semvec/pypi-packages huggingface dataset:
pyscail 0.1.0
A package that helps build cellular automata
Requires Python: >=3.11
Keywords: cellular automata, game of life

# pyscail

**pyscail** is a package for creating cellular automata. It allows you to specify the
allowed states, and the transitions between them, and does everything else for you

![rock-paper-scissors gif](media/rps-gif.gif)

## Installation

You need to have python (>= 3.11) installed on your system. Once you have that,
you can:

```bash
pip install pyscail
```

(or `pip3`, depending on your system)

The project's link on PyPI: https://pypi.org/project/pyscail/

## Usage
See this video for a demonstration of how to use the library: 
https://youtu.be/BjPNs30i2TQ

A brief summary - provide a class with a `next` method and a 
`display` method. Provide a initialization function that returns
an instance of your class given some coordinates. Provide a settings
object that you can make using method provided by the library.
Optionally, provide a function that will be called once each generation.

Then, simply call `scail.run` to run the ruleset.


![Belusov-Zhabotinsky gif](media/bz-gif.gif)

## Demos
See the following video for a demonstration on how to write code using this
library.

See the demos folder for a lot more (and more varied) examples on how to use the 
library. Written demo automata include:

- Conway's game of life
- The modified game of life with extinction
- Langton's ant 

![Langton gif](media/langton-gif.gif)
- Wireworld
- Rock-Paper-Scissors automata 
- Belusov-Zhabotinsky reaction (https://www.hermetic.ch/pca/bz.htm)
- the Mandelbrot and Julia sets
- A simulation of grain growth in metals (https://www.sciencedirect.com/science/article/pii/1359646296000553)
- And lastly, this demo of many of the above rulesets combined into one 
ruleset and run all together, then displayed as a weighted average

![everything gif](media/everything-gif.gif)

## Other

### Kernel Caching
Kernel caching is an option you can enable through `kernels.initialize_kernel_caching`
If this is set, then instead of being calculated every frame, the neighborhoods
of a given point will be calculated once then cached. This will probably
not cause any issues unless you change your neighborhood strategy mid-simulation.

Still, I didn't notice a significant speedup upon implementing caching, so for now
it is just an option that is turned off by default.
nuitka-hatch 1.5
hatch nuitka plugin
Requires Python: >=3.7

# hatch-nuitka

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

-----

**Table of Contents**

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

## Installation

```console
pip install hatch-nuitka
```

## License

`hatch-nuitka` is distributed under the terms of the [MIT](https://spdx.org/licenses/MIT.html) license.
xcloudClients 0.4.0
这是一个国信行云数据库并发查询python程序,主要应用于自动通报

行云数据库JDBC包。主要供中国电信、中国移动等通信公司或国家电网等使用国信行云数据库公司使用.
# xcloudClients

## 概述

`xcloudClients` 是一个设计用于通过 JPype 使用 JDBC 在 XCloud 系统上进行数据库操作的 Python 包。它可以高效地管理数据库连接，并利用预配置的客户端实例池来进行并发数据库访问，从而实现 SQL 查询的线程安全执行。

## 特性

- **线程安全的数据库连接**：在多线程中安全管理并发数据库操作。
- **连接池管理**：限制同时打开的数据库游标数量，防止系统过载。
- **异步查询执行**：利用 Python 的 `concurrent.futures` 异步执行查询。
- **资源管理**：自动管理 JDBC 资源并确保正确关闭 JVM 和数据库连接。
- **错误处理**：强大的错误处理能力，能够处理数据库连接问题和 SQL 执行错误。

## 安装

要安装 `xcloudClients`，需要 Python 3.6 或更高版本。您可以直接通过 pip 从 PyPI 安装：

```bash
pip install xcloudClients
 先决条件
 在安装包之前，请确保已经安装并正确配置了 JPype，因为它是 JDBC 连接所必需的。如果还未安装，可以使用 pip 安装 JPype：


```bash
pip install JPype1

## 先决条件
## 在安装包之前，请确保已经安装并正确配置了 JPype，因为它是 JDBC 连接所必需的。如果还未安装，可以使用 pip 安装 JPype：

```bash

pip install JPype1
## 使用方法
## 这里是一个简单的示例，演示如何使用 xcloudClients 来管理数据库连接和执行查询：

## 设置数据库客户端
## 首先，配置数据库客户端设置：

```python
from xcloudClients import ClientManager

# 定义客户端配置
client_configs = [
    {'ip': '192.168.1.100', 'username': 'admin', 'password': 'secret'}
]

# 使用配置初始化 ClientManager
manager = ClientManager(client_configs=client_configs, max_cursors=10)
执行查询
您可以通过从 SQL 文件读取查询，并使用 ClientManager 来执行它们：

```python
# SQL文件的路径
sql_file_path = 'path/to/your/queries.sql'

# 从文件读取 SQL 查询
queries = manager.read_multi_sql_file(sql_file_path)

# 执行查询并检索结果
results = manager.execute_queries(queries, if_header_included=True)
for result in results:
    print(result)


贡献
欢迎对 xcloudClients 做出贡献！请随意 fork 仓库，进行您的更改，并提交 pull 请求。