semvec/pypi-packages huggingface dataset:
ctadl-jadx-fact-generator-plugin 0.6.2
CTADL JADX fact generator plugin
Requires Python: >=3.9

# CTADL JADX Fact Generator Plugin

This project is part of the [CTADL Taint Analyzer](https://github.com/sandialabs/ctadl).

This project provides a plugin for CTADL so that it can perform taint analysis on Java bytecode.
It is based on [jadx](https://github.com/skylot/jadx) code analysis.

# Installation

Use pip.

    $ pip install ctadl-jadx-fact-generator

Afterward, if ctadl is installed, you can do:

    $ ctadl import jadx /path/to/apk

See `ctadl --help` for more detauls.

Make sure, when you run ctadl, that `JAVA_HOME` is properly set up in your environment or Java is in your path.
If you forget, it'll remind you.
tinyurl-mcp-server 0.1.3
TinyURL MCP Server
Requires Python: >=3.10

# TinyURL MCP Server

A simple MCP server for generating short links using TinyURL API.

## Configuration

```json
{
    "mcpServers": {
        "tinyurl": {
            "command": "uvx",
            "args": ["tinyurl-mcp-server"],
            "env": {
                "TINYURL_API_KEY": "your_tinyurl_api_key"
            }
        }
    }
}
```
rjfrank 1.0.4
An honorary Python module celebrating Randy Frank.
Requires Python: >=3.8

# rjfrank

🎉 An honorary Python module celebrating Randy Frank's legendary contributions.

This playful module includes memorable quotes, fun attributes, and a stylish farewell message when removed from runtime.

---

## Install

```bash
pip install rjfrank
```

## Usage

```bash
>> import rjfrank
>> dir(rjfrank)
>> rjfrank.catan_negotiations()
>> rjfrank.movie_quotes()
>> rjfrank.retire()
>> rjfrank.ode()
>> del rjfrank
```

---

## License

MIT License

---

## Credits

This project was inspired by an idea from **David Bremer** to honor **Randy Frank**.

![initial_idea.png](randy.png)
difpy2 0.1.0
A super-fast in-memory duplicate & similar image finder
Requires Python: >=3.12

# difpy2

[![PyPI version](https://img.shields.io/pypi/v/difpy2.svg)](https://pypi.org/project/difpy2/)  
[![Python versions](https://img.shields.io/pypi/pyversions/difpy2.svg)](https://pypi.org/project/difpy2/)  
[![License: MIT](https://img.shields.io/badge/License-MIT-blue.svg)](LICENSE.txt)

A **super-fast**, **in-memory** duplicate & similar image finder built on perceptual-hash bucketing and Numba-accelerated comparison.

---

## Features

- **Zero on-disk output**: everything runs in RAM  
- **Exact & “similar” mode** (custom MSE threshold)  
- **Perceptual-hash + histogram pre-bucketing** to prune comparisons  
- **Numba-JIT** mean-squared-error with early bailout  
- **Thread-pooled** image loading & feature extraction  
- **CLI** and **Python API**  

---

## Installation

```bash
pip install difpy2
Requires Python ≥ 3.12

Quickstart
CLI
bash
Copy
Edit
difpy2 \
  -D /path/to/images \
  --px_size 50 \
  --bins 8 \
  --sim 0.0     # exact duplicates only; use >0 for “similar” mode
Options

-D, --dirs … one or more image directories

-r, --recursive … recurse into subfolders

-px, --px_size … resize images to px×px for comparison

-b, --bins … per-channel histogram buckets

-s, --sim … MSE threshold (0.0 = exact only)

-t, --threads … number of worker threads

Python API
python
Copy
Edit
from difpy2 import DuplicateFinder

finder = DuplicateFinder(
    directories=["/path/to/images"],
    px_size=50,
    hist_bins=8,
    similarity=0.0,    # exact duplicates
    threads=4,
)

results, lower_quality, stats = finder.run()

# results: { primary_image_path: [[duplicate_path, mse], …], … }
# lower_quality: [all duplicate/similar image paths]
# stats: { total_files, featurized, groups, duration_s }
Project Layout
arduino
Copy
Edit
difpy2/
├── difpy_opt.py         # core implementation
├── README.md
├── LICENSE.txt
├── pyproject.toml
└── …
Contributing
Fork the repo

Create a feature branch

Run tests & linters

Submit PR

License
This project is licensed under the MIT License. See LICENSE.txt.
mswappinit 2025.4.30
a personal, opinionated python app initializer
Requires Python: >=3.12

# mswappinit

This package is expected to only be used by @mwartell for personal development projects.
I've published it only after copying it into my third new project and figured an import
would be easier. Others are certainly welcome to use it, but I'd be surprised.

This library provides three application bootstrap utilities

1. project - a configuration dotenv loader that makes nice parameter accessors
2. log - a logger that is pleasing to the author
3. quick_db - a pickledb instance for quick and dirty persistence

## project

dotenv is used to load environment variables from a file named .env these could be
something like: `AWS_PROFILE=cluster` and these will all be loaded into the environment
as expected.

this module provides convenience attribute access to project specific log variables that
are loaded from the dotenv file. A `PROJECT_NAME` must be defined and then all other
variables of the form `{PROJECT_NAME}_{VAR}` can be accessed as attributes of the project
object.

For example, if the `PROJECT_NAME` is "rag" and the dotenv file contains
`RAG_DATA=/path/to/data` then the value of `project.data` will be the
Path object `/path/to/data`.

For convenience, the values are upcast to the most likely type. For example,
if the value is "true" or "false" it will be converted to a boolean. If the
value is a number it will be converted to an int or float. If the value is a

# log

Using `from mswappinit import log` creates a development simple logger with
`log.debug`, `log.info` and so on. Logs only go to stderr.

# quick_db

If `quick_db` is imported, a [pickleDB][https://patx.github.io/pickledb/]
instance will be created in `project.data`.  This is a json backed key-value
store. Writes should use the context manager:

    from mswappinit.quick_db import quick_db
    with quick_db:
        db.set("Cyclopedidae", ["Palaeomyrmidon", "Cyclopes didactylus"])

which ensures a `quick_db.save()` when the context exits.
telepycore 1.5.3
Telegram bot library

#### Tele
Telegram bot library.  

view [readthedocs](https://tele.readthedocs.io)  
[GitLab](https://gitlab.com/2411eliko/tele)  
[pypi](https://pypi.org/project/telepy-bot/)  
![Build Status](https://img.shields.io/pypi/dm/telepy)  
##### Installation

requires python 3.4 or higher.

`pip3 install telepycore`

```python 
from Tele import *


@bot('text')
def echo(update):
    update.reply(update.text)


account('TOKEN')
bot_run()

```