I built a ChatGPT plugin to answer questions about data hosted in Datasette describes a new experimental Datasette plugin to enable people to query data hosted in a Datasette interface via ChatGPT, asking human language questions that are automatically converted to SQL and used to generate a readable response.

Using Datasette in GitHub Codespaces is a new tutorial showing how Datasette can be run in GitHub's free Codespaces browser-based development environments, using the new datasette-codespaces plugin.

Examples of sites built using Datasette now includes screenshots of Datasette deployments that illustrate a variety of problems that can be addressed using Datasette and its plugins.

Semantic search answers: Q&A against documentation with GPT3 + OpenAI embeddings shows how Datasette can be used to implement semantic search and build a system for answering questions against an existing corpus of text, using two new plugins: datasette-openai and datasette-faiss, and a new tool: openai-to-sqlite.

Datasette 0.64 is out, and includes a strong warning against running SpatiaLite in production without disabling arbitrary SQL queries, plus a new --setting default_allow_sql off setting to make it easier to do that. See Datasette 0.64, with a warning about SpatiaLite for more about this release. A new tutorial, Building a location to time zone API with SpatiaLite, describes how to safely use SpatiaLite and Datasette to build and deploy an API for looking up time zones for a latitude/longitude location.

Datasette 1.0a2: Upserts and finely grained permissions describes the new upsert API and much improved permissions capabilities introduced in the latest Datasette 1.0a2 alpha release.

Datasette’s new JSON write API: The first alpha of Datasette 1.0 introduces the new write API shipped in the first of the Datasette 1.0 alpha series of releases, including detailed descriptions of two demos that show how the API can be used.

Datasette 0.63 is out. Here are the annotated release notes.

Exploring the training data behind Stable Diffusion describes the process of building and deploying a 4GB searchable SQLite database using Datasette, starting with Parquet data that was used to train the Stable Diffusion image generation model. See also Exploring 12 Million of the 2.3 Billion Images Used to Train Stable Diffusion’s Image Generator.

Analyzing ScotRail audio announcements with Datasette—from prototype to production provides a detailed walk-through of the process of constructing an initial rapid prototype using Datasette Lite, extending it with a custom plugin and then deploying it as a full Datasette instance using GitHub Actions and Vercel.

Datasette 0.62 introduces compatibility with Pyodide for Datasette Lite, and incorporates a number of bug fixes, plugin hook upgrades and other improvements.

New tutorial and accompanying ten minute video: Cleaning data with sqlite-utils and Datasette.

s3-ocr is a new tool which can run OCR (via Amazon Textract) against every PDF file in an S3 bucket and write the results to a searchable SQLite database, ready to use with Datasette. Read more about it in s3-ocr: Extract text from PDF files stored in an S3 bucket.

Datasette Lite is a new way to run Datasette: entirely in your browser, thanks to the Pyodide project which provides a full Python environment compiled to WebAssembly. You can use it to explore any SQLite database file hosted on a CORS-enabled static hosting provider, which includes GitHub and GitHub Pages. Read more about this project in Datasette Lite: a server-side Python web application running in a browser.

Datasette for geospatial analysis describes how Datasette can be used in conjunction with SpatiaLite to work with geospatial data, including details of several geospatial plugins and tools from the Datasette ecosystem.

• Examples in the CLI documentation can now all be copied and pasted without needing to remove a leading $. (#551)
• Documentation now covers Setting up shell completion for bash and zsh. (#552)

• New experimental sqlite-utils tui interface for interactively building command-line invocations, powered by Trogon. This requires an optional dependency, installed using sqlite-utils install trogon. There is a screenshot in the documentation. (#545)
• sqlite-utils analyze-tables command (documentation) now has a --common-limit 20 option for changing the number of common/least-common values shown for each column. (#544)
• sqlite-utils analyze-tables --no-most and --no-least options for disabling calculation of most-common and least-common values.
• If a column contains only null values, analyze-tables will no longer attempt to calculate the most common and least common values for that column. (#547)
• Calling sqlite-utils analyze-tables with non-existent columns in the -c/--column option now results in an error message. (#548)
• The table.analyze_column() method (documented here) now accepts most_common=False and least_common=False options for disabling calculation of those values.

• Dropped support for Python 3.6. Tests now ensure compatibility with Python 3.11. (#517)
• Automatically locates the SpatiaLite extension on Apple Silicon. Thanks, Chris Amico. (#536)
• New --raw-lines option for the sqlite-utils query and sqlite-utils memory commands, which outputs just the raw value of the first column of evy row. (#539)
• Fixed a bug where table.upsert_all() failed if the not_null= option was passed. (#538)
• Fixed a ResourceWarning when using sqlite-utils insert. (#534)
• Now shows a more detailed error message when sqlite-utils insert is called with invalid JSON. (#532)
• table.convert(..., skip_false=False) and sqlite-utils convert --no-skip-false options, for avoiding a misfeature where the convert() mechanism skips rows in the database with a falsey value for the specified column. Fixing this by default would be a backwards-incompatible change and is under consideration for a 4.0 release in the future. (#527)
• Tables can now be created with self-referential foreign keys. Thanks, Scott Perry. (#537)
• sqlite-utils transform no longer breaks if a table defines default values for columns. Thanks, Kenny Song. (#509)
• Fixed a bug where repeated calls to table.transform() did not work correctly. Thanks, Martin Carpenter. (#525)
• Improved error message if rows_from_file() is passed a non-binary-mode file-like object. (#520)

• New s3-credentials delete-objects command (docs) for deleting one or more keys from the specified bucket. #83

• New openai-to-sqlite query data.db SQL command for executing SQL queries against a database with access to custom OpenAI SQL functions. #11
• New chatgpt(prompt) and chatgpt(prompt, system_prompt) SQL functions for use with openai-to-sqlite query.

• Added pip and setuptools as explicit dependencies. This fixes a bug where Datasette could not be installed using Rye. (#2065)

• New --omit-background option to the shot command to optionally create transparent PNGs. Thanks, Ben Welsh. #108
• Fixed bug that caused shot-scraper to fail to take screenshots on Windows. Thanks, Omer Rosenbaum. #104
• New --silent option for the shot, multi, pdf and html commands, to disable the default console output. #107

• Fix for "You did not supply a value for binding parameter" error. #4

• Fixed an error in the checkins_detail view. #15

• :param parameters in SQL queries are now supported. #3

• Initial release. Install this plugin to expose the first database in your Datasette instance as a ChatGPT plugin, provided you have preview access to that feature. #1