semvec/pypi-packages huggingface dataset:
brenthy-tools-beta 4.0.8
A library for interacting with Brenthy (`brenthy_api`) and a collection of tools common to Brenthy Core and `brenthy_api`.
Requires Python: >=3.6

# Brenthy
Here lives the source code for Brenthy, the framework for developing and deploying new kinds of blockchain in the Python programming language.

## Learn about Brenthy:

Main docs:
- [Introduction to Brenthy](/Documentation/Brenthy/Meaning/IntroductionToBrenthy.md)
- [Running from Source](/Documentation/Brenthy/User/RunningFromSource.md)
- [Installation](/Documentation/Brenthy/User/InstallingBrenthy.md)
- Create Blockchains for Brenthy: _coming soon..._

Overview of all docs: [/Documentation/DocsOverview.md](/Documentation/DocsOverview.md)


## Walytis
Walytis is the novel blockchain Brenthy was originally built for.
Read the [Introduction to Walytis](/Documentation/Walytis/Meaning/IntroductionToWalytis.md) to learn more.
The source code for Walytis is located under [./blockchains/Walytis_Beta](./blockchains/Walytis_Beta/ReadMe.md)
mcp-query 0.1.0
A tool to query Context7 MCP server for documentation
Requires Python: >=3.6

# Context7 MCP Query Script

## Overview

The `mcp_query.py` script enables Aider to query the Context7 MCP server for up-to-date library documentation, enhancing coding assistance with current information.

## Why Aider?

Aider was chosen for this integration because of its:
- Seamless command-line workflow integration
- Token-efficient design
- Focused context management
- Support for cost-effective models like DeepSeek

### Key Advantages Over Alternatives

1. **Token Efficiency**  
   Aider only adds necessary files to chat sessions and pulls related context via repository mapping, saving tokens compared to tools like Cursor that may index entire codebases.

2. **Cost Effectiveness**  
   Large projects can exceed 20k tokens with other tools, while Aider's focused approach keeps token usage manageable, especially when combined with economical models.

3. **Optimized Workflow**  
   The combination of Aider and Context7 MCP ensures documentation can be fetched and utilized without exceeding token limits.

## Usage

```bash
python mcp_query.py [query]
```

Replace `[query]` with your search term for Context7 documentation.

## Requirements

- Python 3.x
- Aider installed and configured
- Context7 MCP server access
ngenicpy 0.5.2
Python package for simple access to Ngenic Tune API.
Requires Python: >=3.12
Keywords: api, hass, integration, ngenic, sdk

# Ngenic Tune Python API Wrapper

This python package simplifies access to the Ngenic Tune API.
It can be used for viewing or edit your Tune configuration.

Both sync and async APIs are provided - async APIs are prefixed with `async_`.

**NOTE**: This API wrapper is not yet finished, and only implements a subset of all the APIs. The interface may very well change.

## Prerequisite

### Obtain an API token

An API token may be obtained here: https://developer.ngenic.se/

## Installation

```
$ pip install ngenicpy
```

## Example

```python
import json

from ngenicpy import Ngenic

# try/finally
try:
    ngenic = Ngenic(token="YOUR-API-TOKEN")
except NgenicException as e:
        print(str(e))
finally:
    ngenic.close()

# as context manager
with Ngenic(token="YOUR-API-TOKEN") as ngenic:
    tunes = ngenic.tunes()
    for tune in tunes:
        print("Tune %s\nName: %s\nTune Name: %s" %
                (
                    tune.uuid(),
                    tune["name"],
                    tune["tuneName"]
                )
        )

    tune = ngenic.tune("TUNE-UUID")

    rooms = tune.rooms()
    for room in rooms:
        print("Room %s\nName: %s\nTarget Temperature: %d" %
                (
                    room.uuid(),
                    room["name"],
                    room["targetTemperature"]
                )
        )

    # Update a room
    room = tune.room(room_uuid="ROOM-UUID")
    room["name"] = "Livingroom"
    room.update()

    nodes = tune.nodes()
    for node in nodes:
        node_status = node.status()

        print("Node %s\nType: %s" %
                (
                    node.uuid(),
                    node.get_type()
                )
        )

        if node_status:
            print("Battery: %s\nRadio Signal: %s" %
                    (
                        str(node_status.battery_percentage()),
                        str(node_status.radio_signal_percentage())
                    )
            )

        measurements = node.measurements()
        for measurement in measurements:
            print("%s: %d" %
                    (
                        measurement.get_type(),
                        measurement["value"]
                    )
            )
```

Async example

```python
import json

from ngenicpy import Ngenic

async with AsyncNgenic(token="YOUR-API-TOKEN") as ngenic:
    tunes = await ngenic.async_tunes()
    for tune in tunes:
        print("Tune %s\nName: %s\nTune Name: %s" %
                (
                    tune.uuid(),
                    tune["name"],
                    tune["tuneName"]
                )
        )
```

## Reference

[Ngenic Tune Public API](https://developer.ngenic.se/)
hdocker-nuke 1.1.3
Quickly `kill`, then `rm` a container
Requires Python: >=3.10

![GitHub Repo stars](https://img.shields.io/github/stars/hamolicious/docker-nuke?style=flat-square&label=Github%20Stars)
[![PyPI - Version](https://img.shields.io/pypi/v/hdocker-nuke?style=flat-square)](https://pypi.org/project/hdocker-nuke/)

# docker-nuke

Quickly `kill`, then `rm` a docker container by it's name or SHA.

```bash
% docker-nuke ollama
Targets Locked:
         - 635c0c064feaa404d1d4b9638bb5cc1d1cff98ca9e4bf3d9b533d093a233d3d1 ollama
Fire? (y/N)
```

## Install

```bash
pipx install hdocker-nuke
```