semvec/pypi-packages huggingface dataset:
dune.gdt 2022.5.3
Python for Dune-Gdt

```
# This file is part of the dune-xt project:
#   https://zivgitlab.uni-muenster.de/ag-ohlberger/dune-community/dune-xt
# Copyright 2009-2021 dune-xt developers and contributors. All rights reserved.
# License: Dual licensed as BSD 2-Clause License (http://opensource.org/licenses/BSD-2-Clause)
#      or  GPL-2.0+ (http://opensource.org/licenses/gpl-license)
#          with "runtime exception" (http://www.dune-project.org/license.html)
# Authors:
#   Felix Schindler (2017)
#   René Fritze     (2016, 2018 - 2019)
#   Tobias Leibner  (2020 - 2021)
```
dune.xt 2022.5.3
Python for Dune-Gdt

```
# This file is part of the dune-xt project:
#   https://zivgitlab.uni-muenster.de/ag-ohlberger/dune-community/dune-xt
# Copyright 2009-2021 dune-xt developers and contributors. All rights reserved.
# License: Dual licensed as BSD 2-Clause License (http://opensource.org/licenses/BSD-2-Clause)
#      or  GPL-2.0+ (http://opensource.org/licenses/gpl-license)
#          with "runtime exception" (http://www.dune-project.org/license.html)
# Authors:
#   Felix Schindler (2017)
#   René Fritze     (2016, 2018 - 2019)
#   Tobias Leibner  (2020 - 2021)
```
en-ww2spacy 0.0.9
This is a spaCy pipeline for processing primary and secondary sources pertaining to World War 2

This is a spaCy pipeline for processing primary and secondary sources pertaining to World War 2

| Feature | Description |
| --- | --- |
| **Name** | `en_ww2spacy` |
| **Version** | `0.0.9` |
| **spaCy** | `>=3.4.4,<3.5.0` |
| **Default Pipeline** | `sentencizer`, `span_ruler`, `military_personnel`, `find_ghetto`, `clean_spans`, `clean_tank`, `clean_ships` |
| **Components** | `sentencizer`, `span_ruler`, `military_personnel`, `find_ghetto`, `clean_spans`, `clean_tank`, `clean_ships` |
| **Vectors** | 0 keys, 0 unique vectors (0 dimensions) |
| **Sources** | n/a |
| **License** | n/a |
| **Author** | [W.J.B. Mattingly](https://github.com/wjbmattingly/ww2-spacy) |

### Label Scheme

<details>

<summary>View label scheme (34 labels for 1 components)</summary>

| Component | Labels |
| --- | --- |
| **`span_ruler`** | `AIRBORN_DIVISION`, `AMPHIBIOUS_VESSEL`, `ANTI_TANK`, `ARMORED_DIVISION`, `ARMY_GROUP`, `BATTALION`, `BATTLE`, `BATTLESHIP`, `BLADE`, `CAMP`, `CARRIER`, `CARRIER_ESCORT`, `CAVALRY`, `CORPS`, `CRUISER`, `DESTROYER`, `FIELD_ARMY`, `FLAMETHROWER`, `FRIGATE_DESTROYER_ESCORT`, `GRENADE`, `GUNBOAT`, `INFANTRY_DIVISION`, `MACHINE_GUN`, `MINE_VESSEL`, `MORTAR`, `MOUNTAIN_DIVISION`, `OPERATION`, `PISTOL`, `PLANE`, `RIFLE`, `SHOTGUN`, `SUBMACHINE_GUN`, `SUBMARINE`, `TANK` |

</details>
aicommit 0.1.0
Generate AI powered commit messages
Requires Python: >=3.7

# autocommit

AI-Generated Git Commit Messages

Includes two tools: `commit.py` and `scan_repo.py`

Install the `aicommit` command with `pip install aicommit`

## commit

An interactive CLI tool that generates 5 commit message suggestions for all the changes in your current Git repo. After you pick and edit the commit message you want, it performs the commit.

![ezgif-1-1425a5f8d5](https://user-images.githubusercontent.com/23818/208993321-ec3a41d1-2208-4054-bc4d-c12279fa2484.gif)

**NOTE:** it commits all changes, untracked and unstaged, in your current repo.

On first run, it will prompt you for your OpenAI API key. Sign up for OpenAI if you haven't. Grab your API key by going to the dropdown on the top right, selecting "View API Keys" and creating a new key. Copy this key.

## scan_repo

`scan_repo` runs through all the commits in your repository to generate a CSV with AI-suggested commit messages side-by-side with your original commit messages.

To run scan_repo, copy `.env.example` to `.env` and add your OPENAI_KEY.

To update the repo it runs on, modify the `GITHUB_REPO_URL` variable at the top of `scan_repo.py`

# Publishing to pip

Version bump and clear out `dist/`

```
python3 -m build
twine check dist/*
twine upload dist/* --verbose
```
mg-sql 0.0.1
Создание файлов конфигурация
Requires Python: >=3.10,<4.0

# Подготовка

Для работы с БД я создал библиотеку на основе `SqlAlchemy`.

Главно, что нужно сделать для работы с этой библиотекой, это заранее вызвать конструктор класса `SQL`, который создаст
подключение к СУБД

```python
SQL(SqlUrlConnect.СУБД(user='', password='', host='', name_db=''))
```

- `SqlUrlConnect` - Класс с шаблонами формирования `url` для подключения к СУБД

# Использование

## Использование в асинхронной Функции/Методе

```python
import asyncio
from mg_sql.sql_async import SqlUrlConnect
from mg_sql.sql_async.base import SQL
from sqlalchemy.ext.asyncio import create_async_engine, AsyncSession, AsyncConnection, AsyncEngine

@SQL.get_session_decor
async def ReadDB(_session: AsyncSession):
    res = await SQL.read_execute_raw_sql(_session, raw_sql=""" SQL ЗАПРОС = :ключ """, params={'ключ':Значение})

asyncio.run(ReadDB())
```

- `raw_sql=''` - SQL запрос
- `params:dict[str,Any]` - Параметры в шаблонные

## Создание таблиц

```python
import asyncio
from mg_sql.sql_async.base import SQL
from mg_sql.sql_async.model_logic import RawSqlModel

class ИмяТаблицы(RawSqlModel):
    """Пользователи"""
    table_name = 'ИмяТаблицы'

    @classmethod
    def create_table(cls) -> str:
        return """
CREATE TABLE ИмяТаблицы (
 id INTEGER,
 user_id INTEGER,
);
CREATE UNIQUE INDEX ix_users_vk_user_id ON users_vk (user_id);
    """

asyncio.run(SQL.create_models(
    [ИмяТаблицы]
))
```

<!-- ## Использование в FastApi

```python
@router.api_route("/Путь", methods=["POST"])
async def ИмяМаршрутизатора(request: Request, session: AsyncSession = Depends(SQL.get_session)):
    res = await SQL.read_execute_raw_sql(session, raw_sql='', params={})
```

- `raw_sql=''` - SQL запрос
- `params:dict[str,Any]` - Параметры в шаблонные
 -->
nonebot-plugin-bfinfo 0.0.5
nonebot plugin bfinfo
Requires Python: >=3.7.3,<4.0
Keywords: pip,nonebot2,nonebot,battlefield,nonebot_plugin

<p align="center">
  <a href="https://v2.nonebot.dev/"><img src="https://v2.nonebot.dev/logo.png" width="200" height="200" alt="nonebot"></a>
</p>
<div align="center">
<h1 align="center">🔥 nonebot_plugin_bfinfo</h1>


✨ 战地1、5战绩查询 ✨

</div>

<p align="center">
  <a href="https://github.com/GC-ZF/nonebot_plugin_bfinfo/blob/main/LICENSE">
    <img src="https://img.shields.io/github/license/GC-ZF/nonebot_plugin_bfinfo" alt="license">
  </a>
  <a href="https://pypi.python.org/pypi/nonebot_plugin_bfinfo">
    <img src="https://img.shields.io/pypi/v/nonebot_plugin_bfinfo" alt="pypi">
  </a>
  <img src="https://img.shields.io/badge/python-3.7.3+-blue" alt="python">
  <img  src="https://visitor-badge.glitch.me/badge?page_id=nonebot_plugin_bfinfo" /><br />
</p></br>

## 插件描述

一款基于[Nonebot2](https://github.com/nonebot/nonebot2)的插件

调用[Stats API for the Battlefield series](https://api.gametools.network/docs)，用于QQ私聊或群聊发送战地游戏ID，返回基础信息以及最佳兵种、最佳枪械、最佳载具、最佳模式信息

由于API返回信息不全，获取的json存在一些问题，无法获取正确信息

* 战地一
  * 等级(`rank`)字段为0
  * 总治疗量(`heals`)字段为None
* 战地五
  * 总治疗量(`heals`)字段为None
  * 最佳兵种(`classes`)字段中所有数据为0
  * 最佳游戏模式(`gamemodes`)字段不存在

因为期末考试，中间隔了好久才完成，文件夹**本地测试源码**中存放了未加入nonebot框架以前的源码，可以在编译器中直接调试

* BF1_record：初步完成基本功能，输入游戏ID，绘制基础信息
* Battlefield_Test：`03数据分析.py`中实现输入游戏ID，绘制基础信息以及最佳兵种、最佳枪械、最佳载具、最佳模式信息

提供以上源码是为了方便测试，如果你有更好的解决办法，欢迎留言

API如下，将`{player_name}`替换为游戏ID即可在浏览器中查看信息

```python
https://api.gametools.network/bf1/all/?name={player_name}&lang=en-us
https://api.gametools.network/bfv/all/?name={player_name}&lang=en-us    
```

本人未系统学习过py,靠仅有的cpp和py的一点点理解制作的,如果有任何问题、建议,欢迎[issues](https://github.com/GC-ZF/nonebot_plugin_bfinfo/issues)

## 安装
```python
pip install nonebot_plugin_bfinfo
```
## 配置项
在`bot.py`中添加
```python
nonebot.load_plugin("nonebot_plugin_bfinfo")
```
## 命令

在群聊或私聊中发送`BFI+ID`，`BFV+ID`

## 示例

<div align="center">
  <img height="300px" src="https://test1.jsdelivr.net/gh/GC-ZF/nonebot_plugin_bfinfo/BFI示例图片.png">
</div>

<div align="center">
  <img height="300px" src="https://test1.jsdelivr.net/gh/GC-ZF/nonebot_plugin_bfinfo/BFV示例图片.png">
</div>

## 历史

2022.07.05 成功提交给nonebot2，第一次贡献代码，激动！

2022.07.08 修复win环境下，字体缺失，主要原因是配置了Linux的绝对路径，获取文字材质。改为直接在插件中存放**华文行楷.TTF**



欢迎小🍟入群927254485