I spend a lot of time on the command line. My most frequently used commands are git (by far), and rails (mostly for rails test) or rspec (depending on the project). Most invocation of both commands require arguments. And most of those arguments are paths to files. In big projects, typing paths to files can be tedious, even with tab completion. My productivity trick for that is using Zsh Line Editor widgets.

Let’s see a widget in action:

The world is awful. The world is much better. The world can be much better.

Max Roser’s point of view resonated with me:

If we want more people to dedicate their energy and money to making the world a better place, then we should make it much more widely known that it is possible to make the world a better place.

For this we have to remember that all three statements are true at the same time: the world is awful, the world is much better, and the world can be much better.

Useful Uses of cat

I agree with the author: Using cat to start a pipelines is about composability of commands, and makes it easier to build pipelines in steps. Technically, you could be adding an extra process that you don’t need, but in day to day unix pipe operations, the performance is never an issue.

Data Looks Better Naked

Great illustration of how bad data visualization can be better, by removing design elements. My favorite is the pie chart.

I recently discovered Nushell. It’s billed as a “new kind of shell”. What caught my eye is not so much the actual shell usage: Executing commands, redirecting output, working with files, etc. I was interested in the concept of structured data:

Everything is data

Nu pipelines use structured data so you can safely select, filter, and sort the same way every time. Stop parsing strings and start solving problems.

Nushell comes with support for a variety of formats (e.g. JSON, YAML, csv):

> open package.json | get dependencies
╭──────────────────────────────────┬─────────────╮
│ @fontsource-variable/caveat      │ ^5.1.0      │
│ @fontsource-variable/raleway     │ ^5.1.0      │
│ @fortawesome/fontawesome-free    │ ^6.7.2      │
│ @hotwired/turbo-rails            │ ^8.0.12     │
│ @popperjs/core                   │ ^2.11.8     │
│ @rails/actioncable               │ ^8.0.100    │
│ @rails/activestorage             │ ^8.0.100    │
│ @rails/ujs                       │ ^7.1.3-4    │
│ @ttskch/select2-bootstrap4-theme │ ^1.5.2      │
│ autoprefixer                     │ ^10.4.20    │
│ bootstrap                        │ ^4.5.3      │
│ esbuild                          │ ^0.19.3     │
│ jquery                           │ 3.7.1       │
│ nodemon                          │ ^3.1.9      │
│ popper.js                        │ ^1.15.0     │
│ postcss                          │ ^8.4.30     │
│ postcss-cli                      │ ^10.1.0     │
│ sass                             │ ^1.67.0     │
│ select2                          │ ^4.1.0-rc.0 │
│ startbootstrap-sb-admin          │ ^6.0.2      │
╰──────────────────────────────────┴─────────────╯

Pipes can be built up:

> open package.json | get dependencies | transpose | where column0 =~ @rails
╭───┬──────────────────────┬──────────╮
│ # │       column0        │ column1  │
├───┼──────────────────────┼──────────┤
│ 0 │ @rails/actioncable   │ ^8.0.100 │
│ 1 │ @rails/activestorage │ ^8.0.100 │
│ 2 │ @rails/ujs           │ ^7.1.3-4 │
╰───┴──────────────────────┴──────────╯

Converting between formats is a breeze:

> open package.json | get dependencies | to yaml
'@fontsource-variable/caveat': ^5.1.0
'@fontsource-variable/raleway': ^5.1.0
'@fortawesome/fontawesome-free': ^6.7.2
'@hotwired/turbo-rails': ^8.0.12
'@popperjs/core': ^2.11.8
'@rails/actioncable': ^8.0.100
'@rails/activestorage': ^8.0.100
'@rails/ujs': ^7.1.3-4
'@ttskch/select2-bootstrap4-theme': ^1.5.2
autoprefixer: ^10.4.20
bootstrap: ^4.5.3
esbuild: ^0.19.3
jquery: 3.7.1
nodemon: ^3.1.9
popper.js: ^1.15.0
postcss: ^8.4.30
postcss-cli: ^10.1.0
sass: ^1.67.0
select2: ^4.1.0-rc.0
startbootstrap-sb-admin: ^6.0.2

And there is a built in explore TUI command that you can pipe data to (open file.csv | explore) to drill in and out of data interactively. Lovely.

I’m just getting started with Nushell, but already seems like a useful tool to have for data exploration and transformation.

Cheating is All You Need

Steve Yegge writes (a lot!) about AI. His take is very interesting: Basically LLMs are in a race to the bottom. Each LLM is not that different from the next. The important bit is about context: Providing the LLM with enough context to do the task at hand. I’ve only had limited experience playing around with LLMs, but I definitely think that they only work when they are provided enough context to perform the task at hand. Providing can be tedious. If you want it to help you write a unit test, well it needs access to the class in question. And it’s collaborators. And the factories that the test uses. And so on. Copy/pasting all of that is a lot. The more interesting claims about AI I’ve seen are for tools that integrate with your editor (or IDE) to provide the context to the LLM.

Nearly All Binary Searches and Mergesorts are Broken

Interesting take about algorithm correctness: The author wrote a buggy implementation of a binary search in the Java language. And the bug, is the same one that his PhD teacher had in his book! The bug was for some ranges of inputs (not all), which is why it’s so pervasive and hard to spot, until you specifically start to look for it.

We programmers need all the help we can get, and we should never assume otherwise. Careful design is great. Testing is great. Formal methods are great. Code reviews are great. Static analysis is great. But none of these things alone are sufficient to eliminate bugs: They will always be with us. A bug can exist for half a century despite our best efforts to exterminate it. We must program carefully, defensively, and remain ever vigilant.

The Mythical IO-Bound Rails App

The author makes good arguments that if Rails in the wild was really IO bound all the time, than the recent YJIT improvements in Ruby versions would not have resulted in reported ~25% improvements in real apps. The improvements suggests that a good chunk of the time was being spent in Ruby. He then goes to point out that actually measuring IO is complicated, and that CPU starvation can look like IO.

Rails is better low code than low code

Radan Skorić’s points out that the argument for low-code (and even low-code) is that it can get you to your goal faster, and by people that are not experienced programmers. It resonates with me that it can quickly fall apart, once your applications reached a point that is not the platform use case.

I recently learned about a person I know that used one of those low-code platforms to quickly build an application that could be web-native, and also a native Android and iPhone app. Once the web portion was launched, it quickly got into performance issues, because each page was making hundreds (or even thousands) of AJAX requests to the server. However, he couldn’t really fix the problem, because the platform was not design to deal with the level of data that they wanted. They were stuck.

Trying out Solid Queue and Mission Control with PostgreSQL

Andrew Atkinson writes ab out his experience with Solid Queue and Postgres. I’m keeping an eye on Solid Queue, but have not yet made the switch from GoodJob.