semvec/pypi-packages huggingface dataset:
homelab_config 0.3.0
homelab config with consul
Requires Python: <3.14,>=3.10

# homelab_config

[![✅ Code Quality & Tests](https://github.com/shawndeng-homelab/homelab-config/actions/workflows/ci-tests.yaml/badge.svg)](https://github.com/shawndeng-homelab/homelab-config/actions/workflows/ci-tests.yaml)
[![🚀 Release Build & Publish](https://github.com/shawndeng-homelab/homelab-config/actions/workflows/package-release.yaml/badge.svg)](https://github.com/shawndeng-homelab/homelab-config/actions/workflows/package-release.yaml)
[![📚 Deploy Documentation](https://github.com/shawndeng-homelab/homelab-config/actions/workflows/docs-deploy.yaml/badge.svg)](https://github.com/shawndeng-homelab/homelab-config/actions/workflows/docs-deploy.yaml)

一个基于 Consul 的家庭实验室配置管理工具，提供环境感知和缓存功能。

## 功能特点

- 🌍 多环境支持 (dev/staging/prod)
- 🔒 安全的配置存储和访问
- 🚀 高性能缓存机制
- ⚡ 灵活的 Consul 连接管理
- 🔄 自动故障转移支持
- 📝 完整的类型注解支持

## 安装

```bash
# 使用 pip 安装
pip install homelab_config

# 使用 uv 安装
uv pip install homelab_config
```

## 快速开始

```python
from homelab_config import create_client

# 创建客户端
client = create_client()

# 获取配置 (使用默认环境)
config = client("app/myapp/config")

# 获取特定环境的配置
dev_config = client("app/myapp/config,dev")
prod_config = client("app/myapp/config,prod")
```

## 配置

支持通过环境变量进行配置：

```bash
# 运行环境设置
HOMELAB_ENVIRONMENT=dev

# Consul 服务器地址 (支持多个地址，用逗号分隔)
HOMELAB_CONSUL_URLS=http://localhost:8500

# Consul 认证令牌 (可选)
HOMELAB_CONSUL_TOKEN=your-token

# 连接缓存时间 (秒)
HOMELAB_CONSUL_CACHE_TTL=300
```
log-tool 0.0.2
DESCRIPTION
Requires Python: >=3.9

# log-tool

[![PyPI - Version](https://img.shields.io/pypi/v/log-tool.svg)](https://pypi.org/project/log-tool)
[![PyPI - Python Version](https://img.shields.io/pypi/pyversions/log-tool.svg)](https://pypi.org/project/log-tool)

-----

**Table of Contents**

- [Installation](#installation)
- [License](#license)

## Installation

```console
pip install log-tool
```

## License

`log-tool` is distributed under the terms of the [MIT](https://spdx.org/licenses/MIT.html) license.
typedfzf 1.0.5
Yet another fzf wrapper.
Requires Python: >=3.9

# typedfzf

[![PyPI - Version](https://img.shields.io/pypi/v/typedfzf.svg)](https://pypi.org/project/typedfzf)
[![PyPI - Python Version](https://img.shields.io/pypi/pyversions/typedfzf.svg)](https://pypi.org/project/typedfzf)
[![pre-commit.ci status](https://results.pre-commit.ci/badge/github/FlavioAmurrioCS/typedfzf/main.svg)](https://results.pre-commit.ci/latest/github/FlavioAmurrioCS/typedfzf/main)

-----

**Table of Contents**

- [typedfzf](#typedfzf)
  - [Installation](#installation)
  - [License](#license)

## Installation

```console
pip install typedfzf
```

## License

`typedfzf` is distributed under the terms of the [MIT](https://spdx.org/licenses/MIT.html) license.
runtool 1.0.9
Install binary from github release.
Requires Python: >=3.9
Keywords: binary, github, install, release

# runtool

[![PyPI - Version](https://img.shields.io/pypi/v/runtool.svg)](https://pypi.org/project/runtool)
[![PyPI - Python Version](https://img.shields.io/pypi/pyversions/runtool.svg)](https://pypi.org/project/runtool)
[![pre-commit.ci status](https://results.pre-commit.ci/badge/github/FlavioAmurrioCS/runtool/main.svg)](https://results.pre-commit.ci/latest/github/FlavioAmurrioCS/runtool/main)

-----

**Table of Contents**

- [runtool](#runtool)
  - [Installation](#installation)
  - [License](#license)

## Installation

```console
pip install runtool
```

## License

`runtool` is distributed under the terms of the [MIT](https://spdx.org/licenses/MIT.html) license.
ultranLP 1.0.0
Ultra-fast, comprehensive NLP preprocessing library with advanced tokenization
Requires Python: >=3.8
Keywords: nlp, text-processing, tokenization, preprocessing, machine-learning, natural-language-processing

# UltraNLP - Ultra-Fast NLP Preprocessing Library

🚀 **Ultra-fast, comprehensive NLP preprocessing with advanced tokenization**

## Features

- ⚡ **Ultra-fast tokenization** - Handles $20, 20Rs, emails, hashtags, emojis
- 🧹 **Comprehensive text cleaning** - HTML, URLs, emojis, normalization
- 🔤 **Smart spell correction** - With caching and performance optimization
- 📦 **Batch processing** - Parallel processing for large datasets
- 🎯 **Production ready** - Memory efficient, thread-safe

## Quick Start
dynetan 2.2.2
A Python implementation for Dynamical Network Analysis.
Requires Python: >=3.9

Dynamical Network Analysis
===========================

![last release](https://img.shields.io/gitlab/v/release/comp-biochem-csu/dynetan)
[![PyPI](https://img.shields.io/pypi/v/dynetan)](https://pypi.org/project/dynetan/)
[![Read-The-Docs Status](https://readthedocs.org/projects/dynamical-network-analysis/badge/?version=latest)](https://dynamical-network-analysis.readthedocs.io/en/latest/?badge=latest)
[![CI/CD Status](https://img.shields.io/gitlab/pipeline-status/comp-biochem-csu/dynetan)](https://gitlab.com/comp-biochem-csu/dynetan/-/pipelines)
[![Codecov](https://codecov.io/gl/comp-biochem-csu/dynetan/branch/master/graph/badge.svg)](https://codecov.io/gl/comp-biochem-csu/dynetan)
![License](https://img.shields.io/gitlab/license/comp-biochem-csu/dynetan)


The Python implementation of Dynamical Network Analysis was built to provide all
functionalities necessary to the analysis of Molecular Dynamics (MD) simulations
using the Dynamical Network Analysis method.

Install
-------

Install the latest version of Dynamical Network Analysis:

    $ pip install dynetan

For additional details, please see `INSTALL.md`.

Tutorial
--------

Several jupyter notebook tutorials have been prepared as an introduction to this package and were released in an independent repository:

https://gitlab.com/comp-biochem-csu/dynetan_tutorial

Documentation
------------------------

The full documentation can be found at
https://dynamical-network-analysis.readthedocs.io/en/latest/index.html

Resources and References
------------------------

For the background on Dynamical Network Analysis, see the following papers that
describe its development:

* [Generalized correlation-based dynamical network analysis: a new
high-performance approach for identifying allosteric communications in molecular
dynamics trajectories. J. Chem. Phys. (2020).
DOI: 10.1063/5.0018980](https://doi.org/10.1063/5.0018980)

* [Experimental and computational determination of tRNA dynamics. FEBS Letters
(2010). DOI: 10.1016/j.febslet.2009.11.061](https://doi.org/10.1016/j.febslet.2009.11.061)

* [Exit strategies for charged tRNA from GluRS. JMB (2010).
DOI: 10.1016/j.jmb.2010.02.003](https://doi.org/10.1016/j.jmb.2010.02.003)

* [Dynamical Networks in tRNA:protein complexes. PNAS (2009).
DOI: 10.1073/pnas.0810961106](https://doi.org/10.1073/pnas.0810961106)
projgen 0.2
A CLI tool to generate project structure from a JSON file
Requires Python: >=3.7




# ProjGen 🛠️

A CLI tool to generate directory and file structures from a JSON file.

## Install

```bash
pip install projgen
```
## Usage
```bash
projgen path/to/project-structure.json
```
- Enter the project_name, it is optional

## Write the project structure in project-structure.json - A example below
```json
{
  "project_name": "my-fastapi-app",
  "project-structure": [
    { "level": 1, "type": "folder", "name": "app" },
    { "level": 2, "type": "file", "name": "app/main.py" },
    { "level": 2, "type": "folder", "name": "app/utils" },
    { "level": 1, "type": "file", "name": "README.md" },
    { "level": 1, "type": "file", "name": ".gitignore" }
  ]
}
```
## To run this clone project use this 
```bash
# build first using pip
pip install .
# then
projgen path_to_file.json
```