1,455 posts tagged “datasette”
Datasette is an open source tool for exploring and publishing data.
2020
Weeknotes: incremental improvements
I’ve been writing my talk for PyCon Argentina this week, which has proved surprisingly time consuming. I hope to have that wrapped up soon—I’m pre-recording it, which it turns out is much more work than preparing a talk to stream live.
[... 630 words]OCTO Speaker Series: Simon Willison—Personal Data Warehouses: Reclaiming Your Data. I’m giving a talk in the GitHub OCTO (Office of the CTO) speaker series about Datasette and my Dogsheep personal analytics project. You can register for free here—the stream will be on Thursday November 12, 2020 at 8:30am PST (4:30pm GMT).
Dogsheep: Personal analytics with Datasette. The second edition of my new Datasette Weekly newsletter, talks about Dogsheep, Dogsheep Beta, Datasette 1.0 and features datasette-cluster-map as the plugin of the week.
Weeknotes: evernote-to-sqlite, Datasette Weekly, scrapers, csv-diff, sqlite-utils
This week I built evernote-to-sqlite (see Building an Evernote to SQLite exporter), launched the Datasette Weekly newsletter, worked on some scrapers and pushed out some small improvements to several other projects.
Building an Evernote to SQLite exporter
I’ve been using Evernote for over a decade, and I’ve long wanted to export my data from it so I can do interesting things with it.
[... 1,879 words]evernote-to-sqlite (via) The latest tool in my Dogsheep series of utilities for personal analytics: evernote-to-sqlite takes Evernote note exports en their ENEX XML format and loads them into a SQLite database. Embedded images are loaded into a BLOB column and the output of their cloud-based OCR system is added to a full-text search index. Notes have a latitude and longitude which means you can visualize your notes on a map using Datasette and datasette-cluster-map.
Datasette Weekly: Datasette 0.50, git scraping, extracting columns (via) The first edition of the new Datasette Weekly newsletter—covering Datasette 0.50, Git scraping, extracting columns with sqlite-utils and featuring datasette-graphql as the first “plugin of the week”
Datasette Weekly (via) I’m trying something new: I’ve decided to start an email newsletter called the Datasette Weekly (I’m already worried I’ll regret that weekly promise) which will share news about Datasette and the Datasette ecosystem, plus tips and tricks for getting the most out of Datasette and SQLite.
Weeknotes: Mainly Datasette 0.50
Most of what I’ve been up to this week is covered in Datasette 0.50: The annotated release notes and Git scraping: track changes over time by scraping to a Git repository.
[... 196 words]Datasette 0.50: The annotated release notes
I released Datasette 0.50 this morning, with a new user-facing column actions menu feature and a way for plugins to make internal HTTP requests to consume the JSON API of their parent Datasette instance.
[... 792 words]Bedrock: The SQLitening (via) Back in March 2018 www.mozilla.org switched over to running on Django using SQLite! They’re using the same pattern I’ve been exploring with Datasette: their SQLite database is treated as a read-only cache by their frontend servers, and a new SQLite database is built by a separate process and fetched onto the frontend machines every five minutes by a scheduled task. They have a healthcheck page which shows the latest version of the database and when it was fetched, and even lets you download the 25MB SQLite database directly (I’ve been exploring it using Datasette).
Running Datasette on DigitalOcean App Platform (via) I spent some time with DigitalOcean’s new App Platform today, which is a Heroku-style PaaS that starts at $5/month. It looks like it could be a really good fit for Datasette. Disk is ephemeral, but if you’re publishing read-only data that doesn’t matter since you can build the SQLite database as part of the deployment and bundle it up in the Docker/Kubernetes container.
Potential new elevator pitch / tagline for Datasette: The best way to publish data online (via) One of the biggest challenges I’ve had with Datasette is compressing it into a single elevator pitch or tagline that helps answer the question “what does this software do?”—the project does a lot of different things, so finding the right angle for explaining it has proved really difficult. I’m workshopping a new tagline over on the Datasette discussion forum—feedback, suggestions and challenges very welcome!