semvec/pypi-packages huggingface dataset:
secure-mcp-gateway 2.1.7
Enkrypt Secure MCP Gateway
Requires Python: >=3.8
Keywords: MCP, gateway, secure, middleware, async, python, model context protocol, guardrails, Enkrypt, Enkrypt AI, EnkryptAI, AI

# Enkrypt Secure MCP Gateway

A secure gateway for Model Control Protocol (MCP) that enables safe and controlled access to MCP servers.

```bash
pip install secure-mcp-gateway

```

For documentation and usage instructions, please visit our GitHub repository:

**[https://github.com/enkryptai/secure-mcp-gateway](https://github.com/enkryptai/secure-mcp-gateway)**

## License

### Enkrypt AI MCP Gateway Core

This project's core functionality is licensed under the MIT License.

<!-- In addition to the MIT License, the following additional terms apply:

- You can freely use, modify, and distribute this software as part of your commercial product

- You can use this as part of your commercial product if your product is not an MCP gateway or gateway-based service

- You cannot sell this gateway as a standalone product -->

For the full license text, see the `LICENSE.txt` file in the repository.

### Enkrypt AI Guardrails, Logo, and Branding

© 2025 Enkrypt AI. All rights reserved.

Enkrypt AI software is provided under a proprietary license. Unauthorized use, reproduction, or distribution of this software or any portion of it is strictly prohibited.

Terms of Use: [https://www.enkryptai.com/terms-and-conditions](https://www.enkryptai.com/terms-and-conditions)

Privacy Policy: [https://app.enkryptai.com/privacy-policy](https://app.enkryptai.com/privacy-policy)

Enkrypt AI and the Enkrypt AI logo are trademarks of Enkrypt AI, Inc.
easyqc 1.3.0
Seismic viewer for numpy
Requires Python: >=3.10

# EasyQC
Seismic Viewer for numpy arrays using pyqtgraph.

## Usage Instructions
The goal is to provide an interactive seismic viewer at the python prompt.
NB: if you use `ipython` use the `%gui qt` magic command before !

### Keyboard Shortcuts
-   **ctrl + A**: increase display gain by +3dB 
-   **ctrl + Z**: deacrease display gain by +3dB
-   **ctrl + P**: take screenshot to clipboard
-   **ctrl + P**: propagates display accross all windows (same window size, same axis, same gain)
-   **ctrl + S**: captures screenshot of the plot area in the clipboard
-   **up/down/right/left arrows**: pan using keyboard

### Minimum working example to display a numpy array.

```python
import numpy as np
import scipy.signal

from easyqc.gui import viewseis

ntr, ns, sr, dx, v1 = (500, 2000, 0.002, 5, 2000)
data = np.zeros((ntr, ns), np.float32)
data[:, 500:600] = scipy.signal.ricker(100, 4)

# create a record with 400 traces and 2500 samples
noise = np.random.randn(ntr, ns) / 10
# create an arbitrary layout of 2 receiver lines of 200 sensors
a, b = np.meshgrid(np.arange(ntr / 2) * 8 + 2000, np.arange(2) * 50 + 5000)
# the header is a dictionary of numpy arrays, each entry being the same length as the number of traces
header = {'receiver_line': b.flatten(), 'receiver_number': a.flatten()}

# show the array with the header
fig0 = viewseis(data, si=.002, h=header, title='clean')
fig1 = viewseis(data + noise, si=.002, h=header, title='noisy')

```

## Install Instructions

### 1) From pypi using pip:
`pip install easyqc`

### 2) From sources using pip:
I suggest to use a virtual environment and install in development mode (in-place)
```
git clone https://github.com/oliche/easyqc.git
cd easyqc
pip install -e .
```

### 3) From sources using uv

I suggest to install a new `uv`environment and run from sources in development mode.

#### Installation
```
git clone https://github.com/oliche/easyqc.git
uv python install 3.13
uv venv --python 3.13
uv pip install -e .
```


## Contribution
`pdm` is used to manage the dependencies and the virtual environment. `pip install pdm` to install it.

Pypi Release checklist
- Update version in `pyproject.toml`
- Linting:
  - `ruff check .`
  - `ruff format .` 
- publish on pypi:
```shell
rm -fR dist
rm -fR .pdm-build
pdm publish
```
- tag the commit 
```shell
git tag -a 1.0.0
git push origin 1.0.0
```
amulet-leveldb 1.0.3
A Cython wrapper for Mojang's custom LevelDB.
Requires Python: ~=3.8

# Amulet LevelDB

A Cython wrapper for Mojang's modified LevelDB library.


## Install
`pip install amulet-leveldb`

## Use
```py
from leveldb import LevelDB

create_if_missing = True  # optional input. Default False.
db = LevelDB("path/to/db", create_if_missing)
db.put(b"key", b"value")
print(db.get(b"key"))
# b"value"
```

See the [source code](src/leveldb/_leveldb.pyx) for full documentation.
feeluown 5.1a0
*nix music player
Requires Python: >=3.10
Keywords: media, player, application, PyQt6, music

## FeelUOwn - feel your own

[![Documentation Status](https://readthedocs.org/projects/feeluown/badge/?version=latest)](http://feeluown.readthedocs.org)
[![Build Status](https://github.com/feeluown/feeluown/actions/workflows/build.yml/badge.svg?branch=master)](https://github.com/feeluown/FeelUOwn)
[![Coverage Status](https://coveralls.io/repos/github/feeluown/FeelUOwn/badge.svg)](https://coveralls.io/github/feeluown/FeelUOwn)
[![PyPI](https://img.shields.io/pypi/v/feeluown.svg)](https://pypi.python.org/pypi/feeluown)
[![python](https://img.shields.io/pypi/pyversions/feeluown.svg)](https://pypi.python.org/pypi/feeluown)

FeelUOwn 是一个稳定、用户友好以及高度可定制的音乐播放器。

[![macOS 效果预览](https://github.com/user-attachments/assets/6d96c655-e35b-46d8-aaec-4d4dc202347f)](https://www.bilibili.com/video/av46787694/)

### 特性

- 稳定、易用：
  - 一键安装，各流行平台均有打包（如 Arch Linux, Windows, macOS 等）
  - 有各媒体资源平台的插件，充分且合理的利用全网免费资源（如 Youtube Music 等）
  - 基础功能完善，桌面歌词、资源智能替换、多音质选择、nowplaying 协议等
  - 核心模块有较好的测试覆盖、核心接口保持较好的向后兼容
  - 大模型加持：AI 电台、自然语言转歌单等
- 可玩性强：
  - 提供基于 TCP 的交互控制协议
  - 基于文本的歌单，方便与朋友分享、设备之间同步
  - 支持基于 Python 的配置文件 `.fuorc`，类似 `.vimrc` 和 `.emacs`

### 快速试用

使用系统包管理器一键安装 FeelUOwn 及其扩展吧！

对于 Arch Linux 和 macOS，你可以分别使用如下方式安装：
```sh
# Arch Linux
yay -S feeluown          # 安装稳定版，最新版的包名为 feeluown-git
yay -S feeluown-netease  # 按需安装其它扩展
yay -S feeluown-ytmusic
yay -S feeluown-bilibili

# macOS（推荐优先尝试在 Release 页面下载打包好的安装包！）
brew tap feeluown/feeluown
brew install feeluown --with-battery # 安装 FeelUOwn 以及扩展
feeluown genicon                     # 在桌面生成 FeelUOwn 图标
```

Windows 和 macOS 用户可以在 Release 页面下载预打包好的二进制。
Gentoo, NixOS, Debian, openSUSE 等 Linux 发行版也支持使用其系统包管理器安装！
详情可以参考文档：https://feeluown.readthedocs.io/ ，
也欢迎你加入开发者/用户[交流群](https://t.me/joinchat/H7k12hG5HYsGy7RVvK_Dwg)。

### 免责声明

FeelUown（以下简称“本软件”）是一个个人媒体资源播放工具。本软件提供的所有功能和资料
不得用于任何商业用途。用户可以自由选择是否使用本产品提供的软件。如果用户下载、安装、
使用本软件，即表明用户信任该软件作者，软件作者对任何原因在使用本软件时可能对用户自己
或他人造成的任何形式的损失和伤害不承担责任。

任何单位或个人认为通过本软件提供的功能可能涉嫌侵犯其合法权益，应该及时向 feeluown
组织书面反馈，并提供身份证明、权属证明及详细侵权情况证明，在收到上述法律文件后，
feeluown 组织将会尽快移除被控侵权内容。（联系方式： yinshaowen241 [at] gmail [dot] com ）
codpilot-cli 0.1.0
A multi-agent CLI tool that integrates with GitHub to review PRs, create features, and suggest changes.
Requires Python: >=3.14
Keywords: cli, codpilot, github

# CodePilot CLI

A multi agent CLI tool that integrates with GitHub that can help you to review pull requests, create new features, and suggest changes on your behalf — all from your terminal.

## Features

**Review PR** — Analyzes the pull request and posts inline comments with suggestions.

**Create Feature** — It can implements new features, then opens a draft pull request against the target repository.

**Suggest Changes** — Participate in GitHub Issue discussions, analyze the codebase and conversation, and post technical suggestions as comments.

## Available Commands

| Command                        | Description                   |
| ------------------------------ | ----------------------------- |
| `codepilot run`                | Run the agent                 |
| `codepilot reset-github-token` | Reset the stored GitHub token |
| `codepilot change-llm`         | Change the LLM model          |
| `codepilot --version, -v`      | Show the current version      |

`codepilot run` has the following options:

- Review PR
- Create Feature
- Suggest Changes

## Prerequisites

- Python 3.14+
- A GitHub personal access token
- An API key for at least one LLM provider (Gemini, OpenAI, or Anthropic)

## Installing locally

```bash
git clone https://github.com/<your-username>/ai-coding-agent.git
cd codepilot
pip install -e .
```

Verify the installation:

```bash
codepilot --version
```

## Usage

```bash
codepilot run
```

The interactive prompt will walk you through:

1. Selecting an agent (Review PR / Create Feature / Suggest Changes)
2. Entering the GitHub URL (PR, repository, or issue depending on the agent)
3. Choosing an LLM provider (Gemini / OpenAI / Anthropic)
4. Providing API credentials for github and LLM (cached in your system keychain for future runs)

## Supported Models

| Provider  | Model                        |
| --------- | ---------------------------- |
| Gemini    | `gemini-3-flash-preview`     |
| OpenAI    | `gpt-5-mini`                 |
| Anthropic | `claude-3-7-sonnet-20250219` |
gh-pydantic-ai 0.3.3
GitHub Copilot Provider for Pydantic AI
Requires Python: >=3.13

# gh-copilot-pydantic-ai

[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)
[![PyPI version](https://badge.fury.io/py/gh-pydantic-ai.svg)](https://badge.fury.io/py/gh-pydantic-ai)
[![Python Version](https://img.shields.io/pypi/pyversions/gh-pydantic-ai.svg)](https://pypi.org/project/gh-pydantic-ai)

GitHub Copilot Provider for Pydantic AI.

Inspired by [ericc-ch/copilot-api/](https://github.com/ericc-ch/copilot-api/).

## Installation

Install the package using pipx or your favorite package manager:

```bash
pip install gh-pydantic-ai
# or with uv
uv tool install gh-pydantic-ai
```

## CLI Usage

### Authentication

First, you need to authenticate with your GitHub account.

```bash
gh-clai-internal auth
```

### Query

After authentication, you can use the `gh-clai` command to interact with GitHub Copilot:

```bash
gh-clai "What is the capital of France?"
```

## Library Usage

This library also provides `GHCopilotModel` for integration with Pydantic AI.

```python
from gh_pydantic_ai import GHCopilotChatModel
from pydantic_ai import Agent

agent = Agent(
    model=GHCopilotChatModel()
)

result = agent.run_sync("What is the capital of France?")
print(result)
```

## Commands

- `gh-clai`: Main command to interact with GitHub Copilot, works same as `clai` command from `pydantic-ai`.
- `gh-clai-internal`: Internal commands for authentication and other utilities.
  - `auth`: Authenticate with GitHub.
  - `models`: List available models.
  - `usage`: Show usage information.