semvec/pypi-packages huggingface dataset:
branch-and-bound-AA-test 0.1.0
A knapsack problem solved with branch and bound
Requires Python: >=3.6

A knapsack problem solver with branch and bound

The finction will be as:
```python
knapsack_branch_and_bound(W, items)
```
with W <- Total weight, items <- list of tuples, the have (value, weight)
Example,  W = 10 , items = [(10, 2), (5, 3), (15, 5), (7, 7), (6, 1), (18, 4), (3, 1)] gives result 39
himage 1.0.0
A small library, of high level image processing tools
Requires Python: >=3.10

A set of various convenient functions useful in image processing, written in python.

## Example of usage

```py
from himage import imshow, multimshow, imread

im = imread("image.png")

imshow(im)
multimshow([im, im, im], titles = ['title 1', 'title 2', 'title 3'], n_cols=3)
```
afw 0.0.21
-

# afw
Tests Automation Framework

# Check Python installation
python3 --version

# If Python is not installed, install it using Homebrew
brew install python

# Create a virtual environment
python3 -m venv venv

# Activate the virtual environment
source venv/bin/activate  # On macOS and Linux
# .\venv\Scripts\activate  # On Windows

# Install dependencies
pip install -r requirements.txt
streamlit-custom-componentt 0.0.2
Streamlit component that allows you to annotate PDFs
Requires Python: >=3.7

# Streamlit PDF Annotator

Streamlit component that allows you to annotate PDFs easily, built with Vue3 and Vite.

## Quickstart

Ensure you have [Python 3.6+](https://www.python.org/downloads/), [Node.js](https://nodejs.org) and [npm](https://docs.npmjs.com/downloading-and-installing-node-js-and-npm) installed.

1. Clone this repository:
``` bash
git clone git@github.com:gabrieltempass/streamlit-component-vue-vite-template.git
```

2. Go to the `frontend` directory and initialize and run the component template frontend:
``` bash
cd streamlit-component-vue-vite-template/annotator/frontend
```
``` bash
npm install
npm run dev
```

3. From a separate terminal, go to the repository root directory, create a new Python virtual environment, activate it and install Streamlit and the template as an editable package:
``` bash
cd streamlit-component-vue-vite-template
```
``` bash
python3 -m venv venv
. venv/bin/activate
pip install streamlit
pip install -e .
```

Still from the same separate terminal, run the example Streamlit app:
``` bash
streamlit run annotator/example.py
```

If all goes well, you should see something like this:

![Quickstart Success](quickstart.png)

Modify the frontend code at `annotator/frontend/src/MyComponent.vue`.
Modify the Python code at `annotator/__init__.py`.
FlawlessAPI 0.3.0
一个高性能的API服务框架
Requires Python: >=3.9

# 使用示例：
    examples_of_Use.py

# 功能特性：
1. 路由系统
   - 支持动态路由
   - 支持多种HTTP方法
   - 路由缓存优化

2. 中间件支持
   - CORS中间件
   - 限流中间件
   - CSRF防护
   - 可自定义中间件

3. 缓存系统
   - LRU缓存
   - Redis缓存
   - 可扩展的缓存接口

4. 模板引擎
   - 支持异步渲染
   - 缓存支持
   - 自定义过滤器

5. 文件处理
   - 文件上传
   - 静态文件服务
   - 安全检查

6. WebSocket支持
   - 实时通信
   - 广播功能
   - 消息处理器

7. 数据库支持
   - 异步数据库操作
   - 事务支持
   - 连接池管理

8. 国际化
   - 多语言支持
   - 动态翻译
   - 本地化配置

9. 任务队列
   - 异步任务处理
   - 状态跟踪
   - 并发控制

10. 服务注册与发现
    - 服务注册
    - 服务发现
    - 心跳检测

11. API文档
    - OpenAPI规范
    - Swagger UI
    - 自动文档生成

12. 监控和追踪
    - 性能监控
    - 分布式追踪
    - 指标收集

# 安装依赖：
    pip install -r requirements.txt

# 快速开始：
1. 创建应用实例
2. 配置必要选项
3. 添加路由和处理函数
4. 启动应用

# 配置说明：
见 config/settings.py

# API文档：
访问 /docs 查看API文档