Effective Programs - 10 Years of Clojure - Rich Hickey

One of the big benefits of clojure being dynamic is that everything is data (e.g. a map, set, vector or list). This is what allows reuse. - The vast core library of functions that manipulate those data structures can be used for everything in your program, cos it's all data. - Most clojure libraries take and/or return data, reducing the need for clumsy adaptors, or even worse not being able to get at the data you need cos the library writer was really enthusiastic about encapsulation of everything they thought was of no use to consumers. - You don't have a person class, you have a map with a first name and last name. Now the function that turns first + last name into full name can be reused for any other map with the same keys. (A rather spurious example, but a real one would take a large codebase and an essay to describe) I can only recommend watching some of Rich Hickey's talks, particularly these ones, they're not entirely about types, but they express the above ideas much better than I can: - Simple made easy [link] - Effective programs [this video] - Are we there yet? (this one is more about OOP, but unless you're using something like haskell, idris etc its relevant for your type system of choice) [link]

That's quite a judgement call to make based on the utility of error messages. I can't remember the last time I was blocked based on a Clojure error message anyway. Errors are less frequent and usually pretty obvious. I think you're wrong to say core devs don't understand modern programming, but you'd probably be right to say that they didn't prioritize making it approachable and stooping to the lowest common denominator. And it's not just Clojure, but datomic, core.async, spec -- all solving real problems in modern large scale programming with elegance. Watch Rich's 'Effective Programs' talk [1] and lmk if you still feel that he's out of touch with modern large scale programming. I think he's pretty in tune. [1] [this video]

Consider reading/watching Rich Hickey's talk Effective Programs [0][1] and Maybe Not [2][3] In [0] in particular there're slides 22/23, here is part of the transcript but makes more sense with the slides on: > And you can call them problems, and I'm going to call them the problems of programming. And I've ordered them here [...] I've ordered them here in terms of severity. And severity manifests itself in a couple of ways. Most important, cost. What's the cost of getting this wrong? At the very top you have the domain complexity, about which you could do nothing. This is just the world. It's as complex as it is. > > But the very next level is the where we start programming, right? We look at the world and say, "I've got an idea about how this is and how it's supposed to be and how, you know, my program can be effective about addressing it". And the problem is, if you don't have a good idea about how the world is, or you can't map that well to a solution, everything downstream from that is going to fail. There's no surviving this misconception problem. And the cost of dealing with misconceptions is incredibly high. > >So this is 10x, a full order of magnitude reduction in (?) severity before we get to the set of problems I think are more in the domain of what programming languages can help with, right? And because you can read these they'll all going to come up in a second as I go through each one on some slide so I'm not going to read them all out right now. But importantly t

I don't find that too surprising, Rich tends to let things bake internally (in his head and at Cognitect) for a while before releasing anything publicly for consumption and feedback. Most of Clojure's current development is around tooling [1] and some changes to move clojure.spec out of alpha. I believe they want to accomplish this for 1.10, but I'm not sure where I remember hearing that. Alex Miller has mentioned that Cognitect built and continues to work on a tool that tracks all of your functions with spec definitions and generatively tests them only when the function or one of its dependencies changes. This would be extremely helpful since generative testing can be expensive to run, especially if you want to generate huge amounts of test cases. It'd be nice to say "test all of my codebase's functions 10 million times" and then have that information stored locally with the code. In Rich's "Effective Programs" talk [2] he outlines the "10x problems" that Clojure was targeted at solving. In it there are two 10x problems that weren't solved by Clojure: resource utilization and libraries. There's not much Clojure can do to solve resource utilization as it's dependent on the host (JVM), but the library problem (especially Clojure libraries with spec definitions) is solvable (though there seems to be some disagreement on whether only allowing growth in libraries in a practical). Pure speculation: All of their tooling projects (spec, codec, tool.deps, and the above mentioned gene

As mentioned, types are in the standard, and certain implementations provide compile time warnings of type and other issues...[0] The biggest non-feature advantage (the condition system is a pretty big feature though missing from everything else) is the mindset of writing programs, which other dynamic languages typically don't get right. The idea of "growing" a program, and responding to change, is part of that mindset and once it's internalized a lot of the language decisions make a lot more sense. e.g. "trace", "break", "compile" are all part of the standard, all available at runtime, whereas in other languages you tend to have a separation of the runtime from any "IDE feature" like debugging break points, tracing function calls, and compiling (not "eval"ing) new code. Other languages + IDEs are getting there but there's so much more to go. In Java land, with the support of things like JRebel, we can make pretty significant modifications to a running program like add/change/remove methods to a class. But what about any existing objects I may have instantiated? Those are left around, referring to the old code. In Lisp, redefining classes works out of the box (no need to wait decades for JRebel to show up), and "update-instance-for-redefined-class" is a standard generic function, which you can write a version of to handle conversion of existing objects. No mysterious old versions of objects running around, you didn't have to bring down the program to restart it, nice. It's a

Honestly, I think this series of blog posts could have had a more complete title: "Principals of Data Oriented Programming (aka, Idiomatic Clojure) " All of these ideas (and I think they are good ones) are inspired heavily by Rich Hickey's talks and rational behind developing the Clojure language (the author of the post states as much). And while you can use these techniques in other languages/paradigms/problem domains, they are really intended to work well inside the constructs of Clojure, and when applied to "information-driven situated programs" [0] (read business applications with dynamic requirements). As for some of the short-comings you mentioned: "But you still need a mechanism to manage mutating data" Clojure supports this through the use of locking constructs like atoms. [1] "I think what it's getting at is that you don't really know the precise type of your data, over time, in a distributed system, so it's good to include the flexibility to handle that. That makes sense to me. but generic data structures aren't necessarily always the right way to handle that." Clojure attempts to bridge the gap between generic data-structures and strongly-typed constructs using run-time specifications. [2] I mean, the ideas presented here can be generally useful, but your mileage may vary if the principals take you too far out of the idiomatic for your particular language/paradigm/problem domain. If that's the case, you could find yourself wasting energy swimming up stream. [0] - [