499 posts tagged “projects”
Posts about projects I have worked on.
2019
twitter-to-sqlite 0.6, with track and follow. I shipped a new release of my twitter-to-sqlite command-line tool this evening. It now includes experimental features for subscribing to the Twitter streaming API: you can track keywords or follow users and matching Tweets will be written to a SQLite database in real-time as they come in through the API. Since Datasette supports mutable databases now you can run Datasette against the database and run queries against the tweets as they are inserted into the tables.
Weeknotes: Design thinking for journalists, genome-to-sqlite, datasette-atom
I haven’t had much time for code this week: we’ve had a full five day workshop at JSK with Tran Ha (a JSK alumni) learning how to apply Design Thinking to our fellowship projects and generally to challenges facing journalism.
[... 870 words]genome-to-sqlite. I just found out 23andMe let you export your genome as a zipped TSV file, so I wrote a little Python command-line tool to import it into a SQLite database.
Weeknotes: ONA19, twitter-to-sqlite, datasette-rure
I’ve decided to start writing weeknotes for the duration of my JSK fellowship. Here goes!
[... 919 words]sqlite-utils 1.11. Amjith Ramanujam contributed an excellent new feature to sqlite-utils, which I’ve now released as part of version 1.11. Previously you could enable SQLite full-text-search on a table using the .enable_fts() method (or the “sqlite-utils enable-fts” CLI command) but it wouldn’t reflect future changes to the table—you had to use populate_fts() any time you inserted new records. Thanks to Amjith you can now pass create_triggers=True (or --create-triggers) to cause sqlite-utils to automatically add triggers that keeps the FTS index up-to-date any time a row is inserted, updated or deleted from the table.
Working with many-to-many relationships in sqlite-utils (via) I just released sqlite-utils 1.9 with syntactic sugar support for creating many-to-many relationships for records stored in SQLite databases.
Single sign-on against GitHub using ASGI middleware
I released Datasette 0.29 last weekend, the first version of Datasette to be built on top of ASGI (discussed previously in Porting Datasette to ASGI, and Turtles all the way down).
[... 1,612 words]datasette-cors (via) My other Datasette ASGI plugin: this one wraps my asgi-cors project and lets you configure CORS access from a list of domains (or a set of domain wildcards) so you can make JavaScript calls to a Datasette instance from a specific set of other hosts.
datasette-auth-github (via) My first big ASGI plugin for Datasette: datasette-auth-github adds the ability to require users to authenticate against the GitHub OAuth API. You can whitelist specific users, or you can restrict access to members of specific GitHub organizations or teams. While it’s structured as a Datasette plugin it also includes ASGI middleware which can be applied to any ASGI application.
Datasette 0.29 (via) I shipped Datasette 0.29! • ASGI all the way down! Plus a new asgi_wrapper plugin hook letting plugins do all kinds of powerful new things • New mechanism for secret plugin configuration options • Facet by date • ?_through= for joins through m2m tables. Much more.
db-to-sqlite 1.0 release. I’ve released version 1.0 of my db-to-sqlite tool, which lets you create a SQLite database copy of any database supported by SQLAlchemy (I’ve tested it against MySQL and PostgreSQL). The tool has a bunch of new features: you can use --redact to redact specific columns, specify --table multiple times to copy a subset of tables, and the --all option now efficiently adds all foreign keys at the end of the import. The project now has unit tests which run against MySQL and PostgreSQL in Travis CI. Also included in the README: a shell one-liner for creating a local SQLite copy of a remote Heroku Postgres database based on extracting the connection string from a Heroku config environment variable.
Porting Datasette to ASGI, and Turtles all the way down
This evening I finally closed a Datasette issue that I opened more than 13 months ago: #272: Port Datasette to ASGI. A few notes on why this is such an important step for the project.
[... 1,082 words]json-flatten. A little Python library I wrote that attempts to flatten a JSON object into a set of key/value pairs suitable for transmitting in a query string or using to construct an HTML form. I first wrote this back in 2015 as a Gist—I’ve reconstructed the Gist commit history in a new repository and shipped it to PyPI.
Convert Locations.kml (pulled from an iPhone backup) to SQLite. I’ve been playing around with data from my iPhone using the iPhone Backup Extractor app and one of the things it exports for you is a Locations.kml file full of location history data. I wrote a tiny script using Python’s ElementTree XMLPullParser to efficiently iterate through the Placemarks and yield them as dictionaries, which I then batch-inserted into sqlite-utils to create a SQLite database.
paginate-json (via) I released a fun tiny utility: paginate-json, which knows how to paginate through JSON APIs that use the HTTP Link header for pagination. I built it so I could pull data from the GitHub API and pipe it directly into SQLite via sqlite-utils.
datasette-render-binary (via) Yet another tiny Datasette plugin. This one attempts to render binary data in a slightly more readable fashion—it shows ASCII characters as they are, and shows all other data as monospace octets. Useful as a tool for exploring new unfamiliar databases as it makes it easier to spot if a binary column may contain a decipherable binary format.
datasette-bplist (via) It turns out an OS X laptop is positively crammed with SQLite databases, and many of them contain values that are data structures encoded using Apple’s binary plist format. datasette-bplist is my new plugin to help explore those files: it provides a display hook for rendering their contents, and a custom bplist_to_json() SQL function which can be used to extract and query information that is embedded in those values. The README includes tips on how to pull interesting EXIF data out of the SQLite database that sits behind Apple Photos.
datasette-jq (via) I released another tiny Datasette plugin: datasette-jq registers a single custom SQL function, jq(), which lets you execute the jq expression language against a JSON column (or literal value) to filter and transform the JSON data. The README includes a link to a live demo—it’s a neat way to play with the jq micro-language.
sqlite-utils 1.0. I just released sqlite-utils 1.0, with a couple of handy new features over 0.14: it can now automatically add columns to a database table if you attempt to insert data which doesn’t quite fit (using alter=True in the Python API or the --alter option to the “sqlite-utils insert” command). It also has the ability to output nested JSON column values on the command-line using the new --json-cols option. This is the first project I’ve marked as a 1.0 release in a very long time—I’ll be sticking to semver for this project from now on, bumping the major version only in the case of a backwards incompatible change.
Datasette 0.28—and why master should always be releasable
It’s been quite a while since the last substantial release of Datasette. Datasette 0.27 came out all the way back in January.
[... 1,326 words]asgi-cors (via) I’ve been trying out the new ASGI 3.0 spec and I just released my first piece of ASGI middleware: asgi-cors, which lets you wrap an ASGI application with Access-Control-Allow-Origin CORS headers (either “*” or dynamic headers based on an origin whitelist).
Hello world for ASGI running on Glitch (via) I’m continuing to experiment with Python 3 running on Glitch. This evening on my walk home from work I built this “hello world” demo on my phone, partly to see if Glitch was a workable mobile development environment—it passed with flying colours! The demo is a simple hello world implemented using the new ASGI 3.0 specification, running on the daphne reference server. Click the “via” link for my accompanying thread on Twitter, which includes a short screencast (also recorded on my phone) showing Glitch in action.
Running Datasette on Glitch
Update 28th May 2025: Sadly Glitch is shutting down user project hosting, so this tutorial is no longer relevant.
[... 1,020 words]csv-diff 0.3.1 (via) I released a minor update to my csv-diff CLI tool today which does a better job of displaying a human-readable representation of rows that have been added or removed from a file—previously they were represented as an ugly JSON dump. My script monitoring changes to the official list of trees in San Francisco has been running for a month now and has captured 23 commits!
Generating a commit log for San Francisco’s official list of trees
San Francisco has a neat open data portal (as do an increasingly large number of cities these days). For a few years my favourite file on there has been Street Tree List, a list of all 190,000 trees in the city maintained by the Department of Public Works.
[... 1,051 words]I commissioned an oil painting of Barbra Streisand’s cloned dogs
Last year, Barbra Streisand cloned her dog, Sammie.
[... 517 words]sqlite-utils: a Python library and CLI tool for building SQLite databases
sqlite-utils is a combination Python library and command-line tool I’ve been building over the past six months which aims to make creating new SQLite databases as quick and easy as possible.
[... 1,237 words]db-to-sqlite (via) I just released version 0.2 of a tiny CLI utility I’ve been working on. It builds on top of SQLAlchemy and lets you connect to any SQLAlchemy-supported database and convert the data from it to a local SQLite database file. The new --all option will mirror all available tables (including foreign key relationships), or you can use --sql to save the results of custom SQL queries.
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.
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.
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