semvec/pypi-packages huggingface dataset:
nonebot-plugin-sleep 0.1.1
来一份精致的睡眠套餐

<div align="center">
  <a href="https://v2.nonebot.dev/store"><img src="https://github.com/A-kirami/nonebot-plugin-template/blob/resources/nbp_logo.png" width="180" height="180" alt="NoneBotPluginLogo"></a>
  <br>
  <p><img src="https://github.com/A-kirami/nonebot-plugin-template/blob/resources/NoneBotPlugin.svg" width="240" alt="NoneBotPluginText"></p>
</div>

<div align="center">

# nonebot-plugin-sleep

_✨ NoneBot 来份精致的睡眠套餐 ✨_


<a href="./LICENSE">
    <img src="https://img.shields.io/github/license/mas-alone/nonebot-plugin-sleep.svg" alt="license">
</a>
<a href="https://pypi.python.org/pypi/nonebot-plugin-sleep">
    <img src="https://img.shields.io/pypi/v/nonebot-plugin-sleep.svg" alt="pypi">
</a>
<img src="https://img.shields.io/badge/python-3.8+-blue.svg" alt="python">

</div>

## 📖 介绍

想拥有一份精致的睡眠套餐吗? ^ ^

发送指令让bot给你吧!

## 💿 安装

<details>
<summary>使用 nb-cli 安装</summary>
在 nonebot2 项目的根目录下打开命令行, 输入以下指令即可安装

    nb plugin install nonebot-plugin-sleep

</details>

<details>
<summary>使用包管理器安装</summary>
在 nonebot2 项目的插件目录下, 打开命令行, 根据你使用的包管理器, 输入相应的安装命令

<details>
<summary>pip</summary>

    pip install nonebot-plugin-sleep
</details>
<details>
<summary>pdm</summary>

    pdm add nonebot-plugin-example
</details>
<details>
<summary>poetry</summary>

    poetry add nonebot-plugin-example
</details>
<details>
<summary>conda</summary>

    conda install nonebot-plugin-example
</details>

打开 nonebot2 项目根目录下的 `pyproject.toml` 文件, 在 `[tool.nonebot]` 部分追加写入

    plugins = ["nonebot_plugin_sleep"]

</details>

## ⚙️ 注意

bot必须为 管理员/群主 才有禁言的权限

否则只回复晚安。且无法禁言管理员！

## 🎉 使用
### 指令表
`/sleep`<br>
禁言发指令的用户8小时，bot回复晚安。<br><br>
`/sleep 10`<br>
禁言发指令的用户10小时，bot回复晚安。<br><br>
 **sleep** 后面带数字的话就禁言对应的时长，必须为整数， **最多24** 也就是1天，如果超过24则也禁言1天， **最小1** 也就是1小时，不带数字就是第一个例子了默认8小时。
leafcutter 2.0.2
Leafcutter python implementation

# leafcutter

[Yang I. Li](https://thelilab.com/)<sup>1</sup>, [David A. Knowles](https://daklab.github.io/)<sup>1</sup>, [Jack Humphrey](https://jackhump.github.io/), Alvaro N. Barbeira, Scott P. Dickinson, Hae Kyung Im, [Jonathan K. Pritchard](http://web.stanford.edu/group/pritchardlab/home.html)

This branch has a Python/pytorch/pyro reimplementation of the LeafCutter differential splicing test. Users (including us!) often had problems installing the RStan based package. 

You should be able to install with `python -m pip install leafcutter`. 

The installation process will install `leafcutter-cluster` and `leafcutter-ds` as command line tools. 

<img src="./docs/logo.png" width="200"> **Annotation-free quantification of RNA splicing.**

Leafcutter quantifies RNA splicing variation using short-read RNA-seq data. The core idea is to leverage spliced reads (reads that span an intron) to quantify (differential) intron usage across samples. The advantages of this approach include
* easy detection of novel introns
* modeling of more complex splicing events than exonic PSI
* avoiding the challenge of isoform abundance estimation
* simple, computationally efficient algorithms scaling to 100s or even 1000s of samples

For details please see our [bioRxiv preprint](http://www.biorxiv.org/content/early/2017/09/07/044107) and corresponding [Nature Genetics publication](https://www.nature.com/articles/s41588-017-0004-9).

Additionally, for full details on the leafcutter for Mendelian Diseases (leafcutterMD) method that performs outlier splicing detection, see our [Bioinformatics publication](http://dx.doi.org/10.1093/bioinformatics/btaa259).

Full documentation is available at <http://davidaknowles.github.io/leafcutter/>

If you have usage questions we've setup a Google group here: <https://groups.google.com/forum/#!forum/leafcutter-users>

We've developed a leafcutter [shiny](https://shiny.rstudio.com/) app for visualizing leafcutter results: you can view an example [here](https://leafcutter.shinyapps.io/leafviz/). This shows leafcutter differential splicing results for a comparison of 10 brain vs. 10 heart samples (5 male, 5 female in each group) from [GTEx](https://www.gtexportal.org/home/).
vk-pygeom 1.0.5
This is a collection of geometry related python packages
Requires Python: >=3.8

# vk_pygeom
This is a collection of geometry related python packages

# License
This software is released under the condition described in the LICENSE.

## install
```
python3 -m pip install vk_pygeom
```
or
```
pip install git+ssh://git@github.com/vk2gpz/vk_pygeom.git
```
(notice that ':' in "pip install git+ssh://git@github.com:vk2gpz/vk_pygeom.git" needs to be changed to '/')


## test
python
```
>>> import vk.geom.grid.geodesicdome as gd
>>> gd.main()
```

## build distribution archive
```
python3 -m pip install --upgrade build
python3 -m build
```

## uploading the distribution archive (change testpypi to pypi for official upload)
```
python3 -m pip install --upgrade twine
python3 -m twine upload --repository testpypi dist/*
```
vba-precompiler 0.0.1
Precompile VBA code.
Requires Python: >=3.7

[![Coverage Status](https://coveralls.io/repos/github/Beakerboy/VBA-Precompiler/badge.png?branch=main)](https://coveralls.io/github/Beakerboy/VBA-Precompiler?branch=main) ![Build Status](https://github.com/Beakerboy/VBA-Precompiler/actions/workflows/python-package.yml/badge.svg)
# VBA-Precompiler

## About
The Microsoft VBA language includes a simple precompilation language (Conditional Compilation). This tool allows users to specify environment parameters to convert a conditional-module-body into a preprocessed-module-body.

This software operates as recommended in the [Microsoft VBA Language Specification](https://winprotocoldoc.blob.core.windows.net/productionwindowsarchives/MS-CFB/%5bMS-CFB%5d.pdf).

## Requirements
vba_precompiler is tested on python 3.8 and higher.

## Installation
Use the package manager [pip](https://pip.pypa.io/en/stable/) to install VBA-Precompiler.
```
pip install vba_precompiler
```

## Getting Started
vba_precompiler will take a specified directory that contains vba source code, and a set of environment values, and produce a set of matching vba source files in which code is excluded as directed by the precomiler directives.

For example, the following
```
Attribute VB_Name = "Input"
#Const TestType="testing"
#If Win16 Or Then
    foo = 6
#ElseIf Win32
    foo = 7
#EndIf
'Additional VBA code follows
```

Will be transformed to the following:
```
Attribute VB_Name = "Input"
'#Const TestType="testing"
'#If Win16 Then
    foo = 6
'#ElseIf Win32
'    foo = 7
'#EndIf
'Additional VBA code follows
```
To run the program
```
python vba_precompiler.py [-h] [-s SYSTEM] [-v VERSION] [-o OUTPUT] directory

positional arguments:
  directory             The source directory.

options:
  -h, --help            show this help message and
                        exit
  -s, --system          System Type, Win16, Win32, Win64, or Mac.
  -v, --version         VBA version, 6 or 7.
  -o, --output         output path, defaults to ./build.

examples:
  python -m vba_precompiler -s Win32 -v 7 -o ./build32_7 ./project
```

## Tests
The tests directory contains complete unit and functional tests.

## Contributing
Contributions are welcome. Please ensure new features include unit tests to maintain 100% coverage. All code must adhere to the [PEP8 Standards](https://peps.python.org/pep-0008/) for both formatting and naming. Method signatures must be fully annotated.