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Show HN: Feels Like Paper

"Feels Like Paper!" is a series of prototypes about augmenting physical paper through AI. Various ML models, LLMs and a mixed reality headset are used to infuse physical paper and ink with properties of the digital world without compromising on their physical traits.

Show HN: TeaTime – distributed book library powered by SQLite, IPFS and GitHub

Recently there seem to be a surge in SQLite related projects. TeaTime is riding that wave...<p>A couple of years ago I was intrigued by phiresky's post[0] about querying SQLite over HTTP. It made me think that if anyone can publish a database using GitHub Pages, I could probably build a frontend in which users can decide which database to query. TeaTime is like that - when you first visit it, you'll need to choose your database. Everyone can create additional databases[1]. TeaTime then queries it, and fetches files using an IPFS gateway (I'm looking into using Helia so that users are also contributing nodes in the network). Files are then rendered in the website itself. Everything is done in the browser - no users, no cookies, no tracking. LocalStorage and IndexedDB are used for saving your last readings, and your position in each file.<p>Since TeaTime is a static site, it's super easy (and free) to deploy. GitHub repo tags are used for maintaining a list of public instances[2].<p>Note that a GitHub repository isn't mandatory for storing the SQLite files or the front end - it's only for the configuration file (config.json) of each database, and for listing instances. Both the instances themselves and the database files can be hosted on Netlify, Cloudflare Pages, your Raspberry Pi, or any other server that can host static files.<p>I'm curious to see what other kinds of databases people can create, and what other types of files TeaTime could be used for.<p>[0] <a href="https://news.ycombinator.com/item?id=27016630">https://news.ycombinator.com/item?id=27016630</a><p>[1] <a href="https://github.com/bjesus/teatime-json-database/">https://github.com/bjesus/teatime-json-database/</a><p>[2] <a href="https://github.com/bjesus/teatime/wiki/Creating-a-TeaTime-instance">https://github.com/bjesus/teatime/wiki/Creating-a-TeaTime-in...</a>

Show HN: TeaTime – distributed book library powered by SQLite, IPFS and GitHub

Recently there seem to be a surge in SQLite related projects. TeaTime is riding that wave...<p>A couple of years ago I was intrigued by phiresky's post[0] about querying SQLite over HTTP. It made me think that if anyone can publish a database using GitHub Pages, I could probably build a frontend in which users can decide which database to query. TeaTime is like that - when you first visit it, you'll need to choose your database. Everyone can create additional databases[1]. TeaTime then queries it, and fetches files using an IPFS gateway (I'm looking into using Helia so that users are also contributing nodes in the network). Files are then rendered in the website itself. Everything is done in the browser - no users, no cookies, no tracking. LocalStorage and IndexedDB are used for saving your last readings, and your position in each file.<p>Since TeaTime is a static site, it's super easy (and free) to deploy. GitHub repo tags are used for maintaining a list of public instances[2].<p>Note that a GitHub repository isn't mandatory for storing the SQLite files or the front end - it's only for the configuration file (config.json) of each database, and for listing instances. Both the instances themselves and the database files can be hosted on Netlify, Cloudflare Pages, your Raspberry Pi, or any other server that can host static files.<p>I'm curious to see what other kinds of databases people can create, and what other types of files TeaTime could be used for.<p>[0] <a href="https://news.ycombinator.com/item?id=27016630">https://news.ycombinator.com/item?id=27016630</a><p>[1] <a href="https://github.com/bjesus/teatime-json-database/">https://github.com/bjesus/teatime-json-database/</a><p>[2] <a href="https://github.com/bjesus/teatime/wiki/Creating-a-TeaTime-instance">https://github.com/bjesus/teatime/wiki/Creating-a-TeaTime-in...</a>

Show HN: TeaTime – distributed book library powered by SQLite, IPFS and GitHub

Recently there seem to be a surge in SQLite related projects. TeaTime is riding that wave...<p>A couple of years ago I was intrigued by phiresky's post[0] about querying SQLite over HTTP. It made me think that if anyone can publish a database using GitHub Pages, I could probably build a frontend in which users can decide which database to query. TeaTime is like that - when you first visit it, you'll need to choose your database. Everyone can create additional databases[1]. TeaTime then queries it, and fetches files using an IPFS gateway (I'm looking into using Helia so that users are also contributing nodes in the network). Files are then rendered in the website itself. Everything is done in the browser - no users, no cookies, no tracking. LocalStorage and IndexedDB are used for saving your last readings, and your position in each file.<p>Since TeaTime is a static site, it's super easy (and free) to deploy. GitHub repo tags are used for maintaining a list of public instances[2].<p>Note that a GitHub repository isn't mandatory for storing the SQLite files or the front end - it's only for the configuration file (config.json) of each database, and for listing instances. Both the instances themselves and the database files can be hosted on Netlify, Cloudflare Pages, your Raspberry Pi, or any other server that can host static files.<p>I'm curious to see what other kinds of databases people can create, and what other types of files TeaTime could be used for.<p>[0] <a href="https://news.ycombinator.com/item?id=27016630">https://news.ycombinator.com/item?id=27016630</a><p>[1] <a href="https://github.com/bjesus/teatime-json-database/">https://github.com/bjesus/teatime-json-database/</a><p>[2] <a href="https://github.com/bjesus/teatime/wiki/Creating-a-TeaTime-instance">https://github.com/bjesus/teatime/wiki/Creating-a-TeaTime-in...</a>

Show HN: TeaTime – distributed book library powered by SQLite, IPFS and GitHub

Recently there seem to be a surge in SQLite related projects. TeaTime is riding that wave...<p>A couple of years ago I was intrigued by phiresky's post[0] about querying SQLite over HTTP. It made me think that if anyone can publish a database using GitHub Pages, I could probably build a frontend in which users can decide which database to query. TeaTime is like that - when you first visit it, you'll need to choose your database. Everyone can create additional databases[1]. TeaTime then queries it, and fetches files using an IPFS gateway (I'm looking into using Helia so that users are also contributing nodes in the network). Files are then rendered in the website itself. Everything is done in the browser - no users, no cookies, no tracking. LocalStorage and IndexedDB are used for saving your last readings, and your position in each file.<p>Since TeaTime is a static site, it's super easy (and free) to deploy. GitHub repo tags are used for maintaining a list of public instances[2].<p>Note that a GitHub repository isn't mandatory for storing the SQLite files or the front end - it's only for the configuration file (config.json) of each database, and for listing instances. Both the instances themselves and the database files can be hosted on Netlify, Cloudflare Pages, your Raspberry Pi, or any other server that can host static files.<p>I'm curious to see what other kinds of databases people can create, and what other types of files TeaTime could be used for.<p>[0] <a href="https://news.ycombinator.com/item?id=27016630">https://news.ycombinator.com/item?id=27016630</a><p>[1] <a href="https://github.com/bjesus/teatime-json-database/">https://github.com/bjesus/teatime-json-database/</a><p>[2] <a href="https://github.com/bjesus/teatime/wiki/Creating-a-TeaTime-instance">https://github.com/bjesus/teatime/wiki/Creating-a-TeaTime-in...</a>

Show HN: App that asks ‘why?’ every time you unlock your phone

Show HN: App that asks ‘why?’ every time you unlock your phone

Show HN: App that asks ‘why?’ every time you unlock your phone

Show HN: App that asks ‘why?’ every time you unlock your phone

Show HN: App that asks ‘why?’ every time you unlock your phone

Show HN: App that asks ‘why?’ every time you unlock your phone

Show HN: Silent Poems – Visual expression of unspoken thoughts

An interactive digital art project that turns typed text into flowing, abstract animated symbols. The symbols connect fluidly, much like handwriting, but in an entirely abstract way. Each letter has its own design, and then each instance of the letter has a different seed such that you have slight differences - the same as with handwriting.

Show HN: Silent Poems – Visual expression of unspoken thoughts

An interactive digital art project that turns typed text into flowing, abstract animated symbols. The symbols connect fluidly, much like handwriting, but in an entirely abstract way. Each letter has its own design, and then each instance of the letter has a different seed such that you have slight differences - the same as with handwriting.

Show HN: Silent Poems – Visual expression of unspoken thoughts

An interactive digital art project that turns typed text into flowing, abstract animated symbols. The symbols connect fluidly, much like handwriting, but in an entirely abstract way. Each letter has its own design, and then each instance of the letter has a different seed such that you have slight differences - the same as with handwriting.

Show HN: Silent Poems – Visual expression of unspoken thoughts

An interactive digital art project that turns typed text into flowing, abstract animated symbols. The symbols connect fluidly, much like handwriting, but in an entirely abstract way. Each letter has its own design, and then each instance of the letter has a different seed such that you have slight differences - the same as with handwriting.

Show HN: SQLite Plugin for Jekyll

I love Jekyll, especially the Datafiles[0] feature, which lets you use CSV/JSON/YAML files and iterate through them. Mixed with the Jekyll Data Pages generator[1], which lets you create a page for every row in your dataset, it is a very powerful combination.<p>However, Liquid is a terrible language for data-mangling, and simple filtering/sorting/merging can become very annoying. So I wrote a Jekyll SQLite plugin that lets you use the same data interface in Jekyll/Liquid, but backed by a SQLite file(s).<p>It gives you the simplicity of the Baked Data pattern[2], and the flexibility of using SQL for data-wrangling, within a static site generator.<p>As a demo, I took the northwind dataset, and generated a site[3] with a few sample queries[4]. It demos both site-level, and page-level queries alongside data-pages generator to generate a page for every product/category/customer.<p>I've been using this across a few sites in production for almost a year, looking for feedback on usage semantics and feature suggestions.<p>[0]: <a href="https://jekyllrb.com/docs/datafiles/" rel="nofollow">https://jekyllrb.com/docs/datafiles/</a><p>[1]: <a href="https://github.com/avillafiorita/jekyll-datapage_gen">https://github.com/avillafiorita/jekyll-datapage_gen</a><p>[2]: <a href="https://simonwillison.net/2021/Jul/28/baked-data/" rel="nofollow">https://simonwillison.net/2021/Jul/28/baked-data/</a><p>[3]: <a href="https://northwind.captnemo.in/" rel="nofollow">https://northwind.captnemo.in/</a><p>[4]: <a href="https://github.com/captn3m0/northwind">https://github.com/captn3m0/northwind</a>

Show HN: SQLite Plugin for Jekyll

I love Jekyll, especially the Datafiles[0] feature, which lets you use CSV/JSON/YAML files and iterate through them. Mixed with the Jekyll Data Pages generator[1], which lets you create a page for every row in your dataset, it is a very powerful combination.<p>However, Liquid is a terrible language for data-mangling, and simple filtering/sorting/merging can become very annoying. So I wrote a Jekyll SQLite plugin that lets you use the same data interface in Jekyll/Liquid, but backed by a SQLite file(s).<p>It gives you the simplicity of the Baked Data pattern[2], and the flexibility of using SQL for data-wrangling, within a static site generator.<p>As a demo, I took the northwind dataset, and generated a site[3] with a few sample queries[4]. It demos both site-level, and page-level queries alongside data-pages generator to generate a page for every product/category/customer.<p>I've been using this across a few sites in production for almost a year, looking for feedback on usage semantics and feature suggestions.<p>[0]: <a href="https://jekyllrb.com/docs/datafiles/" rel="nofollow">https://jekyllrb.com/docs/datafiles/</a><p>[1]: <a href="https://github.com/avillafiorita/jekyll-datapage_gen">https://github.com/avillafiorita/jekyll-datapage_gen</a><p>[2]: <a href="https://simonwillison.net/2021/Jul/28/baked-data/" rel="nofollow">https://simonwillison.net/2021/Jul/28/baked-data/</a><p>[3]: <a href="https://northwind.captnemo.in/" rel="nofollow">https://northwind.captnemo.in/</a><p>[4]: <a href="https://github.com/captn3m0/northwind">https://github.com/captn3m0/northwind</a>

Show HN: Trilogy – A Reusable, Composable SQL Experiment

Recipe: Add a semantic layer to SQL; use it drop the requirement for joins/group_by; add in type-checking and a lightweight python-esque import syntax to enable reuse and hierarchical querying.<p>Trilogy is intended to provide an accessible but deep alternative to raw SQL. It offers a new-but-inspired-by-SQL syntax that compiles to various dialects of SQL (with DuckDB as the default).<p>The target audience is people that really like SQL for analytics and data engineering, but want less boilerplate and sharp edges and looser coupling to the DB.<p>Semantic models can be easily shared, composed and iterated on in an interactive session, preserving the adhoc workflows that make SQL so powerful.<p>The "higher level" of the language vis-a-vis SQL makes it straightforward to extend into ETL (an experimental basic DBT integration is available), offering potential to optimize a processing graph across intermediate staging nodes automatically.<p>This higher level of abstraction also offers some nice opportunities for more reliable text to SQL for LLMs. A similarly basic integration is available to demonstrate this, as is a very basic VsCode extension and electron-based IDE.<p>Tech stack is primarily Python. Open source, MIT license. Github is linked from demo page. Thoughts, feedback, contributions all welcome!<p>Note: renamed from PreQL (see prior show <a href="https://news.ycombinator.com/item?id=40728938">https://news.ycombinator.com/item?id=40728938</a>) to avoid confusion with the many PreQLs of the world. The `SQL pun` naming space is unfortunately well-explored.<p>Other SQL replacements (all great, all worth a look!):<p>PRQL (pipelined SQL alternative, all new syntax) <a href="https://news.ycombinator.com/item?id=36866861">https://news.ycombinator.com/item?id=36866861</a><p>Malloy (all new syntax, semantic focus) <a href="https://news.ycombinator.com/item?id=30053860">https://news.ycombinator.com/item?id=30053860</a><p>preql (much more ambitious, all new syntax) <a href="https://news.ycombinator.com/item?id=26447070">https://news.ycombinator.com/item?id=26447070</a>

Show HN: Trilogy – A Reusable, Composable SQL Experiment

Recipe: Add a semantic layer to SQL; use it drop the requirement for joins/group_by; add in type-checking and a lightweight python-esque import syntax to enable reuse and hierarchical querying.<p>Trilogy is intended to provide an accessible but deep alternative to raw SQL. It offers a new-but-inspired-by-SQL syntax that compiles to various dialects of SQL (with DuckDB as the default).<p>The target audience is people that really like SQL for analytics and data engineering, but want less boilerplate and sharp edges and looser coupling to the DB.<p>Semantic models can be easily shared, composed and iterated on in an interactive session, preserving the adhoc workflows that make SQL so powerful.<p>The "higher level" of the language vis-a-vis SQL makes it straightforward to extend into ETL (an experimental basic DBT integration is available), offering potential to optimize a processing graph across intermediate staging nodes automatically.<p>This higher level of abstraction also offers some nice opportunities for more reliable text to SQL for LLMs. A similarly basic integration is available to demonstrate this, as is a very basic VsCode extension and electron-based IDE.<p>Tech stack is primarily Python. Open source, MIT license. Github is linked from demo page. Thoughts, feedback, contributions all welcome!<p>Note: renamed from PreQL (see prior show <a href="https://news.ycombinator.com/item?id=40728938">https://news.ycombinator.com/item?id=40728938</a>) to avoid confusion with the many PreQLs of the world. The `SQL pun` naming space is unfortunately well-explored.<p>Other SQL replacements (all great, all worth a look!):<p>PRQL (pipelined SQL alternative, all new syntax) <a href="https://news.ycombinator.com/item?id=36866861">https://news.ycombinator.com/item?id=36866861</a><p>Malloy (all new syntax, semantic focus) <a href="https://news.ycombinator.com/item?id=30053860">https://news.ycombinator.com/item?id=30053860</a><p>preql (much more ambitious, all new syntax) <a href="https://news.ycombinator.com/item?id=26447070">https://news.ycombinator.com/item?id=26447070</a>

Show HN: Trilogy – A Reusable, Composable SQL Experiment

Recipe: Add a semantic layer to SQL; use it drop the requirement for joins/group_by; add in type-checking and a lightweight python-esque import syntax to enable reuse and hierarchical querying.<p>Trilogy is intended to provide an accessible but deep alternative to raw SQL. It offers a new-but-inspired-by-SQL syntax that compiles to various dialects of SQL (with DuckDB as the default).<p>The target audience is people that really like SQL for analytics and data engineering, but want less boilerplate and sharp edges and looser coupling to the DB.<p>Semantic models can be easily shared, composed and iterated on in an interactive session, preserving the adhoc workflows that make SQL so powerful.<p>The "higher level" of the language vis-a-vis SQL makes it straightforward to extend into ETL (an experimental basic DBT integration is available), offering potential to optimize a processing graph across intermediate staging nodes automatically.<p>This higher level of abstraction also offers some nice opportunities for more reliable text to SQL for LLMs. A similarly basic integration is available to demonstrate this, as is a very basic VsCode extension and electron-based IDE.<p>Tech stack is primarily Python. Open source, MIT license. Github is linked from demo page. Thoughts, feedback, contributions all welcome!<p>Note: renamed from PreQL (see prior show <a href="https://news.ycombinator.com/item?id=40728938">https://news.ycombinator.com/item?id=40728938</a>) to avoid confusion with the many PreQLs of the world. The `SQL pun` naming space is unfortunately well-explored.<p>Other SQL replacements (all great, all worth a look!):<p>PRQL (pipelined SQL alternative, all new syntax) <a href="https://news.ycombinator.com/item?id=36866861">https://news.ycombinator.com/item?id=36866861</a><p>Malloy (all new syntax, semantic focus) <a href="https://news.ycombinator.com/item?id=30053860">https://news.ycombinator.com/item?id=30053860</a><p>preql (much more ambitious, all new syntax) <a href="https://news.ycombinator.com/item?id=26447070">https://news.ycombinator.com/item?id=26447070</a>