semvec/pypi-packages huggingface dataset:
thinftp 0.1.1
A very minimal FTP server
Requires Python: >=3.11

# thinFTP

[![PyPI](https://img.shields.io/pypi/v/thinftp.svg)](https://pypi.org/project/thinftp/)
[![License](https://img.shields.io/github/license/harishtpj/thinftp.svg)](LICENSE)
[![Documentation](https://readthedocs.org/projects/thinftp/badge/?version=latest)](https://thinftp.readthedocs.io/)

> A lightweight, configurable, and fully-featured FTP server written in pure Python.

---

# ✨ Features

- 📁 **File-based backend** with root isolation
- 🔐 **User authentication** via customizable logic
- 🧵 **Multithreaded** server for concurrent clients
- 📡 Supports **PASV mode** and basic FTP commands
- ⚙️ **Extensible architecture** via handler and command hooks
- 🐍 **Python standard library only** — no dependencies

---

# 📦 Installation

```bash
pip install thinftp
```

# 🚀 Usage

For a quick FTP server on your local directory, run:

```bash
thinftp
```

for more options, run `thinftp --help`

# 📚 Documentation
Full documentation is available at [thinftp.readthedocs.io](https://thinftp.readthedocs.io/)

It includes:

- API reference
- Configuration examples

# ✍🏻 Contributing
Contributions are welcome! While the basic functionality of this project works, there is a lot of room for improvement.  If you have any suggestions or find any bugs, please [open an issue](https://github.com/harishtpj/thinftp/issues/new/choose) or [create a pull request](https://github.com/harishtpj/thinftp/pulls).

# 📝 License

#### Copyright © 2025 [M.V.Harish Kumar](https://github.com/harishtpj). <br>

#### This project is [MIT](https://github.com/harishtpj/thinftp/blob/31f6ad825cf8714c8542209f56586605c3d6c629/LICENSE) licensed.
fluaaiagentsdk 1.0.9
SDK para integração com agentes da plataforma FluaAI
Requires Python: >=3.7


# SDK de Agentes Fluaai

SDK em Python para interagir com a API de Agentes da Fluaai, oferecendo integração simples com LLMs e operadores, suporte a streaming, e respostas estruturadas em classes tipadas.

## Funcionalidades

- Invocação de agentes LLM e Operador
- Streaming em tempo real de respostas
- Tratamento consistente de diferentes engines
- Respostas tipadas com classes ou compatíveis com JSON
- Suporte a ferramentas e processamento de conversas

*1.0.9 - New Parameter debug
*1.0.8 - Fix :)
*1.0.7 - Refactor
*1.0.6 - Fix & Simplificação das variáveis dinâmicas.
*1.0.5 - Atualização de serviço.
*1.0.4 - Introdução das variáveis dinâmicas (dynamic_variables).
*1.0.3 - Suporte a identificação de "channel" para registro de monitoramento dos seus agentes!
plotynium 0.1.0
plotynium is a Data Visualization framework for Python, inspired by Observable Plot
Requires Python: >=3.10

[![docs](https://github.com/bourbonut/plotynium/actions/workflows/docs.yml/badge.svg)](https://bourbonut.github.io/plotynium)
[![CI](https://github.com/bourbonut/plotynium/actions/workflows/ci.yml/badge.svg)](https://github.com/bourbonut/plotynium/actions/workflows/ci.yml)
[![Ruff](https://img.shields.io/badge/code_style-ruff-2a1833)](https://github.com/astral-sh/ruff)

# Plotynium

Plotynium is a *Data Visualization* framework for Python, inspired by  [Observable Plot](https://observablehq.com/plot/).

## Installation

```bash
pip install git+https://github.com/bourbonut/plotynium
```

It will be available soon on Pypi.

## Example

```py
import polars as pl
from sklearn.datasets import load_digits
from sklearn.decomposition import PCA
from sklearn.preprocessing import StandardScaler

import plotynium as ply

mnist = load_digits()
scaler = StandardScaler()
X_scaled = scaler.fit_transform(mnist.data)
pca = PCA(n_components=2)
components = pca.fit_transform(X_scaled)

# Prepare your data with Polars, Pandas or manually
df = pl.DataFrame(components, schema=["Component 1", "Component 2"])
df = df.insert_column(2, pl.Series("digit", mnist.target))

plot = ply.plot(
    marks=[
        ply.dot(
            df.to_dicts(),
            x="Component 1",
            y="Component 2",
            stroke="digit",
            symbol="digit",
        )
    ],
    color={"scheme": ply.Interpolation.RAINBOW},
    symbol={"legend": True},
    style={"background": "#0d1117", "color": "#e6edf3"},
)

with open("pca.svg", "w") as file:
    file.write(str(plot))
```

<p align="center">
    <img src="https://raw.githubusercontent.com/bourbonut/plotynium/refs/heads/main/docs/images/pca-github.svg?sanitize=true"></img>
</p>
img-splicer 2.0.6
img-splicer


This Python package provides a lightweight interface for parsing, constructing, 
and modifying PNG image files using only built-in libraries. It allows users to 
inspect and manipulate PNG file structure at the chunk level, enabling custom 
edits to metadata, color profiles, and raw image data. The library is designed 
for developers who need fine-grained control over PNG internals without 
relying on external imaging dependencies. Ideal for educational purposes, 
format exploration, or crafting minimal image-processing tools, it offers 
a clean and extensible foundation for working directly with the PNG specification.
mfetch 3.0
A terminal system information tool with customizable logos and colors.

# Minimal-Fetch Version 2.1

Minimal fetch is a more aesthetically pleasing system fetching tool written in Python!

Please note this has had some major performance issues as of the latest update, I am working on fixing them

**This repo ins't activly being worked on anymore. I still take PRs and Issues, but there are no planned feture updates. :)**

## What it looks like
<img src="https://github.com/ToxicWaveHD/Minimal-Fetch/blob/main/prev/2024-05-09_11-01.png" align="center" width="600px"/>
 
<details>
  <summary>More logos: </summary>

  <img src="https://github.com/ToxicWaveHD/Minimal-Fetch/blob/main/prev/2024-04-30_21-08_1.png" align="center" width="600px"/>
  <br></br>

  <img src="https://github.com/ToxicWaveHD/Minimal-Fetch/blob/main/prev/2024-04-30_21-09.png" align="center" width="600px"/>
  <br></br>

  <img src="https://github.com/ToxicWaveHD/Minimal-Fetch/blob/main/prev/2024-04-30_21-10.png" align="center" width="600px"/>
  <br></br>

  <img src="https://github.com/ToxicWaveHD/Minimal-Fetch/blob/main/prev/2024-04-30_21-10_1.png" align="center" width="600px"/>
  <br></br>

  <img src="https://github.com/ToxicWaveHD/Minimal-Fetch/blob/main/prev/2024-04-30_21-10_2.png" align="center" width="600px"/>
  <br></br>

  <img src="https://github.com/ToxicWaveHD/Minimal-Fetch/blob/main/prev/2024-04-30_21-11.png" align="center" width="600px"/>
  <br></br>

  <img src="https://github.com/ToxicWaveHD/Minimal-Fetch/blob/main/prev/2024-04-30_21-11_1.png" align="center" width="600px"/>
  <br></br>
</details>

STILL A WIP DO NOT EXPECT IT TO BE FLAWLESS  (Please do report any issues you find)

## Install with
```
sudo pip install git+https://github.com/ToxicWaveHD/Minimal-fetch
```
And simply run with
```
mfetch
```
Note: this requires the dependencies: `python3`, `pillow`, `click`

You can install the dependencies with

For Ubuntu/Debian-based: ```sudo apt install python3 python3-pillow python-click```

For Arch-based: ```sudo pacman -S python3 python-pillow python-click```


## Config howto
WARNING FAIL-SAFES HAVE YET TO BE ADDED IF YOU ENCOUNTER ANY ERRORS WHILE RUNNING AFTER EDITING THE CONFIG REVERT ANY CHANGES MADE

The config is located at ```~/.config/mfetch/options```

If it is not run `pip show mfetch` and copy the `location` then
copy `<for mentioned location>/mfetch/options` to `~/.config/mfetch`

Any improvements, features or new logos would be very welcome :)