semvec/pypi-packages huggingface dataset:
warehouser 0.3.9
Medical Procurement of Ukraine DataLakeHouse project.
Requires Python: >=3.10.12

# Dbm

Project with usefull utilities for managing you DB.

## Usage

### Config

#### 1. Config via dict

Create you config in dictionary:

```python
config = {
    "dms": "mysql",
    "host": "host",
    "port": "port",
    "user": "<your user>",
    "password": "<your password>",
    "database": "<your_db_name>"
}
```

#### *IMPORTANT* : Make sure to use ENV variables for user and password:

Example
```python
user = os.environ.get('MYSQL_PROD_USER')
password = os.environ.get('MYSQL_PROD_PWD')
```

#### 2. class config

Alternatively - you can create it dirrectly in DBmanagerConfig class.

```python 
from dbmanager import DBmanagerConfig

conf = return DBmanagerConfig(
    'mysql',
    '<your database>',
    user,
    password,
    host='host',
    port='port')
```

### DBmanager creation

```python
from dmanager import make_db_manager
from sqlalchemy import MetaData

metadata = MetaData()

dbm = make_db_manager(config, metadata)
```

**metadata** - sqlalchemy class for storing all infor about tales.
Even if you dont have it yet in your project - you must create it.

### DBmanager usage example

```python
import pandas as pd
from sqlalchemy import Integer, MetaData
from sqlalchemy.orm import DeclarativeBase, mapped_column, Mapped

from dbmanager import make_db_manager
from dbmanager.manager import DBmanager

METADATA = MetaData()

def make_dbm(dbms: str) -> DBmanager:
    config['dbms'] = dbms
    return make_db_manager(config, METADATA)

class Base(DeclarativeBase):
    metadata = METADATA


class FooTable(Base):
    __tablename__ = 'foo_bar_table'

    id: Mapped[int] = mapped_column(Integer, primapy_key=True)
    data: Mapped[str]



if __name__ == '__main__':
    dbm = make_dbm('mysql')
    dbm.create_table(FooTable)
    data = pd.read_csv('somecsv.csv')
    dbm.upsert(FooTable, data)
```
djzhpcom 0.1.0
点对点加密Python库
Requires Python: >=3.6

# djzhpcom 加密库开发文档

## 项目概述
djzhpcom 是一个基于点对点加密算法的Python库，提供安全的加密通信功能。

## 功能特性
- 点对点加密通信
- 安全的密钥交换机制
- 支持多种加密算法
- 高性能加密/解密操作

## 安装方法
```bash
# 本地开发安装
pip install -e .

# 发布后安装
pip install djzhpcom
```

## 快速开始
```python
import djzhpcom

# 初始化加密器
encryptor = djzhpcom.P2PEncryptor()

# 加密数据
encrypted = encryptor.encrypt("Hello World")

# 解密数据
decrypted = encryptor.decrypt(encrypted)
```

## 开发计划
1. 实现基础加密算法
2. 添加密钥交换功能
3. 优化性能
4. 编写完整文档

## 贡献指南
欢迎提交Pull Request，请遵循PEP8编码规范。
pt-dev-utils 1.2.0
Internal utility package for PT backend developers
Requires Python: >=3.8

# 🚀 pt_dev_utils
        
        [![PyPI version](https://img.shields.io/pypi/v/pt-dev-utils.svg)](https://pypi.org/project/pt-dev-utils/)
        [![Python](https://img.shields.io/pypi/pyversions/pt-dev-utils.svg)](https://pypi.org/project/pt-dev-utils/)
        [![License](https://img.shields.io/badge/license-Internal%20Use%20Only-blue.svg)](https://github.com/smitjethwa/pt_dev_utility)
        
        **pt_dev_utils** is a lightweight internal Python utility package crafted to streamline backend development in the PT system. It includes modular, reusable functions that help keep your codebase **clean**, **efficient**, and **DRY**.
        
        > 🔧 Built for internal use — optimized for speed, clarity, and team productivity.
        
        ---
        
        ## ✨ Features
        
        - 📂 **File Utilities**: Standardized file operations (read, write, path handling)
        - 📋 **Validation Functions**: Common data validators for backend pipelines
        - 💡 **Minimal Dependencies**: Designed to stay lean and fast
        
        ---
        
        ## 📦 Installation
        
        Install from PyPI using pip:
        
        ```bash
        pip install pt-dev-utils
        ```
        
        ---
        
        ## ✅ Example Usage
        
        ```python
        from pt_dev_utils import load_csv_as_records, read_csv_as_dict_list
        
        records = load_csv_as_records('data/sample.csv')
        print(records)
        # [('John', 25, 'Engineer'), ('Jane', 30, 'Manager')]
        
        # Read all columns with default headers
        data = read_csv_as_dict_list('data.csv')
        
        # Read with selected columns
        data = read_csv_as_dict_list(
                'data.csv',
                selected_columns=['name', 'age']
            )
        
        
        # Read with custom headers
        data = read_csv_as_dict_list(
                'data.csv',
                custom_headers=['name', 'age', 'city']
            )
        
        ```
        ---
        
        
        ## 📚 Documentation
        
        📖 [Read full documentation](https://pt-dev-utils.web.app)  
        📦 [View on PyPI](https://pypi.org/project/pt-dev-utils/)  
        📂 [GitHub Repository](https://github.com/smitjethwa/pt_dev_utility)
        
        ---
        
        ## 🧾 Changelog
        
        ### v1.1.8
        - Added publishable docs
        - Minor bug fixes
        
        ---
        
        ## 🛠 Contributing
        
        This package is primarily maintained for internal use. For suggestions or bug reports, please open an issue on the [GitHub repo](https://github.com/smitjethwa/pt_dev_utility/issues).
        
        ---
        
        ## 🔐 License
        
        **Internal Use Only** – All rights reserved © PT System.
habimapper 0.0.1a0
Interface for predicting and mapping benthic habitat (substrates) from any side-scan sonar mosaic.
Requires Python: <3.13
Keywords: pingmapper, sonar, ecology, remotesensing, sidescan, sidescan-sonar, aquatic, humminbird, lowrance, gis, oceanography, limnology

# HabiMapper
Interface for predicting and mapping benthic habitat (substrates) from any side-scan sonar mosaic.
mcp-gusantong-data 0.3.0
Add your description here
Requires Python: >=3.13

# Quick Start

### 1、进入到魔塔社区 
https://www.modelscope.cn/

#### 搜索: 股三通

#### 点击服务详情 进行部署

### 2、下载Cherry Studio客户端

#### 点击MCP设置-添加服务

##### 例如：
```JSON
{
  "mcpServers": {
    "mcp-gusantong-data": {
      "type": "sse",
      "url": "服务地址"
    }
  }
}
```
shangan 0.1.1
kaogong cli tool
Keywords: python, kaogong, shangan


# 上岸(ShangAn)-命令行考公刷题工具
## 简介
上岸(ShangAn)是一个用于刷考公题的命令行工具。它通过向指定的后端服务发送请求，获取随机的选择题，并允许用户在命令行中输入答案进行答题。该工具可以帮助考公的用户方便地进行刷题练习。
## 功能特性
- 从后端服务获取随机选择题。
- 支持自定义后端服务的根地址。
## 安装与运行
环境要求
- Python 3.x
- pip

运行步骤
1. pip安装```shangan```
```
pip install shangan
```
2. 运行
```
shangan
```
oracle11g-mcp-server 1.0.6
Model Context Protocol server to access oracle, supporting Oracle 11g and above.
Requires Python: >=3.12

# oracle11g-mcp-server
Model Context Protocol server to access oracle, supporting Oracle 11g and above.


## Quickstart

add this to your cursor `mcp.json` config files:

```json
{
  "mcpServers": {
    "oracle11g-mcp-server": {
      "command": "uvx",
      "args": [
        "oracle11g-mcp-server"
      ],
      "env": {
        "ORACLE_CONNECTION_STRING": "username/password@hostname:password/service_name",
        "LIB_DIR": "D:\\tools\\instantclient19.26.0.0.0dbru\\instantclient_19_26"
        "DQL_LIMITS_ROWS": "1000"
      }
    }
  }
}
```

### Prerequisites

- UV (pacakge manager)
- Python 3.12+
- Cursor
- Oracle Client


###
uv run python -m build

uv run twine upload --repository pypi dist/*