datasette-app VS sqlite-utils

Hah, Softbank isn't the goal here!

I realized that Datasette is the first project of my entire career where if I was still working on it in 15 years time I wouldn't feel bored yet. There's just SO MUCH scope for interesting applications of the core idea.

As such, I want to work on it for decades. But it's lonely working on it alone (the community around it has been growing and is delightful, but it's not the same as having a full-time team.)

So the question I'm trying to answer is how to make the project financially sustainable in the long-run - not just for myself, but so I can pay for a team to work on it with me.

There are plenty of other examples of open source projects that have turned SaaS hosting into a sustainable business model - WordPress and GitLab are just two of the best examples. It feels like it's a reasonably well-trodden path.

Plus... I want people to be able to use my software. Currently to use Datasette as an individual you either have to "pip" or "brew" install it, or you can try the macOS Electron app - https://datasette.io/desktop - but I want newsrooms to be able to use it to collaborate on data. And most newsrooms aren't well equipped to configure a Linux server.

So I realized that a hosted SaaS version can solve two issues at once: it can help the audience I care about actually benefit from the value of the software so far, and it provides a reasonably realistic path to financial sustainability for the project as a whole.

And yeah, I'd also like to make a ton of money out of it myself too!

It would be nice if his stuff worked better, ironically. The Datasette app for Mac seems to be constantly stuck on loading (yes I have 0.2.2):

https://github.com/simonw/datasette-app/issues/139

Amd his screen capture library can't capture Canvas renderings:

https://simonwillison.net/2022/Mar/10/shot-scraper/

Lost two days at work on that.

Speaking of technology not working as expected.

I'd love to get the desktop app working on Linux and Windows.

I did manage to get a prototype working on Windows, despite having VERY little experience working on that platform: https://github.com/simonw/datasette-app/issues/71

The bit I'm stuck on is how to turn that prototype into an application with an installer that's signed so people can download and run it.

I have trouble answering this question myself, and I created it!

The problem I have is that it can be applied to too many different problems.

I personally have used it for the following (a truncated summary):

- Publishing data online to allow other people to explore it, for example https://scotrail.datasette.io and https://russian-ira-facebook-ads.datasettes.com/

- Building websites, by combining it with custom templates. https://datasette.io and https://www.niche-museums.com and https://til.simonwillison.net are three examples

- Building my own combined search engine over a bunch of different data. https://github-to-sqlite.dogsheep.net is this for my GitHub issues and commits and issue comments across 100+ projects

- Similarly, building a code search engine across multiple repos (partly to demonstrate how far you can go with custom plugins): https://ripgrep.datasette.io

- Any time I have a CSV file I open it in the Datasette Desktop macOS app first to start exploring it: https://datasette.io/desktop

- As a prototyping tool. It's the fastest way I know of to get from some data files (CSV or JSON) to a working JSON API - and a GraphQL API too using this plugin: https://datasette.io/plugins/datasette-graphql

- Messing around with geospatial data - here's a write-up of my favourite experiment with that so far: https://simonwillison.net/2021/Jan/24/drawing-shapes-spatial...

This is a bewilderingly wide array of things! And I keep on finding new problems I can apply it to:

Of course, if all you have is a hammer, everything looks like a nail. But thanks to the plugin system (and the amazing flexibility of SQLite under the good) I can reshape my hammer into all sorts of interesting shapes!

I've been trying to capture some of this at https://datasette.io/for

This is one of my biggest marketing challenges for the project though. If someone asks you for an elevator pitch you need to do better than spending 15 minutes talking through a wide ranging bulleted list!

You can use my Datasette software to explore the database: https://datasette.io/desktop - that's the Mac version but you can run the underlying software on Windows too.

Then you can either run "pip install datasette" and "datasette healthkit.db" or you can install the Datasette Desktop app from https://datasette.io/desktop and use that to open the database file.

You may find my Datasette Desktop Mac application useful: it provides a read-only interface over SQLite and cdn oprn both SQLite files and CSV files: https://datasette.io/desktop

This is really interesting to see. I've been trying to solve a similar problem over the past few weeks - bundling up a Python web application as an installable Desktop app, in my case for https://datasette.io/desktop - so it's really interesting to see how they've approached the problem.

I ended up including a full copy of Python using https://github.com/indygreg/python-build-standalone - it looks like they've bundled Conda.

I wrote up detailed notes on how I solved the Python bundling problem in https://simonwillison.net/2021/Sep/8/datasette-desktop/#how-... and in https://til.simonwillison.net/electron/python-inside-electro...

I've been having a ton of fun building this. The code is all open source at https://github.com/simonw/datasette-app - it's my first time working with Electron and the biggest task was figuring out how to bundle Python inside an Electron app, which I wrote about in detail here: https://til.simonwillison.net/electron/python-inside-electron

https://github.com/simonw/sqlite-utils

So, his code might not be a good place to find best patterns (for ex, I don't think they are fully typed), but his repos are very pragmatic, and his development process is super insightful (well documented PRs for personal repos!). Best part, he blogs about every non-trivial update, so you get all the context!

Sounds like your problem is with SQLAlchemy, not with SQLite.

My https://sqlite-utils.datasette.io library might be a better fit for you. It's a much thinner abstraction than SQLAlchemy.

There are a few things you can do here.

SQLite is great at JSON - so I often dump JSON structures in a TEXT column and query them using https://www.sqlite.org/json1.html

I also have plugins for running jq() functions directly in SQL queries - https://datasette.io/plugins/datasette-jq and https://github.com/simonw/sqlite-utils-jq

I've been trying to drive the cost of turning semi-structured data into structured SQL queries down as much as possible with https://sqlite-utils.datasette.io - see this tutorial for more: https://datasette.io/tutorials/clean-data

This is also an area that I'm starting to explore with LLMs. I love the idea that you could take a bunch of messy data, tell Datasette Cloud "I want this imported into a table with this schema"... and it does that.

I have a prototype of this working now, I hope to turn it into an open source plugin (and Datasette Cloud feature) pretty soon. It's using this trick: https://til.simonwillison.net/gpt3/openai-python-functions-d...

I've baked a ton of different SQLite tricks - including things like full-text indexing support and advanced alter table methods - into my sqlite-utils CLI tool and Python library: https://sqlite-utils.datasette.io

My Datasette project provides tools for exploring, analyzing and publishing SQLite databases, plus ways to expose them via a JSON API: https://datasette.io

I've also written a ton of stuff about SQLite on my two blogs:

- https://simonwillison.net/tags/sqlite/

- https://til.simonwillison.net/sqlite

This is really fun. I have an experimental branch of my sqlite-utils CLI tool (which has dozens of sub-commands) running with this now and it really did only take 4 lines of code - I'm treating Trogon as an optional dependency because people using my package as a Python library rather than a CLI tool may not want the extra installed components:

https://github.com/simonw/sqlite-utils/commit/ec12b780d5dcd6...

There's an animated GIF demo of the result here: https://github.com/simonw/sqlite-utils/issues/545#issuecomme...

My project https://datasette.io/ is ideal for this kind of thing. You can use https://sqlite-utils.datasette.io/ to load JSON data into a SQLite database, then publish it with Datasette.

I've been using this for about six months now and I absolutely love it.

Make never stuck for me - I couldn't quite get it to fit inside my head.

Just has the exact set of features I want.

Here's one example of one of my Justfiles: https://github.com/simonw/sqlite-utils/blob/fc221f9b62ed8624... - documented here: https://sqlite-utils.datasette.io/en/stable/contributing.htm...

I also wrote about using Just with Django in this TIL: https://til.simonwillison.net/django/just-with-django

SQLite with the open source toolchain I've been building over the past five years:

https://datasette.io as the interface for running queries against (and visualizing) my data.

https://sqlite-utils.datasette.io/ as a set of tools for creating and modifying my databases (inserting JSON or CSV data, enabling full text search text)

https://dogsheep.github.io as a suite of tools for importing my personal data - see also this talk I gave about that project: https://simonwillison.net/2020/Nov/14/personal-data-warehous...

Here's an example: https://github.com/simonw/sqlite-utils/pull/468

> After identifying about 7 commits (with pretty basic/useless messages, and no PR link!), I then had to find the corresponding PRs based on timestamps, and search the PR history for PRs merged around those timestamps.

Not sure if this would save any time, but it is possible to search PRs by commit. For example, say git blame led me to this commit: https://github.com/simonw/sqlite-utils/commit/129141572f249e...

I could have found PR #373 via this search: https://github.com/simonw/sqlite-utils/pulls?q=bb16f52681b6d...

> I thus treat PRs as ephemeral

I think I see what you're saying but as others have pointed out, sometimes you want to add screenshots etc to the context, and you can't capture this kind of info in commit messages. So then you have two choices: issues or PRs.

> Then any review comments are preferably not addressed directly in the PR

I would think that sometimes you really do want to have a back and forth conversation in the PR, rather than just a "make this change" -> "ok done" type of feedback loop.

I view the PR as an decent place for all of this because it's basically a commit of commits, capturing the related changes/conversation/context all in a single place at the point of merge.