semvec/pypi-packages huggingface dataset:
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sphinx-ansible 0.0.2
Imagine a world where your documentation is also your Ansible playbook

sphinx-ansible
--------------

`sphinx-ansible` is an extension that allow you to include real Ansible tasks in your documentation and run them like if it was a regular playbook. The result is recorded in the final document.

`sphinx-ansible` will also fit well in a CI/CD workflow and become a wait to ensure the documentation works as expected. It also avoid the tedious maintenance of the task output examples in a documentation. Finally, it's also a way to convert your existing functional tests in manual for your users.


Documentation: https://sphinx-ansible.readthedocs.io/en/latest/
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ModernRelay 0.0.3
An asynchronous, highly configurable SMTP relay
Requires Python: >=3.6

Modern Relay
============

Welcome to Modern Relay's documentation! The intention for this project is to build a mail relay that works seamlessly in
the new IT landscape of cloud providers, API access, and the security measures that come with them. I've found that
federating Microsoft 365 tenants and requiring MFA for all accounts is a great leap forward in securing organizations,
but it introduces new strains on IT to integrate legacy devices/applications that an organization may not want to replace.

Modern Relay solves this problem by being a drop in replacement for the IIS-based SMTP relays that an organization
likely already has in place. There are configurable "delivery agents" that Modern Relay uses to convert mail coming in
from SMTP to different delivery schemes like an HTTP request to an API (e.g. Microsoft Graph). By leveraging APIs to
different mail providers, you can skip licensing hassles, 2FA/app password woes, custom Exchange Online connectors, and
adding another SPF address to your record.

Features
========

* Fully asynchronous
* Uses customizable delivery actions based on the origin IP address
* Queues mail in the event of delivery failure for later resending
* Access control to allow certain origin addresses/subnets or certain destination domains
* Supports anonymous and plain login schemes
* Supports STARTTLS if you provide the certs
* Supports Microsoft Graph API mail delivery

Requirements
============

You need **at least Python 3.6** to use this library

Supported Platforms
-------------------

``ModernRelay`` is tested on **CPython** and |PyPy3.7|_
for the following platforms:

* Windows 10
* Ubuntu 20.04
* Ubuntu 18.04

.. |PyPy3.7| replace:: **PyPy3.7**
.. _`PyPy3.7`: https://www.pypy.org/

Installation
============

For Linux or Windows environments where you're managing your own python installation, install with ``pip``::

    pip install modernrelay

You will need to set the appropriate environment variables for your chosen delivery agents. See individual agent
documentation for more details.

If an installer is more your speed, go download a Windows msi installer from the releases section and run it.

Building
========

You can install this package in a virtual environment like so::

    $ python3 -m venv /path/to/venv
    $ source /path/to/venv/bin/activate
    $ git clone https://github.com/blbuford/ModernRelay.git
    $ cd ModernRelay
    $ pip install -e .[dev]

License
=======

``ModernRelay`` is released under the MIT License.
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flamechess 0.3.1
Flamechess Tools
Requires Python: >=3.5.0

# Flamechess Tools
这个包包含鹿棋（捉鳖）棋谱播放器、棋谱记录器，以及后续大部分的flamechess中的python部分
## 1 简介
### 1.1 安装方法
* 命令行输入`pip install flamechess`

*这个文档正在完善中......
## 2 具体模块介绍
### 2.1 棋谱记录器
#### 2.1.1 使用方法
* 直接运行：按照指示输入`code1`和`code2`
* 作为引用或在命令行：调用main函数，参数为`code1`, `code2`
#### 2.1.2 程序结构
* `ChessBoard`类用于获取和设置棋盘
* `tpe`函数用于判断棋盘码类型并选择API
* `Recorder`类用于作为记录器，记录棋谱
* `main`函数作为入口函数调用Recorder类执行相关操作
### 2.2 鹿棋（捉鳖）棋谱播放器
#### 2.2.1 使用方法
##### 2.2.1.1 棋谱写法
* 奇数行写局面
* 偶数行写策略
* 0代表空，Z代表后行者，z代表先行者
##### 2.2.1.2 config.ini写法
* section名称为棋类的名称，推荐使用英文或拼音，提高兼容性
* 具体需要的参数： 

| 参数名称 | 可设置的值 | 意义 |
| ------ | -------- | ---- |
| `chess_type` | `luqi`/`zhuobie`/... | 同section名 |
| `policy_file` | `*.txt` | 棋谱策略文件名 |
| `board_size` | `[int, int]` | 棋盘大小 |
| `reading_size` | `[int, int]` | 要读取的区域的大小 |
| `mirror` | `True`/`False` | 是否镜像 |
| `rotation` | `True`/`False` | 是否旋转 |
| `read_continuously` | `True`/`False` | 是否采用连续读取方式 |


##### 2.2.1.3 启动方法
* 直接运行：按照指示输入棋的类型和棋盘码
* 作为引用或在命令行：调用main函数，参数为棋的类型（`chess_type`）和棋盘码（`code`）
#### 2.2.2 程序结构
* `State`类是棋盘状态的基类
* `Board`类负责执行主要操作  
*详情请见注释
#### 2.2.3 引用
* 引用了play.py中的`ChessBoard`和`tpe`，用于获取和设置棋盘
### 2.3 久棋规则
* 未完成的部分
### 2.4 蒙特卡洛树搜索算法
* `Tree`类是接口类，`game`参数用于传入规则
### 2.5 捉鳖策略器
 * 根据蒙特卡洛树搜索算法制作的捉鳖策略器
 * 依赖于chessTerm平台
 #### 2.5.1 使用方法
 * 使用`main`函数并传入userId
## 3 更新日志
* 0.1.0 最初版本
* 0.1.1 解决了README.md不能渲染的bug
* 0.1.2 彻底解决了README.md不能渲染的bug
* 0.1.3 更新了README.md和url
* 0.1.4 修复了一些已知问题，删除了不该出现的文件
* 0.2.0 将luqi.py的棋盘接口改为了chessTerm的websocket接口，对README.md进行了一些修改完善，修复了若干已知问题
* 0.2.1 删除luqi.py的log记录
* 0.3.0 加入了蒙特卡洛树搜索算法（MCTS.py），并依此做出了zhuobie_player.py
bellbird 0.0.1
Library that parses differential equations (PDEs) strings and automates the creation of scripts for PyEFVLib using the element-based finite volume method.

# bellbird

Library that parses differential equations (PDEs) strings and automates the creation of scripts for PyEFVLib using the element-based finite volume method. 

## Dependencies & Installation

- [Python 3](https://www.python.org/downloads/) (3.8.2);
- [meshio](https://pypi.org/project/meshio/) (4.0.15);
- [numpy](https://numpy.org/) (1.17.4);
- [pandas](https://pandas.pydata.org/)(1.1.3);
- [scipy](https://www.scipy.org/) (1.5.3);
- [PyEFVLib](https://pypi.org/project/PyEFVLib/) (1.0.1);


## Usage

```python
import sys,os
sys.path.append(os.path.join(os.path.dirname(__file__), os.pardir))
import bellbird

# Heat Transfer
model = bellbird.Model(
	name = "Heat Transfer",
	equationsStr = ["k * div( grad(T) ) + q = rho * cp * d/dt(T)"],
	variables   = ["T"],
	properties = {
		"Body":{
			"k" : 10000.0,
			"q" : 0.0,
			"rho" : 1.0,
			"cp" : 1.0,
		},
	},
	boundaryConditions = [
		bellbird.InitialCondition("T", 0.0),
		bellbird.BoundaryCondition("T", bellbird.Dirichlet, "West", 0.0),
		bellbird.BoundaryCondition("T", bellbird.Dirichlet, "East", 100.0),
		bellbird.BoundaryCondition("T", bellbird.Neumann, "South", 0.0),
		bellbird.BoundaryCondition("T", bellbird.Neumann, "North", 0.0),
	],
	meshPath = "mesh.msh",
	timeStep = 0.05,
	tolerance = 1e-4,
	maxNumberOfIterations = 300,
	sparse = False,
)

model.run()
```