zillion VS endoflife.date

I've also been frustrated when testing out tools that kinda keep you locked into one predetermined view, table, or set of tables at a time. I made a semantic data modeling library that puts together queries (and of course joins) for you as it uses a drill-across querying technique, and can also join data across different data sources in a secondary execution layer.

https://github.com/totalhack/zillion

Disclaimer: this project is currently a one man show, though I use it in production at my own company.

https://github.com/totalhack/zillion

Semantic data warehousing and analytics tool written in python. It has experimental/half-baked NLP features to query your warehouse by interacting with the semantic layer with AI, instead of the normal approach of having an LLM write SQL and needing to know your entire schema.

Hey All, I wanted to share Zillion -- an open source Python data modeling and analytics library with experimental natural language features powered by OpenAI, LangChain, and Qdrant. Zillion acts as a semantic layer on top of your data, writes SQL so you don't have to, and easily bolts onto existing database infrastructure via SQLAlchemy Core.

Built it for me, but available to all -- Zillion: a python data modeling and analytics library.

https://github.com/totalhack/zillion

More details/docs can be found in the GitHub repo: https://github.com/totalhack/zillion

Nice work. I had considered implementing something similar in https://github.com/totalhack/zillion down the road, probably as a layer on top.

Zillion: https://github.com/totalhack/zillion

A python data warehousing / modeling / analytics library that can unify multiple datasources and writes SQL for you. It's alpha level at the moment and I just slowly chip away when time allows, though I'm using it in production in another project (which does make money).

This seems fun, but certainly unnecessary. All of those questions could be answered in seconds using a warehouse tool like Looker or Metabase or https://github.com/totalhack/zillion (disclaimer: I'm the author and this is alpha-level stuff, though I use it regularly).

At first glance this seems more confusing, particularly the grouping/aggregation syntax, though I suppose that's something I'd just get used to. Some of the syntactic sugar is nice, but some things are also unlike SQL for no apparent reason which just makes adoption harder than necessary (join syntax for example).

IMO the main selling point would be the "database agnostic" part, but I already achieve that through SQLAlchemy Core and/or a warehouse layer like https://github.com/totalhack/zillion (disclaimer: I'm the author and this is alpha-level stuff, though I use it regularly). It seems like many newer DB technologies/services I'd want to use either speak PostgreSQL or MySQL wire protocol anyway.

The roadmap is worth a read, as it notes some limitations and expected challenges supporting the wide variety of DBMS features and syntax. That said, I can see where this might be useful in the cases where I do have to jump into direct SQL, but want the flexibility to easily switch the back end DB for that code -- that's assuming it can cover the use cases that forced me to write direct SQL in the first place though.

> where you can see overlapped timelines when support ended

I tried to generate a visual timeline for a given page (https://github.com/endoflife-date/endoflife.date/pull/2859, has some screenshots), but it was limited to a single page (so you'd only see nokia devices at once for eg).

It turned out that it is too hard to generate clear charts with vague data. We often only know whether is device is supported or not (true/false, see comments about samsung below in this thread), and don't have clear release dates.

I'll get to it someday (PRs welcome), but it might not work for the usecase we want (picking phones) because data on mobiles is very vague.

repairability score -> sounds interesting, will file an issue and see. The hard part is that there's no clear identifiers for devices (SWID/CPE are just not good enough) for us to track this kind of data from elsewhere easily.

Here's the PR where it was added by a user, "Based on a Rails core team member's comment"...

A lot of the communications regarding End of Life for Support is done very effectively here: https://endoflife.date/

https://endoflife.date (not mine)

a little similar to endoflife.date if anyone has ever come across it for Software versions?

We do this at https://endoflife.date API, and it works quite well.

I've created the `db.json` with the [end of life](https://endoflife.date/) api.

Something I've recently worked on is building an SQLite database of all the dependencies my organisation uses, which makes it possible to write our own queries and reports. The tool is all Open Source (https://dmd.tanna.dev) and has a CLI as well as the SQLite data.

Ive used it to look for software that's out of date (via https://endoflife.date), to find vulnerablilities (via https://osv.dev) and get license information (via https://deps.dev)

It's been hugely useful for us understanding use of internal and external dependencies, and I wish I'd built it earlier in my career so I could've had it for other companies I've worked at!

This is neat: https://endoflife.date/

I'm looking for a 3rd party vendor that can do the mindlessly tedious work of maintaining a library of software support dates. Think hundreds of thousands/millions of versions of software in an enterprise with ridiculous tech debt. Something like endoflife.date but much more far encompassing.