semvec/pypi-packages huggingface dataset:
chromium-profile-cli 0.3.0
CLI tool for accessing Chromium browser data (tabs, history, bookmarks)
Requires Python: >=3.11
Keywords: bookmarks, brave, browser, chrome, chromium, cli, history, tabs

# chromium-profile-cli

Command-line tool for accessing Chromium browser data (tabs, history, bookmarks).

Works with **Brave**, **Chrome**, and **Chromium**.

## Installation

```bash
# Using uvx (recommended)
uvx chromium-profile-cli

# Or install with pip
pip install chromium-profile-cli
```

## First Run

On first run, chromium-profile-cli will automatically detect installed browsers and prompt you to select one:

```bash
$ chromium-profile-cli status

🔍 Multiple browser profiles detected:

  1. brave      /Users/you/Library/Application Support/BraveSoftware/Brave-Browser/Default
  2. chrome     /Users/you/Library/Application Support/Google/Chrome/Default

Select a browser [1]: 1

💾 Save as default? [Y/n]: y
✓ Saved to ~/.config/chromium-sync/profile
```

## Commands

### Configuration

```bash
# Show current configuration
chromium-profile-cli config show

# Interactively select a browser
chromium-profile-cli config set

# Manually set profile path
chromium-profile-cli config set-path /path/to/profile
```

### Tabs

```bash
# Show local browser tabs
chromium-profile-cli tabs local

# Show tabs from all synced devices
chromium-profile-cli tabs synced

# JSON output
chromium-profile-cli tabs local --json
```

### History

```bash
# Search by text (substring match)
chromium-profile-cli history -q github

# Search by regex pattern
chromium-profile-cli history -p "docs\\.python\\.org"

# Limit results
chromium-profile-cli history -q python -l 50

# Filter by date
chromium-profile-cli history --days 7
chromium-profile-cli history --after 2026-01-01
chromium-profile-cli history --before 2026-02-01

# JSON output
chromium-profile-cli history -q python --json
```

### Bookmarks

```bash
# List all bookmarks
chromium-profile-cli bookmarks list

# Search bookmarks
chromium-profile-cli bookmarks search python

# Filter by folder ID
chromium-profile-cli bookmarks list --folder 123

# JSON output
chromium-profile-cli bookmarks search python --json
```

### Status

```bash
# Check what data is accessible
chromium-profile-cli status
```

## Environment Variables

Set `CHROMIUM_PROFILE_PATH` to override auto-detection:

```bash
export CHROMIUM_PROFILE_PATH=~/.config/google-chrome/Default
chromium-profile-cli status
```

## How It Works

Reads directly from your browser's local profile files:

- **History**: SQLite database
- **Bookmarks**: JSON file
- **Synced Tabs**: LevelDB (contains tabs from all your synced devices)

No authentication or network requests required.

## License

Apache 2.0
bulkman 1.2.1
Bulkhead pattern implementation with Trio for structured concurrency and resilient circuit breaking
Requires Python: >=3.9

# Bulkman

**Enterprise-Grade Bulkhead Pattern for Python**

Bulkman is a robust, production-ready implementation of the Bulkhead pattern, designed to isolate resources and prevent cascading failures in mission-critical distributed systems. It supports both modern async (Trio) and traditional synchronous (Threading) workloads with zero overhead.

## Key Capabilities

- **Resource Isolation**: Limits concurrent access to prevent service exhaustion.
- **Circuit Breaker Integration**: Built-in distributed circuit breaking via `resilient-circuit`.
- **Dual Mode**:
    - **Async**: Native [Trio](https://trio.readthedocs.io/) support for high-concurrency IO.
    - **Sync**: Zero-overhead `ThreadPoolExecutor` implementation for CPU-bound or blocking IO tasks.
- **Observability**: Full `contextvars` support for distributed tracing (OpenTelemetry/Datadog).
- **Type Safe**: 100% type-hinted and rigorously tested (>92% coverage).

## Documentation

- **[User Guide](docs/user_guide.md)**: Installation, Quick Start (Async), and Configuration.
- **[Synchronous / Threading Guide](docs/threading_bulkhead.md)**: Best practices for blocking workloads (Flask, Django, Scripts).
- **[Contributing](docs/contributing.md)**: Setup, testing, and contribution guidelines.

## Quick Install

```bash
pip install bulkman
```

## Quick Example (Blocking/Threading)

For legacy or synchronous applications, use `BulkheadThreading`:

```python
from bulkman import BulkheadThreading, BulkheadConfig

# Configure
config = BulkheadConfig(name="db_writer", max_concurrent_calls=10, timeout_seconds=5.0)
bulkhead = BulkheadThreading(config)

# Execute
try:
    future = bulkhead.execute(my_blocking_function, data)
    result = future.result(timeout=5.0)
    print(result.result)
except TimeoutError:
    print("System overloaded")
```

👉 **[See the User Guide for Async/Trio examples](docs/user_guide.md)**

## License

Licensed under the [Apache License 2.0](LICENSE).
dbgeng-mcp 0.1.0
A Model Context Protocol server for the Windows Debugging Engine (dbgeng)
Requires Python: >=3.10
Keywords: debugger, windbg, dbgeng, mcp, reverse-engineering, windows

# dbgeng-mcp

A Model Context Protocol (MCP) server that interfaces with the Windows Debugging Engine (`dbgeng.dll`) using a native C++ bridge (pybind11).

> **Alpha software** — this project is under active development. APIs and tool names may change between releases. Feedback and bug reports are welcome.

## Features
- Native x64 debugging on Windows.
- Managed debugging session lifecycle.
- Core process control (Launch, Attach, Break, Continue, Step).
- State inspection (Registers, Memory, Stack).

## Prerequisites

### Windows (target machine)
- **Python 3.10+** (x64)
- **Debugging Tools for Windows** — install via the Windows SDK:
  1. Download the [Windows SDK](https://developer.microsoft.com/en-us/windows/downloads/windows-sdk/).
  2. During install, select **"Debugging Tools for Windows"**. No other components are required.
  3. The installer places `dbgeng.dll` under `C:\Program Files (x86)\Windows Kits\10\Debuggers\x64\`.

  > The system `dbgeng.dll` in `System32` works as a fallback, but the SDK version is recommended for full functionality. The server auto-discovers the SDK installation via the registry.

## Installation

```powershell
pip install dbgeng-mcp
```

To build from source instead, see [CONTRIBUTING.md](CONTRIBUTING.md).

## Usage

### Running the MCP server
```powershell
dbgeng-mcp
```

### Agent configuration

Add the server to your agent's MCP configuration file.

**Claude Desktop** (`claude_desktop_config.json`):
```json
{
  "mcpServers": {
    "dbgeng": {
      "command": "dbgeng-mcp"
    }
  }
}
```

**Claude Code** (`.mcp.json`):
```json
{
  "mcpServers": {
    "dbgeng": {
      "command": "dbgeng-mcp"
    }
  }
}
```
symlib 1.5.4
A library for working with data from the Symphony and MW-est zoom-in suites.
Requires Python: >=3.6
Keywords: python

# Symphony
This repository contains code related to the Symphony zoom-in simulation suite.

The website for this simulation suite as well as the documentaiton for the symlib analysis library can be found at [https://phil-mansfield.github.io/symphony/index.htm](http://web.stanford.edu/group/gfc/symphony/)