semvec/pypi-packages huggingface dataset:
nonebot-plugin-pokesomeone 0.1.1
指定戳一戳
Requires Python: >=3.8,<4.0

<div align="center">
  <a href="https://github.com/canxin121">
    <img src="https://socialify.git.ci/canxin121/nonebot_plugin_pokesomeone/image?font=Raleway&forks=1&issues=1&language=1&logo=https%3A%2F%2Fcanxin121.github.io%2Fdocs%2Flogo.png&name=1&owner=1&pattern=Charlie%20Brown&pulls=1&stargazers=1&theme=Auto" width="700" height="350">
  </a>
  <h1>nonebot-plugin-pokesomeone</h1>
</div>

<p align="center">
    <a href="https://pypi.python.org/pypi/nonebot-plugin-pokesomeone">
    <img src="https://img.shields.io/pypi/v/nonebot-plugin-pokesomeone" alt="pypi">
    </a>
    <img src="https://img.shields.io/pypi/pyversions/nonebot-plugin-pokesomeone" alt="python">
    <br />
    <a href="https://onebot.dev/">
    <img src="https://img.shields.io/badge/OneBot-v11-black?style=social&logo=data:image/png;base64,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" alt="onebot">
    <img src="https://img.shields.io/github/last-commit/canxin121//nonebot_plugin_pokesomeone" alt="github">
    </a>
</p>
<div align="left">

## 最新版本号0.1.0

# 使用方法:  

> 假设 nb的CommandStart 为/

则 /戳@某人n(次)   
或 /戳n(次)某人,  
或 /戳   然后根据提示继续  


# env.*配置

| 配置名        | 含义                | 默认值 |
| ------------- | ------------------- | ------ |
| po_max        | 最多戳的次数        | 3      |
| po_black_list | 不可使用的qq或群 号 | [""]   |
| po_white_list | 不可戳的qq号        | [""]   |
easy-ge 0.1.12.4
A package that simplifies usage of Great Expectations tool for Data Validation.
Requires Python: >=3.10,<3.13
Keywords: Great Expectations,data quality,data validation



A package that simplifies data validation in your pipeline by abstracting the complexity
of Great Expectations away. Easy G.E (_pronounced ee-zee-jee-ee_) is designed for common
use cases (in-memory and file scenarios), enabling you to set up tests in minutes without
having to get acquainted with Great Expectations itself.

to get started simply run
```python
pip install easy-ge # or easy-ge[google] for google backend
```

For more information and detailed instructions, check out the [GitHub
repository](https://github.com/Elsayed91/easy_ge).
xmcda 0.3
Read, write and manipulate XMCDA objects
Requires Python: >=3.6

Read, write and manipulate XMCDA objects
========================================

This package enables the manipulating MCDA objects, as defined in the standard data interexchange format [XMCDA](https://www.decision-deck.org/xmcda/)

XMCDA is a data standard which allows to represent MultiCriteria Decision Analysis (MCDA) data elements in XML according to a clearly defined grammar, designed by the [Decision Deck Consortium](https://www.decision-deck.org/).
surquest-utils-appstoreconnect-analytics-api 0.0.1rc1
Client library for AppStore Connect Analytics API

![GitHub](https://img.shields.io/github/license/surquest/python-appstore-analytics-api?style=flat-square)
![GitHub Workflow Status (with branch)](https://img.shields.io/github/actions/workflow/status/surquest/python-appstore-analytics-api/test.yml?branch=main&style=flat-square)
![Coverage](https://img.shields.io/endpoint?url=https://gist.githubusercontent.com/surquest/6e25c317000917840152a5e702e71963/raw/python-appstore-analytics-api.json&style=flat-square)
![PyPI - Downloads](https://img.shields.io/pypi/dm/surquest-GCP-logger?style=flat-square)
![PyPI](https://img.shields.io/pypi/v/surquest-GCP-logger)

# Introduction

This is a Python library for the AppStore Analytics API and allows you to easily access the analytics data of your python apps.

# Installation

```bash
pip install surquest-utils-appstoreconnect-analytics-api
```

# Usage

```python
import datetime as dt
from surquest.utils.appstoreconnect.analytics import (
    Client as AppStoreConnectClient,
    Analytics as AppStoreConnectAnalytics,
    Formatter,
    Frequency,
    Measures,
    Dimension,
)

# Create client
client = AppStoreConnectClient(
    mayacinfo="ADD-YOUR-MYACINFO", # is a Cookie value from https://appstoreconnect.apple.com/
)

# Create analytics object
analytics = AppStoreConnectAnalytics(
    client=client
)

# Get time series data
data = analytics.get_time_series(
    app_ids=["ADD-YOUR-APP-ID"],
    measure=Measures.INSTALLS,
    start_date=dt.date(2021, 1, 1),
    end_date=dt.date(2021, 1, 31),
    grouping=Group.COUNTRY
    frequency=Frequency.DAY,
    )

print("YOUR DATA:", data)
```

# Development

```
docker build `
     --tag surquest/utils/appstoreconnect:dev `
     --file package.base.dockerfile `
     --target test .

docker run --rm -it `
 -v "${pwd}:/opt/project" `
 -w "/opt/project/test" `
 -e "APPID={ADD-YOUR-APP-ID}" `
 -e "MYACINFO={ADD-YOUR-MYACINFO}" `
 surquest/utils/appstoreconnect:dev pytest
```

# License

This project is licensed under the terms of the MIT license.
dataplane 0.1.3
The data engineering library to build robust, reliable and on time data pipelines in Python.
Requires Python: >=3.7
Keywords: workflow,data-science,data,airflow,etl,dataplane,data-engineering,data-pipelines,datawarehouse,automation,data-analysis,scheduler

# dataplane-python-package
The data engineering library to build robust, reliable and on time data pipelines in Python.

### To use with Dataplane Data Platform
Install Python Package on Dataplane: https://learn.dataplane.app/installing-python-packages<br />
Recipes to use Dataplane Python Package: https://recipes.dataplane.app/office-365/sharepoint-api

### Run tests in repo root
```shell
pytest -s
```

### For a specific test

```shell
pytest -s src/dataplane/data_storage/test_sharepoint_upload.py
pytest -s -k test_sharepoint.py
```

### Troubleshooting errors
If an error occurs, try removing .pytest_cache and ```__pycache__``` - can happen after devcontainers build

```shell
find . | grep -E "(/__pycache__$|\.pyc$|\.pyo$)" | xargs rm -rf
rm -rf /home/vscode/.local/lib/python3.10/site-packages/
```

### S3 / Minio for testing in VS code devcontainers
* Go to http://localhost:9011
* Login with: username: admin and password: hello123
* bucket: dataplanebucket
SupOpNumTools 1.0.0
Package for engineer in physics and photonics
Requires Python: >=3.9

# SupOpToolBox
Package

**ToolBox of functions for physicists in photonics**

*Developed by Institut d'Optique Graduate School / France*

This project is still **in development**. To contribute, look at the *Collaboration* section.

## Table of Contents
0. [About SupOptique](#about-supoptique)
1. [General Info](#general-info)
2. [Installation](#installation)
3. [How To Use](#how-to-use)

## About SupOptique
Founded in 1917, the Institut d'Optique Graduate School is a world leader in higher education, research and innovation in optics and photonics.

The Institut trains physics engineers, master's students and some of the most innovative PhDs in business and academia.
At the heart of networks of excellence, its international influence is based both on the quality of the training it provides and on its research and technology transfer.

The Institut is a major engineering school member of University Paris-Saclay and is established on the campuses of excellence of Paris-Saclay and Bordeaux, as well as Saint-Etienne.

The scientific contributions of its research center are major : the researchers publish on average one article per week and are quoted 30 times daily.

For more informations : [Institut d'Optique](https://www.institutoptique.fr/en)

## General Info

This repository contains **Python Functions** for physicists. They are classified in the following categories :
- sig1D : 1D signal generation and processing (vector)
- img2D : 2D image generation and processing (matrix)
- elecmodel : numerical model for electronic systems


## Installation

You can **clone** this repository into your own work directory (using git).

If you're not familiar to Git repository, you can also **download** the [archived file - zip](https://github.com/jvillemejane/SupOpToolboxes/archive/refs/heads/main.zip) of the repository.

## How To Use

For more details, see the [SupOpNumTools documentation page](https://iogs-digital-methods.github.io/SupOpNumTools/)