semvec/pypi-packages huggingface dataset:
flask-crud-api 0.0.1
基于flask快速、优雅实现restful接口
Requires Python: >=3.9

# flask-crud-api

本库旨在帮助后端开发人员快速构建一个基于`flask`框架的后端项目。

## 参数说明

1. 分页相关

```shell
__page 页码
__page_size 每页数量

# 如果需要禁用分页，可以使用此字段，请谨慎使用
__page_disable
```

2. 添加、修改数据字段

```shell
# 鉴于开发时，一次查询将会给出对应的字段模型及相关解释
# 创建、修改数据时可以使用此字段
```

3. 过滤字段

```shell
# 这部分字段请结合实际在后端代码中添加需要被过滤的字段内容

# 例如：
view_filter_fields = (("pk", "="),)
view_filters = (SearchFilter, )
```

4. 排序字段

```python
# 如果需要进行排序，请配置view_order_fields、view_filters
"""
view_order_fields = (("__order_pk", 'desc'), )
view_filters = (OrderFilter, ...)
"""

# 例如
view_order_fields = (
    ("__order_pk", 'desc'), 
    ("__order_pk", 'asc'), 
)
view_filters = (SearchFilter, OrderFilter)

# 传递query参数 __order_pk=asc 即可实现pk的升序
# 传递query参数 __order_pk=desc 即可实现pk的降序
```
eap-mcp-server 0.1.2
EAP MCP Server
Requires Python: >=3.12

# EAP MCP Server

[English](#english) | [中文](#chinese)

## English

### Overview
EAP MCP Server is a Python-based server application designed for handling Message Control Protocol (MCP) communications. It specializes in EAP (Enterprise Application Platform) data integration and provides intelligent data analysis capabilities.

### Features
- EAP data integration and processing
- Intelligent data analysis and insights
- Real-time data monitoring and visualization
- Advanced data processing using pandas
- Interactive data visualization with matplotlib
- Command-line interface for easy operation

### Requirements
- Python >= 3.12
- Required packages:
  - argparse >= 1.4.0
  - matplotlib >= 3.10.3
  - mcp >= 1.6.0
  - pandas >= 2.2.3
  - requests >= 2.32.3

### Installation
```bash
pip install eap-mcp-server
```

### Usage
```bash
eap-mcp-server [options]
```

### Development
To set up the development environment:
1. Clone the repository
2. Install dependencies:
```bash
pip install -e .
```

## Chinese

### 概述
EAP MCP Server 是一个基于 Python 的服务器应用程序，专门用于处理企业应用平台（EAP）数据接入和智能化分析。它提供强大的数据处理、分析和可视化功能，帮助企业实现数据驱动的决策。

### 功能特点
- EAP 数据接入与集成
- 智能化数据分析与洞察
- 实时数据监控与可视化
- 基于 pandas 的高级数据处理
- 使用 matplotlib 的交互式数据可视化
- 便捷的命令行操作界面

### 系统要求
- Python >= 3.12
- 所需包：
  - argparse >= 1.4.0
  - matplotlib >= 3.10.3
  - mcp >= 1.6.0
  - pandas >= 2.2.3
  - requests >= 2.32.3

### 安装
```bash
pip install eap-mcp-server
```

### 使用方法
```bash
eap-mcp-server [选项]
```

### 开发
设置开发环境：
1. 克隆仓库
2. 安装依赖：
```bash
pip install -e .
```
foxwire 0.1.0
Python implementation of the FoxWire protocol
Requires Python: >=3.6


# Biblioteca em python para Comunicação FoxWire

Implementação em python do protocolo FoxWire usando um conversor UBS-Serial comum e um resistoor. O arquivo FoxWire contém as funções para fazer o computador se comportar como um ***Host***.

### Exemplos:
- `FXS50_FoxWire.py`: contém as funções para se comunicar com os sensores FX-S50.
- `FXS50_change_addr.py`: Altera o endereço de um sensor.
- `FXS50_configure.py`: Altera as configurações do sensor.

### Circuito com sensor FX-S50 ou outros dispositivos:
![Alt text](../docs/fx_serial.png)

 [!NOTE]  
> É possivel conectar varios dispositivos diferentes desde que tenham endereços distintos.

## Funções da FoxWire.py

### `init(port='COM16')`
**Descrição**: Inicializa a comunicação serial com o Arduino.  
**Parâmetros**:
  - `port` (*str*): Porta serial a ser utilizada (ex.: `COM3` no Windows ou `/dev/ttyUSB0` no Linux). Padrão: `'COM16'`.

### `logif(txt, log)`
**Descrição**: Exibe mensagens no console se o log estiver habilitado.  
**Parâmetros**:  
- `txt` (str): Mensagem a ser exibida.  
- `log` (bool): Define se o log está habilitado.  

---

### `send(data, recive_size, log=False)`
**Descrição**: Envia dados e recebe uma resposta.  
**Parâmetros**:  
- `data` (list): Dados a serem enviados (em bytes).  
- `recive_size` (int): Número de bytes esperados na resposta.  
- `log` (bool): Habilita ou desabilita o log (padrão: False).  
**Retorna**: Resposta recebida (bytes) ou None em caso de erro.  

---

### `pack_check(addr, log=False)`
**Descrição**: Envia um pacote do tipo CHECK (envia 1 bytes e recebe 1). Verifica a conexão de um dispositivo em um endereço específico.  
**Parâmetros**:  
- `addr` (int): Endereço do dispositivo.  
- `log` (bool): Habilita ou desabilita o log (padrão: False).  
**Retorna**: Resposta recebida (bytes) ou None em caso de erro. 

---

### `pack_read(device_addr, addr, log=False)`
**Descrição**: Envia um pacote do tipo READ (envia 2 bytes e recebe 1). Tipicamente é usado para ler um valor de um endereço de um dispositivo.  
**Parâmetros**:  
- `device_addr` (int): Endereço do dispositivo.  
- `addr` (int): Endereço interno para leitura.  
- `log` (bool): Habilita ou desabilita o log (padrão: False).  
**Retorna**: Valor lido ou None em caso de falha.  

---

### `pack_write(device_addr, addr, val, log=False)`
**Descrição**: Envia um pacote do tipo WRITE (envia 3 bytes e recebe 1). Escreve um valor em um endereço de um dispositivo.  
**Parâmetros**:  
- `device_addr` (int): Endereço do dispositivo.  
- `addr` (int): Endereço interno para escrita.  
- `val` (int): Valor a ser escrito.  
- `log` (bool): Habilita ou desabilita o log (padrão: False).  
**Retorna**: Valor confirmado ou None em caso de falha.  

---

### `scan(log=False)`
**Descrição**: Busca dispositivos conectados na rede.  
**Parâmetros**:  
- `log` (bool): Habilita ou desabilita o log (padrão: False).  
**Retorna**: Lista de endereços dos dispositivos encontrados.
snak 0.1.1
Python Standalone Build Management Tool
Requires Python: >3.8
Keywords: python, build, management, standalone, virtualenv

# `snak` — Python Standalone Build Management Tool

`snak` is a lightweight CLI utility to manage multiple **self-contained Python builds** and virtual environments,
without touching your system Python installation.

It downloads **prebuilt Python binaries**
(from [python-build-standalone](https://github.com/astral-sh/python-build-standalone)) directly, allowing you
to **install, update, switch, and create virtual environments** independently and safely.

---

## Features

* 📦 Install standalone Python builds easily
* 🔄 Create and manage multiple virtual environments
* 🔍 List and inspect installed versions and environments
* ⚙️ Minimal configuration with sane defaults
* 🛡️ System-safe: does not interfere with your system's Python
* 🖥️ Works on **Linux** and **macOS**

---

## Installation

You can install `snak` globally by running:

```bash
curl -L https://raw.githubusercontent.com/mosquito/snak/refs/heads/master/src/snak.py | sudo install -Dm 755 /dev/stdin /usr/local/bin/snak
```

Alternatively, you can save the script manually and place it somewhere in your `$PATH`.

```bash
pip install --user snak
```

---

## Usage

```bash
snak [COMMAND] [SUBCOMMAND] [OPTIONS...]
```

High-level command structure:

| Command    | Description                       |
| ---------- | --------------------------------- |
| `env`      | Manage virtual environments       |
| `versions` | Manage standalone Python versions |
| `config`   | Manage `snak` configuration       |

Run `snak --help` to view all available commands.

---

## Examples

### Install a new standalone Python version

```bash
snak versions list
snak versions install 3.12.2
```

### Create a new virtual environment

```bash
snak env create myenv
# (optionally install packages)
snak env create myenv -p requests flask
```

### Activate an environment

```bash
eval $(snak env activate myenv)
```

*(Note: use `eval` to source the activation in your current shell.)*

### List all environments

```bash
snak env list
```

### Remove a virtual environment

```bash
snak env remove myenv
```

### Show installed Python versions

```bash
snak versions list
```

---

## Configuration

`snak` uses a simple INI-style configuration file:

* **User mode**: `~/.local/share/snak/config.ini`
* **Root mode (sudo)**: `/etc/snak.ini`

You can show or edit the configuration:

```bash
snak config show
snak config set paths cache ~/.cache/snak/

# for reverting to default just set empty value
snak config set paths cache ""
```

---

## Requirements

`snak` uses only standard libraries and does not require external Python packages.

You need just a few things to run `snak`:

* Linux or macOS
* Python 3.8+

---

## Why `snak`?

* No need to compile Python from source.
* Fully isolated environments.
* Great for experimenting with different Python versions easily.

---

## License

MIT License.
cartesia-mcp 0.1.6
The official Cartesia MCP server
Requires Python: >=3.13

## Cartesia MCP Server

This is the official Cartesia MCP server which allows other MCP clients such as OpenAI agents, Curso and Claude Desktop to perform text to speech, transcribe audio, localize spech etc. 

### Cartesia Setup

Ensure that you have created an account on Cartesia and gotten your API key. There is a free tier with 20,000 credits per month.

### Installation

Install the python package using `pip install cartesia-mcp` 

Add the following to your MCP settings file such as `claude_desktop_config.json` 

```
{
  "mcpServers": {
    "cartesia-mcp": {
      "command": "uvx",
      "args": ["cartesia-mcp"],
      "env": {
        "CARTESIA_API_KEY": "<insert-your-api-key-here>",
        "OUTPUT_DIRECTORY": // directory to store generated files
      }
    }
  }
}
```

Try asking Claude to 
- list all feminine, masculine, or gender neutral Cartesia voices
- to provide more information about voice X
- to convert a text phrase to audio using a particular voice
- to generate audio to connect two existing audio segments (specify file paths)
- to create a new voice from an existing voice
PSARPS 0.1.3
Get metadata about Planet Scope ARPS satellite imagery
Requires Python: >=3.10

# PSARPS - Planet Scope ARPS Satellite Imagery Metadata Tool

A Python library and CLI tool for retrieving tide metadata for Planet Scope ARPS (Automated Rapid Preprocessing System) satellite imagery.

## Features

- Extract acquisition time from ARPS QA raster images
- Find the closest tide station to the image location
- Get the tide height at the time of image acquisition
- Simple command-line interface

## Installation

### From PyPI

```bash
pip install psarps
```

### From GitHub

```bash
pip install git+https://github.com/tayden/psarps.git
```

## Usage

### Command Line Interface

Get tide information for a Planet Scope ARPS QA raster image:

```bash
arps info path/to/your_image_qa.tif
```

Example output:
```
Acquisition Time: 2023-05-01 14:30:45
Tide Height (m): 2.34
Station Name: Victoria
Station Distance (m): 5432
```

### Python API

```python
import psarps

# Get tide information
tide_info = psarps.get_tide_height("path/to/your_image_qa.tif")

# Access the tide data
acquisition_time = tide_info['acquisition_time']
tide_height = tide_info['tide_height']
station_name = tide_info['station_name']
station_distance = tide_info['station_distance']

# Get just the acquisition time
acq_time = psarps.get_acquisition_time("path/to/your_image_qa.tif")

# Get the closest tide station
closest_station = psarps.get_closest_tide_station("path/to/your_image_qa.tif")
```

## Development

### Setup Development Environment

```bash
# Clone the repository
git clone https://github.com/tayden/psarps.git
cd psarps

# Install with development dependencies
uv pip install ".[dev]"
```

### Common Development Commands

- Run tests: `pytest`
- Lint code: `ruff check src/ tests/`
- Format code: `ruff format src/ tests/`

## Requirements

- Python 3.13+
- See pyproject.toml for dependencies

## License

MIT
Wrapper4AI 0.1.2
A lightweight multi-provider wrapper for LLM chat with history and token management.
Requires Python: >=3.7

# Wrapper4AI

**Multi-provider, pluggable LLM wrapper with token counting, history management, and seamless extensibility.**

> 🔧 Designed for developers building chat-based AI tools with OpenAI, Gemini, Bedrock, DeepSeek, Anthropic, and more.

---

## 🚀 Features

- 🔌 **Unified interface** for multiple LLM providers
- 💬 **Chat history tracking** with token trimming
- 🔢 **Token counting** with Tiktoken for OpenAI models
- 📚 **Extensible handler base** for adding new models
- ✅ **Testable client API** with clean abstraction

---

## 🛠️ Installation

```bash
  pip install git+https://github.com/DKethan/Wrap4AI.git
```

Or if you package it to PyPI:

```bash
  pip install wrapper4AI
```

---

## 🧩 Supported Providers

- ✅ OpenAI (`gpt-4o`, `gpt-3.5`, ... all OpenAI language models )
- ✅ Google Gemini 
- ✅ Amazon Bedrock 
- ✅ DeepSeek 
- ✅ Meta LLaMA 
- ✅ HuggingFace Interface
- ✅ Anthropic Claude 
- ✅ Perplexity AI 
- ✅ HuggingFace

---

## 🔧 Usage

### 1. Connect to a provider

```python
from wrapper4AI.wrap import connect

client = connect(provider="openai", model="gpt-4o", api_key="sk-xxx")
```

### 2. Basic Chat

```python
response = client.chat("Tell me a joke.")
print(response)
```

### 3. With History

```python
history = [
    {"role": "user", "content": "What is Python?"},
    {"role": "assistant", "content": "A programming language."},
    {"role": "user", "content": "Who created it?"}
]
print(client.chat_with_history(history))
```


---

## 🧪 Testing

```bash
  python -m tests.test_openai_001 # make sure to add your api key in the test file
```
gdoc-dumper 0.3.0
Lightweight python package for downloading Google Docs documents in various formats.
Requires Python: >=3.10

# 📄 gdoc-dumper <br>
Lightweight python package for downloading Google Docs documents in various formats

# 🚀 Installation
Simply install with pip or another package manager:<br><br>
```pip install gdoc-dumper```

# 🔨 Usage<br>
## 🅰 Async
```python
import asyncio

from gdoc_dumper import Downloader, Formats, FileManager

# Asynchronously download google document as bytes
async def main() -> None:
    content: bytes = await Downloader.adownload(url="<GDOC URL>", file_format=Formats.PDF)
    # You also can save file after downloading it using FileManager
    await FileManager.asave_bytes(content, path="<DESIRED PATH as PATH or String>")

asyncio.run(main())
```
You also can stream download file and save it

```python
import asyncio
from typing import AsyncGenerator

from gdoc_dumper import Downloader, Formats, FileManager


async def main() -> None:
    stream: AsyncGenerator[bytes, None] = Downloader.astream_download(
        url="<GDOC URL>",
        file_format=Formats.PDF,
    )
    await FileManager.asave_stream(stream, path="file.pdf")


asyncio.run(main())
```

## 🔁 Sync
```python
from gdoc_dumper import Downloader, Formats, FileManager

# Download google document as bytes
content: bytes = Downloader.download(url="<GDOC URL>", file_format=Formats.PDF)

# You also can save file after downloading it using FileManager
path = FileManager.save_bytes(content, path="<DESIRED PATH as PATH or String>")

```

# ✅ Available formats
```python
from gdoc_dumper import Formats

print(Formats.TXT.value) # txt
print(Formats.PDF.value) # pdf
print(Formats.DOCX.value) # docx
print(Formats.EPUB.value) # epub
print(Formats.HTML.value) # html
print(Formats.OPEN_DOCUMENT_TEXT.value) # odt
print(Formats.RICH_TEXT.value) # rtf
print(Formats.ZIP.value) # zip
```

# ⭐ License
[MIT License](https://github.com/natrofimov/gdoc-dumper/blob/DEV/LICENSE)