Today we released SQLFluff 1.0.0, the first stable release of SQLFluff.
- Does this mean there are no more bugs? No.
- Does this mean we're going to stop developing new features? No.
- Does this mean that this is a tool that is now broadly usable for many teams? Yes.
We've intentionally chosen to release 1.0.0 at a time of relative stability within SQLFluff and not at a time when new big structural changes are being made. This means that there's a good chance that this release is broadly usable. This also recognises that through the hard work of a huge number of contributors that we've built out this from a fringe tool, to something which gets over 500k downloads a month and over 4k stars on Github.
We've been lucky enough as a project to be supported by an excellent community of almost 100 different contributors and a core group of very dedicated maintainers. On top of that a few callouts by the wider industry have been hugely influential to the growth of the graph above:
- Back in 2020, we had the opportunity to launch SQLFluff to the dbt community at coalesce 2020. That was just as native dbt integration was approaching somewhat stable status, which has since been spun out into a separate package.
- One of the core maintainers Daniel Mateus Pires (@dmateusp), wrote an excellent piece for towardsdatascience, which caused the next big hike, especially in Github stars.
- SQLfluff was included in MegaLinter which exposes an even larger audience to sql linting.
- During June 2021 I talked about the story so far and why we need something like SQLFluff as an industry on the python podcast.
Beyond Github stars, looking at the download data we can see a pretty steady increase in download, but also in the diversity of different concurrent use cases. It does look like a few very heavy users dominate the downloads, but this is a sign that it's been integrated into the CI flows of major organisations.
So what now?
There's still a lot to do, and some more exciting things on the horizon. If you want to be part of this and join the team of contributors, come and hang out in our slack community or on our twitter account where people can help you get started. If you're a long time user, keep submitting bug reports and inputting on issues on Github.
If you've never used SQLFluff before, or are hesitant about starting to use it in your day to day work, now might be a good time to try it. We have guides on how to get started with the tool, and how to get started with rolling out to a team in our docs.