semvec/pypi-packages huggingface dataset:
RefractMLMonitor 1.2.2
A Python package to monitor the drift in the machine learning models leveraging Snowflake ML Capabilities

# Drift Package

## Overview

The RefractMLMonitor Package is designed to monitor and detect data drift in machine learning models. It helps in identifying changes in the input data distribution over time, which can affect the performance of the model.

## Features

- **Feature Drift Detection**: Detects changes in the input feature's data distribution.
- **Label Drift Detection**: Identifies changes in the distribution of the labels.
- **Prediction Drift Detection**: Monitors changes in the distribution of the model predictions.
- **Performance Drift Detection**: Tracks changes in the performance metrics of the model.
- **Alert Generation**: Generates alerts when significant drift is detected.
- **Report Generation**: Provides detailed reports on the detected drift.
- **Integration with Snowflake**: Stores drift data and alerts in Snowflake tables.

## Installation

To install the Drift Package, use the following command:

```bash
pip install RefractMLMonitor
```
hbsearch 0.1.2
Various BM25 algorithms for document ranking


# Hybrid Search

## Installation

```
pip install hbsearch
```
## Usage
### Example
```
from hbsearch import hybird_search,hybird_search_top_k

toy_doc_string = (
    '精确模式，试图将句子最精确地切开，适合文本分析；全模式，'
    '把句子中所有的可以成词的词语都扫描出来, 速度非常快，但是不能解决歧义；'
    '搜索引擎模式，在精确模式的基础上，对长词再次切分，提高召回率，适合用于搜索引擎分词。'
    'I am from China, I like math.'
  )

query = '精确模式'

#chunk size for long text
chunk_size=10
# search results
results_and_score, results = hybird_search(query, toy_doc_string, chunk_size)

# print the result list
print(*results_and_score, sep="\n")


# top k search results, 
top_k = 5


# get search results
results_and_score = hybird_search_top_k(query, toy_doc_string,top_k, chunk_size)

# print the result list
print(*results_and_score, sep="\n")
```
### Output
```
----------using 2*GPUs----------
Building prefix dict from the default dictionary ...
Loading model from cache /tmp/jieba.cache
Loading model cost 0.601 seconds.
Prefix dict has been built successfully.
('精确模式，试图将句子', 0.03278688524590164)
('最精确地切开，适合文', 0.03200204813108039)
('本分析；全模式，把句', 0.03149801587301587)
('决歧义；搜索引擎模式', 0.031009615384615385)
('，在精确模式的基础上', 0.030834914611005692)
('词语都扫描出来, 速', 0.030309988518943745)
('子中所有的可以成词的', 0.03007688828584351)
('度非常快，但是不能解', 0.029857397504456328)
('，对长词再次切分，提', 0.028985507246376812)
('高召回率，适合用于搜', 0.02857142857142857)
('索引擎分词。I am', 0.028169014084507043)
(' from China', 0.027777777777777776)
(', I like math', 0.0273972602739726)
('.', 0.02702702702702703)
----------using 2*GPUs----------
('精确模式，试图将句子', 0.03278688524590164)
('最精确地切开，适合文', 0.031024531024531024)
('高召回率，适合用于搜', 0.0304147465437788)
('本分析；全模式，把句', 0.030330882352941176)
('，在精确模式的基础上', 0.03021353930031804)
```
docplates 1.0.3
Docplates is a PDF document templater which uses Jinja2 and LaTeX/WeasyPrint backends to create documents.
Requires Python: >=3.8
Keywords: documentation, templating, pdf

[![pipeline status](https://gitlab.oscdev.io/software/docplates/docplates/badges/main/pipeline.svg)](https://gitlab.oscdev.io/software/docplates/docplates/commits/main)
[![coverage report](https://gitlab.oscdev.io/software/docplates/docplates/badges/main/coverage.svg)](https://gitlab.oscdev.io/software/docplates/docplates/commits/main)

# Docplates

Docplates is a PDF document templater which uses Jinja2 and LaTeX/WeasyPrint backends to create documents.


# Installing

Docplates can be simply installed by running:

    pip install docplates

Or if you prefer the development branch, one could use:

    pip install git+https://gitlab.oscdev.io/software/docplates/docplates.git

Alternatively if you prefer installing from a checked out git repository:

    pip install .

Lastly, you could also build it and install the wheel...

    tox -e build
    pip install dist/docplates-*.whl


# Documentation

  * [Docplates Documentation](https://software.pages.oscdev.io/docplates/docplates)
  * [Contributing](https://gitlab.oscdev.io/oscdev/contributing/-/blob/master/README.md)

# Support

  * [Issue Tracker](https://gitlab.oscdev.io/software/docplates/docplates/-/issues)


# License

Docplates is licensed under the [GNU GPL v3 License](LICENSE).
ghana-nlp 0.1.5
A Python library for interacting with the GhanaNLP APIs
Requires Python: >=3.6

# Ghana NLP Python Library 

The **[Ghana NLP API](https://translation.ghananlp.org/) Python Library** provides an easy way to integrate local African language technologies into your Python projects. Whether you're looking for **translation**, **speech-to-text (STT)**, or **text-to-speech (TTS)**, this library makes it simple and intuitive to get started.

## Features

- **Translation**: Translate text between supported African languages (e.g., English to Twi).
- **Speech-to-Text (STT)**: Convert audio files into text.
- **Text-to-Speech (TTS)**: Generate natural-sounding speech from text in local languages.

## Installation

You can install the library directly from PyPI:

```bash
pip install ghana-nlp
```
And update to the lastest version

```bash
python -m pip install --upgrade ghana-nlp
```

## Usage

### Initialize the Library

First, import the library and set your API key:

```python
from ghana_nlp import GhanaNLP

nlp = GhanaNLP(api_key="your_api_key_here")
```

### Translation 

Translate from English to Twi:

```python
result = nlp.translate("Hello, how are you?", language_pair="en-tw")
print(result)  # Wo ho te sɛn?
```

### Speech-to-Text (STT)

Convert an audio file (WAV format) to text:

```python
result = nlp.speech_to_text("your_audio_file.wav", language="tw")
print(result) 
```

### Text-to-Speech (TTS)

Convert text to speech:

```python
result = nlp.text_to_speech("Good morning", lang="tw")
print(result)  # audio binary, write a code to either serve to an audio file or play directly
```

Check this repo to guide you with dealing with audio binary data: [EXAMPLE CODE](https://github.com/PhidLarkson/ghananlp-tts-python)


## Supported Languages

The library supports multiple African languages, including:
- **English (en)**
- **Twi (tw)**
- **Ga (gaa)**
- **Ewe (ee)**
- **Fante (fat)**
- **Dagbani (dag)**, and more!

## Error Handling

The library provides clear error messages if something goes wrong, such as incorrect language codes or invalid API requests. Check the `message` field in the response for details.

## License

This library is licensed under the MIT License.

---

For more details, check out the [documentation](https://pkwolffe.hashnode.dev/ghana-nlp-python-library) and start building cool stuff with **Ghana NLP**! 🎉
ezplugins 1.3.6
EZPlugins is an easy to use plugin framework.
Requires Python: >=3.8
Keywords: framework, plugin, plugins

[![pipeline status](https://gitlab.oscdev.io/software/ezplugins/badges/master/pipeline.svg)](https://gitlab.oscdev.io/software/ezplugins/commits/master)
[![coverage report](https://gitlab.oscdev.io/software/ezplugins/badges/master/coverage.svg)](https://gitlab.oscdev.io/software/ezplugins/commits/master)

# EZPlugins

EZPlugins is an easy to use plugin framework with a great deal of flexibility.


# Installing

EZPlugins can be simply installed by running:

    pip install ezplugins

Or if you prefer the development branch, one could use:

    pip install git+https://gitlab.oscdev.io/software/ezplugins.git

If you want to install from a source distribution (extract the tarball first), or checked-out git repository run the following
command:

    python setup.py install


# Documentation

  * [EZPlugins Documentation](https://software.pages.oscdev.io/ezplugins)
  * [Contributing](https://gitlab.oscdev.io/oscdev/contributing/-/blob/master/README.md)

# Support

  * [Issue Tracker](https://gitlab.oscdev.io/software/ezplugins)


# License

EZPlugins is licensed under the [MIT License](LICENSE).