I'm not sure these projects will ever "go anywhere," but at the very least I'm honing my craft as a programmer. I've learned so much, and I have so much more to learn.
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100 karma · joined December 17, 2018
I'm not sure these projects will ever "go anywhere," but at the very least I'm honing my craft as a programmer. I've learned so much, and I have so much more to learn.
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The repo includes a fairly full test suite as well as examples that demonstrate multi-process communication between CLIPS rules engines.
My purpose in providing this library (and other CLIPS libraries I've released) is to expand the usecases in which CLIPS can be leveraged. Feedback welcome.
This article caught my eye because it's focused on imperative programming, and I've been very focused on declarative vs imperative programming over the last few years. I implemented a version of your function in CLIPS, a Rules-based language that takes a declarative approach to code:
(defrule sum-is-0 (list $? ?first $? ?second $?) (test (= 0 (+ ?first ?second))) => (println TRUE))
(defrule sum-is-not-0 (not (and (list $? ?first $? ?second $?) (test (= 0 (+ ?first ?second))))) => (println FALSE))
(assert (list 1 0 2 -1)) (run) (exit)
The theorem you write in Lean to prove the function kind-of exists in CLIPS Rules; you define the conditions that must occur in order to execute the Right Hand Side of the Rule. Note that the above simply prints `TRUE` or `FALSE`; it is possible to write imperative `deffunction`s that return values in CLIPS, but I wanted to see if I could draw parallels for myself between Lean code and theorems. Here's a gist with the simple version and a slightly more robust version that describes the index at which the matching numbers appear: https://gist.github.com/mrryanjohnston/680deaee87533dfedc74b...
Thank you for writing this and for your work on Lean! This is a concept that's been circling in my head for a minute now, and I feel like this article has unlocked some level of understanding I was missing before.
Location: Pittsburgh, Pa
Remote: Yes
Willing to relocate: No
Technologies: CLIPS, Ruby (on Rails), Go, JavaScript, C, SQL
Résumé: https://drive.google.com/file/d/1M-tC7qpehmsJfd3JBk3KtXEQ5wDJz89t
Email: mrryanjohnston (at) gmail
Website: https://ryjo.codes
12+ years of experience writing code professionally, active in open source, passionate about education and freedom of knowledge. Very interested in Rules Engines. Love working on teams of self-starters, enjoy pushing the boundaries of my understanding. Comfortable mentoring others as well as helping non-technical folks with difficult-to-grok concepts.If you haven't seen it, here's a past post that got some good traction on HN that you might find interesting: https://news.ycombinator.com/item?id=40201729
> Conventional programming languages, such as FORTRAN and C, are designed and optimized for the procedural manipulation of data (such as numbers and arrays). Humans, however, often solve complex problems using very abstract, symbolic approaches which are not well suited for implementation in conventional languages. Although abstract information can be modeled in these languages, considerable programming effort is required to transform the information to a format usable with procedural programming paradigms.
> One of the results of research in the area of artificial intelligence has been the development of techniques which allow the modeling of information at higher levels of abstraction. These techniques are embodied in languages or tools which allow programs to be built that closely resemble human logic in their implementation and are therefore easier to develop and maintain. These programs, which emulate human expertise in well defined problem domains, are called expert systems. The availability of expert system tools has greatly reduced the effort and cost involved in developing an expert system.
You also touch on something in this article that I've found quite powerful: putting things in terms of digesting an input string character-by-character. Then, we offload all of the reasoning logic to our algorithm. We write very thin i/o logic, and then the algorithm does the rest.
Using debuggers makes a lot of sense in this case. If I had to switch context that frequently between relatively stable applications, it would be helpful to have a debugger framework for doing work.
`printf` statements are helpful when the error exists beneath the debugger: in the application framework itself.
> they're not always available
100% agreed. `printf` is "one tool" I can use to follow the control flow of a function call across frameworks, programming languages, and even operating systems. It's also something I can reliably assume my coworkers have in their tool belt, and thus provides a common language that even multiple different organizations can use to cross-collaborate a specific debugging session.
Precisely!
This is a great use case! I'd be interested in seeing what you come up with.
> in which format the code/rule-base is kept
When you use constructs-to-c, the generated C files represent your rules engine constructs as pointers to pointers of CLIPSLexeme, CLIPSFloat, CLIPSInteger, and CLIPSBitMap structs. It does not store it as the raw clips code fed into the interpreter. You can later use functions like `save-facts` to generate the rules in CLIPS syntax based on these pointers to pointers of structs.
When you compile your code including the c files generated by the constructs-to-c command, you must update the main.c file as well as the makefile that ships with CLIPS. During that update, there are a few things you must do:
1. add the generated c files to the makefile 2. you remove the function calls in the main.c file that cause CLIPS to capture STDIN and STDOUT. That is: you remove one layer of abstraction that sits between your rules and i/o streams. 3. you remove the generic CreateEnvironment function call in main.c and replace it with InitCImage_1, a function that calls CreateRuntimeEnvironment.
CreateRuntimeEnvironment differs from CreateEnvironment because you are able to pass in pre-built:
1. symbolTable 2. floatTable 3. integerTable 4. bitmapTable
Which are your rules engine constructs represented in C.
In addition to these four things, CreateRuntimeEnvironment passes in functions the user may have defined as UserDefinedFunctions (UDFs) in C. This is a more direct path than having CLIPS first interpret CLIPS rules like `(defrule foo =>)` and then translate them into these C representations.
> you have seemed to use it more for "indexing" and "caching", which is a domain shared by other interpreters used for the web
That's the idea! I think CLIPS is a good framework for a generic run-loop (or `while` loop). If you can conceptualize your app as such, you can reap the benefits inherent in the rete algorithm within your application logic.
To see what I mean, take a look at the tcp server in the CLIPSockets repo: https://github.com/mrryanjohnston/CLIPSockets/blob/6.4.1/exa...
UPDATE: I edited the link to point to the 6.4.1 tag version of the repo. The `main` branch is using the latest (7.x) from CLIPS svn as the base.
UPDATE2: I edited my previous comment to specify that it is a tcp server, not an http server.
As to this point: I don't at present have "real world" experience writing CLIPS. My experience thus far has been entirely research-driven based on observations I've made in "real world" scenarios.
If you want to read about some other people who have used CLIPS in real world scenarios, here's the most comprehensive HN thread to date so far on the subject:
https://news.ycombinator.com/item?id=40201729 - 30 days ago
One in particular that stands out to me is the usage of CLIPS in MTG:Arena, a real-time web-based card game with and arguably large amount of rules.
If I'm understanding your meaning, you mean "interpreted" in a sense that it translates to C code, and C code is interpreted and translated into machine code. Is that accurate?
It's possible that you and I are referring to different things when we use the word "interpreted." When I think "interpreted" in the context of computer programming, I'm thinking in terms of interpreted-at-runtime programming languages like Ruby, Python, and CLIPS before you use `constructs-to-c`. In my mind, using `constructs-to-c` changes this from an "interpreted" to a "compiled" language in that the expert system you write in CLIPS code is its own language with its own data structures, algorithms, and DSL. When you use `constructs-to-c`, you "compile" your application using the programming language of your expert system, thus it is no longer interpreted at run time.
Yes
> But does this actually give a speed-up?
There is an objective benefit to using `constructs-to-c` and that is something you mention in your original comment: you generate a single binary file containing all of your business logic, thus avoiding running a "fully interpreted" app in production.
In order to determine if it gives a performance boost to your particular rules engine, you should test it out and benchmark it with something you'd consider a "real world" example.
Music to my ears :) thanks for sharing this!
- pattern matching - custom DSL - caching
I find it difficult to summarize in an "elevator pitch," and I only started seeing things fall into place after trying to use it in earnest on my own. I highly recommend reading the CLIPS documentation posted on the main CLIPS website. The PDFs are long, but quite complete and well written.
Self promotion: If you prefer something a little more interactive, check out the Tour of CLIPS I made: https://ryjo.codes/tour-of-clips.html
Just a heads up: this is not light reading. Rules-based programming is a confusing departure from traditional programming; there's more "magic" involved, similar to convention-over-configutation in other languages/frameworks. The benefits outweigh the upfront learning cost, though.
Here is a recent post on HN that recently got some traction and has some pretty good discussions: Tour of CLIPS (2022) - https://news.ycombinator.com/item?id=40201729
If anyone is working directly with CLIPS, let me know! I'm actively working on a low level networking library called CLIPSockets, and would like to work with the language full time some day.
CLIPSockets: Clips low-level socket implementation - https://news.ycombinator.com/item?id=40300303
> So first, a quick summary of how the rules engine works. When a game of Magic is in progress on MTG Arena, the program that is tracking the state of the game and enforcing all the rules-correct card interactions is called the Game Rules Engine (GRE). It's one of the two main programs that we work on. It's written in a combination of C++ and a language called CLIPS, which is a variant of LISP.
Also for your consideration, clipspy, which exposes CLIPS in Python: https://github.com/noxdafox/clipspy
You bring up something awesome about CLIPS: it's easy to tailor it to your needs. Once you have your CLIPS code, you can trim out the parts you don't need using compiler flags. Once you have a compiled `clips` binary with only the constructs you need (defrules and deffacts, maybe?), you can execute it, load your rules/facts into the engine, and then generate C code for your specific rules engine. This compiles into an even smaller/faster binary. You can do all of this from within CLIPS proper. Check out the Advanced Progamming Guide section 11: Creating a CLIPS Run-time Program https://www.clipsrules.net/documentation/v641/apg641.pdf