microcosm VS d3

Manual via https://pkg.go.dev/database/sql with handwritten SQL in the majority of places... but with a wrapper to handle the more complex search scenarios.

For example these from a multi-tenant SaaS forum platform...

This helper to get connections: https://github.com/microcosm-cc/microcosm/blob/master/helper... used like this for inserts: https://github.com/microcosm-cc/microcosm/blob/master/models... and this for reads https://github.com/microcosm-cc/microcosm/blob/master/models... .

But searches... i.e. highly consistent SELECT queries with different WHERE statements (and potentially FROM statements), then in each project I tend to have an idea of a search struct ( https://github.com/microcosm-cc/microcosm/blob/master/models... ) that will validate the inputs and represent the search query, and then something that will consume that and build the SQL for it ( https://github.com/microcosm-cc/microcosm/blob/master/models... ). This isn't pretty... but it's easy for me to tune, debug, and keeps the rest of the code base very maintainable... all the complexity is here in the search.

The vast majority of SQL is very very simple and needs no ORM, and the complexity is just in the search scenario where I want to be able to tune the performance more than an ORM would allow me to do so.

Yes this was done with a combination of GSAP Scrolltrigger https://gsap.com/docs/v3/Plugins/ScrollTrigger/ and https://d3js.org/

d3 - very power visualization library enabling dynamic visualizations. docs

Yep, Evidence is doing good work. We were most directly inspired by VitePress; we spent months rewriting both D3’s docs (https://d3js.org) and Observable Plot’s docs (https://observablehq.com/plot) in VitePress, and absolutely loved the experience. But we wanted a tool focused on data apps, dashboards, reports — observability and business intelligence use cases rather than documentation. Compared to Evidence, I’d say we’re trying to target data app developers more than data analysts; we offer a lot of power and expressiveness, and emphasize custom visualizations and interaction (leaning on Observable Plot or D3), as well as polyglot programming with data loaders written in any language (Python, R, not just SQL).

D3.js: A robust library to visualize your data and create interactive data-driven visualizations.

They are images so it could be any number of things, datawrapper, charts.js, d3.js to name a few options.

I made this interactive visualization that attempts to show the real-time frequency and location of births around the world. A country’s annual births (i.e. the country’s population times its birthrate) were distributed across all of the populated locations in each country, weighted by the population distribution (i.e. more populated areas got a greater fraction of the births). Data Sources and Tools Population and birthrate data for 2023 was obtained from Wikipedia (Population and birth rates). Population distribution across the globe was obtained from Socioeconomic Data and Applications Center (sedac) at Columbia University. Data is processed and visualized at a 1 degree x 1 degree resolution, each of which has a different probability of a birth occurring in a specific time period. D3.js was used to create the map elements and html, css and javascript were used to create the user interface.

When I go to the homepage of types/d3 the only hint for any kind of documentation is what seems to be the main github page of d3. It's highly possible I'm missing something here, so sorry if I am but I can't find any documentation of how you are supposed to type these library objects.

Website: D3.js official site

D3js