semvec/pypi-packages huggingface dataset:
paper-sanitizer 1.0.0
CLI that strips prompt-injection triggers from academic papers
License: MIT
Requires Python: >=3.9

# 🧼 Paper-Sanitizer

> Strip prompt-injection tricks from academic papers **before** they hit your LLM pipeline.

Researchers keep showing how easy it is to hide  
`Ignore all previous instructions`  
inside a PDF or LaTeX file and fool automated summarizers. Paper-Sanitizer is a tiny command-line tool that removes those hidden instructions, flags stealthy white-on-white text, and rates the overall risk. Use it as a pre-flight check in RAG systems, peer-review helpers, or your own reading workflow.

---

## Key features

| Stage | What it does |
|-------|--------------|
| **Stage 1** | Regex firewall – removes obvious prompt-injection phrases |
| **Stage 2** | Detects invisible text (white or ≤ 1 pt) and suspicious PDF metadata |
| **Stage 3** | Emits detailed event log, word-level diff (`--diff`), and a *risk class* (`low / medium / high`) |

Supported inputs: **PDF**, **.tex**, **.txt** (more coming).

---

## Quick start

### 1 · Install

```bash
# Requires Python ≥ 3.9
pipx install git+https://github.com/mctar/paper-sanitizer.git
# – or –
pip install git+https://github.com/mctar/paper-sanitizer.git
devolv-commit 0.1.1
Generate human-friendly Git commit messages from staged changes
License: MIT
Requires Python: >=3.7
Keywords: git, commit, automation, cli

# devolv-commit

✨ Auto-generate meaningful, smart Git commit messages based on staged code changes.

No more `git commit -m "fix stuff"` — just run `git dc`, and you're done.

---

## 🚀 Features

- 🔍 Analyzes staged diffs to understand your code changes
- 🧠 Generates human-like commit messages
- 🪝 Optional Git hook to auto-fill commit messages
- ✅ Clean, professional output — no templates or fluff
- ♻️ Follows [Conventional Commits v1.0.0](https://www.conventionalcommits.org/en/v1.0.0/) for standardization
- ⚡️ Blazing fast — not AI-powered, but built with a lean homegrown engine
- 🧪 Test suite with coverage

---

## 📦 Installation

```bash
pip install devolv-commit
```

---

## 💡 Usage

Generate a commit message and commit it:

```bash
git dc
```
---

## 📥 Manually Install Git Hook (Optional)

Automatically generate a commit message when you run `git commit`:

```bash
git dc install-hook
```

This installs a `prepare-commit-msg` hook that fills in the message field.
You can edit it before committing.

---

## 🧪 Testing

Run tests with coverage:

```bash
pytest --cov=devolv_commit --cov-report=term-missing
```

---

## ✅ Conventional Commit Support

We follow the [Conventional Commits v1.0.0](https://www.conventionalcommits.org/en/v1.0.0/) standard to enhance changelogs, release notes, and CI workflows.

Example commit messages:

- `feat: add support for multi-file diffs`
- `fix(core): handle edge case in parser`
- `refactor(utils): clean up class detection logic`

---

## 📜 License

MIT © [Devolvdev](https://github.com/devolvdev)
queue-leu-leu 1.1
Collection of Python scripts, showing minimal examples of objects following each other.
License: MIT
Requires Python: >=3.9

# Queue leu leu
Collection of Python scripts, showing minimal examples of objects following each other.


### Content
* [arc follow](https://github.com/xorblo-doitus/queue_leu_leu/tree/main/src/queue_leu_leu/arc)
* [joint follow](https://github.com/xorblo-doitus/queue_leu_leu/tree/main/src/queue_leu_leu/joint)
* [orbit follow](https://github.com/xorblo-doitus/queue_leu_leu/tree/main/src/queue_leu_leu/orbit)
* [trail follow](https://github.com/xorblo-doitus/queue_leu_leu/tree/main/src/queue_leu_leu/trail)
* [polygon follow](https://github.com/xorblo-doitus/queue_leu_leu/tree/main/src/queue_leu_leu/polygon) (this one is a shape editor)


### Installation
Just install it with the command: ``pip install queue_leu_leu`` <br>
Or for installation with a clone of this repo: ``pip install .``

If you want to build it yourself, install the module ``build`` and run the command: ``python -m build``.


### Dependencies
All the scripts use [PyGame](https://github.com/pygame/pygame) to work. <br>
Mainly, to use the [Vector2](https://www.pygame.org/docs/ref/math.html?highlight=vector2#pygame.math.Vector2) object, but you can use any other library that includes standard Vector things. <br>
The rest, is just to visualize the algorithms with more informations.


### Contributors
[@ZetaMap](https://github.com/ZetaMap) and [@xorblo-doitus](https://github.com/xorblo-doitus)
azerbaijani-stopwords 0.1.0
A lightweight Python package providing Azerbaijani stopwords for NLP tasks.
License: MIT
Requires Python: >=3.6

# Azerbaijani Stopwords

`azerbaijani_stopwords` is a lightweight Python package that provides a curated list of Azerbaijani stopwords for natural language processing (NLP) tasks.

## Why?

When processing Azerbaijani text for tasks like sentiment analysis, classification, or search, it's often necessary to remove common words that do not carry much meaning—like "və", "da", or "ilə". This package helps you do that easily.

## Installation

```bash```
You can use the following command to install library
```pip install azerbaijani_stopwords```

## How to use?

```python
from azerbaijani_stopwords import AZERBAIJANI_STOPWORDS

text = "Bu gün hava çox gözəldir və mən parkda gəzirəm."
words = text.lower().split()

filtered_words = [word for word in words if word not in AZERBAIJANI_STOPWORDS]

print(filtered_words)

# Output: ['gün', 'hava', 'gözəldir', 'parkda', 'gəzirəm.']

```