422 items tagged “datasette”
Datasette is an open source tool for exploring and publishing data.
2019
socrata2sql (via) Phenomenal new open source tool released by Andrew Chavez at the Dallas Morning News. Socrata is the open data portal software used by huge numbers of local governments worldwide. socrata2sql is a tool that interacts with the standard Socrata API and can use it to suck down a dataset and save it as a SQLite, PostgreSQL, MySQL or other SQLAlchemy-supported database. I just tried this and it took a single command to create a SQLite database of every police arrest in Dallas in the past five years.
The Datasette Ecosystem. I’ve written a page of documentation that introduces the wider Datasette Ecosystem: csvs-to-sqlite, sqlite-utils, db-to-sqlite, dbf-to-sqlite, markdown-to-sqlite and a full collection of Datasette plugins.
Datasette 0.27 (via) The latest release of Datasette introduces an option to output tables and SQL query results as newline-delimited JSON—plus a new “datasette plugins” command for listing available plugins.
SQLite in 2018: A state of the art SQL dialect (via) In 2018 SQLite gained boolean literals, window functions, filter clauses, upserts and the ability to rename a column. If you want to try it out the latest official datasetteproject/datasette Docker image now bundles SQLite 3.26.
Usable Data (via) A Paul Ford essay from February 2016 in which he advocates for SQLite as the ideal format for sharing interesting data. I don’t know how I missed this one—it predates Datasette, but it perfectly captures the benefits that I’m trying to expose with the project. “In my dream universe, there would be a massive searchable torrent site filled with open, explorable data sets, in SQLite format, some with full text search indexes already in place.”
Exploring search relevance algorithms with SQLite
SQLite isn’t just a fast, high quality embedded database: it also incorporates a powerful full-text search engine in the form of the FTS4 and FTS5 extensions. You’ve probably used these a bunch of times already: many iOS, Android and desktop applications use SQLite under-the-hood and use it to implement their built-in search.
[... 1,390 words]2018
Fast Autocomplete Search for Your Website
Every website deserves a great search engine—but building a search engine can be a lot of work, and hosting it can quickly get expensive.
[... 4,159 words]Fast Autocomplete Search for Your Website (via) I wrote a tutorial for the 24 ways advent calendar on building fast autocomplete search for a website on top of Datasette and SQLite. I built the demo against 24 ways itself—I used wget to recursively fetch all 330 articles as HTML, then wrote code in a Jupyter notebook to extract the raw data from them (with BeautifulSoup) and load them into SQLite using my sqlite-utils Python library. I deployed the resulting database using Datasette, then wrote some vanilla JavaScript to implement autocomplete using fast SQL queries against the Datasette JSON API.
Building smaller Python Docker images
Changes are afoot at Zeit Now, my preferred hosting provider for the past year (see previous posts). They have announced Now 2.0, an intriguing new approach to providing auto-scaling immutable deployments. It’s built on top of lambdas, and comes with a whole host of new constraints: code needs to fit into a 5MB bundle for example (though it looks like this restriction will soon be relaxed a little—update November 19th you can now bump this up to 50MB).
[... 1,872 words]How to Instantly Publish Data to the Internet with Datasette
I spoke about my Datasette project at PyBay in August and they’ve just posted the video of my talk.
[... 58 words]The interesting ideas in Datasette
Datasette (previously) is my open source tool for exploring and publishing structured data. There are a lot of ideas embedded in Datasette. I realized that I haven’t put many of them into writing.
[... 2,857 words]Slides, notes and links from my Datasette talk at PyBay (via) I presented a session about Datasette at the PyBay conference in San Francisco this morning. I talked about the project itself and demonstrated ways of creating and publishing databases using csvs-to-sqlite, Datasette Publish and my new sqlite-utils library.
How to Instantly Publish Data to the Internet with Datasette
I presented a session about Datasette at the PyBay 2018 conference in San Francisco. I talked about the project itself and demonstrated ways of creating and publishing databases using csvs-to-sqlite, Datasette Publish and my new sqlite-utils library.
[... 2,043 words]Analyzing US Election Russian Facebook Ads
Two interesting data sources have emerged in the past few weeks concerning the Russian impact on the 2016 US elections.
[... 922 words]Analyzing US Election troll tweets with Datasette
FiveThirtyEight published nearly 3 million tweets from accounts associated with the Russian “Internet Research Agency”, based on research by Darren Linvill and Patrick Warren at at Clemson University.
[... 110 words]Datasette unit tests: monkeytype_call_traces (via) Faceted browse against every function call that occurs during the execution of Datasette’s test suite. I used Instagram’s MonkeyType tool to generate this, which can run Python code and generates a SQLite database of all of the traced calls. It’s intended to be used to automatically add mypy annotations to your code, but since it produces a SQLite database as a by-product I’ve started exploring the intermediary format using Datasette. Generating this was as easy as running “monkeytype run `which pytest`” in the Datasette root directory.
Datasette: publish_subcommand hook + default plugins mechanism, used for publish heroku/now (via) I just landed a new plugin hook to Datasette master: publish_subcommand, which lets you define new publisher subcommands for the “datasette publish” CLI tool in addition to Heroku and Zeit Now. As part of this I’ve refactored the heroku/now publisher implementations into two default plugins that ship as part of Datasette—I hope to use this pattern for other core functionality in the future.
XARs: An efficient system for self-contained executables (via) Really interesting new open source project from Facebook: a XAR is a new way of packaging up a Python executable complete with its dependencies and resources such that it can be distributed and executed elsewhere as a single file. It’s kind of like a Docker container without Docker—it uses the SquashFS compressed read-only filesystem. I can’t wait to try this out with Datasette.
The Now CDN (via) Huge announcement from Zeit Now today: all .now.sh deployments are now served through the Cloudflare CDN, which means they benefit from 150 worldwide CDN locations that obey HTTP caching headers. This is particularly relevant for Datasette, since it serves far-future cache headers by default and uses Cloudflare-compatible HTTP/2 push hints to accelerate 302 redirects. This means that both the “datasette publish now” CLI command and the Datasette Publish web app will now result in Cloudflare-accelerated deployments.
datasette-vega (via) I wrote a visualization plugin for Datasette that uses the excellent Vega “visualization grammar” library to provide bar, line and scatter charts configurable against any Datasette table or SQL query.
Query Parquet files in SQLite. Colin Dellow built a SQLite virtual table extension that lets you query Parquet files directly using SQL. Parquet is interesting because it’s a columnar format that dramatically reduces the space needed to store tables with lots of duplicate column data—most CSV files, for example. Colin reports being able to shrink a 1291 MB CSV file from the Canadian census to an equivalent Parquet file weighing just 42MB (3% of the original)—then running a complex query against the data in just 60ms. I’d love to see someone get this extension working with Datasette.
Datasette 0.23: CSV, SpatiaLite and more (via) The big new feature in 0.23 is CSV export: any Datasette table or query can now be exported as CSV, including the option to get all matching rows in one giant CSV file taking advantage of Python 3 async and Datasette’s efficient keyset pagination. Also in this release: improved support for SpatiaLite and various JSON API improvements including the ability to expand foreign key labels in JSON and CSV responses.
SpatiaLite — Datasette documentation. Datasette’s documentation now includes extensive coverage of the SpatiaLite extension for SQLite: how to install it, how to import latitude/longitude points, shapefiles and GeoJSON data into SpatiaLite tables, and how to run SQL queries against it that take advantage of spatial indexes. I’m learning SpatiaLite at the moment and filling out the documentation with each new trick I learn as I go—as Mark Pilgrim once taught me, the best way to learn a new technology is to write about it.
Datasette Facets
Datasette 0.22 is out with the most significant new feature I’ve added since the initial release: faceted browse.
[... 1,189 words]sqlitebiter. Similar to my csvs-to-sqlite tool, but sqlitebiter handles “CSV/Excel/HTML/JSON/LTSV/Markdown/SQLite/SSV/TSV/Google-Sheets”. Most interestingly, it works against HTML pages—run “sqlitebiter -v url ’https://en.wikipedia.org/wiki/Comparison_of_firewalls’” and it will scrape that Wikipedia page and create a SQLite table for each of the HTML tables it finds there.
Datasette: Full-text search. I wrote some documentation for Datasette’s full-text search feature, which detects tables which have been configured to use the SQLite FTS module and adds a search input box and support for a _search= querystring parameter.
Datasette: The Metropolitan Museum of Art (via) The Metropolitan Museum of Art publish a CSV file on GitHub with details of 464,360 items from their collection. I turned it into a searchable Datasette instance.
Notes from my appearance on the Changelog podcast
After I spoke at Zeit Day SF last weekend I sat down with Adam Stacoviak to record a 25 minute segment for episode 296 of the Changelog podcast, talking about Datasette. We covered a lot of ground!
[... 536 words]Datasette 0.21: New _shape=, new _size=, search within columns. Nothing earth-shattering here but it’s accumulated enough small improvements that it warranted a new release. You can now send ?_shape=array to get back a plain JSON array of results, ?_size=XXX|max to get back a specific number of rows from a table view and ?_search_COLUMN=text to run full-text search against a specific column.