semvec/pypi-packages huggingface dataset:
nn-zoo 1.1.1
A collection of PyTorch utilities
License: MIT
Requires Python: >=3.11
Keywords: pytorch, machine-learning, deep-learning

# nn-zoo

![PyPI - Python Version](https://img.shields.io/pypi/pyversions/nn-zoo)
![PyPI - Version](https://img.shields.io/pypi/v/nn-zoo)
![PyPI - License](https://img.shields.io/pypi/l/nn-zoo)
![PyPI - Downloads](https://img.shields.io/pypi/dm/nn-zoo)

## Overview

This repository contains a collection reusable machine learning models and utilities. The goal is to provide a set of tools that can be easily integrated into other projects. The models are implemented using PyTorch and are designed to be easily extended and modified. Inspired by projects like [Hugging Face Transformers](https://github.com/huggingface/transformers) and [PyTorch Lightning](https://github.com/Lightning-AI/pytorch-lightning).

## Table of Contents

- [Overview](#overview)
- [Installation](#installation)
- [Contributing](#contributing)
- [License](#license)

## Installation

To install the package, run the following command:

```bash
pip install nn-zoo
```

## Contributing

Contributions are welcome! For bug reports or requests please submit an issue.
To install the package in development mode, run the following command:

```bash
git clone https://github.com/karanravindra/nn-zoo.git
cd nn-zoo
pip install -r dev-requirements.txt
```

## License

This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.
MolVizr3D 1.0.0
MolVizr3D: Molecular Visualizer in 3D.
License: MIT
Requires Python: >=3.6
Keywords: python, chemistry, chemistry-visualization, MolVizr3D


# MolVizr3D: Molecular Visualizer in 3D



![Downloads](https://img.shields.io/pypi/dm/MolVizr3D) ![PyPI](https://img.shields.io/pypi/v/MolVizr3D) ![Python Version](https://img.shields.io/pypi/pyversions/MolVizr3D.svg) ![License](https://img.shields.io/pypi/l/MolVizr3D)



MolVizr3D is a Python package designed to provide an intuitive and powerful solution for visualizing molecular structures in three dimensions. This package supports various molecule formats such as SDF, MOL, and more, allowing users to easily load and render complex molecular structures with high-quality 3D graphics.



**Key Features:**



* `Wide Format Support:` Load and visualize molecular structures from various file formats including SDF, MOL, and others.

* `High-Quality 3D Rendering:` Generate detailed and accurate 3D visualizations of molecular structures.

* `Interactive Visualization:` Rotate, zoom, and explore molecules interactively to better understand their geometry and properties.

* `Customization:` Customize visual aspects such as colors, styles, and labels to suit your specific needs.

* `Integration:` Seamlessly integrates with other computational chemistry tools and workflows.



The current version parse only `sdf` files!



## Installation



Install MolVizr3D with pip



```python

  pip install MolVizr3D

```



## Examples



Import package as:



```python

import molvizr3d as mv3d

```



To check mv3d version:



```python

# check mv3d version

print(mv3d.__version__)



# this version parse only sdf files

```



To visualize the structure of compound using its `sdf` file:



```python

# sdf file

sdf_file_name_1 = 'test\Conformer3D_COMPOUND_CID_7979.sdf'

sdf_file = os.path.join(os.getcwd(), sdf_file_name_1)



# visualize compound by sdf file

mv3d.td(sdf_file)

```



To visualize the structure of compound using its InChI



```python

# InChI

inchi = 'InChI=1S/C3H8/c1-3-2/h3-4H,1H2,2H3'



# visualize compound by inchi

mv3d.td_by_inchi()

```



## FAQ



For any question, contact me on [LinkedIn](https://www.linkedin.com/in/sina-gilassi/) 



## Authors



- [@sinagilassi](https://www.github.com/sinagilassi)
Ominis-OSINT 0.4.8
Discover online mentions of a query or username. Identify potential social profiles and forums.
License: MIT
Requires Python: >=3.9


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