nmesh 0.1.2

GNU Tools for python

NMesh

Modules • Code structure • Installing the application • Makefile commands • Environments • Running the application Ressources

NMesh is a Python package that provides two high-level features:

• A simple Mesh processor
• A list of tool to convert mesh files into point cloud

You can reuse your favorite Python packages such as NumPy, SciPy and Cython to extend ZakuroCache integration.

Modules

At a granular level, NMesh is a library that consists of the following components:

Component	Description
nmesh	Contains the implementation of NMesh
nmesh.core	Contain the functions executed by the library.
nmesh.pc	Processor for the point cloud
nmesh.tests	Unit tests

Code structure

from setuptools import setup
from nmesh import __version__
setup(
    name='nmesh',
    version=__version__,
    packages=[
        "nmesh",
        "nmesh.core",
        "nmesh.pc",
        "nmesh.tests"
    ],
    url='https://github.com/JeanMaximilienCadic/nmesh',
    include_package_data=True,
    package_data={"": ["*.yml"]},
    long_description="".join(open("README.md", "r").readlines()),
    long_description_content_type='text/markdown',
    license='MIT',
    author='Jean Maximilien Cadic',
    python_requires='>=3.6',
    install_requires=[r.rsplit()[0] for r in open("requirements.txt")],
    author_email='[e-mail]',
    description='GNU Tools for python',
    classifiers=[
        "Programming Language :: Python :: 3.6",
        "License :: OSI Approved :: MIT License",
    ]
)

Installing the application

To clone and run this application, you'll need the following installed on your computer:

• Git
• Docker Desktop
  • Install Docker Desktop on Mac
  • Install Docker Desktop on Windows
  • Install Docker Desktop on Linux
• Python

Install the package:

# Clone this repository and install the code
git clone https://github.com/JeanMaximilienCadic/nmesh

# Go into the repository
cd nmesh

Makefile commands

Exhaustive list of make commands:

install_wheels
sandbox_cpu
sandbox_gpu
build_sandbox
push_environment
push_container_sandbox
push_container_vanilla
pull_container_vanilla
pull_container_sandbox
build_vanilla
build_wheels
auto_branch 

Environments

Docker

Note

Running this application by using Docker is recommended.

To build and run the docker image

make build
make sandbox

PythonEnv

Warning

Running this application by using PythonEnv is possible but not recommended.

make install_wheels

Running the application

from nmesh import NMesh, cfg
m = NMesh(cfg.drive.bull)
m.show()

Ressources

• Vanilla: https://en.wikipedia.org/wiki/Vanilla_software
• Sandbox: https://en.wikipedia.org/wiki/Sandbox_(software_development)
• All you need is docker: https://www.theregister.com/2014/05/23/google_containerization_two_billion/
• Dev in containers : https://code.visualstudio.com/docs/remote/containers
• Delta lake partitions: https://k21academy.com/microsoft-azure/data-engineer/delta-lake/