This website uses cookies, pixel tags, and similar technologies (“Cookies”) for the purpose of enabling site operations and for performance, personalisation, and marketing purposes. We use our own Cookies and some from third parties. Only essential Cookies are used by default. By clicking “Accept All” you consent to the use of non-essential Cookies (i.e., functional, analytics, and marketing Cookies) and the related processing of personal data. You can manage your consent preferences by clicking Manage Preferences. You may withdraw a consent at any time by using the link “Cookie Preferences” in the footer of our website.
Our Privacy Notice is accessible here. To learn more about the use of Cookies on our website, please view our Cookie Notice.
A couple weeks back I spoke at the PostgreSQL London meetup (slides below), hosted at the Deliveroo offices in London. There were a load of other great talks in the night, and it’s always good to catchup with other PostgreSQL users in London.
Here are the slides from my talk on SQLpy. Without rehashing the whole talk, I just want to summarise a couple of things based off the questions I received at the end.
SQLpy is intended to be a very lightweight wrapper around your already implemented Python database interface library.
SQLpy is meant to help you organise your SQL queries and to stop including SQL strings in your Python source code.
SQLpy is guaranteed to run the exact code you write, compared to an ORM which will “compile” your code and generate a query.
Because SQLpy does so little, you’re free to use any design pattern you like to work with your data.
