```{toctree}
:caption: User Guide
:hidden:
installation/index
fundamentals/index
tutorial/index
```

```{toctree}
:caption: Reference
:hidden:
reference/index
reference/cli
```

```{toctree}
:caption: Contributing Guide
:hidden:
dev/contributing
dev/dev_installation
```

```{toctree}
:caption: About
:hidden:
about/changelog
about/license
```

# LobsterPy documentation

**Date**: {sub-ref}`today`

**Useful links**:
[Github Repository](https://github.com/DigiMatChem/LobsterPy) |
[PyPI](https://pypi.org/project/lobsterpy/) |
[Issues & Ideas](https://github.com/DigiMatChem/LobsterPy/issues) |

LobsterPy is a package that enables automatic analysis of LOBTSER outputs to get summarized bonding information and relevant bond plots. Additionally, one can also generate features for machine learning studies from LOBSTER outputs.

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:class-container: text-center
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:::{grid-item-card}
:link: fundamentals/index
:link-type: doc
:class-header: bg-light
**Fundamental Aspects**
^^^
This guide contains a detailed explanation of the key functionalites on 
which LobsterPy automatic analysis is based on.
:::

:::{grid-item-card}
:link: installation/index
:link-type: doc
:class-header: bg-light
**User Guide**
^^^
This guide provides in-depth information for getting started and tutorials for *LobsterPy*.
:::

:::{grid-item-card}
:link: https://materialsproject.github.io/atomate2/user/codes/vasp.html#lobster
:class-header: bg-light
**LOBSTER Workflow**
^^^
Here you can find how to use our completely automated workflow to perform bonding analysis with 
LOBSTER and Lobsterpy via atomate2.
:::


:::{grid-item-card}
:link: dev/dev_installation
:link-type: doc
:class-header: bg-light
**Developer guide**
^^^
Do you want contribute or improve existing functionalities?
Check out the developer guide.
:::
::::