semvec/pypi-packages huggingface dataset:
ebird-codes 0.0.2
Utiltities for dealing with eBird codes.
Requires Python: >=3.8
Keywords: eBird, codes, database, utilities

eBird Codes
===========
eBird Codes is a python library for working with the codes used by eBird.

Overview
--------
.. overview-start

.. overview-end

Install
-------
.. install-start

You can use either `pip`_ or `uv`_ to download the `package`_ from PyPI and
install it into a virtualenv:

.. code-block:: console

    pip install ebird-codes

or:

.. code-block:: console

    uv add ebird-codes


.. _pip: https://pip.pypa.io/en/stable/
.. _uv: https://docs.astral.sh/uv/
.. _package: https://pypi.org/project/ebird-codes/

.. install-end

Project Information
-------------------

* Issues: https://github.com/StuartMacKay/ebird-codes/issues
* Repository: https://github.com/StuartMacKay/ebird-codes

The app is tested on Python 3.8+.

eBird Codes is released under the terms of the `MIT`_ license.

.. _MIT: https://opensource.org/licenses/MIT
Smtry 1.0.7
Obfuscated Python package

# My Python Package

Bu proje, basit bir Python modÃ¼lÃ¼ iÃ§erir. ModÃ¼l, belirli iÅŸlevleri yerine getirmek iÃ§in kullanÄ±lÄ±r.

## Kurulum

### Pip ile Kurulum
escape-unk 1.6
Escape unknown symbols in SentecePiece vocabularies
Requires Python: >=3.7

# escape-unk
Escape unknown symbols in SentecePiece vocabularies.
This is particulary useful for [MarianNMT](https://github.com/marian-nmt/marian) toolkit which does not support replacing unknown tokens with most attentive word in the source (see [here](https://github.com/marian-nmt/marian-dev/issues/732), thanks to @emjotde for the idea).

**IMPORTANT NOTE**: this solution is far from ideal, as the model, especially if it has not been trained with escaped chars, may fail to copy the escaped unknown characters. Ideally, you should train your SentencePiece vocabulary with `--byte_fallback` option. This is just a workaround for scenarios where model does not have byte fallback or can not be re-trained.

## Install
Just install it from PyPi
```
pip install escape-unk
```

## Background
There are some scenarios where your machine translation model has to translate sentencences containing characters unknown for the SentencePiece vocabulary.
Neural models usually start to hallucinate, throw out garbage or just don't know hot to translate when an unknown character comes to the input.
In the cases where those characters simply need to be copied, escaping them to their hexadecimal representation, can be useful if the model manages to copy the escaped symbols.

Escape Chinese characters in an English-German vocabulary is just like:
```bash
echo "Beijing (Chinese: 北京) is the capital of the People's Republic of China" | escape-unk -m vocab.deen.spm
```
```
Beijing (Chinese: [[e58c97e4baac]]) is the capital of the People's Republic of China
```

or escaping emojis
```bash
echo "I ❤️ you" | escape-unk -m vocab.deen.spm
```
```
I [[e29da4efb88f]] you
```

So instead of:
```bash
echo "Beijing (Chinese: 北京) is the capital of the People's Republic of China" | marian-decoder -c model.config.yml
```
```
Peking (chinesisch: ) ist die Hauptstadt der Volksrepublik China
```

we will have:
```bash
echo "Beijing (Chinese: 北京) is the capital of the People's Republic of China" | escape-unk -m vocab.deen.spm | marian-decoder -c model.config.yml
```
```
Beijing (chinesisch: [[e58c97e4baac]]) ist die Hauptstadt der Volksrepublik China
```

and the full pipeline with `unescape-unk`:
```bash
echo "Beijing ..." | escape-unk -m vocab.deen.spm | marian-decode -c config.yml | unescape-unk
```
```
Beijing (chinesisch: 北京) ist die Hauptstadt der Volksrepublik China
```

**WARNING**: if an escaped sequence is not correctly copied by the translator and generates an invalid sequence,
the character is omitted and substituted by an empty string.
If you want it to fail when this happens, use `--strict`/`-s` mode with `unescape-unk` command.
Nezuki 2.0.1
Un pacchetto di moduli che implementa funzionalità relative all'Home Server e gestione dei servizi forniti dalla Domotica. I moduli forniti anche se usati dal server della domotica possono essere utilizzati in qualsiasi ambito se il loro utilizzo rispechcia pienamente le necessità.
Requires Python: >=3.11
Keywords: nezuki

# Nezuki

Nezuki è una libreria Python modulare per varie integrazioni relativi all'Home Server con Ubuntu.

Il modulo Nezuki include una serie di funzionalità relative alla gestioned el server ma anche della domotica ed offre funzionalità che possono essere usate anche fuori da questi contesti.

## Caratteristiche

Per visualizzare aggiornamenti, deprecazioni, nuove funzionalità vedere il file CHANGELOG.md

Ogni modulo ha la sua relativa documentazione specifica, per un uso specifico e dettagliato visualizzare la relativa documentazione (README.md), di seguito un uso generale e piccola demo su come installare Nezuki e qualche esempio di funzionamento.

## Installazione

Puoi installare Nezuki tramite pip:

```bash
pip install Nezuki
```

## Esempio