有的时候简单就是美，

For the work I do, where Jupyter running Python 3 notebooks with Pandas and SqlAlchemy is enough, I prefer to use the “pure Python” method, because the tools are well understood and well supported, and a tremendous amount of work has been done by the Python community to make the tools work well on Windows. And if I ever am working on a large enough data set that my laptop alone can’t handle it, using Docker to run my notebooks on cloud providers’ platforms is wonderfully easy.

That said, if you are coming into this just looking to use Python to tackle a data analysis or scientific computing problem and want to get started with minimal fuss, a distribution like Anaconda is without a doubt the fastest way to get started.

推荐SQLAlchemy给做传统数据库数据持久化

SQLAlchemy is the Python SQL toolkit and Object Relational Mapper (ORM) that gives application developers the full power and flexibility of SQL.

It provides a full suite of well known enterprise-level persistence patterns, designed for efficient and high-performing database access, adapted into a simple and Pythonic domain language.