semvec/pypi-packages huggingface dataset:
cvo251203app 0.2.0
Development flow as Paleofuturistic Python
Requires Python: >=3.12

# cvo251203app

Development flow as Paleofuturistic Python!!!

## Usage

Legacy: `pip install cvo251203app`

Preferred: `uv add cvo251203app`

## Developing further

> Development flow as [Paleofuturistic Python](https://github.com/schubergphilis/paleofuturistic_python)

Prerequisite: [uv](https://docs.astral.sh/uv/)

### Setup

- Clone this repository.
- Download additional dependencies: `uv sync --all-extras --dev`
- Optional: validate the setup with `uv run python -m unittest`

### Workflow

- Download dependencies (if you need any): `uv add some_lib_you_need`
- Develop (optional, tinker: `uvx --with-editable . ptpython`)
- QA:
    - Format: `uv run ruff format`
    - Lint: `uv run ruff check`
    - Type check: `uv run mypy`
    - Test: `uv run python -m unittest`
- Build (to validate it works): `uv build`
- Review documentation updates: `uv run mkdocs serve`
- Make a pull request.
BelNorm 0.3.0
Belarusian text normalizer
Requires Python: >=3.12

Belarusian Text Normalization Library
=====================================

This library provides tools for preparing Belarusian text for Text-to-Speech (TTS) applications. Key features include:

- Splitting text into sentences
- Normalizing numbers and abbreviations
- Handling common Belarusian contractions and special symbols

Designed for easy integration, this library helps ensure that text is correctly formatted and pronounced by TTS systems.

Usage example
-------------

    from BelNorm import BelSplitter, NormalizerLLM
    from BelG2P import BelG2PWrapper

    g2p=BelG2PWrapper()
    normalizer=NormalizerLLM("gemini/gemini-flash-lite-latest")
    splitter=BelSplitter()

    text="Нейкі беларускі тэкст. І прачытаць яго трэба 3 разы."
    print(f"Input text: {text}")

    for paragraph in splitter.parse([text]):
        for sentence in paragraph:
            if not sentence.is_normalized:
                print("Normalization required: "+sentence.text)
                sentence.normalize(normalizer.normalize)
                print(sentence.text)
            print(sentence.convert_tts(g2p.convert))

Do not forget to add some environment variable for LLM usage. For Gemini, it should be GEMINI_API_KEY.
pyg-bond 0.0.19
Utilities for converting australian bill/bond futures to price. Also simple price to yield and yield to price.
Requires Python: >=3.6

# pyg-bond
The package contains simple bond price manipulation needed for Futures trading:

- conversion of australian bank bills quotes to prices (IR Comdty in Bloomberg)
- conversion of australian bond futures quotes to prices (XMA/YMA Comdty in Bloomberg)
- Simple derivation of price & duration from yield for bonds
- Newton Raphson yield & duration calculation from a given price using gradient descent