semvec/pypi-packages huggingface dataset:
musconv 0.0.2
Generate supercell and check supercell convergence with SCF forces
License: MIT

# musconv

musconv is a python package for generating near cubic supercells and for checking the convergence of a supercell size with respect to atomic forces induced by an interstitial impurity at a Voronoi site.

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|-----|----------------------------------------------------------------------------|
|Latest release| [![PyPI version](https://badge.fury.io/py/musConv.svg)](https://badge.fury.io/py/musConv) [![License](https://img.shields.io/github/license/positivemuon/musConv.svg)](https://pypi.org/project/musConv/) |

## Installation
1.) Install from [pypi](https://pypi.org/project/musconv/0.0.1/) as;

```pip install musconv```


2.) Install the repository as:

```
git clone https://github.com/positivemuon/musconv.git
cd musconv/
python setup.py install
```



## Available Scripts
```
musConv/
    ├── __init__.py
    └── supcgen.py
    └── chkconv.py
```

## i.) supcgen.py

Generates a nearly cubic supercell (SC) using the pymatgens [CubicSupercellTransformation](https://pymatgen.org/pymatgen.transformations.advanced_transformations.html). Inserts an intersitial atom (default is hydrogen) in the supercell
at a Voronoi interstitial site. One of it methods initializes the  supercell generation and the other re-initializes generation of a
larger supercell-size than the former.

To quickly run the script if installed try;

 ```python examples/run_supcgen.py```

when not installed try:

```python musconv/supcgen.py examples/LiF.cif```


## ii.) chkconv.py

This script checks if a supercell (SC) size is converged for muon site calculations
using results of unrelaxed atomic forces from a one shot DFT SCF calculation
or other potential. Structure input is an ase Atom data while forces as array data.

To quickly run the script if installed try;

```python examples/run_chkconv.py```

or

```python examples/run_chkconv2.py  examples/LiF.cif```

when not installed try:

```python musconv/chkconv.py examples/LiF_p1.cif examples/LiF_p1_forces.txt```
airlabs 0.0.7
Python wrapper for AirLabs
License: MIT

**Project Portfolio: https://github.com/calebyhan/CalebHan**

[![PyPI version](https://badge.fury.io/py/airlabs.svg)](https://badge.fury.io/py/airlabs)
[![Documentation Status](https://readthedocs.org/projects/airlabs/badge/?version=latest)](https://airlabs.readthedocs.io/en/latest/?badge=latest)

# airlabs

Python wrapper for [AirLabs](https://airlabs.co/).


## Installation
----------------------

Use the package manager [pip](https://pip.pypa.io/en/stable/) to install airlabs.

```bash
pip install airlabs
```


## Usage
----------------------

```python
import airlabs

# Gets airline information about American Airlines
airlabs.airlines(iata_code="AA")

# Gets information about real-time flights
airlabs.flights()
```


## Documentation
----------------------

Documentation found in https://airlabs.readthedocs.io/en/latest/.


## Contributing
----------------------

Pull requests are welcome. For major changes, please open an issue first
to discuss what you would like to change.

Please make sure to update tests as appropriate.


## License
----------------------

[MIT](https://choosealicense.com/licenses/mit/)
dbt-schema-generator 0.1.1a2
A command-line tool to generate schema.yml files for specified dbt models
License: MIT
Requires Python: >=3.9

# dbt Schema Generator

A command-line tool to generate schema.yml files for specified dbt models.

## Installation

Install the package using pip:

```
pip install dbt_schema_generator
```

# Usage

You can use the dbt_schema_generator command-line tool with the following options:

-m, --models: A comma-separated list of model names to include in the schema.yml file.
-p, --path: A path to include models in the schema.yml file.


Examples:

```
dbt_schema_generator -m model1,model2,model3
dbt_schema_generator --models model1,model2,model3
```

```
# Using this format, dbt_schema_generator would generate a schema.yml file for all models within your_folder
dbt_schema_generator -path models/your_folder
dbt_schema_generator --path models/your_folder
```
NOTE: When using path the format should always be models/ the folder unless you have changed the model-paths in your dbt_project.yml

**NOTE: When using the `--path` option, the format should always be `models/your_folder` unless you have changed the `model-paths` in your `dbt_project.yml`.**



## **!!!!IMPORTANT!!!!: Be very careful when using the --path method as this would overwrite any schema.yml currently within the folder**