prosto VS Lunar

> Joins are what makes relational modeling interesting!

It is the central part of RM which is difficult to model using other methods and which requires high expertise in non-trivial use cases. One alternative to how multiple tables can be analyzed without joins is proposed in the concept-oriented model [1] which relies on two equal modeling constructs: sets (like RM) and functions. In particular, it is implemented in the Prosto data processing toolkit [2] and its Column-SQL language. The idea is that links between tables are used instead of joins. A link is formally a function from one set to another set.

[1] Joins vs. Links or Relational Join Considered Harmful https://www.researchgate.net/publication/301764816_Joins_vs_...

[2] https://github.com/asavinov/prosto data processing toolkit radically changing how data is processed by heavily relying on functions and operations with functions - an alternative to map-reduce and join-groupby

One idea is to use columns instead of cells. Each column has a definition in terms of other columns which might also be defined in terms of other columns. If you change value(s) in some source column then these changes will propagate through the graph of these column definitions. Some fragments of this general idea were implemented in different systems, for example, Power BI or Airtable.

This approach was formalized in the concept-oriented model of data which relies on two basic elements: mathematical functions and mathematical sets. In contrast, most traditional data models rely on only sets. Functions are implemented as columns. The main difficulty in any formalization is how to deal with columns in multiple tables.

This approach was implemented in the Prosto data processing toolkit: https://github.com/asavinov/prosto

Having Python expressions within a declarative language is a really good idea because we can combine low level logic of computations of values with high level logic of set processing.

A similar approach is implemented in the Prosto data processing toolkit:

https://github.com/asavinov/prosto

Although Prosto is viewed as an alternative to Map-Reduce by relying on functions, it also supports Python User-Defined Functions in its Column-SQL:

Most of the self-service or no-code BI, ETL, data wrangling tools are am aware of (like airtable, fieldbook, rowshare, Power BI etc.) were thought of as a replacement for Excel: working with tables should be as easily as working with spreadsheets. This problem can be solved when defining columns within one table: ``ColumnA=ColumnB+ColumnC, ColumnD=ColumnAColumnE`` we get a graph of column computations* similar to the graph of cell dependencies in spreadsheets.

Yet, the main problem is in working multiple tables: how can we define a column in one table in terms of columns in other tables? For example: ``Table1::ColumnA=FUNCTION(Table2::ColumnB, Table3::ColumnC)`` Different systems provided different answers to this question but all of them are highly specific and rather limited.

Why it is difficult to define new columns in terms of other columns in other tables? Short answer is that working with columns is not the relational approach. The relational model is working with sets (rows of tables) and not with columns.

One generic approach to working with columns in multiple tables is provided in the concept-oriented model of data which treats mathematical functions as first-class elements of the model. Previously it was implemented in a data wrangling tool called Data Commander. But them I decided to implement this model in the *Prosto* data processing toolkit which is an alternative to map-reduce and SQL:

https://github.com/asavinov/prosto

It defines data transformations as operations with columns in multiple tables. Since we use mathematical functions, no joins and no groupby operations are needed and this significantly simplifies and makes more natural the task of data transformations.

Moreover, now it provides *Column-SQL* which makes it even easier to define new columns in terms of other columns:

https://github.com/asavinov/prosto/blob/master/notebooks/col...

Hamilton is more similar to the Prosto data processing toolkit which also relies on column operations defined via Python functions:

https://github.com/asavinov/prosto

However, Prosto allows for data processing via column operations in many tables (implemented as pandas data frames) by providing a column-oriented equivalents for joins and groupby (hence it has no joins and no groupbys which are known to be quite difficult and require high expertise).

Prosto also provides Column-SQL which might be simpler and more natural in many use cases.

The whole approach is based on the concept-oriented model of data which makes functions first-class elements of the model as opposed to having only sets in the relational model.

One alternative to SQL (type of thinking) is Column-SQL [1] which is based on a new data model. This model is relies on two equal constructs: sets (tables) and functions (columns). It is opposed to the relational algebra which is based on only sets and set operations. One benefit of Column-SQL is that it does not use joins and group-by for connectivity and aggregation, respectively, which are known to be quite difficult to understand and error prone in use. Instead, many typical data processing patterns are implemented by defining new columns: link columns instead of join, and aggregate columns instead of group-by.

More details about "Why functions and column-orientation" (as opposed to sets) can be found in [2]. Shortly, problems with set-orientation and SQL are because producing sets is not what we frequently need - we need new columns and not new table. And hence applying set operations is a kind of workaround due the absence of column operations.

This approach is implemented in the Prosto data processing toolkit [0] and Column-SQL[1] is a syntactic way to define its operations.

[0] https://github.com/asavinov/prosto Prosto is a data processing toolkit - an alternative to map-reduce and join-groupby

[1] https://prosto.readthedocs.io/en/latest/text/column-sql.html Column-SQL (work in progress)

[2] https://prosto.readthedocs.io/en/latest/text/why.html Why functions and column-orientation?

> This is closer to the way that humans perceive the world — mapping between whatever aspect of external reality you are interested in and the data model is an order of magnitude easier than with relational databases.

One approach to modeling data based on mappings (mathematical functions) is the concept-oriented model [1] implemented in [2]. Its main feature is that it gets rid of joins, groupby and map-reduce by manipulating data using operations with functions (mappings).

> Everything is pre-joined — you don’t have to disassemble objects into normalised tables and reassemble them with joins.

One old related general idea is to assume the existence of universal relation. Such an approach is referred to as the universal relation model (URM) [3, 4].

[1] A. Savinov, Concept-oriented model: Modeling and processing data using functions, Eprint: arXiv:1911.07225 [cs.DB], 2019 https://www.researchgate.net/publication/337336089_Concept-o...

[2] https://github.com/asavinov/prosto Prosto Data Processing Toolkit: No join-groupby, No map-reduce

[3] https://en.wikipedia.org/wiki/Universal_relation_assumption

[4] R. Fagin, A.O. Mendelzon and J.D. Ullman, A Simplified Universal Relation Assumption and Its Properties. ACM Trans. Database Syst., 7(3), 343-360 (1982).

(Currently, it is not actively developed and the focus is moved to a similar project - https://github.com/asavinov/prosto - also focused on data preprocessing and feature engineering)

Pretty sure Lunar [0] can do this for you, and you can buy a lifetime license.

[0]: https://lunar.fyi/

I've had good luck with the Lunar app - it manages my Dell and LG monitors on an M2. (No affiliation) https://lunar.fyi

Wild! I am working on exactly the same thing now for Lunar (https://lunar.fyi), and I'm also calling it Night Mode ^_^ what a coincidence

I've been trying to make "white regions in dark backgrounds" less painful for months, but doing that at the system level on macOS is incredibly hard. I see you're doing it with CSS filters, which make sense in the limited scope of an article. But applying something like that on the whole macOS UI would cause confusion.

I already use something similar on the iPhone: I read on the Kindle app which has white text on black background, then I have a full red Color Tint filter on the Triple Back Tap shortcut which I use before reading. Very similar effect to your solution, although I don't have images in my books.

I was comparing anti-piracy measures with DRM, I don't have actual DRM in my app. I can't block users that really bought the app from using it (which is what DRM is notorious for).

But I do have a license verification for the Pro features (https://lunar.fyi/#pro), and that is what people are cracking in the app. I only added more protection around this verification.

Lunar

There's no Reduce White Point on Mac as far as I am aware. However, you can use the fantastic Lunar [0] app to achieve this, as it supports "Sub-Zero Dimming".

To use it, I think you just need to start Lunar, and then press the Reduce Brightness button on your keyboard until it goes below the minimum Mac allows.

[0] https://lunar.fyi

As the dev of a macOS app that breaks all the time because of external hardware, the tone of the article hits close to home. (I’m talking about https://lunar.fyi/ whose brightness control commands can be blocked by USB-C hubs, “smart” monitors, too long cables etc.)

I had to disable public GitHub issues on the app repo [1] because people seemed to fuel each other with spiteful comments and “why can’t you just!!” sentences.

The contact form still attracts many such “entitled” people and it hurts to wake up to such messages, but at least I can choose to ignore those if I can’t bring anything to the discussion. There’s no peer pressure.

These people are expecting too much from a handful of developers who are sharing a lot of free work and time that could have been spent better than hunting new IDs in URLs and updating regular expressions.

[1] https://github.com/alin23/Lunar

Last year I bought a second computer for my music studio. I wanted to use the same set of 2 monitors and wired keyboard + trackpad on both machines.

I wrote simple scripts to switch my monitor inputs with keyboard shortcuts (even simpler with Lunar, amazing new Mac app — https://lunar.fyi), which saved me from having to press annoying input-source buttons.

But I couldn't for the life of me find a simple, suitable software controllable KVM switch. That still requires the hardware button to be controlled, so frustrating.

Some people like the process of writing code, more than the end result. I had a few months of that feeling, but nowadays it’s rarely about writing for me.

Just the other day I used Copilot to explain the disassembly of macOS KeyboardBacklight code, so that I can turn off the keyboard lights when using Lunar’s Blackout (https://lunar.fyi/#blackout)

It even helped me generate the ObjC function signatures from assembly and use the right calling convention in Swift afterwards. It really feels like magic.

I would have no joy in writing that code, it’s mostly bridging and translation anyway. I just need it to do this thing so that people can take advantage of it.

Lunar - Price: Free (optional premium one-time purchase) Menu bar app for macOS that allows you to adjust your display's brightness and color temperature. (Pro version also available.)