semvec/pypi-packages huggingface dataset:
Multifunctional-Calculator 0.0.7
多功能计算库（整合decimal）
Requires Python: >=3.10

# 强大的计算工具（整合decimal）

### 解决de问题
* 使用decimal库，防止0.1+0.2=0.30...4的局面
* 每个方法皆可输入多个数字，拒绝addition(1, addition(2, 3))

### 多功能
* 额外添加StringsCalculator

### 调用方法
```
from Multifunctional_Calculator.NumbersCalculator import *

"""
nc / NC / NumbersCalculator : 计算数字运算的类
addition : 加法
subtraction : 减法
multiplication : 乘法
division : 除法
power : 乘方
factorial : 阶乘
sqrt : 开根号
"""

print(nc().addition(1, 2, 3, 4)) 
```
vision-rl 0.0.5
Visual Reinforcement Learning tools

# VisionRL

A Python package for visual Reinforcement Learning environments and tools.

# VisionRL

A Python package for visual Reinforcement Learning environments and tools.

## Design Philosophy

This library is designed as a Gymnasium-compatible extension, focused on computer vision, visualization, UI, and explainability for reinforcement learning. The design follows a layered and modular approach where each concern is clearly separated:

- **Gymnasium handles agent contracts**.
- **VisionRL handles human understanding**.
- **Core logic is minimal and stable**.
- **Features are added via wrappers**, not rewrites.
- **UI, CV, and explainability are optional layers**.

## Project Structure

### 🔹 `vision_rl/` (Root Package)
The main Python package. Everything inside is part of the public or internal API.

### 🔹 `vision_rl/core/` – Core Abstractions
Defines the foundational building blocks.
- Extends Gymnasium’s `Env`.
- Adds support for visual observations, UI hooks, and debug callbacks.
- **Key Files**: `visual_env.py` (Base class), `mixins.py` (Reusable components).

### 🔹 `vision_rl/wrappers/` – Environment Enhancements
The core extension mechanism. Most new features live here.
- Modifies Gym environments without changing their code.
- Handles frame stacking, visual conversions, heatmaps, and logging.

### 🔹 `vision_rl/envs/` – Ready-to-Use Environments
Prebuilt environments for demonstration and best practices.
- Examples: `VisualFrozenLake`, `VisualCartPole`.

### 🔹 `vision_rl/ui/` – Human-Facing Interfaces
Tools for visualization and interaction. Optional for training, critical for demos.
- Renders steps, plots metrics, and handles dashboards.

### 🔹 `vision_rl/monitors/` – Training Analysis Tools
Tools to analyze agent behavior over time.
- Track rewards, action distributions, and learning progress.

### 🔹 `vision_rl/utils/` – Shared Utilities
Helper functions for CV, rendering, and image processing. No environment logic lives here.

### 🔹 `vision_rl/register.py` – Gym Integration
Connects environments to Gymnasium’s registry (e.g., `gym.make("VisualFrozenLake-v0")`).