semvec/pypi-packages huggingface dataset:
owlt-mcp-server 0.2.9
A translator named owlt mcp server powered by professional LLMs
Requires Python: >=3.11.8

# owlt-mcp-server
owlt-mcp-server is a mcp server which focus on TARGET language chinese and english translation. on the stage it is free to use. It intergates some LLMs translation power.


## How to use
you can use it by **uvx** on mainstream mcp client IDE.
for example add below to mcp_config.json on Windsurf:
```
"translate_server":  {
    "command":  "uvx",
    "args":  [
        "owlt-mcp-server"
    ]
}
```
The mcp server supports **document translate** and **computer domain translate**.  
example:
```
use youdao translate to chinese "everyday is a new day"
```
```
use xx-tool translate to chinese "everyday is a new day"
```
translate document 翻译文档
```
translate document from chinese to english "C:\Users\dada\iran.pdf"
```
## Wanted api donate
types-inifile 0.4.0.20250703
Typing stubs for inifile
Requires Python: >=3.9

## Typing stubs for inifile

This is a [PEP 561](https://peps.python.org/pep-0561/)
type stub package for the [`inifile`](https://github.com/mitsuhiko/python-inifile) package.
It can be used by type-checking tools like
[mypy](https://github.com/python/mypy/),
[pyright](https://github.com/microsoft/pyright),
[pytype](https://github.com/google/pytype/),
[Pyre](https://pyre-check.org/),
PyCharm, etc. to check code that uses `inifile`. This version of
`types-inifile` aims to provide accurate annotations for
`inifile==0.4.*`.

This package is part of the [typeshed project](https://github.com/python/typeshed).
All fixes for types and metadata should be contributed there.
See [the README](https://github.com/python/typeshed/blob/main/README.md)
for more details. The source for this package can be found in the
[`stubs/inifile`](https://github.com/python/typeshed/tree/main/stubs/inifile)
directory.

This package was tested with
mypy 1.16.1,
pyright 1.1.400,
and pytype 2024.10.11.
It was generated from typeshed commit
[`dbd3ad356ef3bceae506fb71a29a48b6192213ba`](https://github.com/python/typeshed/commit/dbd3ad356ef3bceae506fb71a29a48b6192213ba).
twitter-xyber 2.0.0
Twitter xyber merupakan library untuk melakukan scraping data twitter. Project ini disupport oleh XYBER.
Requires Python: >=3.7

# twitter-xyber

Twitter xyber merupakan library untuk melakukan scraping data Twitter. Project ini disupport oleh XYBER.

## Instalasi

```bash
pip install twitter-xyber
```

## Penggunaan

```python
from twitter_xyber.scraper import TwitterScraper

scraper = TwitterScraper(headless=True, username='your_username', password='your_password')
# scraper.login()
result = scraper.search_user("nama user")
print(result)
```
daas-mcp-server 0.0.3
DaaS MCP Server
Requires Python: >=3.13

# CVAD Model Context Protocol (MCP) Server

A Model Context Protocol (MCP) server implementation for DaaS that provides AI assistants with the ability to interact with DaaS environments.

## Overview

The DaaS MCP Server extends AI capabilities to Citrix DaaS environments by providing a set of tools that allow AI assistants to interact with your DaaS site.

This server implements the Model Context Protocol (MCP), a standardized way for AI agents to interact with external systems and tools.

## Installation

### Prerequisites

- Python 3.13 or higher
- [uv](https://github.com/astral-sh/uv) - Fast Python package manager and installer
- Generate your own [Service Principle](https://developer-docs.citrix.com/en-us/citrix-cloud/citrix-cloud-api-overview/get-started-with-citrix-cloud-apis) to access DaaS API

### Setup

1. Clone the repository
2. Navigate to the project directory:

   ```bash
   cd daas-mcp
   ```

3. Install the package and its dependencies with uv sync:

   ```bash
   uv sync
   ```

## Project Structure

- `src/`: Main package directory
  - `server.py`: MCP server implementation
  - `tools.py`: Tool implementations for interacting with DaaS
  - `constants.py`: Project constants
  - `resources.py`: Resource implementations
  - `utils/`: Utility modules for authentication, logging, etc.

## Usage

### Starting the Server

To start the CVAD MCP Server using uv:

```bash
uv run .\src\server.py
```

The server uses stdio as the transport mechanism.

## Development

### Development Dependencies

Install the development dependencies with uv:

```bash
uv sync --dev
```

### Debug Mode

Navigate to the project directory:

```bash
cd daas-mcp
```

Run the server with inspector mode:

```bash
mcp dev server.py
```

### Code Quality

This project uses Ruff for linting and formatting.

To run the linter:

```bash
uv run ruff check
```

To auto-fix the lint issues:

```bash
uv run ruff check --fix
```

To format the code:

```bash
uv run ruff format
```

## Publishment

```bash
uv pip install build twine
```

```bash
python -m build
```

```bash
python -m twine upload dist/*
```

## Security Considerations

- The server identifies sensitive operations that require special permissions
- Authentication is handled through Citrix Cloud authentication mechanisms
- Token caching is implemented securely

## License

Copyright (c) 2025. Cloud Software Group, Inc. All Rights Reserved. Confidential & Proprietary.
bfpy-brainy 0.1.0
A simple python package that interprets and compiles Brainfuck code.
Requires Python: >=3.9

# Brainfuck Py

This is a simple python package that interprets and compiles Brainfuck code.

USE:


```` python
from brainfuck-py import BfInterpreter
from brainfuck-py import BfCompiler

interpreter = BfInterpreter()
compiler = BfCompiler()

bf = "+"*65 + "."

interpreter.interpret(bf) //Outputs A
compiler.compile(bf, "compiled") //Creates a program in your project's root folder with the name compiled along with C code of the same name.
````
cogent3-ete3 2025.7.3
cogent3 plugin for ete3
Requires Python: <3.14,>=3.11
Keywords: biology, genomics, statistics, phylogeny, evolution, bioinformatics

# A plugin for converting a [cogent3](https://cogent3.org/) tree to [ete3](http://etetoolkit.org/) tree object 
[![Coverage Status](https://coveralls.io/repos/github/YapengLang/cogent3-ete3/badge.svg?branch=main)](https://coveralls.io/github/YapengLang/cogent3-ete3?branch=main)
[![Release](https://github.com/YapengLang/cogent3-ete3/actions/workflows/release.yml/badge.svg?branch=main)](https://github.com/YapengLang/cogent3-ete3/actions/workflows/release.yml)

Developed an app that takes a cogent3 `PhyloNode` then returns an ete3 `PhyloTree`, plus an app for edge colouring.

## cogent3 to ete3 tree
```
from cogent3 import load_tree, get_app
from cogent3_ete3.style import show_legend

tree = load_tree("data/tree_large_scale.newick")

conv = get_app("cogent3_to_ete3")
t = conv(tree)
```
`t` is an ete3 `PhyloTree`.

## colour edges by a mapping
The `ete3_colour_edge` app allows you to colour information on selected edges. The app applies a colour to named edges. This means for colouring internal edges the node must have names.

```
edge_to_cat = {"Vombatidae_Vombatus_ursinus": "A",
 "Dasyuridae_Sarcophilus_harrisii": "B",
 "Peramelidae_Echymipera_kalubu" : "C",
 "Pseudochiridae_Pseudochirulus_forbesi": "D"}

cat_to_colour={"A":"blue", 
 "B":"blue", 
 "C":"red", 
 "D":"orange"}

cl = get_app("ete3_colour_edge", edge_to_cat=edge_to_cat, cat_to_colour=cat_to_colour)
t = cl(t)
```

You can use the convenient function to show a legend.

```
show_legend(t, cat_to_colour, legend_title="Your Category")
```

In the pop-up window, you can explore further and render the tree in a file as you progress:

<img src="https://figshare.com/ndownloader/files/55664936" alt="tree1" width="450" />
bfpy-package-brainy7890 0.1.0
A simple python package that interprets and compiles Brainfuck code.
Requires Python: >=3.9

# BfPy

This is a simple python package that interprets and compiles Brainfuck code.

USE:


```` python
from BfPy import BfInterpreter
from BfPy import BfCompiler

interpreter = BfInterpreter()
compiler = BfCompiler()

bf = "+"*65 + "."

interpreter.interpret(bf) //Outputs A
compiler.compile(bf, "compiled") //Creates a program in your project's root folder with the name compiled along with C code of the same name.
````
AsroNLP 0.1.20
Paket NLP untuk pengolahan teks Bahasa Indonesia
Requires Python: >=3.6

# AsroNLP

**AsroNLP** adalah paket Natural Language Processing (NLP) khusus untuk pengolahan teks Bahasa Indonesia. Paket ini menyediakan fitur preprocessing lengkap seperti pembersihan teks, tokenisasi, normalisasi, stemming, serta analisis sentimen berbasis kamus leksikon positif dan negatif.

---

## Fitur Utama

- Pembersihan teks dari emoji, angka, simbol, URL, mention, dan duplikat data
- Tokenisasi teks Bahasa Indonesia menggunakan NLTK
- Penghapusan stopwords Bahasa Indonesia
- Normalisasi kata menggunakan kamus kata baku
- Stemming dengan algoritma Sastrawi
- Analisis sentimen dengan kamus leksikon positif dan negatif
- Deteksi sumber komentar (Media atau Individual)
- Visualisasi hasil analisis: distribusi sentimen, wordcloud, dan frekuensi kata
- Mendukung data dari YouTube (`comment`) dan Twitter (`full_text`)

---

## Instalasi

Instalasi paket AsroNLP beserta dependensinya dapat dilakukan dengan:

```bash
pip install pandas openpyxl rich nltk Sastrawi regex matplotlib wordcloud swifter
pip install asronlp==0.1.20
gil-node-openai 0.1.0
OpenAI nodes for the Gil-Flow project
Requires Python: >=3.8

# Gil-Node-OpenAI

This package provides nodes for interacting with the OpenAI API within the Gil-Flow ecosystem.

## Provided Nodes

- **OpenAIConnector**: Manages the connection and authentication with the OpenAI API.
- **ImageGenerator**: Generates images using DALL-E.
gil-node-data 0.1.0
Data processing and I/O nodes for the Gil-Flow project
Requires Python: >=3.8

# Gil-Node-Data

This package provides nodes for data processing and I/O within the Gil-Flow ecosystem.

## Provided Nodes

- **Data-ReadFile**: Reads data from a specified file path.
- **Data-Transform**: Transforms data using a specified function or script.
abstractart 0.2.0
Randomly generating abstract stickman
Requires Python: >=3.12

# AbstractArt

A python script that generates abstract art using turtle. Every time you run this program it will produce a unique art that is never seen before. You are welcome.

This is an experiment by a 12yo and a 9yo.

![screenshot.png](./screenshot.png)

# Getting Started

Install it using uv:

```bash
uv tool install abstractart
```

Run it using:

```bash
abstractart
```

If you want the non abstract, regular version of this art. Then you can run:

```bash
stickman
```