semvec/pypi-packages huggingface dataset:
nada-numpy 0.6.0
Nada-Numpy is a Python library designed for algebraic operations on NumPy-like array objects on top of Nada DSL and Nillion Network.
Requires Python: <4.0,>=3.10

# Nada-Numpy

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## Features

### Use Numpy Array Features

- **Dot Product**: Compute the dot product between two NadaArray objects.
- **Element-wise Operations**: Perform element-wise addition, subtraction, multiplication, and division with broadcasting support.
- **Stacking**: Horizontally and vertically stack arrays.

### Use additional Array helpers

- **Shuffling**: Our implementation shuffles a 1D array using the Benes network, which rearranges elements in a deterministic yet seemingly random order. The Benes network is commonly used in sorting and switching circuits and requires the input array length to be a power of two (e.g., 2, 4, 8, 16). The shuffled array contains the same elements as the input, just in a different order.

### Use Decimal Numbers in Nada

- **Rational Number Support**: Our implementation of `Rational` and `SecretRational` allows the use of simplified implementations of decimal numbers on top of Nillion.

## Installation

### Using pip

```bash
pip install nada-numpy
```

### From Sources

You can install the nada-numpy library using Poetry:

```bash
git clone https://github.com/NillionNetwork/nada-numpy.git
pip3 install ./nada-numpy
```

## Testing

To test that the version installed works as expected, you can use poetry as follows:

```bash
poetry install
poetry run pytest
```

## Join Nillion community and contribute

Please join the Nillion community on [Discord](https://discord.com/invite/nillionnetwork).

See the [CONTRIBUTING](./CONTRIBUTING.md) file for how to contribute to `nada-numpy`.

## License

This project is licensed under the Apache2 License. See the LICENSE file for details.
nagausspy 0.2
Tools for reading and analyzing Gaussian output files
Requires Python: >=3.8

# NaGausspy
[![coverage report](https://gitlab.com/nafomat/nagausspy/badges/master/coverage.svg)](https://gitlab.com/nafomat/nagausspy/-/commits/master)
[![pipeline status](https://gitlab.com/nafomat/nagausspy/badges/master/pipeline.svg)](https://gitlab.com/nafomat/nagausspy/-/commits/master)
[![Latest Release](https://gitlab.com/nafomat/nagausspy/-/badges/release.svg)](https://gitlab.com/nafomat/nagausspy/-/releases)


## Installation
The easiest way of installation is using Pypi with pip:
`pip install nagausspy`

## Documentation
The documentation is available at [Gitlab Pages](https://nafomat.gitlab.io/nagausspy/)

## TODO

- Add more tests
- Improve optimization step reading
- Simpler and clear documentation