pysphalt 0.1.18

Library of Descriptive and Predictive Models for Brazilian Asphalt Materials Data

Pysphalt

Library of machine learning models for Brazilian asphalt material data.

• Installation
• Local Quickstart
  • 1. Install dependencies
• Building Docs
• Deploy to PyPi

Installation

pip install pysphalt

Local Quickstart

The fastest way to get Pysphalt up and running locally for development.

1. Install dependencies

There are three things to install

1. Conda
2. Python libraries
3. Pre-commit hooks

Create a new miniconda environment.

conda create -n pysphalt python=3.10
conda activate pysphalt

Install all python libraries. Libraries related to development are kept separate, in requirements-dev.txt. Make sure to add any dependencies you introduce into these files!

pip install -r requirements.txt -r requirements-dev.txt

Install pre-commit and spin it up:

pre-commit install
pre-commit

⚠️ Whenever you work on this codebase, remember to activate the conda environment:

conda activate pysphalt

Building Docs

cd docs
make html

You can access the generated docs on docs/build/html/index.html

Deploy to PyPi

Deploys to PyPi are managed automatically by Github Actions. To upload a new version of the library, just bump the version field on pyproject.toml and push a new tag to main. The Action to publish a new version to PyPi will be triggered by the pushing the tag.