semvec/pypi-packages huggingface dataset:
pyratbay 2.0.1
Python Radiative Transfer in a Bayesian Framework
Requires Python: >=3.9

# Pyrat Bay: Python Radiative Transfer in a Bayesian framework

<img alt="pyratbay" src="https://github.com/pcubillos/pyratbay/blob/master/docs/figures/pyrat_logo.png" width="190">

> A Forward-modeling and retrieval code to model exoplanet atmospheres and spectra.

[![Tests](https://github.com/pcubillos/pyratbay/actions/workflows/python-package.yml/badge.svg?branch=master)](https://github.com/pcubillos/pyratbay/actions/workflows/python-package.yml)
[![Documentation Status](https://readthedocs.org/projects/pyratbay/badge/?version=latest)](https://pyratbay.readthedocs.io/en/latest/?badge=latest)
[![PyPI](https://img.shields.io/pypi/v/pyratbay.svg)](https://pypi.org/project/pyratbay)
[![Conda Version](https://img.shields.io/conda/vn/conda-forge/pyratbay.svg)](https://anaconda.org/conda-forge/pyratbay)
[![GitHub](https://img.shields.io/github/license/pcubillos/pyratbay.svg?color=blue)](https://pyratbay.readthedocs.io/en/latest/license.html)


### Install as:
```
pip install pyratbay
```
or:
```
conda install -c conda-forge pyratbay
```

### Docs at:
<https://pyratbay.readthedocs.io/en/latest/>

### Cite as ([ADS](https://ui.adsabs.harvard.edu/abs/2021arXiv210505598C)):

```bibtex
@ARTICLE{CubillosBlecic2021mnrasPyratBay,
       author = {{Cubillos}, Patricio E. and {Blecic}, Jasmina},
        title = "{The PYRAT BAY framework for exoplanet atmospheric modelling: a population study of Hubble/WFC3 transmission spectra}",
      journal = {\mnras},
     keywords = {radiative transfer, methods: statistical, planets and satellites: atmosphere, Astrophysics - Earth and Planetary Astrophysics, Astrophysics - Instrumentation and Methods for Astrophysics},
         year = 2021,
        month = aug,
       volume = {505},
       number = {2},
        pages = {2675-2702},
          doi = {10.1093/mnras/stab1405},
archivePrefix = {arXiv},
       eprint = {2105.05598},
 primaryClass = {astro-ph.EP},
       adsurl = {https://ui.adsabs.harvard.edu/abs/2021MNRAS.505.2675C},
      adsnote = {Provided by the SAO/NASA Astrophysics Data System}
}
```
pydantic-fixedwidth 0.2.2
Custom Pydantic models for parsing and serializing fixed-width format of data.
Requires Python: <4.0,>=3.9

# pydantic-fixedwidth

[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)
[![codecov](https://codecov.io/gh/lasuillard-s/pydantic-fixedwidth/graph/badge.svg?token=R5pQWB43DP)](https://codecov.io/gh/lasuillard-s/pydantic-fixedwidth)
[![PyPI - Version](https://img.shields.io/pypi/v/pydantic-fixedwidth)](https://pypi.org/project/pydantic-fixedwidth/)

Custom Pydantic models for serializing and deserializing fixed-width format data.


## 🚀 Quick Start

Install this package with pip:

```shell
$ pip install pydantic-fixedwidth
```

Usage example:

```python
from datetime import datetime, timezone

from pydantic_fixedwidth import Fixedwidth, Padding
from pydantic_fixedwidth import OrderedField as Field

tzinfo = timezone.utc


class SomeRequest(Fixedwidth):
    string: str = Field(length=8)
    hangul: str = Field(length=6)
    number: int = Field(length=10, justify="right", fill_char=b"0")

    # Just an padding field
    p_: str = Padding(length=10)

    # This field will be ignored in ser/de
    ignore: str = Field(length=10, default="IGNORE", exclude=True)

    ts: datetime = Field(
        length=20,
        to_str=lambda dt: dt.strftime("%Y%m%d%H%M%S%f"),
        from_str=lambda s: datetime.strptime(s, "%Y%m%d%H%M%S%f").replace(tzinfo=tzinfo),
    )


# Format model to bytes
some_request = SomeRequest(
    string="<DFG&",
    hangul="한글",
    number=381,
    ts=datetime(2024, 1, 23, 14, 11, 20, 124277, tzinfo=tzinfo),
)
b = some_request.format_bytes()

assert len(b) == 54
assert b == b"<DFG&   \xed\x95\x9c\xea\xb8\x800000000381          20240123141120124277"

# Parse bytes into model
parsed_request = SomeRequest.parse_bytes(b)

assert parsed_request == some_request
```
sids-basic-processor 0.0.2
A simple utility for text preprocessing (lower, punct removal, stop words).
Requires Python: >=3.7

# sids-basic-processor

A simple, basic utility package for common natural language text preprocessing tasks. It is designed to quickly clean raw text for analysis.

## Features

The `TextProcessor` class performs the following sequential steps:

1.  **Lowercasing**: Converts all text to lowercase.
2.  **Punctuation Removal**: Removes all common punctuation marks.
3.  **Tokenization**: Splits the cleaned text into a list of words.
4.  **Stop Word Removal**: Filters out a predefined set of common English stop words (like "the", "is", "a", etc.).

## Installation

You can install the package using Python's package manager, `pip`:

```bash
pip install sids-basic-processor