semvec/pypi-packages huggingface dataset:
finalflash 0.3.7
A tool for uGMRT primary beam correction
Requires Python: >=3.6

# Finalflash

**Finalflash** is a tool for correcting radio interferometric images using the uGMRT primary beam model. Inspired by Vegeta’s ultimate attack in Dragon Ball Z, this tool provides accurate corrections for uGMRT FITS images.


<p align="center">
  <img src="https://github.com/arpan-52/Finalflash/blob/main/vegeta.gif" alt="FinalFlash Animation" width="500"/>
  <br/>
  <i>Vegeta's Final Flash</i>
</p>



## Installation

Install Finalflash via pip:

```bash

pip3 install finalflash
```
## Usage

```bash

finalflash <input.fits> <output.fits> [--beam threshold --jvla]
```
## Version History

version 0.3.4. - Heavily tested for single-frequency FITS file corrections.

version 0.3.5. - Experimental version for both single and frequency-cube corrections. 

version 0.3.6. - Cube correction with proper header retention for both cubes and single frequency fits images.

version 0.3.7  - Manual beam threshold and support for JVLA beams.

## Citation

If **Finalflash** saves your analysis from the chaos of uncorrected primary beams and handling CASA tasks, give it a little love in your acknowledgements! Add this line in the acknowledgement section:

*"Primary beam corrections were performed using Finalflash, hosted at [https://github.com/arpan-52/Finalflash](https://github.com/arpan-52/Finalflash)."*  

Until it makes its debut on ASCL or I finally write my holography paper, your acknowledgement would be *super* appreciated. As some random user in the internet mentioned:
"Science without ethics is like a spaceship without fuel—sure, it looks good, but it’s going nowhere."
kcai-data-sampling 0.0.6
Samples generation utilities managed with uv
Requires Python: >=3.11

# KC-DATA-SAMPLING

## Installation rapide

```bash
uv venv .venv
source .venv/bin/activate
uv sync 
```

## Lancement

### 1. Génération d'images augmentées et adversariales

```bash
# Images corrompues (augmentations)
python augment_run.py --config examples/augment_all.yml

# Images adversariales (FGSM, PGD, C&W, APGD)
python adversarial_run.py --config examples/adversarial_fgsm.yml
python adversarial_run.py --config examples/adversarial_all.yml
```

**Note**: Ces scripts génèrent maintenant les images **sans inférence**. Les colonnes générées sont :
- `sample_uuid` (nouveau UUID unique)
- `parent_sample_uuid` (lien vers l'échantillon d'origine)
- `image_hash` (hash SHA256)
- `sample_id`, `sample_type`, `class_id`, `class_name`, `split`
- `transform_id`, `transform_name`, `transform_level`, `transform_params`
- `image_bytes`

### 2. Inférence sur les images

```bash
# Inférence de base (garde toutes les colonnes + ajoute prédictions)
python kc_inference.py --config examples/kc_inference.yaml

# mode in-place (onmodifie le fichier directement)
python kc_inference.py --config examples/kc_inference.yaml --in-place
```

#### Options d'inférence disponibles :

**Modes de sortie**  :
- `label_only` : Seulement le label prédit
- `label_prob` : Label + probabilité
- `top_k` : Label + prob + top-K labels et probs
- `all_probs` : Label + prob + toutes les probabilités
- `logits` : Label + prob + logits
- `extended` : Label + prob + all_probs + logits (recommandé)
- `full` : Tout (label + prob + top_k + all_probs + logits)
selenium-fetcher 0.1.0
A simple Selenium-based webpage fetcher for fully rendered HTML
Requires Python: >=3.8

# selenium-fetcher

Simple Python utility to fetch JavaScript-rendered HTML using Selenium + Firefox.

## Usage

```python
from selenium_fetcher import load_url

load_url(
    url="https://example.com",
    file_name="output.html",
    gecko_driver_path="/path/to/geckodriver"
)
mp-explore-source-euparl 0.1.4
Obtain data of EU MPs
Requires Python: >=3.11

<!--
SPDX-FileCopyrightText: 2025 Free Software Foundation Europe e.V. <mp-explore@fsfe.org>

SPDX-License-Identifier: AGPL-3.0-or-later
-->

# MP Explore EUParl

Part of the [MP Explore](https://git.fsfe.org/mp-explore/mp-explore) project.

Data Source for the European Parliament.

## Where to get it

You can get it through the [Python Package Index (PyPI)](https://pypi.org/project/mp_explore_core/):

```sh
$ pip3 install mp_explore_source_euparl
```

## Arguments

- (Optional) `display_browser` When enabled, a browser window is opened displaying the actions being performed.
- (Optional) `mep_url_template` URL template to obtain data from each MEP, `{ID}` will be replaced with the MEP ID.
- (Optional) `full_list_url` URL from where the full list of MEPs is extracted.
- (Optional) `retrieve_emails` When enabled, e-mails will be retrieved. This takes a long time.
- (Optional) `retrieve_committees` When enabled, membership to committees will be retrieves. This takes a long time.
- (Optional) `timeout` Only valid when `retrieve_emails` or `retrieve_committees` are true, time to wait between pages.
star-toffee 1.0.2b0
Package for finding flares in TESS lightcurves
Requires Python: >=3.8

<p align="center">
  <img src="https://raw.githubusercontent.com/JasonReeves702/TOFFEE/refs/heads/main/TOFFEE_Logo.png?token=GHSAT0AAAAAADPCESBXCXJN5D3ATT2HGREM2I3QBEA" width="385" height="223" alt="TOFFEE_Logo" />
</p>

# TOFFEE

Software to detrend and detect flares in TESS lightcurves. Effective in separately detecting overlapping flare events to be complete down to short waiting times.

Read more on the project at: https://github.com/JasonReeves702/TOFFEE

Install using pip with:

pip install star-toffee

Import into Python with:

import toffee
kafka-stubs 2.10.0.2
Type stubs for Confluent Kafka Python client
Requires Python: >=3.10

# kafka-stubs

[![PyPI - Status](https://img.shields.io/pypi/status/kafka-stubs)](https://pypi.org/project/kafka-stubs)
[![PyPI](https://img.shields.io/pypi/v/kafka-stubs)](https://pypi.org/project/kafka-stubs)
[![PyPI - Python Version](https://img.shields.io/pypi/pyversions/kafka-stubs)](https://pypi.org/project/kafka-stubs)
[![PyPI - License](https://img.shields.io/pypi/l/kafka-stubs)](https://pypi.org/project/kafka-stubs)
[![CI Status](https://github.com/tkukushkin/kafka-stubs/actions/workflows/check.yml/badge.svg)](https://github.com/tkukushkin/kafka-stubs/actions/workflows/check.yml)

Type stubs for [Confluent Kafka Python Client](https://pypi.org/project/confluent-kafka/).

## Installation

```bash
pip install kafka-stubs
```