semvec/pypi-packages huggingface dataset:
rfc9457 0.4.1
Implementation of RFC9457 problems.
Requires Python: >=3.10
Keywords: exception, handler, webdev

# RFC9457 implementation for Python
[![uv](https://img.shields.io/endpoint?url=https://raw.githubusercontent.com/astral-sh/uv/main/assets/badge/v0.json)](https://github.com/astral-sh/uv)
[![ruff](https://img.shields.io/endpoint?url=https://raw.githubusercontent.com/astral-sh/ruff/main/assets/badge/v2.json)](https://github.com/astral-sh/ruff)
[![image](https://img.shields.io/pypi/v/rfc9457.svg)](https://pypi.org/project/rfc9457/)
[![image](https://img.shields.io/pypi/l/rfc9457.svg)](https://pypi.org/project/rfc9457/)
[![image](https://img.shields.io/pypi/pyversions/rfc9457.svg)](https://pypi.org/project/rfc9457/)
![style](https://github.com/NRWLDev/rfc9457/actions/workflows/style.yml/badge.svg)
![tests](https://github.com/NRWLDev/rfc9457/actions/workflows/tests.yml/badge.svg)
[![codecov](https://codecov.io/gh/NRWLDev/rfc9457/branch/main/graph/badge.svg)](https://codecov.io/gh/NRWLDev/rfc9457)

`rfc9457` is a set of exceptions to support easy error management and responses
in web based apis.

Each exception easily marshals to JSON based on the
[RFC9457](https://www.rfc-editor.org/rfc/rfc9457.html) spec for use in api
errors.

This library is currently used to support problem details in both Starlette and FastAPI.

[starlette-problem](https://pypi.org/project/starlette-problem)
[fastapi-problem](https://pypi.org/project/fastapi-problem)

## Custom Errors

Subclassing the convenience classes provides a simple way to consistently raise
the same error with details/extras changing based on the raised context.

```python
from rfc9457 import NotFoundProblem


class UserNotFoundError(NotFoundProblem):
    title = "User not found."


UserNotFoundError(
    detail="details",
    custom_key="value",
).marshal()
```

```json
{
    "type": "user-not-found",
    "title": "User not found",
    "status": 404,
    "detail": "details",
    "custom_key": "value",
}
```
proxy-reader 2.1.5
Proxy reader for Python
Requires Python: >=3.12




# proxy-reader - A simple but useful bulk proxies reader and checker.

This is useful when you are working with multiple proxies and want to bulk check
these proxies before using them.
It has iterators to iterate the proxies for easy reading.


## Installation

```
pip install proxy-reader
```

## Changelogs

### [v0.3.0]
*   Add load_list class method to load proxies from list
*   MAJOR: auto detect the proxies format
*   Use new logging config to disable logs and prevent proxy_reader.log from creating
*   Logs can be enabled from user-side
*   Add option to disable proxies checking from __init__


### [v0.2.0] - 2024-10-21

*   Previous unrecorded changes


For more info/queries Telegram: [@runetech](https://t.me/runetech)
windows-capture-mcp 0.1.1
MCP server for capturing Windows screenshots and sharing them as base64 images
Requires Python: >=3.11
Keywords: llm, mcp, screen-capture, screenshot, windows

# WindowsCaptureMCP

An MCP (Model Context Protocol) server for capturing Windows screenshots and sharing them as base64-encoded images with LLMs.

> **Windows only** — This package requires Windows and uses Win32 APIs for screen capture and window management.

## Features

- List and filter visible windows
- Capture windows, full screen, or custom regions
- Low-quality preview images for quick verification before full capture
- Window management (focus, maximize, resize, move)
- Multi-display support
- PNG / JPEG / WebP output formats

## Requirements

- **Windows**
- **Python >= 3.11**

## Installation

```bash
# Using uvx (recommended)
uvx windows-capture-mcp

# Using pip
pip install windows-capture-mcp
```

## MCP Client Configuration

### Claude Code

Run the following command to register the MCP server:

```bash
# Register for all projects (user scope)
claude mcp add windows-capture-mcp -s user -- uvx windows-capture-mcp

# Register for the current project only (project scope)
claude mcp add windows-capture-mcp -s project -- uvx windows-capture-mcp
```

After registration, restart Claude Code to load the new MCP server. You can verify it is running with `/mcp`.

### Claude Desktop

Add the following to your `claude_desktop_config.json`:

```json
{
  "mcpServers": {
    "windows-capture-mcp": {
      "command": "uvx",
      "args": ["windows-capture-mcp"]
    }
  }
}
```

## Available Tools

### Information

| Tool | Description |
|------|-------------|
| `list_windows` | List visible windows with optional title filtering (case-insensitive) |
| `list_displays` | List all connected displays with resolution, position, and scale info |

### Screen Capture (Full Quality)

| Tool | Description |
|------|-------------|
| `capture_window` | Capture a specific window by handle |
| `capture_fullscreen` | Capture an entire display |
| `capture_region` | Capture a rectangular region |

All capture tools support `format` (`"png"`, `"jpeg"`, `"webp"`) and `quality` (1-100) parameters.

### Preview (Lightweight)

| Tool | Description |
|------|-------------|
| `preview_window` | Low-quality preview of a window |
| `preview_fullscreen` | Low-quality preview of a display |
| `preview_region` | Low-quality preview of a region |

Preview images are JPEG at quality 30, resized to max 1280px on the longest side. Use these to verify capture targets before taking full-quality screenshots.

### Window Management

| Tool | Description |
|------|-------------|
| `focus_window` | Bring a window to the foreground |
| `maximize_window` | Maximize a window |
| `resize_window` | Resize a window (keeps position) |
| `move_window` | Move a window (keeps size) |

## Usage Example

```
1. list_windows(filter="Chrome")       → Find browser windows
2. preview_window(hwnd=12345)           → Quick preview to verify
3. capture_window(hwnd=12345)           → Full-quality capture
```

## License

MIT
smartdata-engine 1.0.0
Lightweight, industrial-grade data processing engine for large CSV files
Requires Python: >=3.8
Keywords: data-processing, etl, csv, parquet, analytics, big-data

# SMARTDATA ENGINE

**Industrial-Grade Data Processing Engine for Large CSV Files**

![Version](https://img.shields.io/badge/version-1.0.0-blue)
![Python](https://img.shields.io/badge/python-3.8%2B-green)
![License](https://img.shields.io/badge/license-MIT-orange)

## 🚀 Features

- **Memory-Safe Processing**: Adaptive chunking based on system RAM
- **Fault-Tolerant**: Continue processing even if chunks fail
- **High Performance**: Optimized pandas operations with progress tracking
- **Smart Validation**: Null detection, duplicate checks, schema validation
- **Multiple Output Formats**: CSV, JSON, Parquet support
- **Production Ready**: Comprehensive logging, metrics, and error handling
- **Extensible**: Plugin-style operation system

## 📦 Installation

```bash
# Install from PyPI
pip install smartdata-engine

# Or install locally
git clone https://github.com/yourusername/smartdata-engine.git
cd smartdata-engine
pip install -e .