semvec/pypi-packages huggingface dataset:
cc-cleaner 0.4.1
The cache cleaner for the AI Coding era. Clean up Claude Code, Cursor, npm, pip, cargo caches and more.
Requires Python: >=3.10
Keywords: ai-coding, cache, cargo, claude-code, cleaner, cli, copilot, cursor, developer-tools, disk-space, docker, npm, pip

# cc-cleaner

[![PyPI version](https://badge.fury.io/py/cc-cleaner.svg)](https://badge.fury.io/py/cc-cleaner)
[![Python 3.10+](https://img.shields.io/badge/python-3.10+-blue.svg)](https://www.python.org/downloads/)
[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)

[English](README.md) | [中文](README_CN.md)

**The cache cleaner for the AI Coding era.**

> cc = Claude Code / Cursor / Copilot / Coding Cache

In the AI Coding era, your disk fills up 10x faster—rapid project iteration, massive conversation logs, exploding package caches. `cc-cleaner` knows exactly what to clean.

## Install

```bash
curl -sSL https://raw.githubusercontent.com/elexingyu/cc-cleaner/master/install.sh | bash
```

<details>
<summary>Other installation methods</summary>

```bash
pipx install cc-cleaner   # pipx
uv tool install cc-cleaner # uv
pip install cc-cleaner     # pip
```
</details>

## Usage

```bash
cc-cleaner status          # See what's eating your disk
cc-cleaner clean           # Interactive mode (select what to clean)
cc-cleaner clean all       # Clean all safe caches
cc-cleaner clean claude    # Clean specific tool
cc-cleaner clean all -n    # Dry run (preview only)
```

**Interactive mode** (just run `cc-cleaner clean`):
- Use ↑/↓ to navigate
- Space to toggle selection
- `s` for safe items only, `a` for all, `n` for none
- Enter to confirm, `q` to cancel

**Example output:**

```
$ cc-cleaner status

                        Development Cache Status
┏━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━┳━━━━━━━━━━┓
┃ Cleaner   ┃ Description                  ┃     Size ┃   Risk   ┃
┡━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━╇━━━━━━━━━━┩
│ uv        │ uv Python package cache      │   5.9 GB │   Safe   │
│ npm       │ npm package cache            │   1.2 GB │   Safe   │
│ claude    │ Claude Code logs & telemetry │ 299.6 MB │   Safe   │
│ cargo     │ Cargo registry cache         │ 102.5 MB │   Safe   │
└───────────┴──────────────────────────────┴──────────┴──────────┘

Total cleanable: 7.5 GB
```

## Supported Cleaners (22 total)

| Category | Tools |
|----------|-------|
| **AI Coding** | Claude Code |
| **AI/ML Models** | huggingface, pytorch, whisper, ollama |
| **JavaScript** | npm, yarn, pnpm, bun, nvm |
| **Python** | pip, uv, virtualenv |
| **Browser** | browser-cache (Chrome/Safari/Firefox), playwright, browser-tools (Puppeteer/Selenium) |
| **Others** | cargo, go, gradle, cocoapods, homebrew, docker |

## Risk Levels

| Level | Cleaned By Default | Examples |
|-------|-------------------|----------|
| **Safe** | Yes | Download caches, logs, telemetry |
| **Moderate** | `--force` | Conversation transcripts, shared stores |
| **Dangerous** | `--force` | Docker system prune |

## Contributing

PRs welcome for **Cursor**, **GitHub Copilot**, **Windsurf**, and other AI coding tools!

## License

MIT
nexus-analyzer 2026.1.2
Comprehensive Python project analysis and reporting tool
Requires Python: >=3.9
Keywords: python, cli, analysis, dependency, infrastructure

# NexusAnalyzer

=============

**NexusAnalyzer** is a tool that analyzes Python projects to generate a **comprehensive dependency and architecture map**.

### Features / Özellikler

-   🔍 Scans Python, Web, and Config files / Python, Web ve Config dosyalarını tarar

-   🧩 Lists API endpoints and outgoing requests / API endpointleri ve outgoing istekleri listeler

-   🏗️ Detects infrastructure services and connections (Docker, DB, Nginx, etc.) / Altyapı servisleri ve bağlantıları (Docker, DB, Nginx vs.) tespit eder

-   🌳 Generates the project file tree / Proje dosya ağacını çıkarır

-   ⚡ Detects advanced features (rate-limiting, auth, Celery, WebSocket) / Gelişmiş özellikleri (rate-limiting, auth, Celery, WebSocket) tespit eder

-   📄 Produces reports in Markdown format (`.md`) / Raporları Markdown formatında üretir (`.md`)

### Installation / Kurulum

```bash
pip3.13 install nexus-analyzer
```

```bash
nexus-cli .
```


### Example Output / Örnek çıktı

```bash├── RAPOR_NEXUS_20260121_1256

│   ├── 01_Ozet_ve_Kimlik.md       # Project summary & metadata / Proje özeti ve kimlik
│   ├── 02_API_Endpointleri.md      # API endpoints / API endpointleri
│   ├── 03_Dis_Istekler.md          # Outgoing requests / Dış istekler
│   ├── 04_Gelismis_Ozellikler.md  # Advanced features / Gelişmiş özellikler
│   ├── 05_Altyapi_Config.md        # Infrastructure & connections / Altyapı ve bağlantılar
│   └── 06_Dosya_Agaci.md           # Project file tree / Dosya ağacı`
```

* * * * *
# Türkçe

**NexusAnalyzer**, Python projelerini analiz ederek kapsamlı bir **dependency ve yapı haritası** çıkaran bir araçtır.

### Özellikler

- 🔍 Python, Web ve Config dosyalarını tarar
- 🧩 API endpointleri ve outgoing istekleri listeler
- 🏗️ Altyapı servisleri ve bağlantıları (Docker, DB, Nginx vs.) tespit eder
- 🌳 Proje dosya ağacını çıkarır
- ⚡ Gelişmiş özellikleri (rate-limiting, auth, Celery, WebSocket) tespit eder
- 📄 Raporları Markdown formatında üretir (`.md`)

### Kurulum

```bash
pip3.13 install nexus-analyzer
```

```bash 
nexus-cli .
```

---

# Örnek çıktı

```bash
├── RAPOR_NEXUS_20260121_1256
│   ├── 01_Ozet_ve_Kimlik.md
│   ├── 02_API_Endpointleri.md
│   ├── 03_Dis_Istekler.md
│   ├── 04_Gelismis_Ozellikler.md
│   ├── 05_Altyapi_Config.md
│   └── 06_Dosya_Agaci.md
 
```
orca-sph 26.1.3
OrcaSPH - SPH Fluid Simulator with OrcaLink Integration
Requires Python: >=3.10
Keywords: sph, fluids, simulation, orca, orcalink, fluid-dynamics

# OrcaSPH - SPH Fluid Simulator with OrcaLink Integration

OrcaSPH 是一个 Python 包，提供 SPHSimulator 可执行程序和相关的库文件，支持通过 `pip install orca-sph` 安装，使用 `orcasph` 命令运行。

OrcaSPH 基于 SPlisHSPlasH 流体仿真引擎，集成了 Orca 系统的两个核心功能模块：

- **OrcaLink**：支持 SPH 仿真器与 OrcaLink 服务器的 gRPC 通信，实现流体对刚体的作用力传输和刚体位置/速度接收
- **ParticleRender**：支持粒子数据通过 gRPC 实时传输到渲染服务

Orca 集成允许在分布式系统中运行 SPlisHSPlasH 模拟器，并与其他计算节点进行实时数据交换。

## 系统要求

- **Python**：3.10+ （不再支持 3.8 和 3.9）
- **操作系统**：Linux (x86_64)
- **系统库**：已安装必要的系统库（libGL, libX11 等）

## 安装

### 从 PyPI 安装（推荐）

```bash
pip install orca-sph
```

安装后可以使用：
- **命令行工具**：`orcasph --help`
- **Python 模块**：`import orcasph_client`

## 基本用法

### 启动仿真

```bash
orcasph --scene path/to/scene.json
```

### 常用选项

使用 `orcasph --help` 查看完整的命令行选项，包括：
- `--scene FILE`：场景文件路径（必需）
- `--cpu RANGE`：指定 CPU 核心范围
- `--threads N`：指定 OpenMP 线程数
- `--config FILE`：gRPC 配置文件路径
- `--gui`：启用 GUI 模式运行

## 许可证

本包采用双许可证：

- **SPlisHSPlasH 核心代码**：MIT License (Copyright © 2016 Jan Bender)
- **Orca 扩展**：Proprietary License (Copyright © 2026 Songying Technology Inc.)

详细信息请参考 `LICENSE` 文件。
ons-mkdocs-theme 1.2.5
An ONS MkDocs Theme based on Material for MkDocs for creating documentation websites
Requires Python: <3.13,>=3.10

<p align="center" style="padding: 50px">
    <img src="ons_mkdocs_theme/assets/images/logo.svg" width="450px">
</p>

## :red_car: Getting Started

Setting up your documentation site to use this theme couldn't be easier. The quickest and easiest way to get up and running is to install with `pip`.

To be able to use this theme, you need to be using at least **Python v3.8**.

### :computer: Installation

#### with pip

ONS MkDocs Theme is published as a Python package and can be installed with
`pip`, ideally by using a [virtual environment][virtual environment]. Open up a terminal and install
ONS MkDocs Theme with:

```
pip install ons_mkdocs_theme
```

This will automatically install compatible versions of all dependencies:
[MkDocs], [Markdown], [Pygments] and [Python Markdown Extensions][Python Markdown Extensions].

!!! tip

    If you don't have prior experience with Python, we recommend reading
    [Using Python's pip to Manage Your Projects' Dependencies], which is a
    really good introduction on the mechanics of Python package management and
    helps you troubleshoot if you run into errors.

#### with git

ONS MkDocs Theme can be directly used from [GitHub] by cloning the
repository into a subfolder of your project root folder.

Simply create a folder called `ons_mkdocs_theme`. In the terminal, ensure you are in the root folder directory of your project and run the following command:

```
mkdir ons_mkdocs_theme
```

You then need to `cd` into the new directory with the following command:

```
cd ons_mkdocs_theme
```

To clone the theme files, run the following command:

```
git clone https://github.com/ONSdigital/ons_mkdocs_theme
```

Next, install the theme and its dependencies with:

```
pip install -e .
```

[GitHub]: https://github.com/ONSdigital/ons_mkdocs_theme
[virtual environment]: https://realpython.com/what-is-pip/#using-pip-in-a-python-virtual-environment
[semantic versioning]: https://semver.org/
[MkDocs]: https://mkdocs.org
[Markdown]: https://python-markdown.github.io/
[Pygments]: https://pygments.org/
[Python Markdown Extensions]: https://facelessuser.github.io/pymdown-extensions/
[Using Python's pip to Manage Your Projects' Dependencies]: https://realpython.com/what-is-pip/
pyzlbus2 0.1.8
ZeroLab Bus API for Python
Requires Python: >=3.8

# pyZlBus2

ZeroLab Bus API for Python

This package provides an API for interacting with ZeroLab Bus devices using Python.

## Installation

```bash
pip install pyZlBus2
```

## Usage

```python
import pyZlBus2 as zl

zl.test()
# zl.bleDemo()
# zl.serialDemo()
# zl.serialRfDemo()

# Example usage
```

```python
import zlbus_api as zlapi
print(zlapi.ul_getDataFormat().hex(' ').upper())
```

```python
# PyZlBus2 includes zlbus_api module
import pyZlBus2 as zl
print(zl.api.ul_getDataFormat().hex(' ').upper())
```


## License

MIT
orca-link 26.1.3
OrcaLink gRPC Client with MuJoCo-SPH Simulation Integration
Requires Python: >=3.10
Keywords: orcalink, grpc, mujoco, sph, simulation

# OrcaLink - gRPC 会话转发和生命周期管理服务器

![Status](https://img.shields.io/badge/status-active-green) ![License](https://img.shields.io/badge/license-Proprietary-red)

## 概述

**OrcaLink** 是一个企业级的 gRPC 中间件框架，支持：
- 🔄 **实时数据转发**：多客户端、多频道的双向通信
- 💾 **灵活存储**：纯转发模式和统计记账模式可选
- 🧹 **自动生命周期管理**：Session 空闲自动清理，释放资源
- 📊 **完整的统计记账**：所有操作均可被追踪和审计
- ⚡ **高性能**：15K+ msg/sec 吞吐量，<2ms p99 延迟

### 核心特性

✨ **会话隔离** - 每个客户端独立会话，互不干扰

⚡ **高吞吐量** - 
- 纯转发模式：**15K+ msg/sec**，**<2ms p99 延迟**
- 统计记账模式：**10K+ msg/sec**，**<10ms p99 延迟**

🧹 **自动清理** - 
- 空闲 Session 10 分钟后自动清理（可配置）
- 支持最低 10 秒超时，适合测试和演示
- 清理记录完整保存在数据库中

🔄 **灵活配置** - 
- 支持纯转发模式（最低延迟）
- 支持统计记账模式（完整数据追踪）
- 支持 Session 自动清理（资源释放）

💾 **可靠存储** - 基于 SQLite 的高效数据持久化

🚀 **生产级** - 
- 完整的会话管理和资源清理
- 错误恢复和监控指标
- 完整的文档和测试套件

## 系统要求

- **操作系统**：Linux, macOS, Windows
- **Python**：3.10+（用于 Python 客户端）
- **C++ 编译器**：
  - Server：需要支持 C++17 的编译器（GCC 7+, Clang 5+, MSVC 2017+）
  - Client 库：需要支持 C++14 的编译器（GCC 5+, Clang 3.4+）
- **CMake**：3.10+
- **内存**：4GB+

## 安装

### PyPI 安装（推荐）

```bash
pip install orca-link
```

安装后可以使用：
- **Python 客户端**：`import orcalink_client`
- **服务端命令行工具**：`orcalink --help`

## 快速开始

### 启动服务端

```bash
# 安装（如果尚未安装）
pip install orca-link

# 启动服务端
orcalink

# 预期输出:
# ✅ OrcaLink gRPC server started successfully on localhost:50351
# 🧹 Session cleanup enabled (idle timeout: 600s, check interval: 60s)
```

### Python 客户端示例

```python
import orcalink_client

# 连接到服务器
client = orcalink_client.OrcaLinkClient('localhost:50351')

# 加入会话
session = client.join_session(
    session_id=1,
    client_name='my_client',
    publish_channels=[{'channel_id': 1, 'channel_type': 1}]
)

# 发布数据
client.publish_frame(
    session_id=1,
    channel_id=1,
    frame_data={'units': [...]}
)
```

## 许可证

版权所有 © 2025 上海松应科技有限公司  
保留所有权利。

本软件仅供授权用户使用。未经明确授权，禁止复制、修改、分发或使用本软件。
leanautomation 0.1.9
LeanAutomation provides a unified cross-experience Microsoft Fabric SDK.
Requires Python: >=3.8

# Lean Automation: A Unified SDK for Microsoft Fabric

The Lean Automation packages provides a unified, cross-experience Microsoft Fabric SDK. The goal of Lean Automation is to simplify the way you work with Fabric APIs and support deployments and automation allowing you to focus on solving your business problems.


## Quickstart
Lean Automation is available on [PyPi](https://pypi.org/project/Lean Automation/) and can be installed via `pip install leanautomation`.

With Lean Automation installed, you first authenticate by creating a Fabric client. You can use either [FabricInteractiveAuth](https://learn.microsoft.com/en-us/python/api/azure-identity/azure.identity.interactivebrowsercredential?view=azure-python) to use your personal credentials or `FabricServicePrincipal` to use a service principal (which is supported for most but not all APIs).

```python
from Lean Automation import auth, FabricClient
from Lean Automation.auth import FabricInteractiveAuth

fc = FabricClient(auth=auth.FabricInteractiveAuth())
for ws in fc.workspace.ls():
    print(f"{ws.name}: Id:{ws.id} Capacity:{ws.capacityId}")
```
You use Service Principals in a similar way by bringing in the app id, secret, and tenant id. Replace the strings below with your service principals information.

```python
from Lean Automation import auth, FabricClient
from Lean Automation.auth import FabricServicePrincipal

auth = FabricServicePrincipal("APP_ID", "APP_SECRET", "TENANT_ID")
fc = FabricClient(auth=auth)
for ws in fc.workspace.ls():
    print(f"{ws.name}: Id:{ws.id} Capacity:{ws.capacityId}")
```

Lean Automation supports many of the Fabric REST APIs and we appreciate contributions to help us close that gap.

Some of our best supported APIs include:

* Data Warehouse
* Data Engineering
* Real-time Intelligence

Lean Automation has been designed to support Fabric deployment and automation and follows a convention to make it easier to discover and connect APIs.

* List items like workspaces, tables: `fc.<item>.ls()` as in `fc.workspace.ls()`
* Create items like lakehouses, event streams: `fc.<item>.create()` as in `fs.lakehouse.create('NameOfLakehouse')`
* Delete items: `fc.<item>.delete()` as in `fc.warehouse.delete(worskspace_id, warehouse_id)`
sonicwall-api-client 1.0.5
Simple Python client for SonicWall SonicOS REST API (with HTTP Digest Auth).
Requires Python: >=3.9

# SonicWall API Python Client

A simple Python client for interacting with the SonicWall SonicOS REST API, using HTTP Digest Authentication.

## Features

- Login / logout to the SonicOS API
- Check and manage pending configurations
- Generic requests (`GET`, `POST`, `PUT`, `PATCH`, `DELETE`)
- Persistent session support via `requests.Session()`

## Installation

Install the package from PyPI:

```bash
pip install sonicwall-api-client
```

## Import

```python
from sonicwall_api_client import SonicWallClient
```

## Examples

### Initialize the client

```python
# Initialize the client (with optional TFA code)
client = SonicWallClient(
    ip="192.168.1.1",
    port=443,
    username="admin",
    password="password"
    tfa="123456"  # optional, only if TFA is enabled
)
```
> **Note**  
> The `tfa` argument is optional and should only be provided if the SonicWall firewall is configured with Two-Factor Authentication (TFA/2FA).  
> If TFA is not required, you can omit this argument.


### Connect to the firewall

```python
# Log in
success, message, _ = client.login()
if success:
    print("Login successful.")
else:
    print(f"Login failed: {message}")
```

### Check pending configurations

```python
success, message, data = client.get_pending_configurations()
if success:
    print("Pending configurations:", data)
else:
    print(f"Error: {message}")
```

### Commit configurations

```python
success, message, _ = client.commit()
if success:
    print("Configurations committed successfully.")
else:
    print(f"Commit error: {message}")
```

### Discard pending configurations

```python
success, message, _ = client.delete_pending_configurations()
if success:
    print("Pending changes discarded.")
else:
    print(f"Error: {message}")
```

### Generic request

```python
# Without payload
success, message, data = client.request("get", "/zones")
if success:
    print("Zones list:", data)
else:
    print(f"Request error: {message}")

# With payload
payload = {
    "zones": [
        {
            "name": "LAN_IT",
            "security_type": "public",
            "interface_trust": False,
            "auto_generate_access_rules": {
                "allow_from_to_equal": False,
                "allow_from_higher": False,
                "allow_to_lower": False,
                "deny_from_lower": False
            },
        }
    ]
}

success, message, _ = client.request("post", "/zones", payload)
if success:
    print("Object created successfully.")
else:
    print(f"Creation error: {message}")
```

### Logout

```python
success, message, _ = client.logout()
if success:
    print("Logged out successfully.")
else:
    print(f"Logout error: {message}")
```

## License

MIT