semvec/pypi-packages huggingface dataset:
AfroTranslate 0.0.6
This package allows you to obtain translations from Masakhane JoeyNMT based models. Masakhane is a grassroots research community aiming to revive and strengthen African languages through AI.
Requires Python: >=3.6

# AfroTranslate

This package allows you to obtain translations from Masakhane JoeyNMT based models with very few lines of code. Masakhane is a grassroots research community aiming to revive and strengthen African languages through AI.

Available models can be found [here](https://github.com/masakhane-io/masakhane-mt/tree/master/benchmarks).

Note: Please, install the cuda supported version of pytorch to use the GPU. Ex: pip install torch==1.8.0+cu111 -f https://download.pytorch.org/whl/torch_stable.html.


Here are some useful links:

[Masakhane](https://www.masakhane.io/): Visit the Masakhane home page.

[Masakhane web](http://translate.masakhane.io/): Get translations using the Masakhane web application.

[Masakhane Github](https://github.com/masakhane-io): Take a look at the community main projects here!

[JoeyNMT Github](https://github.com/joeynmt/joeynmt): Get hands on JoeyNMT here!

# Test it right now on [Colab](https://colab.research.google.com/drive/1_iqv6EMZ76Pkvmtb94ZxgDfIPGeaMP7-?usp=sharing)!

# Installation
pip install AfroTranslate

# Example:  

## Translation using the English to Fon model

```
from afrotranslate import MasakhaneTranslate

translator = MasakhaneTranslate(model_name="en-fon")

translator.translate("I love you so much!", n_best=1)

'Un yí wǎn nú we tawun'
```

## Loading a model from specified directory

```
translator = MasakhaneTranslate(model_path="<directory-where-your-model-resides>")
```

## Translating several sentences at once

The models are trained on individual sentences, so we automatically detect sentence boundaries in inputs and translate them separately. The output shows alternatives for each of them.

```
translator.translate("I love you so much! Our love is very strong!", n_best=1)

{'Sentence1': 'Un yí wǎn nú we tawun',
 'Sentence2': 'Wanyiyi mǐtɔn ɖò taji tawun'}
```

# Disclaimer

This is a community research project and as such, this service is not a production system. The models are only trained using religious data. Therefore, it should not be used for official translations.

# Acknowledgement

I want to thank [Julia Kreutzer](https://scholar.google.de/citations?user=j4cOSzAAAAAJ&hl=en) for her precious feedback on this work.
str-measure 0.0.3
Measure the length of a string.

# str-measure
[![Library-discord.py](https://img.shields.io/badge/Python-3.7-3778ae?logo=Python&logoColor=ffffff)](https://python.org)

# Overview
Measure the length of a string.    

# Install
Python 3 or higher is required.    
```cmd
# Linux/OS X
$ python -m pip install -U str-measure

# Windows
> py -3 -m pip install -U str-measure
```    

# Example
Measure the length.    
```py
import measure

print(measure.get_length("Hello, World!"))
```    
```
13
```
ccnet 1.0.3
A network-based single-cell RNA-seq data analysis library
Requires Python: >=3.6

# ccnet

*Ccnet*, cell-cell network, is a single-cell RNA sequencing data analysis package based on non-uniform epsilon-neighborhood network (NEN).

## Features

- Different from the traditional analysis of scRNA-seq data, which performs visualization, clustering and trajectory inference using methods based on different theories, *ccnet* accomplishes the three targets in a consistent manner.
- NEN network combines the advantages of both k-neighbors (KNN) and epsilon-neighborhood (EN) to represent the intrinsic manifold of data.


## Installation

Install *ccnet* from pip:

	pip install ccnet

Or, to build and install run from source:

	python setup.py install

## Usage

For the usage of *ccnet*, please refer to the [example](example/example_guo2010.ipynb), where we introduce the relevant analysis steps, including visualization, clustering, pseudotime ordering, finding trajectory-associated genes, etc.

## Contribute

Source Code: [https://github.com/Just-Jia/ccNet.git](https://github.com/Just-Jia/ccNet.git)

## Contacts

My email: junbo_jia@163.com

## License

The project is licensed under the GNU GPLv3 license.