Metadata-Version: 2.1
Name: autocat
Version: 2022.5.23
Summary: Tools for automated generation of catalyst structures and sequential learning
Home-page: https://github.com/aced-differentiate/auto_cat
Author: Lance Kavalsky
Author-email: lkavalsk@andrew.cmu.edu
License: MIT
Classifier: Development Status :: 3 - Alpha
Classifier: Programming Language :: Python :: 3.9
Description-Content-Type: text/markdown
License-File: LICENSE

# AutoCat

AutoCat is a suite of python tools for **sequential learning for materials applications**
and **automating structure generation for DFT catalysis studies.**
Documentation for the package can be found
[here](https://aced-differentiate.github.io/auto_cat).

Development of this package stems from [ACED](https://www.cmu.edu/aced/), as part of the
ARPA-E DIFFERENTIATE program.

## Installation

There are two options for installation, either via `pip` or from the repo directly.

### `pip` (recommended)

If you are planning on strictly using AutoCat rather than contributing to development,
 we recommend using `pip` within a virtual environment (e.g.
 [`conda`](https://docs.conda.io/en/latest/)
 ). This can be done as follows:

```
pip install autocat
```

### Github (for developers)

Alternatively, if you would like to contribute to the development of this software,
AutoCat can be installed via a clone from Github. First, you'll need to clone the
github repo to your local machine (or wherever you'd like to use AutoCat) using
`git clone`. Once the repo has been cloned, you can install AutoCat as an editable
package by changing into the created directory (the one with `setup.py`) and installing
via:
```
pip install -e .
```

## Contributing

Contributions through issues, feature requests, and pull requests are welcome.
Guidelines are provided [here](CONTRIBUTING.md).
