semvec/pypi-packages huggingface dataset:
mymathlib-kuwae 0.1.0
A simple math library
Requires Python: >=3.6

# mymathlib

A simple math library with addition and subtraction.

## Installation


## Usage

```python
from mymathlib import add, subtract

print(add(2, 3))       # => 5
print(subtract(5, 2))  # => 3


---

## ✅ ステップ5：ライセンスを書く（例：MIT）

### 🔹 `LICENSE`

```text
MIT License

Copyright (c) 2025 Your Name

Permission is hereby granted, free of charge, to any person obtaining a copy...
persian-calendar-picker 0.1
یک ویجت انتخاب تاریخ شمسی برای Tkinter
Requires Python: >=3.6

مطمئناً! این نمونه فایل `README.md` را می‌توانید مستقیماً کپی کنید:

```
# Persian Calendar Picker 📅

## معرفی
**Persian Calendar Picker** یک ویجت انتخاب تاریخ شمسی برای **Tkinter** است که به شما امکان انتخاب تاریخ شمسی با طراحی زیبا و کاربرپسند را می‌دهد.

## ویژگی‌ها ✅
- نمایش تقویم شمسی با طراحی زیبا
- امکان تغییر ماه‌ها و انتخاب روزها
- هایلایت تاریخ روز جاری
- مناسب برای برنامه‌های پایتونی با رابط گرافیکی Tkinter

## نصب 📥
برای نصب این پکیج از دستور زیر استفاده کنید:
```
pip install persian_calendar_picker
```

## نحوه استفاده 🛠
```python
import tkinter as tk
from persian_calendar_picker.calendar import PersianCalendar

def on_date_selected(date):
    print(f"تاریخ انتخاب شده: {date}")

root = tk.Tk()
calendar = PersianCalendar(root, callback=on_date_selected)
root.mainloop()
```

## مشارکت 🤝
اگر قصد دارید در بهبود این پروژه کمک کنید، می‌توانید **Pull Request** ارسال کنید یا در بخش **Issues** مشکلات را گزارش دهید.

## مجوز 📜
این پروژه تحت مجوز **MIT** منتشر شده است. استفاده، تغییر و انتشار آن برای عموم آزاد است.

---
ctadl-networkx-export-plugin 0.0.1
Exports the CTADL database to networkx format
Requires Python: >=3.9

# CTADL networkx graph export

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

This project provides a plugin for CTADL to export data flow graph information via networkx.

# Installation

Use pip.

    $ pip install ctadl-networx-export-plugin

Afterward, if ctadl is installed, you can do:

    $ ctadl export --format gml pcode /path/to/a/binary

See `ctadl --help` for more detauls.
sage-book-server 0.1.2
Sage Book Server Package
Requires Python: >=3.10

# Jupyter MCP Server

A basic description of your Jupyter MCP Server package.

## Installation

```bash
pip install sage-book-server
```

Or using uv:

```bash
uv pip install sage-book-server
```

## Running the Server

1. Start Jupyter Lab:
```bash
jupyter lab --port 8888 --IdentityProvider.token MY_TOKEN --ip 0.0.0.0
```

2. In a separate terminal, start the MCP server:
```bash
sage-book-server
```

3. Add the following variables to your environment
```
# Claude Configuration
CLAUDE_API_KEY=""
CLAUDE_MODEL_ID="claude-3-7-sonnet-20250219"
CLAUDE_MODEL_URL="https://sage.alpinex.ai:8760" # use passthrough

# Gemini Configuration
GEMINI_API_KEY=""
GEMINI_MODEL_ID="gemini-2.5-pro-preview-03-25"
GEMINI_MODEL_URL="https://generativelanguage.googleapis.com"

# Server Configuration
MCP_SERVER_URL="http://localhost:8888"
MCP_SERVER_PORT="7888"

# override by docker
JUPYTER_SECRET_KEY="MY_TOKEN"
DATABASE_URL=""
NOTEBOOK_DIR="./"
```


## Notes
- Replace `MY_TOKEN` with your desired authentication token
- The server will be accessible at `http://localhost:8888`
- Make sure to keep all three processes running (Jupyter Lab and both MCP server/client instances)

## MCP Server Setup with `uv`

1. **Install `uv` (if not already installed)**  
   ```bash
   curl -Ls https://astral.sh/uv/install.sh | bash
   ```

2. **Navigate to your directory**  
   ```bash
   cd /path/to/your/project
   ```

3. **Create a `uv`-managed virtual environment (Python 3.10)**  
   ```bash
   uv venv --python=3.10 .venv
   ```

4. **Activate the environment**  
   ```bash
   source .venv/bin/activate
   ```

5. **Install all required packages**  
   ```bash
   uv pip install -r requirements.txt
   ```

6. **Run the MCP server**  
   ```bash
   uv run sage-book-server
   ```
mlotsawa 1.0.0
The purpose of this module is user-friendly translation and transliteration of Classical Tibetan.
Requires Python: >=3.8

# mlotsawa

## Description

The purpose of this module is user-friendly translation and transliteration of Classical Tibetan. 

Currently, separate classes are provided for translation and transliteration tasks. Both classes will accept either a list of strings,
or a single string. The output of each will be of the same type as the input.

You can also run the translator and transliteration functions through a web-based user interface. The web interface will open automatically
when you use the code below. You can use this to serve the app to others on your network, as well.

Under the hood, this module uses the T5 transformer architecture, custom fine-tuned on data
from [Lotsawa House](www.lotsawahouse.org).

The models and datasets used by this project can be found on [Hugging Face](https://huggingface.co/billingsmoore) where you can find more
information on training, data collection, and how to use these models and datasets for your own projects.

This module is part of the larger MLotsawa project for machine translation of Literary Tibetan. The code for the entire project, 
including this module is [available on GitHub here.](https://github.com/billingsmoore/MLotsawa)

## Installation

```
pip install --upgrade mlotsawa
```

## Examples

For transliteration:

```python
from mlotsawa.transliterator import Transliterator 

tibetan_text = '<your Tibetan text>'

transliterator = Transliterator()

phonetics = transliterator.transliterate(tibetan_text)
```

For translation:

```python
from mlotsawa.translator import Translator 

tibetan_text = '<your Tibetan text>' # may be in Tibetan script or phoneticized

translator = Translator()

translation = translator.translate(tibetan_text)
```

To serve the Web based user-interface:

```python
from mlotsawa.webui import WebUI

webui = WebUI()

webui.run()
```

The WebUI.run() method has several optional parameters. These parameters and their default values are shown below.

```python
from mlotsawa.webui import WebUI

webui = WebUI()

webui.run(
    logging=False, # keep log of when translations are done through your host
    log_filepath='mlotsawa_logs.txt', # filepath and filename to be used for the log file (i.e. '/my_log_folder/my_logs.txt)
    port=5000, # which port to run the webui from
    autolaunch=True # automatically start the webapp in your default browser
)
```

## License

Shield: [![CC BY-NC-SA 4.0][cc-by-nc-sa-shield]][cc-by-nc-sa]

This work is licensed under a
[Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License][cc-by-nc-sa].

[![CC BY-NC-SA 4.0][cc-by-nc-sa-image]][cc-by-nc-sa]

[cc-by-nc-sa]: http://creativecommons.org/licenses/by-nc-sa/4.0/
[cc-by-nc-sa-image]: https://licensebuttons.net/l/by-nc-sa/4.0/88x31.png
[cc-by-nc-sa-shield]: https://img.shields.io/badge/License-CC%20BY--NC--SA%204.0-lightgrey.svg

## Owner

[@billingsmoore](https://github.com/billingsmoore)