sqlite-utils
litestream
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sqlite-utils | litestream | |
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35 | 165 | |
1,498 | 9,964 | |
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8.4 | 7.5 | |
16 days ago | 9 days ago | |
Python | Go | |
Apache License 2.0 | Apache License 2.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
sqlite-utils
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Ask HN: High quality Python scripts or small libraries to learn from
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!
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Why you should probably be using SQLite
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.
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Welcome to Datasette Cloud
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...
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SQLite Functions for Working with JSON
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
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Show HN: Trogon – An automatic TUI for command line apps
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...
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I'm sure I'm being stupid.. Copying data from an API and making a database
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.
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Just: A Command Runner
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
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Ask HN: What Do You Use for a Personal Database
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...
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The Perfect Commit
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.
litestream
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Ask HN: SQLite in Production?
I have not, but I keep meaning to collate everything I've learned into a set of useful defaults just to remind myself what settings I should be enabling and why.
Regarding Litestream, I learned pretty much all I know from their documentation: https://litestream.io/
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How (and why) to run SQLite in production
This presentation is focused on the use-case of vertically scaling a single server and driving everything through that app server, which is running SQLite embedded within your application process.
This is the sweet-spot for SQLite applications, but there have been explorations and advances to running SQLite across a network of app servers. LiteFS (https://fly.io/docs/litefs/), the sibling to Litestream for backups (https://litestream.io), is aimed at precisely this use-case. Similarly, Turso (https://turso.tech) is a new-ish managed database company for running SQLite in a more traditional client-server distribution.
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SQLite3 Replication: A Wizard's Guide🧙🏽
This post intends to help you setup replication for SQLite using Litestream.
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Ask HN: Time travel" into a SQLite database using the WAL files?
I've been messing around with litestream. It is so cool. And, I either found a bug in the -timestamp switch or don't understand it correctly.
What I want to do is time travel into my sqlite database. I'm trying to do some forensics on why my web service returned the wrong data during a production event. Unfortunately, after the event, someone deleted records from the database and I'm unsure what the data looked like and am having trouble recreating the production issue.
Litestream has this great switch: -timestamp. If you use it (AFAICT) you can time travel into your database and go back to the database state at that moment. However, it does not seem to work as I expect it to:
https://github.com/benbjohnson/litestream/issues/564
I have the entirety of the sqlite database from the production event as well. Is there a way I could cycle through the WAL files and restore the database to the point in time before the records I need were deleted?
Will someone take sqlite and compile it into the browser using WASM so I can drag a sqlite database and WAL files into it and then using a timeline slider see all the states of the database over time? :)
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Ask HN: Are you using SQLite and Litestream in production?
We're using SQLite in production very heavily with millions of databases and fairly high operations throughput.
But we did run into some scariness around trying to use Litestream that put me off it for the time being. Litestream is really cool but it is also very much a cool hack and the risk of database corruption issues feels very real.
The scariness I ran into was related to this issue https://github.com/benbjohnson/litestream/issues/510
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Pocketbase: Open-source back end in 1 file
Litestream is a library that allows you to easily create backups. You can probably just do analytic queries on the backup data and reduce load on your server.
https://litestream.io/
- Litestream – Disaster recovery and continuous replication for SQLite
- Litestream: Replicated SQLite with no main and little cost
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Why you should probably be using SQLite
One possible strategy is to have one directory/file per customer which is one SQLite file. But then as the user logs in, you have to look up first what database they should be connected to.
OR somehow derive it from the user ID/username. Keeping all the customer databases in a single directory/disk and then constantly "lite streaming" to S3.
Because each user is isolated, they'll be writing to their own database. But migrations would be a pain. They will have to be rolled out to each database separately.
One upside is, you can give users the ability to take their data with them, any time. It is just a single file.
[0]. https://litestream.io/
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Monitor your Websites and Apps using Uptime Kuma
Upstream Kuma uses a local SQLite database to store account data, configuration for services to monitor, notification settings, and more. To make sure that our data is available across redeploys, we will bundle Uptime Kuma with Litestream, a project that implements streaming replication for SQLite databases to a remote object storage provider. Effectively, this allows us to treat the local SQLite database as if it were securely stored in a remote database.
What are some alternatives?
sqlmodel - SQL databases in Python, designed for simplicity, compatibility, and robustness.
rqlite - The lightweight, distributed relational database built on SQLite.
sqliteviz - Instant offline SQL-powered data visualisation in your browser
pocketbase - Open Source realtime backend in 1 file
ImportExcel - PowerShell module to import/export Excel spreadsheets, without Excel
realtime - Broadcast, Presence, and Postgres Changes via WebSockets
octosql - OctoSQL is a query tool that allows you to join, analyse and transform data from multiple databases and file formats using SQL.
k8s-mediaserver-operator - Repository for k8s Mediaserver Operator project
q - q - Run SQL directly on delimited files and multi-file sqlite databases
sqlcipher - SQLCipher is a standalone fork of SQLite that adds 256 bit AES encryption of database files and other security features.
Scoop - A command-line installer for Windows.
litefs - FUSE-based file system for replicating SQLite databases across a cluster of machines