✨ 概述

pyomop 是你的 OMOP 瑞士军刀🔧，用于使用 SQLAlchemy（ORM）处理符合 OHDSI OMOP 通用数据模型（CDM）v5.4 或 v6 的数据库。它支持将查询结果转换为 pandas DataFrame 用于机器学习流水线，并提供处理 OMOP 词汇的工具。表定义基于 omop-cdm 库。Pyomop 旨在成为一个轻量级、易于使用的库，供研究人员和开发者在使用 OMOP CDM 数据库进行实验和测试时使用。它既可以作为命令行工具使用，也可以作为代码中的导入库使用。

• 支持 SQLite、PostgreSQL 和 MySQL。CDM 和词汇表在同一个模式中创建。（详情见下文使用情况）
• 基于LLM的自然语言查询，通过langchain进行。使用情况。
• 🔥 FHIR到OMOP转换工具。（详情请见下文使用）
• 执行QueryLibrary。（详情见下文用法）

如果你觉得这个项目有用，请务必⭐️帮忙！

安装

稳定版发布：

开发版本：

LLM 支持：

✨ 请参阅此笔记本或脚本以获取示例。👇推荐用于高级使用。

Docker

pyomop: OMOP Swiss Army Knife 🔧

✨ Overview

pyomop is your OMOP Swiss Army Knife 🔧 for working with OHDSI OMOP Common Data Model (CDM) v5.4 or v6 compliant databases using SQLAlchemy as the ORM. It supports converting query results to pandas DataFrames for machine learning pipelines and provides utilities for working with OMOP vocabularies. Table definitions are based on the omop-cdm library. Pyomop is designed to be a lightweight, easy-to-use library for researchers and developers experimenting and testing with OMOP CDM databases. It can be used both as a commandline tool and as an imported library in your code.

• Supports SQLite, PostgreSQL, and MySQL. CDM and Vocab tables are created in the same schema. (See usage below for more details)
• LLM-based natural language queries via langchain. Usage.
• 🔥 FHIR to OMOP conversion utilities. (See usage below for more details)
• Execute QueryLibrary. (See usage below for more details)

Please ⭐️ If you find this project useful!

Installation

Stable release:

pip install pyomop

Development version:

git clone https://github.com/dermatologist/pyomop.git
cd pyomop
pip install -e .

LLM support:

pip install pyomop[llm]

✨ See this notebook or script for examples. 👇 MCP SERVER is recommended for advanced usage.

Docker