semvec/pypi-packages huggingface dataset:
sinkove-sdk 0.1.2
A Python SDK for interacting with Sinkove's AI dataset generation API.
Requires Python: >=3.12

# Sinkove SDK

[![PyPI version](https://badge.fury.io/py/sinkove-sdk.svg)](https://badge.fury.io/py/sinkove-sdk)

The Sinkove SDK is a Python library designed to facilitate interaction with Sinkove's AI dataset generation API. This library allows seamless integration with Sinkove's services, enabling organizations to create, manage, and download datasets programmatically.

## Features

- Create and manage datasets
- Download datasets with customizable strategies
- Monitor dataset generation status

## Getting Started

### Installation

You can install the SDK via pip:

```bash
pip install sinkove-sdk
```

### Usage

To use the SDK, you need to set your API key and API URL in the environment variables. Here's a basic example of how to create and download a dataset:

```python
import uuid
from sinkove import Client

def main():
    organization_id = uuid.UUID("your-organization-id")
    model_id = uuid.UUID("your-model-id")

    dataset = Client(organization_id).datasets.create(
        model_id, num_samples=2, args={"prompt": "cardiomegaly"}
    )

    dataset.download("dataset.zip", strategy="skip", wait=True)

if __name__ == "__main__":
    main()
```

### API Documentation

For complete API details, visit the [API documentation](https://api.sinkove.com/docs).

### Official Documentation

Find more detailed documentation about the Sinkove services at [Sinkove Docs](https://docs.sinkove.com).

### Sinkove Console

Access your Sinkove dashboard at the [Sinkove Console](https://cloud.sinkove.com).

## Contributing

Contributions are welcome! Please read the contribution guidelines first. You can start by running the project locally using:

```bash
just build
just test
```
mcp-server-yunxiao 0.1.21
MCP Server for Yunxiao
Requires Python: >=3.10

# 云霄服务 SDK

云霄（YunXiao）是腾讯云 CVM 的内部运维运营平台，提供了一系列强大的管理和运营功能。本 SDK 封装了云霄平台的 API 接口，方便开发者进行集成和使用。

## 功能特性

- 售卖策略查询：获取实例的售卖推荐数据
- 库存管理：查询各区域、机型的库存情况
- 用户管理：查询用户归属和账号信息
- 配额管理：查询和管理资源配额
- 实例管理：查询实例列表、详情和统计信息
- 实例族管理：查询可用的实例族信息

## 环境要求

- Python 3.6+
- 需要配置以下环境变量：
  - `YUNXIAO_API_URL`: 云霄 API 服务地址
  - `YUNXIAO_SECRET_ID`: 访问密钥 ID
  - `YUNXIAO_SECRET_KEY`: 访问密钥 Key

## 安装

```bash
pip install mcp-server-yunxiao
```

## API 说明

### 售卖策略相关
- `describe_sale_policies(**kwargs)`: 查询售卖推荐数据
  - 参数：
    - customhouse: List[str] - 境内外列表
    - region_alias: List[str] - 地域别名列表
    - region: List[str] - 地域列表
    - zone_id: List[int] - 可用区ID列表
    - zone: List[str] - 可用区列表
    - instance_family: List[str] - 实例族列表
    - instance_category: List[str] - 实例分组列表，可选值：CVM/GPU/FPGA/BARE_METAL
    - instance_family_state: List[str] - 实例族状态列表
    - instance_family_supply_state: List[str] - 实例族供货状态列表，可选值：LTS/EOL
    - zone_state: List[str] - 可用区状态列表
    - stock_state: List[str] - 库存状态列表
    - sales_policy: List[int] - 售卖建议列表
    - page_number: int - 页码（必填，默认1）
    - page_size: int - 每页数量（必填，默认20，最大100）
  - 返回：包含售卖策略和库存信息的JSON字符串

### 库存相关
- `describe_inventory(region: str)`: 查询指定地域的库存数据
  - 参数：
    - region: 地域名称，如 ap-guangzhou
  - 返回：包含可用区、实例族、实例类型、库存等信息

### 用户相关
- `get_user_owned_grid(app_id: int)`: 获取用户归属预扣统计
  - 参数：
    - app_id: 用户 AppID
    
- `get_customer_account_info(customer_ids: List[str])`: 获取客户账号信息
  - 参数：
    - customer_ids: 客户 ID 列表

### 配额相关
- `query_quota(region: str)`: 查询配额信息
  - 参数：
    - region: 地域名称

### 实例相关
- `query_instances(region: str)`: 查询实例列表
  - 参数：
    - region: 地域名称

- `get_instance_details(region: str)`: 获取实例详细信息
  - 参数：
    - region: 地域名称

- `get_instance_count(region: str)`: 获取实例数量统计
  - 参数：
    - region: 地域名称

### 实例族相关
- `query_instance_families()`: 查询实例族信息

## 使用示例

```python
from mcp_server_yunxiao.tool_yunxiao import describe_inventory, query_instances

# 查询广州地域的库存情况
inventory = describe_inventory(region="ap-guangzhou")
print(json.loads(inventory))

# 查询实例列表
instances = query_instances(region="ap-guangzhou")
print(json.loads(instances))
```

## 测试

运行单元测试：

```bash
cd yunxiao
python -m pytest tests/test_tool_yunxiao.py -v
```

## 注意事项

1. 请确保在使用前正确配置环境变量
2. API 返回的数据均为 JSON 格式字符串，需要使用 `json.loads()` 解析
3. 在生产环境中使用时，请注意访问频率限制
4. 部分 API 可能需要特定的访问权限，请确保有相应的权限配置

### Usage in Claude Desktop
Add the following configuration to claude_desktop_config.json:

```json
{
  "mcpServers": {
    "tencent-cvm": {
      "command": "uv",
      "args": [
        "run",
        "mcp-server-yunxiao"
      ],
      "env": {
        "YUNXIAO_SECRET_ID": "YOUR_SECRET_ID_HERE",
        "YUNXIAO_SECRET_KEY": "YOUR_SECRET_KEY_HERE"
      }
    }
  }
}
```
pyqcat-viper 0.1.0
The C++ accelerator library for Snake like optimizer.
Requires Python: >=3.7

# pyqcat-viper
---------------

Copyright (c) Origin Quantum Computing 2025.

We implemented the work point allocation algorithm by borrowing Google's Snake optimizer and combining it with test data from ours quantum chips. This algorithm was utilized to implement the work point allocation on the WuKong chip that was gone live in 2023, but now with the increasing size of the chip, the existing program is facing performance problems, so we have to find ways to improve the performance of the system. And Viper is using C++ to rewrite the error calculation part of the logic in the optimizer to improve the overall performance.

## Principles
------------
Using viztracer, it was located that the algorithm speed is mainly limited by the computation of the error function, which will be called ~10000 times per DE algorithm executability, and under the current python framework, the single error function has been optimized to the extreme, but still cannot meet the demand. Therefore, the following two optimization directions are considered, using parallel computing and rewriting the error function using C++.
Since we want to integrate it into a **Python** project, we use *Pybind11* to package Viper into a dynamic library and eventually provide it to Python.

Requirement: https://document.qpanda.cn/docs/e1Az4bl4V7UVBaqW

## Roadmap
----------
- [x] Use viztracer to generate and view call stacks and analyze call elapsed time.
- [x] Study the Python code to make sense of the logic associated with the error calculation.
- [x] Rewrite the entire error calculation flow of the chip using C++.
- [x] Compare the results of the Python version of each step of the error calculation with the C++ version of the calculation.
- [x] Wrapping C++ code into Python and testing it.
- [x] Performance Tuning for Viper.EvaluationModel.
- [x] Replacing the original error calculation model in Python with a new error calculation model and performing stability testing.
- [x] Write a VipOptimizer that completely replaces the previous FreqAllocator.

## Core developers
------------------
This project, pyqcat-viper, is conducted by Origin Quantum - Center of Measurement and Control - Software R&D Department - Group of **Spirit**.

| Developer | Duty | Email | Title |
| :----: | :---- | :---- |:---- |
| Shi, Hanqing |Author of pyqcat-viper, as well as development of the initial version. |shq@originqc.com| Senior Software Engineer at OriginQ |
| Dr. Peng Wang |Researcher of the Google snake like optimizer and wrote the Python version of the workpoint allocation code |pengwang@mail.ustc.edu.cn| PhD Candidate at USTC |
shipxy-api 0.3
亿海蓝Elane船讯网sdk https://www.shipxy.com/

# 亿海蓝-船讯网-sdk
[亿海蓝官网](https://www.shipxy.com/)&nbsp;&nbsp;
[API控制台](https://api.shipxy.com/v3/console/index)&nbsp;&nbsp;
[在线开发文档](https://hiiau7lsqq.feishu.cn/wiki/E0wAwrPpvieGhSk5wLCctNqonVb)&nbsp;&nbsp;
[github](https://github.com/shipxycom/shipxy-api-py)&nbsp;&nbsp;
[gitee](https://gitee.com/shipxycom/shipxy-api-py)&nbsp;&nbsp;
[pypi](https://pypi.org/project/shipxy-api/)&nbsp;&nbsp;

## 示例用法
```
pip install shipxy-api
```
```
from shipxy import Shipxy

key = "请从 API控制台 申请";

if __name__ == '__main__':
    response = Shipxy.GetManyShip(key, "413961925,477232800,477172700")
    print(response)
```
## 开发者在使用过程中如有疑问，可以通过以下方式联系船讯网：

• 商务邮箱：support@shipxy.com

• 技术支持邮箱：service@shipxy.com

• 电话：400-010-8558 

![飞书](./images/飞书.jpg)
![微信](./images/微信.jpg)
autoambience 1.0.0
An utomatic ambient music generator made with a python MIDI connection and a custom Vital synth!
Requires Python: >=3.13

# Auto Ambience
**An automatic ambient music generator made with Python and Vital!**

## Installation and Usage
1. Clone the repository
2. [Install Vital](https://vital.audio/) (which unfortunately requires an account 😭)
3. Open Vital, click the ≡ icon, and select "Open External Preset"
4. Navigate to the repository and select "autoambience.vital"
5. Run "pip install -r requirements.txt" in the repository
6. Run "main.py" with Python in the terminal

Then program, relax, zone out, or do whatever to some infinite ambient music!

## Controls
When run in a terminal, AutoAmbience has a text interface that can be used to play/pause the chords, change the tension mode, and change the rate at which chords are played.

The leftmost button is a simply play/pause button. Pressing it starts playing the music after beginning the program. Pressing it again waits for the current chord to finish before stopping it.

The middle button rotates the tension setting between these 3 options:
1. High Tension - the script will be more likely to choose more tense or exciting options
2. Low tension - the script will be more likely to choose more calm or common options
3. Oscillating tension - the script will change between the two modes automatically, switching when the cumulative tension is high or low

The last button rotates between 5 values for the chord rate, measured in seconds per chord. These values are 9 s/c, 12 s/c, 15 s/c, 18 s/c, and 21 s/c.

Below the buttons, there is also a small display that shows the chord playing currently, and the three chords before it. Unfortunately, due to limitations imposed by the TUI library I'm using (urwird), this doesn't update unless a graphics update is imposed, like switching between the buttons or resizing the window. 

<div align="center">
  <a href="https://shipwrecked.hackclub.com/?t=ghrm" target="_blank">
    <img src="https://hc-cdn.hel1.your-objectstorage.com/s/v3/739361f1d440b17fc9e2f74e49fc185d86cbec14_badge.png" 
         alt="This project is part of Shipwrecked, the world's first hackathon on an island!" 
         style="width: 35%;">
  </a>
</div>
phtool 0.25.717
Photometry Tools
Requires Python: >=3.10

# Photometry Tool

By Dr/Prof Jie Zheng & Dr/Prof LinQiao Jiang

v0.1 2025-06-07

## 综述

编写一个工具，通过命令行可以实现较差测光数据处理的各个步骤。

## 调用模式

根源是提供一个Python包，在py环境中调用函数。通过终端 `py -m phtool command` 加上命令和参数的方式进行终端快捷调用，或者通过 `py -m phtool gui` 的方式调用GUI选择任务和参数（待开发）。

安装后会提供一个终端命令 phtool 直接调用。

## 命令

### biascombine

指定每一幅本底文件，以及合并方式，合并成一个本底文件。

### flatcombine

指定平场文件，以及合并后的本底，可选归一化模式与合并模式，合并成一个平场文件。

### darkcombine

合并暗流，指定每一幅暗流文件，以及合并方式，合并成一个暗流文件。

### imcorr

指定合并后的本底和平场，对科学图像进行改正。如果明确指定平场为1、本底为0，则相应不进行此项改正。可以选择开窗方式。如果不指定暗流，则不进行暗流改正。可以指定坏像元掩码文件。

默认根据头文件中的坐标字段（RA,DEC / CRVAL1,2 ）获得图像中心指向，也可以指定中心关键字，或者直接指定中心赤经赤纬。观测时间根据DATE-OBS和TIME-OBS，曝光时间依据EXPTIME或者EXPOSURE，或者指定时间关键字。然后计算JD/MJD，以及HJD-JD，BJD-TDB。如果fits头已经有JD/MJD/HJD/BJD则不计算。

### find

调用 photutils 进行找源以及FWHM计算，输出星表，按照亮度排序，给出综合的FWHM预估值。

### phot

调用 photutils 进行测光，可选测光模式以及孔径。目标源可以通过直接在图像中指定，或者粗略xy指定，都不指定则根据find给出的结果进行全部测光。

### diffcali

根据phot结果，进行不同指定的较差计算和绘图，可以指定目标。采用全局定标或者指定比较星的方式。

### imgexam

单纯的图像检查工具，展示图像，并且进行等高线、三维图、横截面、纵截面、PSF等绘制。