semvec/pypi-packages huggingface dataset:
bindos 0.2.0
Curvature-based time-series stabilizer with ZOL-Q two-branch Pro engine
Requires Python: >=3.10


# BindOS

BindOS is a small library and CLI that flattens the curvature of numeric time series.
It was born from quantum experiments where it turned noisy fidelity trajectories into almost geodesic curves.

## Install

BindOS is in local development mode:

```bash
pip install -e .

from bindos.core import stabilize

series = [0.8, 0.82, 0.79, 0.81]
res = stabilize(series, steps=10, alpha=0.5)
print("Initial curvature:", res["curvature_initial"])
print("Stabilized curvature:", res["curvature_stabilized"])

Initial curvature: {'mean': 5.55e-17, 'std': 0.05, 'max': 0.05, 'min': -0.05, 'n': 2}
Stabilized curvature: {'mean': 0.0, 'std': 4.88e-05, 'max': 4.88e-05, 'min': -4.88e-05, 'n': 2}

bindos-run hybrid_qgeo_two_branch_hist.csv --column-index 2 --max-rows 100 --steps 20 --alpha 0.4 --output hybrid_qgeo_two_branch_hist_stab.csv

Header: ['iter', 'purity', 'fidelity', 'k1', 'k2', 'D_base', 'D_ghz', 't1', 't2', 'alpha']
Loaded points: 100
Score: {...}
Initial curvature: {...}
Stabilized curvature: {...}
Wrote stabilized CSV to: hybrid_qgeo_two_branch_hist_stab.csv

iter,purity,fidelity,...,fidelity_stabilized
0,0.9861,0.9930,...,0.9930
1,0.9791,0.9894,...,0.9923
2,0.9784,0.9891,...,0.9917


## BindOS Pro: ZOL-Q Two-Branch Engine (IBM Fez demo)

BindOS includes an experimental Pro engine (`stabilize_pro`) implementing a ZOL-Q
two-branch geodesic binding step.

Example on a 4-step purity trajectory derived from an IBM Fez-style Bell experiment:

```python
from bindos import stabilize_pro

series = [1.0, 0.862592, 0.751633, 0.662069]
res = stabilize_pro(
    series,
    steps=16,
    kappa=0.4,
    anchor_mode="linear",
    schedule_mode="cosine",
)

print(res["curvature_initial"])
print(res["curvature_stabilized"])
iflow-mcp_mcp_server_bing 0.1.1
MCP server implementation for Bing Search API integration
Requires Python: >=3.10

# Bing Search MCP Server

A Model Context Protocol (MCP) server for Microsoft Bing Search API integration, allowing AI assistants to perform web, news, and image searches.

[![smithery badge](https://smithery.ai/badge/@leehanchung/bing-search-mcp)](https://smithery.ai/server/@leehanchung/bing-search-mcp)

![Bing Search MCP Server](assets/mcp_server_bing.png)


## Features

- Web search for general information
- News search for recent events and timely information
- Image search for visual content
- Rate limiting to prevent API abuse
- Comprehensive error handling

## Requirements

- Python 3.10 or higher
- Microsoft Bing Search API key
- MCP-compatible client (e.g., Claude Desktop, Cursor)

## Installation

1. Clone this repository
2. Install dependencies:
   ```
   uv venv
   source .venv/bin/activate  # On Windows: .venv\Scripts\activate
   uv pip install -e .
   ```

## Configuration

Set the required environment variables:

```bash
export BING_API_KEY="your-bing-api-key"
export BING_API_URL="https://api.bing.microsoft.com/"  # Optional
```

For Windows:
```cmd
set BING_API_KEY=your-bing-api-key
set BING_API_URL=https://api.bing.microsoft.com/
```

## Usage

### Running the server

```
uvx bing-search-mcp
```

### Configuring with Claude for Desktop

Add the following to your Claude Desktop configuration file (`~/Library/Application Support/Claude/claude_desktop_config.json` on macOS or `%APPDATA%\Claude\claude_desktop_config.json` on Windows):

```json
{
  "mcpServers": {
    "bing-search": {
      "command": "uvx",
      "args": [
        "/path/to/your/bing-search-mcp"
      ],
      "env": {
        "BING_API_KEY": "your-bing-api-key"
      }
    }
  }
}
```
![Claude Code Bing Search MCP](assets/claude_bing_search.png)

## Available Tools

### 1. bing_web_search
General web search for information, websites, and content.

```python
bing_web_search(query: str, count: int = 10, offset: int = 0, market: str = "en-US")
```

### 2. bing_news_search
Search for news articles and current events.

```python
bing_news_search(query: str, count: int = 10, market: str = "en-US", freshness: str = "Day")
```

### 3. bing_image_search
Search for images.

```python
bing_image_search(query: str, count: int = 10, market: str = "en-US")
```

## Getting a Bing API Key

1. Visit [Microsoft Azure Portal](https://portal.azure.com/)
2. Create or sign in to your Azure account
3. Create a new Bing Search resource
4. Go to the resource and find your API key in the "Keys and Endpoint" section

## License

[MIT License](LICENSE)
getpost-fileserver 0.1.0
A simple Python HTTP file server for upload and download, with optional GUI.
Requires Python: >=3.8
Keywords: http, file-server, upload, download, get, post, teaching

# Install
- This is learning project tested in Kali  and Win11.
- In Kali or any Linux, use this command to install:
    - `pipx install getpost-fileserver`
- While in Windows, use:
    - `py -m pip install getpost-fileserver`
- `getpost-fileserver-cli.py` is the no GUI version.
- While `getpost-fileserver.py` is with GUI.
- Tested in Kali and Windows10/11

# Start GUI version `getpost-fileserver.py`
- In Kali's terminal, use `getpost-fileserver.py`.
- In Windows CMD, use `py -m runpy getpost_fileserver.app`.

# Start CLI version `getpost-fileserver-cli.py`
- In Kali's terminal, use `getpost-fileserver-cli.py`.
- In Windows CMD, use `py -m runpy getpost_fileserver.server`.

# Intro
This Tool will run python based http GET and Post webserver.

Usage:
1. The server will list (GET) the content of the current directory where the app located:
    Browse the IP of the machine with the selected port `http://192.168.8.10:80`
    Or you can use one of the following in linux: \
    `wget http://192.168.8.10:80/` \
    Or:
    `curl http://192.168.8.10:80/`

1. The server will accept transferred files (POST) 
    and save them to current directory where the app located.
    You can use one of the following: \
    - Using curl \
    `curl.exe -X POST -H "X-Filename: nmap.exe" --data-binary "@C:\Users\kaled\Downloads\nmap-7.98-setup.exe" http://192.168.8.10:80/` \
    you will get `nmap.exe` after the upload. \
    Where: 
        - `-X` Use the HTTP POST method (send data in the request body).
        - `-H` "X-Filename: nmap.exe". Add a custom HTTP header named X-Filename with value nmap.exe (your server reads this to pick the filename to save).
        - `--data-binary "@C:\Users\kaled\Downloads\nmap-7.98-setup.exe"` Send the exact bytes of that local file as the HTTP request body. The @ tells curl to read the file contents.
        - `http://192.168.8.10:80/` The destination URL (IP and port 80).

    - Using wget \
    `wget --method=POST --header="X-Filename: test.txt" --header="Content-Type: application/octet-stream" --body-file="C:\Users\kaled\Downloads\somefile.txt" "http://192.168.8.10:80/"` \
    Where: \
        - `--method=POST` sets the method to POST.
        - `--header=...` sends the custom X-Filename header.
        - `test.txt` the file name after transferring, it can be anything like `key.pem`.
        - `--body-file=somefile.txt` sends the file as raw binary.
        - `somefile.txt` the file name before transferring, it should be exact.

Created by Kaled Aljebur for learning purposes in teaching classes.