ac9fcf9f1e7990782dcde00a4
BLAKE2b-256 4529378b5823c03304fdccb0e23ac33a1a895a0e89165cdffd612a6b82f20f21

See more details on using hashes here.

File details

Details for the file jerboapy-0.5rc394-cp311-cp311-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for jerboapy-0.5rc394-cp311-cp311-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 e4d4741b07d833746c43a887584dabcc710be38f497a6c97960c3ea2a9bc1c0d
MD5 7c0b7c553c8161d5f77e62bf173949d5
BLAKE2b-256 40e099da06711438685258b2e8726fa57a1fc84251d871c39877aedf50b98560

See more details on using hashes here.

File details

Details for the file jerboapy-0.5rc394-cp310-cp310-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for jerboapy-0.5rc394-cp310-cp310-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 97029f8b12686335fccef8a66670e289d599f3d3dafdd7f2b1c1a6b0a54665ca
MD5 cac171437345f43e793076741a0cf96d
BLAKE2b-256 04dbc39025bdd936d1e41a27f695e23f1e98709996852859769e527f5c28f546

See more details on using hashes here.

File details

Details for the file jerboapy-0.5rc394-cp39-cp39-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for jerboapy-0.5rc394-cp39-cp39-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 0d1ca9bbe15e310df834f2949145f839d176626b7b5497a0bd730339f5d85065
MD5 ecd8d10431b3a3697345f2f595be6a08
BLAKE2b-256 9d82a769d1d81324b17ccddb9b64186cba2306a963eac3744aed68ce04d5c421

See more details on using hashes here.

File details

Details for the file jerboapy-0.5rc394-cp38-cp38-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for jerboapy-0.5rc394-cp38-cp38-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 035c58e602f000e73f7094792b3f32237f67f8d789127f6ffacf5c4f416f4e18
MD5 80180358aaf0baa67c6d5d0d4daf7d31
BLAKE2b-256 53e34118db6a27ffcb01fbb26bfbd01020d4226b2fb3c8d76644e34a8128208e

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