Cover art for podcast The Python Data & Science Podcast.__init__

The Python Data & Science Podcast.__init__

100 EpisodesProduced by Tobias MaceyWebsite

The podcast about how the Python language powers work in data and science

1:13:13

Keep Your Analytics Lint Free With SQLFluff

Summary

The growth of analytics has accelerated the use of SQL as a first class language. It has also grown the amount of collaboration involved in writing and maintaining SQL queries. With collaboration comes the inevitable variation in how queries are written, both structurally and stylistically which can lead to a significant amount of wasted time and energy during code review and employee onboarding. Alan Cruickshank was feeling the pain of this wasted effort first-hand which led him down the path of creating SQLFluff as a linter and formatter to enforce consistency and find bugs in the SQL code that he and his team were working with. In this episode he shares the story of how SQLFluff evolved from a simple hackathon project to an open source linter that is used across a range of companies and fosters a growing community of users and contributors. He explains how it has grown to support multiple dialects of SQL, as well as integrating with projects like DBT to handle templated queries. This is a great conversation about the long detours that are sometimes necessary to reach your original destination and the powerful impact that good tooling can have on team productivity.

Announcements
  • Hello and welcome to Podcast.__init__, the podcast about Python and the people who make it great.
  • When you’re ready to launch your next app or want to try a project you hear about on the show, you’ll need somewhere to deploy it, so take a look at our friends over at Linode. With the launch of their managed Kubernetes platform it’s easy to get started with the next generation of deployment and scaling, powered by the battle tested Linode platform, including simple pricing, node balancers, 40Gbit networking, dedicated CPU and GPU instances, and worldwide data centers. Go to pythonpodcast.com/linode and get a $100 credit to try out a Kubernetes cluster of your own. And don’t forget to thank them for their continued support of this show!
  • We’ve all been asked to help with an ad-hoc request for data by the sales and marketing team. Then it becomes a critical report that they need updated every week or every day. Then what do you do? Send a CSV via email? Write some Python scripts to automate it? But what about incremental sync, API quotas, error handling, and all of the other details that eat up your time? Today, there is a better way. With Census, just write SQL or plug in your dbt models and start syncing your cloud warehouse to SaaS applications like Salesforce, Marketo, Hubspot, and many more. Go to pythonpodcast.com/census today to get a free 14-day trial.
  • Your host as usual is Tobias Macey and today I’m interviewing Alan Cruickshank about SQLFluff, a dialect-flexible and configurable SQL linter
Interview
  • Introductions
  • How did you get introduced to Python?
  • Can you describe what SQLFluff is and the story behind it?
  • SQL is one of the oldest programming languages that is still in regular use. Why do you think that there are so few linters for it?
  • Who are the target users of SQLFluff and how do those personas influence the design and user experience of the project?
  • What are some of the characteristics of SQL and how it is used that contribute to readability/comprehension challenges?
    • What are some of the additional difficulties that are introduced by templating in the queries?
  • How is SQLFluff implemented?
    • How have the goals and design of the project changed since you first began working on it?
  • How do you handle support of varying SQL dialects without undue maintenance burdens?
  • What are some of the stylistic elements and strategies for making SQL code more maintainable?
  • What are some strategies for making queries self-documenting?
    • What are some signs that you should document it anyway?
  • What are some of the kinds of bugs that you are able to identify with SQLFluff?
  • What are some of the resources/references that you relied on for identifying useful linting rules?
  • What are some methods for measuring code quality in SQL?
  • What are the most interesting, innovative, or unexpected ways that you have seen SQLFluff used?
  • What are the most interesting, unexpected, or challenging lessons that you have learned while working on SQLFluff?
  • When is SQLFluff the wrong choice?
  • What do you have planned for the future of SQLFluff?
Keep In Touch Picks Closing Announcements
  • Thank you for listening! Don’t forget to check out our other show, the Data Engineering Podcast for the latest on modern data management.
  • Visit the site to subscribe to the show, sign up for the mailing list, and read the show notes.
  • If you’ve learned something or tried out a project from the show then tell us about it! Email hosts@podcastinit.com) with your story.
  • To help other people find the show please leave a review on iTunes and tell your friends and co-workers
  • Join the community in the new Zulip chat workspace at pythonpodcast.com/chat
Links

The intro and outro music is from Requiem for a Fish The Freak Fandango Orchestra / CC BY-SA

Educational emoji reaction

Educational

Interesting emoji reaction

Interesting

Funny emoji reaction

Funny

Agree emoji reaction

Agree

Love emoji reaction

Love

Wow emoji reaction

Wow

Listen to The Python Data & Science Podcast.__init__

RadioPublic

A free podcast app for iPhone and Android

  • User-created playlists and collections
  • Download episodes while on WiFi to listen without using mobile data
  • Stream podcast episodes without waiting for a download
  • Queue episodes to create a personal continuous playlist
RadioPublic on iOS and Android
Or by RSS
RSS feed
https://www.pythonpodcast.com/feed/mp3/

Connect with listeners

Podcasters use the RadioPublic listener relationship platform to build lasting connections with fans

Yes, let's begin connecting
Browser window

Find new listeners

  • A dedicated website for your podcast
  • Web embed players designed to convert visitors to listeners in the RadioPublic apps for iPhone and Android
Clicking mouse cursor

Understand your audience

  • Capture listener activity with affinity scores
  • Measure your promotional campaigns and integrate with Google and Facebook analytics
Graph of increasing value

Engage your fanbase

  • Deliver timely Calls To Action, including email acquistion for your mailing list
  • Share exactly the right moment in an episode via text, email, and social media
Icon of cellphone with money

Make money

  • Tip and transfer funds directly to podcastsers
  • Earn money for qualified plays in the RadioPublic apps with Paid Listens