Metadata-Version: 2.1
Name: pysphalt
Version: 0.1.16
Summary: Library of Descriptive and Predictive Models for Brazilian Asphalt Materials Data
Home-page: https://pysphalt.readthedocs.io
Author: Rodrigo Castanon
Author-email: Rodrigo Castanon <rodrigo.castanon@poli.ufrj.br>
License: MIT License
        
        Copyright (c) 2023 pysphalt
        
        Permission is hereby granted, free of charge, to any person obtaining a copy
        of this software and associated documentation files (the "Software"), to deal
        in the Software without restriction, including without limitation the rights
        to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
        copies of the Software, and to permit persons to whom the Software is
        furnished to do so, subject to the following conditions:
        
        The above copyright notice and this permission notice shall be included in all
        copies or substantial portions of the Software.
        
        THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
        IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
        FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
        AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
        LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
        OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
        SOFTWARE.
        
Project-URL: Homepage, https://pysphalt.readthedocs.io
Project-URL: Documentation, https://pysphalt.readthedocs.io
Project-URL: Repository, https://github.com/pysphalt/pysphalt
Project-URL: Issues, https://github.com/pysphalt/pysphalt/issues
Classifier: Intended Audience :: Developers
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.10
Description-Content-Type: text/markdown
License-File: LICENSE

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<h1 align="center">Pysphalt</h1>

Library of machine learning models for Brazilian asphalt material data.

-   [Installation](#installation)
-   [Local Quickstart](#local-quickstart)
    -   [1. Install dependencies](#1-install-dependencies)
-   [Building Docs](#building-docs)

## Installation

```shell
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
3. Python libraries
4. Pre-commit hooks

Create a new miniconda environment.

```shell
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!

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

Install `pre-commit` and spin it up:

```shell
pre-commit install
pre-commit
```

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

## Building Docs

```shell
cd docs
make html
```

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