ActiveJob provides simple solutions to two problems faced by Rails developers when writing background jobs: queueing jobs (via the ActiveJob API) and serialization of ActiveRecord objects (via GlobalID).
It doesn’t, however, help with the third problem: writing resilient jobs that can survive in a production environment.
Giles Bowkett posted a great piece on the deep flaws of Agile processes like Scrum. It’s spot-on with my experience. There’s so many choice quotes, it’s hard to pull just one, but I’ll try. Toward the end of the article:
I’ve never seen Scrum-like frameworks for transmuting the work of designers, marketers, or accountants into cartoonish oversimplifications like story points. People are happy to treat these workers as adults and trust them to do their jobs.
I don’t know why this same trust does not prevail in the culture of managing programmers.
After a job converting JIRA Tickets into Story Points into diffs, I eventually realized that good developers deliver results, not promises, points, or even features. I even wrote an entire book about it.
Thankfully, the team at Stitch Fix has no sprints, story points, velocity, or planning poker. We just solve the most important problem at hand, and move onto the next most important one.
Why isn’t Rails leading the way here? Where is the Rails that shocked the world with its elegant API for creating server-side web applications? It seems that it’s still peddling the same solutions for rich user-interfaces as it was over four years ago.
@garybernhardt linked to a short academic paper on code readability, called “What Makes Code Hard to Understand?”. It’s a quick read that details an experiment where researchers showed severals versions of the same program to a bunch of programmers and asked them to guess the output. Each version had the same cyclomatic complexity and lines of code, but differed only in formatting, variable naming, and use of types.
The physical aspects of notation, often considered superficial, can have a profound impact on performance [of programmers to understand what code will do]
In particular, in a program that relied on order of operations, two versions were given, one in which one space was used around operators (
another where the operators were all vertically aligned (
Programmers were more likely to respect the order of mathematical operations in the
whitespace, showing how horizontal space can emphasize the common structure between related calculations.
Also, they presented three versions of code to calculate the area of a rectangle, using free variables, tuples, and a
Programmers took longer to respond to the
rectangledespite it having fewer lines than the
classversion. It is not uncommon in Python to use tuples for (x, y) coordinates, but the syntactic “noise” that is present in the tuples version for variable names (e.g.,
r1_xy_1) and calculations (e.g.,
width = xy_2 - xy_1) likely gave programmers pause when verifying the code’s operation.
This was not something that was initially obvious to me as I learned programming, but I have come to realize the importance of typography in writing code. From my post on the subject over a year ago:
But, it’s not just the content - the code itself - that affects readability. How it’s presented matters and if we’re going to talk about presentation, we have to talk about typography.
I can’t say what a codebase designed to Alan Kay’s idea of “object-oriented” might look like. I can say what your average developer (including myself) actually creates using object-oriented languages, tools, and techniques. The result is a constant battle to tame complexity. I’m going to lay out one source of that complexity, because it’s baked-in to object-orientation, and I debate that it provides any utility in making programs easy to understand or change.
Resque::TermExceptionis really just kicking the can down the road. You might prevent some of your jobs from failing, but you’ll still get failed jobs. Granted, they will fail at a lower rate, but it’s still a rate correlated to the scale of your business.
The underlying problem is that jobs aren’t idempotent.
Check out the entire thing here.
What do we mean by types?
Types are everywhere, they are all around us, even now in your very programs. You can see them when you look at your browser, or when you start up your editor. You can feel them when you go to work, when you go to meetups, when you buy your conference passes.
Morpheus is correct, types are at the absolute core of every program we write, “static” or not.
Today, we’re introducing Resque Brain, an open source application that monitors multiple resque instances. It has a mobile-friendly UI, and provides better tools for managing the failed queue. It also includes some basic monitoring and statistics tasks.
In reading “The Swift Programming Language” to prep for my post on how Swift informs us about programming language trends, I was surprised at how straightforward the language’s features seemed:
I found myself nodding along with each feature introduced. Tuples: check. Named Parameters: check. Default Parameters: check. Protocols: check. Functions: check.
Although the forms of Swift’s various features differ from their analogs in other languages, conceptually, they are the same: the generic type system is similar to Java’s, and the tuples are close enough to Scala’s that all I need to do is understand the syntax.
It really is true that the more languages you know, the easier it is to “pick up” new ones. This is a great reason to learn a new programming language every year.
To the surprise of just about everyone, Apple announced a new programming language, Swift, at WWDC this Monday. This is a rare event for us programmers, as we don’t often get to see what the biggest technology company on the planet (who owns one of the biggest platforms on the planet) thinks about programming language design.
Swift embodies two major themes in programming language design that have come to the forefront in the last several years: functions as first-class values (a given, these days), and, more surprisingly, static typing.