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I use es-toolkit. It is fully in Typescript. Every function can be imported without any extra overhead, for simple functions it just adds a few bytes then to the bundle. I doubt "better performance" since most helpers functions are just tiny and there is no room for significant improvements.

So I think trying to be better here is pointless, better focus on offering more helpful utility functions which might be missing in es-toolkit


Always great to see efforts to make working with data frames easier. Here are some similar data frame libraries for Java:

https://github.com/jtablesaw/tablesaw

https://github.com/dflib/dflib

My preferred way is just use duckdb java API. I didn't see anything better in performance/efficiency. Also a SQL query is often easier to write


Thanks! I'm aware of those great projects. Fahmatrix aims to offer a lightweight, dependency-free alternative that’s easy to embed in any Java app. DuckDB is super impressive, especially for SQL-heavy tasks — but my goal is more about a native, fluent API for those who prefer direct Java code over SQL.


Yes. It has bothered me for a long time too. Maybe the best mix is a dataframe library with basic operations (column select, non-null etc), which also allows SQL for more complex stuff?


Totally agree that SQL can be the best tool for many jobs. My goal with Fahmatrix is to serve the opposite niche: where devs want something that's Java-native, procedural, and simple without reaching for an external engine. SQL support or DSL might come later though — I see the appeal.


Sure. So maybe notehr comment would be to make it (particularly the Series class), as compatible with Java Streams as possible.

Next step would likely be compatibility with popular libraries such as Apache Commons Math: https://commons.apache.org/proper/commons-math/userguide/sta...


Polars and duckdb interoperate nicely and can enable this flexibility


Does Polars have a Java library?


Our Bluesky trends and insight app is live on Uneed today. We'd appreciate an upvote.

In addition to daily user and engagement rankings, we launched a new feed builder for Bluesky last week: http://bluefacts.app/feed-builder

Looking forward to your feedback!


you can do it with a command line like this:

   duckdb -c "attach  'sqlite-database.db' as db;  copy db.table_name to 'table_name.parquet' (format parquet, compression zstd)"


in my test database this is about 20% smaller than the gzipped text SQL statements.


That's not it. This only exports the table's data, not the database. You lose the index, comments, schemas, partitioning, etc... The whole point of OP's article is how to export the indices in an efficient way.

You'd want to do this:

     duckdb -c "ATTACH 'sqlite-database.db' (READ-ONLY); EXPORT DATABASE 'target_directory' (FORMAT parquet, COMPRESSION zstd)"
Also I wonder how big your test database is and it's schema. For large tables Parquet is way more efficient than a 20% reduction.

If there's UUIDs, they're 36 bits each in text mode and 16 bits as binary in Parquet. And then if they repeat you can use a dictionary in your Parquet to save the 16 bits only once.

It's also worth trying to use brotli instead of zstd if small files is your goal.


Here is a chart with the number of Android Apps in Google Play (over time): https://www.appbrain.com/stats/number-of-android-apps


We had this idea to use a page rank based algorithm to compute a influence score based on the score of the people who follow you.

A high score usually indicates a trusted account. Check it out here: https://bluefacts.app/top


Congratulations!

Always good to have some competition, I created this feed builder for Bluesky: https://bluefacts.app/feed-builder

My focus was on simplicity, to get started without difficult setup


Echarts has good documentation and examples so I think it should be vibe coding friendly when you reference the docs (eg with cursor)


We use Echarts on our Bluesky analytics site

https://bluefacts.app/profile/bsky.app

Really great experience, we optimized the imports to reduce bundle size.

For https://www.appbrain.com we also use it and had to optimize it even more.We render it server side and only return the SVG to the client.

Server side rendering is a very powerful feature only very few chart libraries support.


https://apache.github.io/echarts-handbook/en/how-to/cross-pl...

also they have a very lightweight client library to add back interactive things like popups on hover when using server side rendering


I didn't use Timefold but the predecessor Optaplanner, and I remember there were hard constraints which must always be true (eg one room can only be used for one meeting at a given time) and then there were soft constraints which were minimized (eg shorter distance is better)

so an optimization problem can then be described with a set of those hard/soft contraints


Yes! These days, to handle cases with more work than resources to do it, medium constraints are used a lot too (so hard/medium/soft constaints), to penalize the amount of unassigned work. Those are harder than soft constraints, but softer than hard constraints.


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