semvec/pypi-packages huggingface dataset:
name2gender 0.0.5
From names in multiple languages to genders.
Requires Python: >=3.10

# Name2Gender

From names in multiple languages to genders.

## Installation

- From [PyPi](https://pypi.org/project/name2gender/)

```
pip install -U name2gender
```

or

```
uv add -U name2gender
```

- From [Github](https://github.com/vortezwohl/Name2Gender/releases)

```
pip install git+https://github.com/vortezwohl/Name2Gender.git
```

## Quick Start

1. **Import SDKs**

    ```python
    from name2gender import Name2Gender, Gender
    ```

2. **Gender recognition based on names**

    ```python
    n2g = Name2Gender()
    names = ['吴子豪', '吴彦祖', '梅艳芳', '张曼玉',
             'Donald Trump', 'Ivanka Trump',
             'Justin Bieber', 'The Weeknd',
             'Luigi Nicholas Mangione',
             'Elizabeth II', 'Henry VIII']
    for name in names:
        _gender, _prob = n2g(name, return_probability=True)
        print(name, 'is', _gender, 'with a probability of', f'{_prob * 100:.2f}%')

    ```

    stdout:

    ```
    吴子豪 is Gender.Male with a probability of 99.71%
    吴彦祖 is Gender.Male with a probability of 100.00%
    梅艳芳 is Gender.Female with a probability of 99.99%
    张曼玉 is Gender.Female with a probability of 99.92%
    Donald Trump is Gender.Male with a probability of 99.90%
    Ivanka Trump is Gender.Female with a probability of 99.66%
    Justin Bieber is Gender.Male with a probability of 100.00%
    The Weeknd is Gender.Male with a probability of 97.66%
    Luigi Nicholas Mangione is Gender.Male with a probability of 99.27%
    Elizabeth II is Gender.Female with a probability of 99.71%
    Henry VIII is Gender.Male with a probability of 99.90%
    ```

## Use Name2Gender with CLI

1. **Install model**

    ```
    n2g install name2gender-small
    ```

    stdout:

    ```
    Successfully installed model "name2gender-small".
    ```

2. **Predict genders**

    ```
    n2g predict LadyGaga
    ```

    stdout:

    ```
    "LadyGaga" is FEMALE with an probability of 99.64%.
    ```

3. **Uninstall model**

    ```
    n2g uninstall name2gender-small
    ```

    stdout:

    ```
    Model "name2gender-small" is uninstalled.
    ```
machc.core 0.0.1
Provides entities and interactors for the e-commerce business domain.
Requires Python: ==3.8.0

# Machc Core   

Machc Core provides the foundational entities and interactors for the e-commerce business domain, 
enabling developers to build scalable and maintainable applications within the Machanism ecosystem.
It includes essential components such as product management, order processing, and customer 
interactions, all designed to work seamlessly with other Machc modules.

For more information, visit the [Core Lib](https://machc.machanism.org/core/machc.core/index.html).
guanaco 0.3.4
3D CTF correction
Keywords: Tomography

# guanaco
> Python library for doing 3D CTF correction

[![Code style: black](https://img.shields.io/badge/code%20style-black-000000.svg)](https://github.com/psf/black)
[![Language grade: Python](https://img.shields.io/lgtm/grade/python/g/jmp1985/guanaco.svg?logo=lgtm&logoWidth=18)](https://lgtm.com/projects/g/jmp1985/guanaco/context:python)
[![Total alerts](https://img.shields.io/lgtm/alerts/g/jmp1985/guanaco.svg?logo=lgtm&logoWidth=18)](https://lgtm.com/projects/g/jmp1985/guanaco/alerts/)
[![Building](https://github.com/rosalindfranklininstitute/guanaco/actions/workflows/python-package.yml/badge.svg)](https://github.com/rosalindfranklininstitute/guanaco/actions/workflows/python-package.yml)
[![Publishing](https://github.com/rosalindfranklininstitute/guanaco/actions/workflows/python-publish.yml/badge.svg)](https://github.com/rosalindfranklininstitute/guanaco/actions/workflows/python-publish.yml)
[![DOI](https://zenodo.org/badge/337997172.svg)](https://zenodo.org/badge/latestdoi/337997172)

## Installation

In order to build this package, the following dependencies are required:

- The CUDA toolkit
- FFTW

To install from the github repository do the following

```sh
export CUDACXX=${PATH_TO_CUDA}/bin/nvcc
python -m pip install git+https://github.com/rosalindfranklininstitute/guanaco.git@master
```

To install from source, clone this repository. The repository has a submodule
for pybind11 so after cloning the repository run

```sh
git submodule update --init --recursive
```

Then do the following:

```sh
export CUDACXX=${PATH_TO_CUDA}/bin/nvcc
python -m pip install .
```

If you would like to run the tests then, clone this repository and then do the following:

```sh
export CUDACXX=${PATH_TO_CUDA}/bin/nvcc
python -m pip install .[test]
```

## Installation for developers

To install for development, clone this repository and then do the following:

```sh
export CUDACXX=${PATH_TO_CUDA}/bin/nvcc
python -m pip install -e .
```

## Testing

To run the tests, follow the installation instructions for developers and then do the following:

```sh
pytest
```

## Usage

To do a tomographic reconstruction with no CTF correction do something do the following

```sh
guanaco -i images.mrc -o rec.mrc -d gpu
```

To correct all images with the same single defocus something do the following

```sh
guanaco -i images.mrc -o rec.mrc -d gpu --df=20000 --Cs=2.7
```

To correct all images with the same defocus range something do the following

```sh
guanaco -i images.mrc -o rec.mrc -d gpu --df=20000 --Cs=2.7 --ndf=10
```

## Issues

Please use the [GitHub issue tracker](https://github.com/rosalindfranklininstitute/guanaco/issues) to submit bugs or request features.

## License

Copyright Diamond Light Source and Rosalind Franklin Institute, 2021

Distributed under the terms of the GPLv3 license, guanaco is free and open source software.