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-0.2rc340-cp313-cp313t-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl (1.8 MB view details)

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

jerboapy-0.2rc340-cp313-cp313-win_amd64.whl (3.1 MB view details)

Uploaded CPython 3.13Windows x86-64

jerboapy-0.2rc340-cp313-cp313-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl (1.4 MB view details)

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

jerboapy-0.2rc340-cp313-cp313-macosx_12_0_x86_64.whl (1.2 MB view details)

Uploaded CPython 3.13macOS 12.0+ x86-64

jerboapy-0.2rc340-cp312-cp312-win_amd64.whl (2.1 MB view details)

Uploaded CPython 3.12Windows x86-64

jerboapy-0.2rc340-cp312-cp312-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl (1.1 MB view details)

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

jerboapy-0.2rc340-cp312-cp312-macosx_12_0_x86_64.whl (891.0 kB view details)

Uploaded CPython 3.12macOS 12.0+ x86-64

jerboapy-0.2rc340-cp311-cp311-win_amd64.whl (1.0 MB view details)

Uploaded CPython 3.11Windows x86-64

jerboapy-0.2rc340-cp311-cp311-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl (710.7 kB view details)

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

jerboapy-0.2rc340-cp311-cp311-macosx_15_0_arm64.whl (305.3 kB view details)

Uploaded CPython 3.11macOS 15.0+ ARM64

jerboapy-0.2rc340-cp311-cp311-macosx_12_0_x86_64.whl (593.8 kB view details)

Uploaded CPython 3.11macOS 12.0+ x86-64

jerboapy-0.2rc340-cp310-cp310-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl (364.3 kB view details)

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

jerboapy-0.2rc340-cp310-cp310-macosx_12_0_x86_64.whl (305.5 kB view details)

Uploaded CPython 3.10macOS 12.0+ x86-64

jerboapy-0.2rc340-cp39-cp39-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl (2.5 MB view details)

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

jerboapy-0.2rc340-cp38-cp38-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl (2.1 MB view details)

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

File details

Details for the file jerboapy-0.2rc340-cp313-cp313t-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for jerboapy-0.2rc340-cp313-cp313t-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 19e4706395c895d51c43ffafbacaba94c370e545212a14ec0b9a0c3d99ffc8c4
MD5 66f34c628ae8fe93b31a8ea70a7f4896
BLAKE2b-256 4647c34d740205cae4cb9ef194fdb5dbc8e4e83f5b5e44acb73496d487bf0ec3

See more details on using hashes here.

File details

Details for the file jerboapy-0.2rc340-cp313-cp313-win_amd64.whl.

File metadata

File hashes

Hashes for jerboapy-0.2rc340-cp313-cp313-win_amd64.whl
Algorithm Hash digest
SHA256 76e4c4402c8c5d03bd9bc0d9b281aa50b2cf172d5d74f6d4cb3dd0dfd93f199e
MD5 a60e1271849ea0f267ed87bbf197bf0c
BLAKE2b-256 5fc0438484556afb6a368a6f985d704c52a464e2d29a55917130230288c82fde

See more details on using hashes here.

File details

Details for the file jerboapy-0.2rc340-cp313-cp313-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for jerboapy-0.2rc340-cp313-cp313-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 eed352ef7809c6dcda99c8c954c2763435032b8ef82f3fb649c0f651166cfb1c
MD5 b3b30c99326c9f1a51316c08359e7b4b
BLAKE2b-256 4b6f6786f6613e3b2cc91af3dd1030ada993082da227b3d0ca1af40e1245cab3

See more details on using hashes here.

File details

Details for the file jerboapy-0.2rc340-cp313-cp313-macosx_12_0_x86_64.whl.

File metadata

File hashes

Hashes for jerboapy-0.2rc340-cp313-cp313-macosx_12_0_x86_64.whl
Algorithm Hash digest
SHA256 d75befa5635dea43a65398a8b649de05ec9d8b982d836804e3aa9f4adb687a3a
MD5 8ae82626502c713a4dc8cf3b3049cb3d
BLAKE2b-256 abc37f7294fee5b3e980145acc4983f05365a471664c543f84331137b89d6a6a

See more details on using hashes here.

File details

Details for the file jerboapy-0.2rc340-cp312-cp312-win_amd64.whl.

File metadata

File hashes

Hashes for jerboapy-0.2rc340-cp312-cp312-win_amd64.whl
Algorithm Hash digest
SHA256 5faeba0c988077613e8882a03f0a641724aa527fa4a68bfac3d6c329f6299921
MD5 4f31c0001321b4571a7a963c8e90a9eb
BLAKE2b-256 531063bb2bfbf9d1f75bb560c55efdd08f1133b8e0f29341969d7316c94cad94

See more details on using hashes here.

File details

Details for the file jerboapy-0.2rc340-cp312-cp312-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for jerboapy-0.2rc340-cp312-cp312-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 f32e8e91ad314d5888c828e88ebff48e621b7099de8ec00dbd799830e4c05d72
MD5 1ca6a687ba1e7f584e42be6f69ae1eb8
BLAKE2b-256 9dcaa2bc5a0674a454756e7a13454775ca8897a3ea7401dc0680c7516b6f7d42

See more details on using hashes here.

File details

Details for the file jerboapy-0.2rc340-cp312-cp312-macosx_12_0_x86_64.whl.

File metadata

File hashes

Hashes for jerboapy-0.2rc340-cp312-cp312-macosx_12_0_x86_64.whl
Algorithm Hash digest
SHA256 4d20ff0548d187878989c8cf6b9d62e397bf136a64c0aed85bcaa94f9d849f47
MD5 14a70333bad56d910850ede5983f30c5
BLAKE2b-256 82f316ef61a97c0446e84f91c421ef2aefa7ec12953c8a49bf3f60d2534357a0

See more details on using hashes here.

File details

Details for the file jerboapy-0.2rc340-cp311-cp311-win_amd64.whl.

File metadata

File hashes

Hashes for jerboapy-0.2rc340-cp311-cp311-win_amd64.whl
Algorithm Hash digest
SHA256 0c4d0254d90707ce0526e99bef75b276408f2d862cc1532d2a2813ca2975154b
MD5 c6deaeb5d08c84bea6c3abd19bc7ebe3
BLAKE2b-256 61041a269f61ae5ac63caad80ff6e9b87ec8a3cd2b1b9152862f1fa2345565cf

See more details on using hashes here.

File details

Details for the file jerboapy-0.2rc340-cp311-cp311-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for jerboapy-0.2rc340-cp311-cp311-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 33e78d785ea88494ec9d3a2b57b44be65bfe862993a3303a88f5504f68b0b428
MD5 57aebb5f32517261aeac15417ca2af85
BLAKE2b-256 d2701d930e0540fe780f0de4203408974dd932a08439acb7c59cbc86d937dbe3

See more details on using hashes here.

File details

Details for the file jerboapy-0.2rc340-cp311-cp311-macosx_15_0_arm64.whl.

File metadata

File hashes

Hashes for jerboapy-0.2rc340-cp311-cp311-macosx_15_0_arm64.whl
Algorithm Hash digest
SHA256 90b80d5e9cac1bfa0aad3d427f179b818a2db5b981079f0a0ce787390bb1de5c
MD5 49ab24915d10883abb0d057e83f398f6
BLAKE2b-256 a164641ec60c4d9c8b8e686c4531f7c88aa065df6fa0cc5e685af572149948a6

See more details on using hashes here.

File details

Details for the file jerboapy-0.2rc340-cp311-cp311-macosx_12_0_x86_64.whl.

File metadata

File hashes

Hashes for jerboapy-0.2rc340-cp311-cp311-macosx_12_0_x86_64.whl
Algorithm Hash digest
SHA256 ffa2eae862fead8baf36af95fff045079fa58696d16eb9cb40e58c2d5578b64a
MD5 6ff7eed50c9ecb49741464613d9648b4
BLAKE2b-256 2fdc525be1ef3e9b64680ace5d43602c0a55b37c13099c92a22d5f13c316b9e5

See more details on using hashes here.

File details

Details for the file jerboapy-0.2rc340-cp310-cp310-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for jerboapy-0.2rc340-cp310-cp310-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 1702aa3cbed8ca6ae5a950015754a96cb8e091debeb50b7e38e9da0657f51071
MD5 f895e6b068f427e9c972d3c9a454b4b9
BLAKE2b-256 e4b4e26e1238a9f2bb847cc6708363778168dcb30be6b0a3ec6e38a0d029d46e

See more details on using hashes here.

File details

Details for the file jerboapy-0.2rc340-cp310-cp310-macosx_12_0_x86_64.whl.

File metadata

File hashes

Hashes for jerboapy-0.2rc340-cp310-cp310-macosx_12_0_x86_64.whl
Algorithm Hash digest
SHA256 bd08cb8a728dd6754c9c677057e731d37cc2165f8c998d8dd9ba88218ebbecdf
MD5 4bf264343a5f5db15cea312739bb07fc
BLAKE2b-256 001c7bdb2a51ec162a198a48d6b9156165f173597e8a49ac2c7dd53d94f8d2dd

See more details on using hashes here.

File details

Details for the file jerboapy-0.2rc340-cp39-cp39-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for jerboapy-0.2rc340-cp39-cp39-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 3bff6bcc84cf86eed4148c8ab0573386f9518f69371840d56ac5e9b212806910
MD5 f86f3a2c82dbf16a5242a6e8f42c03b8
BLAKE2b-256 f589170227bc92a7a76ab715aee24a84397d2724b4621af13285c96dd5094bcc

See more details on using hashes here.

File details

Details for the file jerboapy-0.2rc340-cp38-cp38-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for jerboapy-0.2rc340-cp38-cp38-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 f4342afd68d24c43bf3e470aa835891788af6fff25ee98a9d96b51a52f922bd4
MD5 a6dd2553584d26f924676cd254e867e7
BLAKE2b-256 925ff1de5258840d06da1fd7a71cdaad98fbf88278fa7feb25ef47042eaf7f44

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