Table of Contents

1. Thread Local storage exhausted
2. The layer of indirection
3. I can fix her
4. Let's write some tests!
5. Summary

Thread Local storage exhausted

In the last post I've described a technique to use dynamic variables by value instead of the name by utilizing the operator PROGV. Apparently it works fine on all Common Lisp implementations I've tried except from SBCL, where the number of thread local variables is by default limited to something below 4000. To add salt to the injury, these variables are not garbage collected.

Try the following code to crash into LDB:

(defun foo ()
  (loop for i from 0 below 4096 do
    (when (zerop (mod i 100))
      (print i))
    (progv (list (gensym)) (list 42)
      (values))))
(foo)

This renders our new technique not very practical given SBCL popularity. We need to either abandon the idea or come up with a workaround.

The layer of indirection

Luckily for us we've already introduced a layer of indirection. Operators to access dynamic variables are called DLET, DSET and DREF. This means, that it is enough to provide a kludge implementation for SBCL with minimal changes to the remaining code.

The old code works the same as previously except that instead of SYMBOL-VALUE we use the accessor DYNAMIC-VARIABLE-VALUE, and the old call to PROGV is now DYNAMIC-VARIABLE-PROGV. Moreover DYNAMIC-EFFECTIVE-SLOT used functions BOUNDP and MAKUNBOUND, so we replace these with DYNAMIC-VARIABLE-BOUND-P and DYNAMIC-VARIABLE-MAKUNBOUND. To abstract away things further we also introduce the constructor MAKE-DYNAMIC-VARIABLE

(defpackage "EU.TURTLEWARE.BLOG/DLET"
  (:local-nicknames ("MOP" #+closer-mop "C2MOP"
                           #+(and (not closer-mop) ecl) "MOP"
                           #+(and (not closer-mop) ccl) "CCL"
                           #+(and (not closer-mop) sbcl) "SB-MOP"))
  (:use "CL"))
(in-package "EU.TURTLEWARE.BLOG/DLET")

(eval-when (:compile-toplevel :execute :load-toplevel)
  (unless (member :bordeaux-threads *features*)
    (error "Please load BORDEAUX-THREADS."))
  (when (member :sbcl *features*)
    (unless (member :fake-progv-kludge *features*)
      (format t "~&;; Using FAKE-PROGV-KLUDGE for SBCL.~%")
      (push :fake-progv-kludge *features*))))

(defmacro dlet (bindings &body body)
  (flet ((pred (binding)
           (and (listp binding) (= 2 (length binding)))))
    (unless (every #'pred bindings)
      (error "DLET: bindings must be lists of two values.~%~
                Invalid bindings:~%~{ ~s~%~}" (remove-if #'pred bindings))))
  (loop for (var val) in bindings
        collect var into vars
        collect val into vals
        finally (return `(dynamic-variable-progv (list ,@vars) (list ,@vals)
                           ,@body))))

(defmacro dset (&rest pairs)
  `(setf ,@(loop for (var val) on pairs by #'cddr
                 collect `(dref ,var)
                 collect val)))

(defmacro dref (variable)
  `(dynamic-variable-value ,variable))

;;; ...

(defmethod mop:slot-boundp-using-class
    ((class standard-class)
     object
     (slotd dynamic-effective-slot))
  (dynamic-variable-bound-p (slot-dvar object slotd)))

(defmethod mop:slot-makunbound-using-class
    ((class standard-class)
     object
     (slotd dynamic-effective-slot))
  (dynamic-variable-makunbound (slot-dvar object slotd)))

With these in place we can change the portable implementation to conform.

#-fake-progv-kludge
(progn
  (defun make-dynamic-variable ()
    (gensym))

  (defun dynamic-variable-value (variable)
    (symbol-value variable))

  (defun (setf dynamic-variable-value) (value variable)
    (setf (symbol-value variable) value))

  (defun dynamic-variable-bound-p (variable)
    (boundp variable))

  (defun dynamic-variable-makunbound (variable)
    (makunbound variable))

  (defmacro dynamic-variable-progv (vars vals &body body)
    `(progv ,vars ,vals ,@body)))

I can fix her

The implementation for SBCL will mediate access to the dynamic variable value with a synchronized hash table with weak keys. The current process is the key of the hash table and the list of bindings is the value of the hash table. For compatibility between implementations the top level value of the symbol will be shared.

The variable +FAKE-UNBOUND+ is the marker that signifies, that the variable has no value. When the list of bindings is EQ to +CELL-UNBOUND+, then it means that we should use the global value. We add new bindings by pushing to it.

#+fake-progv-kludge
(progn
  (defvar +fake-unbound+ 'unbound)
  (defvar +cell-unbound+ '(no-binding))

  (defclass dynamic-variable ()
    ((tls-table
      :initform (make-hash-table :synchronized t :weakness :key)
      :reader dynamic-variable-tls-table)
     (top-value
      :initform +fake-unbound+
      :accessor dynamic-variable-top-value)))

  (defun make-dynamic-variable ()
    (make-instance 'dynamic-variable))

  (defun dynamic-variable-bindings (dvar)
    (let ((process (bt:current-thread))
          (tls-table (dynamic-variable-tls-table dvar)))
      (gethash process tls-table +cell-unbound+)))

  (defun (setf dynamic-variable-bindings) (value dvar)
    (let ((process (bt:current-thread))
          (tls-table (dynamic-variable-tls-table dvar)))
      (setf (gethash process tls-table +cell-unbound+) value))))

We define two readers for the variable value - one that simply reads the value, and the other that signals an error if the variable is unbound. Writer for its value either replaces the current binding, or if the value cell is unbound, then we modify the top-level symbol value. We use the value +FAKE-UNBOUND+ to check whether the variable is bound and to make it unbound.

#+fake-progv-kludge
(progn
  (defun %dynamic-variable-value (dvar)
    (let ((tls-binds (dynamic-variable-bindings dvar)))
      (if (eq tls-binds +cell-unbound+)
          (dynamic-variable-top-value dvar)
          (car tls-binds))))

  (defun dynamic-variable-value (dvar)
    (let ((tls-value (%dynamic-variable-value dvar)))
      (when (eq tls-value +fake-unbound+)
        (error 'unbound-variable :name "(unnamed)"))
      tls-value))

  (defun (setf dynamic-variable-value) (value dvar)
    (let ((tls-binds (dynamic-variable-bindings dvar)))
      (if (eq tls-binds +cell-unbound+)
          (setf (dynamic-variable-top-value dvar) value)
          (setf (car tls-binds) value))))

  (defun dynamic-variable-bound-p (dvar)
    (not (eq +fake-unbound+ (%dynamic-variable-value dvar))))

  (defun dynamic-variable-makunbound (dvar)
    (setf (dynamic-variable-value dvar) +fake-unbound+)))

Finally we define the operator to dynamically bind variables that behaves similar to PROGV. Note that we PUSH and POP from the thread-local hash table DYNAMIC-VARIABLE-BINDINGS, so no synchronization is necessary.

#+fake-progv-kludge
(defmacro dynamic-variable-progv (vars vals &body body)
  (let ((svars (gensym))
        (svals (gensym))
        (var (gensym))
        (val (gensym)))
    `(let ((,svars ,vars))
       (loop for ,svals = ,vals then (rest ,svals)
             for ,var in ,svars
             for ,val = (if ,svals (car ,svals) +fake-unbound+)
             do (push ,val (dynamic-variable-bindings ,var)))
       (unwind-protect (progn ,@body)
         (loop for ,var in ,svars
               do (pop (dynamic-variable-bindings ,var)))))))

Let's write some tests!

But of course, we are going to also write a test framework. It's short, I promise. As a bonus point the API is compatibile with fiveam, so it is possible to drop tests as is in the appropriate test suite.

(defvar *all-tests* '())

(defun run-tests ()
  (dolist (test (reverse *all-tests*))
    (format *debug-io* "Test ~a... " test)
    (handler-case (funcall test)
      (serious-condition (c)
        (format *debug-io* "Failed: ~a~%" c))
      (:no-error (&rest args)
        (declare (ignore args))
        (format *debug-io* "Passed.~%")))))

(defmacro test (name &body body)
  `(progn
     (pushnew ',name *all-tests*)
     (defun ,name () ,@body)))

(defmacro is (form)
  `(assert ,form))

(defmacro pass ())

(defmacro signals (condition form)
  `(is (block nil
         (handler-case ,form
           (,condition () (return t)))
         nil)))

(defmacro finishes (form)
  `(is (handler-case ,form
         (serious-condition (c)
           (declare (ignore c))
           nil)
         (:no-error (&rest args)
           (declare (ignore args))
           t))))

Now let's get to tests. First we'll test our metaclass:

(defclass dynamic-let.test-class ()
  ((slot1 :initarg :slot1 :dynamic nil :accessor slot1)
   (slot2 :initarg :slot2 :dynamic t   :accessor slot2)
   (slot3 :initarg :slot3              :accessor slot3))
  (:metaclass class-with-dynamic-slots))

(defparameter *dynamic-let.test-instance-1*
  (make-instance 'dynamic-let.test-class
                 :slot1 :a :slot2 :b :slot3 :c))

(defparameter *dynamic-let.test-instance-2*
  (make-instance 'dynamic-let.test-class
                 :slot1 :x :slot2 :y :slot3 :z))

(test dynamic-let.1
  (let ((o1 *dynamic-let.test-instance-1*)
        (o2 *dynamic-let.test-instance-2*))
    (with-slots (slot1 slot2 slot3) o1
      (is (eq :a slot1))
      (is (eq :b slot2))
      (is (eq :c slot3)))
    (with-slots (slot1 slot2 slot3) o2
      (is (eq :x slot1))
      (is (eq :y slot2))
      (is (eq :z slot3)))))

(test dynamic-let.2
  (let ((o1 *dynamic-let.test-instance-1*)
        (o2 *dynamic-let.test-instance-2*))
    (signals error (slot-dlet (((o1 'slot1) 1)) nil))
    (slot-dlet (((o1 'slot2) :k))
      (is (eq :k (slot-value o1 'slot2)))
      (is (eq :y (slot-value o2 'slot2))))))

(test dynamic-let.3
  (let ((o1 *dynamic-let.test-instance-1*)
        (exit nil)
        (fail nil))
    (flet ((make-runner (values)
             (lambda ()
               (slot-dlet (((o1 'slot2) :start))
                 (let ((value (slot2 o1)))
                   (unless (eq value :start)
                     (setf fail value)))
                 (loop until (eq exit t) do
                   (setf (slot2 o1) (elt values (random (length values))))
                   (let ((value (slot2 o1)))
                     (unless (member value values)
                       (setf fail value)
                       (setf exit t))))))))
      (let ((r1 (bt:make-thread (make-runner '(:k1 :k2))))
            (r2 (bt:make-thread (make-runner '(:k3 :k4))))
            (r3 (bt:make-thread (make-runner '(:k5 :k6)))))
        (sleep .1)
        (setf exit t)
        (map nil #'bt:join-thread (list r1 r2 r3))
        (is (eq (slot2 o1) :b))
        (is (null fail))))))

Then let's test the dynamic variable itself:

(test dynamic-let.4
  "Test basic dvar operators."
  (let ((dvar (make-dynamic-variable)))
    (is (eql 42 (dset dvar 42)))
    (is (eql 42 (dref dvar)))
    (ignore-errors
     (dlet ((dvar :x))
       (is (eql :x (dref dvar)))
       (error "foo")))
    (is (eql 42 (dref dvar)))))

(test dynamic-let.5
  "Test bound-p operator."
  (let ((dvar (make-dynamic-variable)))
    (is (not (dynamic-variable-bound-p dvar)))
    (dset dvar 15)
    (is (dynamic-variable-bound-p dvar))
    (dynamic-variable-makunbound dvar)
    (is (not (dynamic-variable-bound-p dvar)))))

(test dynamic-let.6
  "Test makunbound operator."
  (let ((dvar (make-dynamic-variable)))
    (dset dvar t)
    (is (dynamic-variable-bound-p dvar))
    (finishes (dynamic-variable-makunbound dvar))
    (is (not (dynamic-variable-bound-p dvar)))))

(test dynamic-let.7
  "Test locally bound-p operator."
  (let ((dvar (make-dynamic-variable)))
    (is (not (dynamic-variable-bound-p dvar)))
    (dlet ((dvar 15))
      (is (dynamic-variable-bound-p dvar)))
    (is (not (dynamic-variable-bound-p dvar)))))

(test dynamic-let.8
  "Test locally unbound-p operator."
  (let ((dvar (make-dynamic-variable)))
    (dset dvar t)
    (is (dynamic-variable-bound-p dvar))
    (dlet ((dvar nil))
      (is (dynamic-variable-bound-p dvar))
      (finishes (dynamic-variable-makunbound dvar))
      (is (not (dynamic-variable-bound-p dvar))))
    (is (dynamic-variable-bound-p dvar))))

(test dynamic-let.9
  "Stress test the implementation (see :FAKE-PROGV-KLUDGE)."
  (finishes                              ; at the same time
    (let ((dvars (loop repeat 4096 collect (make-dynamic-variable))))
      ;; ensure tls variable
      (loop for v in dvars do
        (dlet ((v 1))))
      (loop for i from 0 below 4096
            for r = (random 4096)
            for v1 in dvars
            for v2 = (elt dvars r) do
              (when (zerop (mod i 64))
                (pass))
              (dlet ((v1 42)
                     (v2 43))
                (values))))))

(test dynamic-let.0
  "Stress test the implementation (see :FAKE-PROGV-KLUDGE)."
  (finishes                             ; can be gc-ed
    (loop for i from 0 below 4096 do
      (when (zerop (mod i 64))
        (pass))
      (dlet (((make-dynamic-variable) 42))
        (values)))))

All that is left is to test both dynamic variable implementations:

BLOG/DLET> (lisp-implementation-type)
"ECL"
BLOG/DLET> (run-tests)
Test DYNAMIC-LET.1... Passed.
Test DYNAMIC-LET.2... Passed.
Test DYNAMIC-LET.3... Passed.
Test DYNAMIC-LET.4... Passed.
Test DYNAMIC-LET.5... Passed.
Test DYNAMIC-LET.6... Passed.
Test DYNAMIC-LET.7... Passed.
Test DYNAMIC-LET.8... Passed.
Test DYNAMIC-LET.9... Passed.
Test DYNAMIC-LET.0... Passed.
NIL

And with the kludge:

BLOG/DLET> (lisp-implementation-type)
"SBCL"
BLOG/DLET> (run-tests)
Test DYNAMIC-LET.1... Passed.
Test DYNAMIC-LET.2... Passed.
Test DYNAMIC-LET.3... Passed.
Test DYNAMIC-LET.4... Passed.
Test DYNAMIC-LET.5... Passed.
Test DYNAMIC-LET.6... Passed.
Test DYNAMIC-LET.7... Passed.
Test DYNAMIC-LET.8... Passed.
Test DYNAMIC-LET.9... Passed.
Test DYNAMIC-LET.0... Passed.
NIL

Summary

In this post we've made our implementation to work on SBCL even when there are more than a few thousand dynamic variables. We've also added a simple test suite that checks the basic behavior.

As it often happens, after achieving some goal we get greedy and achieve more. That's the case here as well. In the next (and the last) post in this series I'll explore the idea of adding truly thread-local variables without a shared global value. This will be useful for lazily creating context on threads that are outside of our control. We'll also generalize the implementation so it is possible to subclass and implement ones own flavor of a dynamic variable.

28 Oct 2024 12:00am GMT

Last week I finished a new service written in Common Lisp. It now runs in production© every mornings, and it expands the set of services I offer to clients.

It's the 4th service of this kind that I developed: - they are not big - but have to be done nonetheless, and the quicker the better (they each amount to 1k to 2k lines of Lisp code), - they are not part of a super advanced domain that requires Common Lisp superpowers - I am the one who benefits from CL during development, - I could have written them in Python - and conversely nothing prevented me from writing them in Common Lisp.

So here lies the goal of this post: illustrate that you don't need to need a super difficult problem to use Common Lisp. This has been asked many times, directly to me or on social media :)

At the same time, I want to encourage you to write a little something about how you use Common Lisp in the real world. Sharing creates emulation. Do it! If you don't have a blog you can simply write in a new GitHub repository or in a Gist and come share on /r/lisp. We don't care. Thanks <3

We'll briefly see what my scripts do, what libraries I use, how I deploy them, what I did along the way.

Needless to say that I dogfooded my CIEL (beta) meta-library and scripting tool for all those projects.

Table of Contents

• Scripts n°4 and 2 - shaping and sending data - when you can write Lisp on the side
  • SFTP
  • Deploying
  • Script n°2 and simple FTP
• Scripts n°3 and 1 - complementary web apps
• Lasting words
• Links

Scripts n°4 and 2 - shaping and sending data - when you can write Lisp on the side

My latest script needs to read data from a DB, format what's necessary according to specifications, and send the result by SFTP.

In this case I read a DB that I own, created by a software that I develop and host. So I could have developed this script in the software itself, right? I could have, but I would have been tied to the main project's versioning scheme, quirks, and deployment. I rather had to write this script on the side. And since it can be done on the side, it can be done in Common Lisp.

I have to extract products and their data (price, VAT...), aggregate the numbers for each day, write this to a file, according to a specification.

To read the DB, I used cl-dbi. I didn't format the SQL with SxQL this time like in my web apps (where I use the Mito light ORM), but I wrote SQL directly. I'm spoiled by the Django ORM (which has its idiosyncrasies and shortcomings), so I double checked the different kinds of JOINs and all went well.

I had to group rows by some properties, so it was a great time to use serapeum:assort. I left you an example here: https://dev.to/vindarel/common-lisps-group-by-is-serapeumassort-32ma

Dates have to be handled in different formats. I used local-time of course, and I still greatly appreciate its lispy formatter syntax:

(defun date-yymmddhhnnss (&optional date stream)
  (local-time:format-timestring stream
                                (or date (local-time:now))
                                :format
                                '((:year 4)
                                  (:month 2)
                                  (:day 2)
                                  (:hour 2)
                                  (:min 2)
                                  (:sec 2)
                                  )))

the 2 in (:month 2) is to ensure the month is written with 2 digits.

Once the file is written, I have to send it to a SFTP server, with the client's codes.

I wrote a profile class to encapsulate the client's data as well as some functions to read the credentials from either environment variables, the file system, or a lisp variable. I had a top-level profile object for ease of testing, but I made sure that my functions formatting or sending data required a profile parameter.

(defun send-stock (profile &key date) ...)
(defun write-stock (profile filename) ...)

Still nothing surprising, but it's tempting to only use global parameters for a one-off script. Except the program grows and you pay the mess later.

SFTP

To send the result through SFTP, I had to make a choice. The SFTP command line doesn't make it possible to give a password as argument (or via an environment variable, etc). So I use lftp (in Debian repositories) that allows to do that. In the end, we format a command like this:

lftp sftp://user:****@host  -e "CD I/; put local-file.name; bye"

You can format the command string and run it with uiop:run-program: no problem, but I took the opportunity to release another utility:

• https://github.com/vindarel/lftp-wrapper

First, you create a profile object. This one-liner reads the credentials from a lispy file:

(defvar profile (make-profile-from-plist (uiop:read-file-form "CREDS.lisp-expr"))

then you define the commands you'll want to run:

(defvar command (put :cd "I/" :local-filename "data.csv"))
;; #<PUT cd: "I/", filename: "data.csv" {1007153883}>

and finally you call the run method on a profile and a command. Tada.

Deploying

Build a binary the classic way (it's all on the Cookbook), send it to your server, run it.

(during a testing phase I have deployed "as a script", from sources, which is a bit quicker to pull changes and try again on the server)

Set up a CRON job.

No Python virtual env to activate in the CRON environment...

Add command line arguments the easy way or with the library of your choice (I like Clingon).

Script n°2 and simple FTP

My script #2 at the time was similar and simpler. I extract the same products but only take their quantities, and I assemble lines like

EXTRACTION STOCK DU 11/04/2008
....978202019116600010000001387
....978270730656200040000000991

For this service, we have to send the file to a simple FTP server.

We have a pure Lisp library for FTP (and not SFTP) which works very well, cl-ftp.

It's a typical example of an old library that didn't receive any update in years and so that looks abandoned, that has seldom documentation but whose usage is easy to infer, and that does its job as requested.

For example we do this to send a file:

(ftp:with-ftp-connection (conn :hostname hostname
                                   :username username
                                   :password password
                                   :passive-ftp-p t)
      (ftp:store-file conn local-filename filename))

I left you notes about cl-ftp and my SFTP wrapper here:

• https://dev.to/vindarel/ftp-and-sftp-clients-for-common-lisp-1c3b

Scripts n°3 and n°1 - specialized web apps

A recent web app that I'm testing with a couple clients extends an existing stock management system.

This one also was done in order to avoid a Python monolith. I still needed additions in the Python main software, but this little app can be independent and grow on its own. The app maintains its state and communicates it with a REST API.

It gives a web interface to their clients (so my clients' clients, but not all of them, only the institutional) so that they can:

• search for products
• add them in shopping carts
• validate the cart, which sends the data to the main software and notifies the owner, who will work on them.

The peculiarities of this app are that:

• there is no user login, we use unique URLs with UUIDs in the form: http://command.client.com/admin-E9DFOO82-R2D2-007/list?id=1
• I need a bit of file persistence but I didn't want the rigidity of a database so I am using the clache library. Here also, not a great activity, but it works©. I persist lists and hash-tables. Now that the needs grow and the original scope doesn't cut it any more, I wonder how long I'll survive without a DB. Only for its short SQL queries VS lisp code to filter data.

I deploy a self-contained binary: code + html templates in the same binary (+ the implementation, the web server, the debugger...), with Systemd.

I wrote more on how to ship a standalone binary with templates and static assets with Djula templates here:

• https://lisp-journey.gitlab.io/blog/lisp-for-the-web-build-standalone-binaries-foreign-libraries-templates-static-assets/

I can connect to the running app with a Swank server to check and set parameters, which is super helpful and harmless.

It is possible to reload the whole app from within itself and I did it with no hiccups for a couple years, but it isn't necessary the most reliable, easiest to set up and fastest method. You can do it, but nobody forces you to do this because you are running CL in production. You can use the industry's boring and best practices too. Common Lisp doesn't inforce a "big ball of mud" approach. Develop locally, use Git, use a CI, deploy a binary...

Every thing that I learned I documented it along the way in the Cookbook ;)

Another app that I'll mention but about which I also wrote earlier is my first web app. This one is open-source. It still runs :)

In this project I had my friend and colleague contribute five lines of Lisp code to add a theme switcher in the backend that would help him do the frontend. He had never written a line of Lisp before. Of course, he did so by looking at my existing code to learn the existing functions at hand, and he could do it because the project was easy to install and run.

(defun get-template(template &optional (theme *theme*))
  "Loads template from the base templates directory or from the given theme templates directory if it exists."
  (if (and (str:non-blank-string-p theme)
           (probe-file (asdf:system-relative-pathname "abstock" (str:concat "src/templates/themes/" theme "/" template))))
      ;; then
      (str:concat "themes/" theme "/" template)
      ;; else :D
      template))

He had to annotate the if branches :] This passed the code review.

Lasting words

The 5th script/app is already on the way, and the next ones are awaiting that I open their .docx specification files. This one was a bit harder but the Lisp side was done sucessfully with the efficient collaboration of another freelance lisper (Kevin to not name him).

All those tasks (read a DB, transform data...) are very mundane.

They are everywhere. They don't always need supercharged web framework or integrations.

You have plenty of opportunities to make yourself a favor, and use Common Lisp in the wild. Not counting the super-advanced domains where Lisp excels at ;)

Links

• https://lispcookbook.github.io/cl-cookbook/
• awesome-cl
• companies using Common Lisp in production (at least the ones we know)
• Common Lisp course in videos - it helps me, and you ;) I added 9 videos about CLOS last month, and more are coming. It's 86 minutes of an efficient code-first approach, out of 7+ hours of total content in the course. After this chapter you know enough to read the sources of the Hunchentoot web server or of the Kandria game.

I have done some preliminary Common Lisp exploration prior to this course but had a lot of questions regarding practical use and development workflows. This course was amazing for this! I learned a lot of useful techniques for actually writing the code in Emacs, as well as conversational explanations of concepts that had previously confused me in text-heavy resources. Please keep up the good work and continue with this line of topics, it is well worth the price! [Preston, October of 2024]

22 Oct 2024 5:19pm GMT

Table of Contents

1. Dynamic Bindings
2. The problem
3. The solution
4. Dynamic slots
5. The context
6. Summary

Dynamic Bindings

Common Lisp has an important language feature called dynamic binding. It is possible to rebind a dynamic variable somewhere on the call stack and downstream functions will see that new value, and when the stack is unwound, the old value is brought back.

While Common Lisp does not specify multi-threading, it seems to be a consensus among various implementations that dynamic bindings are thread-local, allowing for controlling the computing context in a safe way.

Before we start experiments, let's define a package to isolate our namespace:

(defpackage "EU.TURTLEWARE.BLOG/DLET"
  (:local-nicknames ("MOP" #+closer-mop "C2MOP"
                           #+(and (not closer-mop) ecl) "MOP"
                           #+(and (not closer-mop) ccl) "CCL"
                           #+(and (not closer-mop) sbcl) "SB-MOP"))
  (:use "CL"))
(in-package "EU.TURTLEWARE.BLOG/DLET")

Dynamic binding of variables is transparent to the programmer, because the operator LET is used for both lexical and dynamic bindings. For example:

(defvar *dynamic-variable* 42)

(defun test ()
  (let ((*dynamic-variable* 15)
        (lexical-variable 12))
    (lambda ()
      (print (cons *dynamic-variable* lexical-variable)))))

(funcall (test))
;;; (42 . 12)

(let ((*dynamic-variable* 'xx))
  (funcall (test)))
;;; (xx . 12)

Additionally the language specifies a special operator PROGV that gives the programmer a control over the dynamic binding mechanism, by allowing passing the dynamic variable by value instead of its name. Dynamic variables are represented by symbols:

(progv (list '*dynamic-variable*) (list 'zz)
  (funcall (test)))
;;; (zz . 12)

The problem

Nowadays it is common to encapsulate the state in the instance of a class. Sometimes that state is dynamic. It would be nice if we could use dynamic binding to control it. That said slots are not variables, and if there are many objects of the same class with different states, then using dynamic variables defined with DEFVAR is not feasible.

Consider the following classes which we want to be thread-safe:

(defgeneric call-with-ink (cont window ink))

(defclass window-1 ()
  ((ink :initform 'red :accessor ink)))

(defmethod call-with-ink (cont (win window-1) ink)
  (let ((old-ink (ink win)))
    (setf (ink win) ink)
    (unwind-protect (funcall cont)
      (setf (ink win) old-ink))))

(defclass window-2 ()
  ())

(defvar *ink* 'blue)
(defmethod ink ((window window-2)) *ink*)

(defmethod call-with-ink (cont (win window-2) ink)
  (let ((*ink* ink))
    (funcall cont)))

The first example is clearly not thread safe. If we access the WINDOW-1 instance from multiple threads, then they will overwrite a value of the slot INK.

The second example is not good either, because when we have many instances of WINDOW-2 then they share the binding. Nesting CALL-WITH-INK will overwrite the binding of another window.

The solution

The solution is to use PROGV:

(defclass window-3 ()
  ((ink :initform (gensym))))

(defmethod initialize-instance :after ((win window-3) &key)
  (setf (symbol-value (slot-value win 'ink)) 'red))

(defmethod call-with-ink (cont (win window-3) ink)
  (progv (list (slot-value win 'ink)) (list ink)
    (funcall cont)))

This way each instance has its own dynamic variable that may be rebound with a designated operator CALL-WITH-INK. It is thread-safe and private. We may add some syntactic sugar so it is more similar to let:

(defmacro dlet (bindings &body body)
  (loop for (var val) in bindings
        collect var into vars
        collect val into vals
        finally (return `(progv (list ,@vars) (list ,@vals)
                           ,@body))))

(defmacro dset (&rest pairs)
  `(setf ,@(loop for (var val) on pairs by #'cddr
                 collect `(symbol-value ,var)
                 collect val)))

(defmacro dref (variable)
  `(symbol-value ,variable))

Dynamic slots

While meta-classes are not easily composable, it is worth noting that we can mold it better into the language by specifying that slot itself has a dynamic value. This way CLOS aficionados will have a new tool in their arsenal.

The approach we'll take is that a fresh symbol is stored as the value of each instance-allocated slot, and then accessors for the slot value will use these symbols as a dynamic variable. Here are low-level accessors:

;;; Accessing and binding symbols behind the slot. We don't use SLOT-VALUE,
;;; because it will return the _value_ of the dynamic variable, and not the
;;; variable itself.
(defun slot-dvar (object slotd)
  (mop:standard-instance-access
   object (mop:slot-definition-location slotd)))

(defun slot-dvar* (object slot-name)
  (let* ((class (class-of object))
         (slotd (find slot-name (mop:class-slots class)
                      :key #'mop:slot-definition-name)))
    (slot-dvar object slotd)))

(defmacro slot-dlet (bindings &body body)
  `(dlet ,(loop for ((object slot-name) val) in bindings
                 collect `((slot-dvar* ,object ,slot-name) ,val))
     ,@body))

Now we'll define the meta-class. We need that to specialize functions responsible for processing slot definitions and the instance allocation. Notice, that we make use of a kludge to communicate between COMPUTE-EFFECTIVE-SLOT-DEFINITION and EFFECTIVE-SLOT-DEFINITION-CLASS - this is because the latter has no access to the direct slot definitions.

;;; The metaclass CLASS-WITH-DYNAMIC-SLOTS specifies alternative effective slot
;;; definitions for slots with an initarg :dynamic.
(defclass class-with-dynamic-slots (standard-class) ())

;;; Class with dynamic slots may be subclasses of the standard class.
(defmethod mop:validate-superclass ((class class-with-dynamic-slots)
                                    (super standard-class))
  t)

;;; When allocating the instance we initialize all slots to a fresh symbol that
;;; represents the dynamic variable.
(defmethod allocate-instance ((class class-with-dynamic-slots) &rest initargs)
  (declare (ignore initargs))
  (let ((object (call-next-method)))
    (loop for slotd in (mop:class-slots class)
          when (typep slotd 'dynamic-effective-slot) do
            (setf (mop:standard-instance-access
                   object
                   (mop:slot-definition-location slotd))
                  (gensym (string (mop:slot-definition-name slotd)))))
    object))

;;; To improve potential composability of CLASS-WITH-DYNAMIC-SLOTS with other
;;; metaclasses we treat specially only slots that has :DYNAMIC in initargs,
;;; otherwise we call the next method.
(defmethod mop:direct-slot-definition-class
    ((class class-with-dynamic-slots) &rest initargs)
  (loop for (key val) on initargs by #'cddr
        when (eq key :dynamic)
          do (return-from mop:direct-slot-definition-class
               (find-class 'dynamic-direct-slot)))
  (call-next-method))

;;; The metaobject protocol did not specify an elegant way to communicate
;;; between the direct slot definition and the effective slot definition.
;;; Luckily we have dynamic bindings! :-)
(defvar *kludge/mop-deficiency/dynamic-slot-p* nil)
(defmethod mop:compute-effective-slot-definition
    ((class class-with-dynamic-slots)
     name
     direct-slotds)
  (if (typep (first direct-slotds) 'dynamic-direct-slot)
      (let* ((*kludge/mop-deficiency/dynamic-slot-p* t))
        (call-next-method))
      (call-next-method)))

(defmethod mop:effective-slot-definition-class
    ((class class-with-dynamic-slots) &rest initargs)
  (declare (ignore initargs))
  (if *kludge/mop-deficiency/dynamic-slot-p*
      (find-class 'dynamic-effective-slot)
      (call-next-method)))

Finally we define a direct and an effective slot classes, and specialize slot accessors that are invoked by the instance accessors.

;;; There is a considerable boilerplate involving customizing slots.
;;;
;;; - direct slot definition: local to a single defclass form
;;;
;;; - effective slot definition: combination of all direct slots with the same
;;;   name in the class and its superclasses
;;;
(defclass dynamic-direct-slot (mop:standard-direct-slot-definition)
  ((dynamic :initform nil :initarg :dynamic :reader dynamic-slot-p)))

;;; DYNAMIC-EFFECTIVE-SLOT is implemented to return as slot-value values of the
;;; dynamic variable that is stored with the instance.
;;;
;;; It would be nice if we could specify :ALLOCATION :DYNAMIC for the slot, but
;;; then STANDARD-INSTANCE-ACCESS would go belly up. We could make a clever
;;; workaround, but who cares?
(defclass dynamic-effective-slot (mop:standard-effective-slot-definition)
  ())

(defmethod mop:slot-value-using-class
    ((class class-with-dynamic-slots)
     object
     (slotd dynamic-effective-slot))
  (dref (slot-dvar object slotd)))

(defmethod (setf mop:slot-value-using-class)
    (new-value
     (class class-with-dynamic-slots)
     object
     (slotd dynamic-effective-slot))
  (dset (slot-dvar object slotd) new-value))

(defmethod mop:slot-boundp-using-class
  ((class class-with-dynamic-slots)
   object
   (slotd dynamic-effective-slot))
  (boundp (slot-dvar object slotd)))

(defmethod mop:slot-makunbound-using-class
  ((class class-with-dynamic-slots)
   object
   (slotd dynamic-effective-slot))
  (makunbound (slot-dvar object slotd)))

With this, we can finally define a class with slots that have dynamic values. What's more, we may bind them like dynamic variables.

;;; Let there be light.
(defclass window-4 ()
  ((ink :initform 'red :dynamic t :accessor ink)
   (normal :initform 'normal :accessor normal))
  (:metaclass class-with-dynamic-slots))

(let ((object (make-instance 'window-4)))
  (slot-dlet (((object 'ink) 15))
    (print (ink object)))
  (print (ink object)))

ContextL provides a similar solution with dynamic slots, although it provides much more, like layered classes. This example is much more self-contained.

The context

Lately I'm working on the repaint queue for McCLIM. While doing so I've decided to make stream operations thread-safe, so it is possible to draw on the stream and write to it from arbitrary thread asynchronously. The access to the output record history needs to be clearly locked, so that may be solved by the mutex. Graphics state is another story, consider the following functions running from separate threads:

(defun team-red ()
  (with-drawing-options (stream :ink +dark-red+)
    (loop for i from 0 below 50000 do
      (write-string (format nil "XXX: ~5d~%" i) stream))))

(defun team-blue ()
  (with-drawing-options (stream :ink +dark-blue+)
    (loop for i from 0 below 50000 do
      (write-string (format nil "YYY: ~5d~%" i) stream))))

(defun team-pink ()
  (with-drawing-options (stream :ink +deep-pink+)
    (loop for i from 0 below 25000 do
      (case (random 2)
        (0 (draw-rectangle* stream 200 (* i 100) 250 (+ (* i 100) 50)))
        (1 (draw-circle* stream 225 (+ (* i 100) 25) 25))))))

(defun gonow (stream)
  (window-clear stream)
  (time (let ((a (clim-sys:make-process #'team-red))
              (b (clim-sys:make-process #'team-blue))
              (c (clim-sys:make-process #'team-grue)))
          (bt:join-thread a)
          (bt:join-thread b)
          (bt:join-thread c)
          (format stream "done!~%")))  )

Operations like WRITE-STRING and DRAW-RECTANGLE can be implemented by holding a lock over the shared resource without much disruption. The drawing color on the other hand is set outside of the loop, so if we had locked the graphics state with a lock, then these functions would be serialized despite being called from different processes. The solution to this problem is to make graphics context a dynamic slot that is accessed with WITH-DRAWING-OPTIONS.

Summary

I hope that I've convinced you that dynamic variables are cool (I'm sure that majority of readers here are already convinced), and that dynamic slots are even cooler :-). Watch forward to the upcoming McCLIM release!

If you like technical writeups like this, please consider supporting me on Patreon.

22 Oct 2024 12:00am GMT

Table of Contents

1. Dynamic Bindings
2. The problem
3. The solution
4. Dynamic slots
5. The context
6. Summary

Dynamic Bindings

Common Lisp has an important language feature called dynamic binding. It is possible to rebind a dynamic variable somewhere on the call stack and downstream functions will see that new value, and when the stack is unwound, the old value is brought back.

While Common Lisp does not specify multi-threading, it seems to be a consensus among various implementations that dynamic bindings are thread-local, allowing for controlling the computing context in a safe way.

Before we start experiments, let's define a package to isolate our namespace:

(defpackage "EU.TURTLEWARE.BLOG/DLET"
  (:local-nicknames ("MOP" #+closer-mop "C2MOP"
                           #+(and (not closer-mop) ecl) "MOP"
                           #+(and (not closer-mop) ccl) "CCL"
                           #+(and (not closer-mop) sbcl) "SB-MOP"))
  (:use "CL"))
(in-package "EU.TURTLEWARE.BLOG/DLET")

Dynamic binding of variables is transparent to the programmer, because the operator LET is used for both lexical and dynamic bindings. For example:

(defvar *dynamic-variable* 42)

(defun test ()
  (let ((*dynamic-variable* 15)
        (lexical-variable 12))
    (lambda ()
      (print (cons *dynamic-variable* lexical-variable)))))

(funcall (test))
;;; (42 . 12)

(let ((*dynamic-variable* 'xx))
  (funcall (test)))
;;; (xx . 12)

Additionally the language specifies a special operator PROGV that gives the programmer a control over the dynamic binding mechanism, by allowing passing the dynamic variable by value instead of its name. Dynamic variables are represented by symbols:

(progv (list '*dynamic-variable*) (list 'zz)
  (funcall (test)))
;;; (zz . 12)

The problem

Nowadays it is common to encapsulate the state in the instance of a class. Sometimes that state is dynamic. It would be nice if we could use dynamic binding to control it. That said slots are not variables, and if there are many objects of the same class with different states, then using dynamic variables defined with DEFVAR is not feasible.

Consider the following classes which we want to be thread-safe:

(defgeneric call-with-ink (cont window ink))

(defclass window-1 ()
  ((ink :initform 'red :accessor ink)))

(defmethod call-with-ink (cont (win window-1) ink)
  (let ((old-ink (ink win)))
    (setf (ink win) ink)
    (unwind-protect (funcall cont)
      (setf (ink win) old-ink))))

(defclass window-2 ()
  ())

(defvar *ink* 'blue)
(defmethod ink ((window window-2)) *ink*)

(defmethod call-with-ink (cont (win window-2) ink)
  (let ((*ink* ink))
    (funcall cont)))

The first example is clearly not thread safe. If we access the WINDOW-1 instance from multiple threads, then they will overwrite a value of the slot INK.

The second example is not good either, because when we have many instances of WINDOW-2 then they share the binding. Nesting CALL-WITH-INK will overwrite the binding of another window.

The solution

The solution is to use PROGV:

(defclass window-3 ()
  ((ink :initform (gensym))))

(defmethod initialize-instance :after ((win window-3) &key)
  (setf (symbol-value (slot-value win 'ink)) 'red))

(defmethod call-with-ink (cont (win window-3) ink)
  (progv (list (slot-value win 'ink)) (list ink)
    (funcall cont)))

This way each instance has its own dynamic variable that may be rebound with a designated operator CALL-WITH-INK. It is thread-safe and private. We may add some syntactic sugar so it is more similar to let:

(defmacro dlet (bindings &body body)
  (loop for (var val) in bindings
        collect var into vars
        collect val into vals
        finally (return `(progv (list ,@vars) (list ,@vals)
                           ,@body))))

(defmacro dset (&rest pairs)
  `(setf ,@(loop for (var val) on pairs by #'cddr
                 collect `(symbol-value ,var)
                 collect val)))

(defmacro dref (variable)
  `(symbol-value ,variable))

Dynamic slots

While meta-classes are not easily composable, it is worth noting that we can mold it better into the language by specifying that slot itself has a dynamic value. This way CLOS aficionados will have a new tool in their arsenal.

The approach we'll take is that a fresh symbol is stored as the value of each instance-allocated slot, and then accessors for the slot value will use these symbols as a dynamic variable. Here are low-level accessors:

;;; Accessing and binding symbols behind the slot. We don't use SLOT-VALUE,
;;; because it will return the _value_ of the dynamic variable, and not the
;;; variable itself.
(defun slot-dvar (object slotd)
  (mop:standard-instance-access
   object (mop:slot-definition-location slotd)))

(defun slot-dvar* (object slot-name)
  (let* ((class (class-of object))
         (slotd (find slot-name (mop:class-slots class)
                      :key #'mop:slot-definition-name)))
    (slot-dvar object slotd)))

(defmacro slot-dlet (bindings &body body)
  `(dlet ,(loop for ((object slot-name) val) in bindings
                 collect `((slot-dvar* ,object ,slot-name) ,val))
     ,@body))

Now we'll define the meta-class. We need that to specialize functions responsible for processing slot definitions and the instance allocation. Notice, that we make use of a kludge to communicate between COMPUTE-EFFECTIVE-SLOT-DEFINITION and EFFECTIVE-SLOT-DEFINITION-CLASS - this is because the latter has no access to the direct slot definitions.

;;; The metaclass CLASS-WITH-DYNAMIC-SLOTS specifies alternative effective slot
;;; definitions for slots with an initarg :dynamic.
(defclass class-with-dynamic-slots (standard-class) ())

;;; Class with dynamic slots may be subclasses of the standard class.
(defmethod mop:validate-superclass ((class class-with-dynamic-slots)
                                    (super standard-class))
  t)

;;; When allocating the instance we initialize all slots to a fresh symbol that
;;; represents the dynamic variable.
(defmethod allocate-instance ((class class-with-dynamic-slots) &rest initargs)
  (declare (ignore initargs))
  (let ((object (call-next-method)))
    (loop for slotd in (mop:class-slots class)
          when (typep slotd 'dynamic-effective-slot) do
            (setf (mop:standard-instance-access
                   object
                   (mop:slot-definition-location slotd))
                  (gensym (string (mop:slot-definition-name slotd)))))
    object))

;;; To improve potential composability of CLASS-WITH-DYNAMIC-SLOTS with other
;;; metaclasses we treat specially only slots that has :DYNAMIC in initargs,
;;; otherwise we call the next method.
(defmethod mop:direct-slot-definition-class
    ((class class-with-dynamic-slots) &rest initargs)
  (loop for (key val) on initargs by #'cddr
        when (eq key :dynamic)
          do (return-from mop:direct-slot-definition-class
               (find-class 'dynamic-direct-slot)))
  (call-next-method))

;;; The metaobject protocol did not specify an elegant way to communicate
;;; between the direct slot definition and the effective slot definition.
;;; Luckily we have dynamic bindings! :-)
(defvar *kludge/mop-deficiency/dynamic-slot-p* nil)
(defmethod mop:compute-effective-slot-definition
    ((class class-with-dynamic-slots)
     name
     direct-slotds)
  (if (typep (first direct-slotds) 'dynamic-direct-slot)
      (let* ((*kludge/mop-deficiency/dynamic-slot-p* t))
        (call-next-method))
      (call-next-method)))

(defmethod mop:effective-slot-definition-class
    ((class class-with-dynamic-slots) &rest initargs)
  (declare (ignore initargs))
  (if *kludge/mop-deficiency/dynamic-slot-p*
      (find-class 'dynamic-effective-slot)
      (call-next-method)))

Finally we define a direct and an effective slot classes, and specialize slot accessors that are invoked by the instance accessors.

;;; There is a considerable boilerplate involving customizing slots.
;;;
;;; - direct slot definition: local to a single defclass form
;;;
;;; - effective slot definition: combination of all direct slots with the same
;;;   name in the class and its superclasses
;;;
(defclass dynamic-direct-slot (mop:standard-direct-slot-definition)
  ((dynamic :initform nil :initarg :dynamic :reader dynamic-slot-p)))

;;; DYNAMIC-EFFECTIVE-SLOT is implemented to return as slot-value values of the
;;; dynamic variable that is stored with the instance.
;;;
;;; It would be nice if we could specify :ALLOCATION :DYNAMIC for the slot, but
;;; then STANDARD-INSTANCE-ACCESS would go belly up. We could make a clever
;;; workaround, but who cares?
(defclass dynamic-effective-slot (mop:standard-effective-slot-definition)
  ())

(defmethod mop:slot-value-using-class
    ((class class-with-dynamic-slots)
     object
     (slotd dynamic-effective-slot))
  (dref (slot-dvar object slotd)))

(defmethod (setf mop:slot-value-using-class)
    (new-value
     (class class-with-dynamic-slots)
     object
     (slotd dynamic-effective-slot))
  (dset (slot-dvar object slotd) new-value))

(defmethod mop:slot-boundp-using-class
  ((class class-with-dynamic-slots)
   object
   (slotd dynamic-effective-slot))
  (boundp (slot-dvar object slotd)))

(defmethod mop:slot-makunbound-using-class
  ((class class-with-dynamic-slots)
   object
   (slotd dynamic-effective-slot))
  (makunbound (slot-dvar object slotd)))

With this, we can finally define a class with slots that have dynamic values. What's more, we may bind them like dynamic variables.

;;; Let there be light.
(defclass window-4 ()
  ((ink :initform 'red :dynamic t :accessor ink)
   (normal :initform 'normal :accessor normal))
  (:metaclass class-with-dynamic-slots))

(let ((object (make-instance 'window-4)))
  (slot-dlet (((object 'ink) 15))
    (print (ink object)))
  (print (ink object)))

ContextL provides a similar solution with dynamic slots, although it provides much more, like layered classes. This example is much more self-contained.

The context

Lately I'm working on the repaint queue for McCLIM. While doing so I've decided to make stream operations thread-safe, so it is possible to draw on the stream and write to it from arbitrary thread asynchronously. The access to the output record history needs to be clearly locked, so that may be solved by the mutex. Graphics state is another story, consider the following functions running from separate threads:

(defun team-red ()
  (with-drawing-options (stream :ink +dark-red+)
    (loop for i from 0 below 50000 do
      (write-string (format nil "XXX: ~5d~%" i) stream))))

(defun team-blue ()
  (with-drawing-options (stream :ink +dark-blue+)
    (loop for i from 0 below 50000 do
      (write-string (format nil "YYY: ~5d~%" i) stream))))

(defun team-pink ()
  (with-drawing-options (stream :ink +deep-pink+)
    (loop for i from 0 below 25000 do
      (case (random 2)
        (0 (draw-rectangle* stream 200 (* i 100) 250 (+ (* i 100) 50)))
        (1 (draw-circle* stream 225 (+ (* i 100) 25) 25))))))

(defun gonow (stream)
  (window-clear stream)
  (time (let ((a (clim-sys:make-process #'team-red))
              (b (clim-sys:make-process #'team-blue))
              (c (clim-sys:make-process #'team-grue)))
          (bt:join-thread a)
          (bt:join-thread b)
          (bt:join-thread c)
          (format stream "done!~%")))  )

Operations like WRITE-STRING and DRAW-RECTANGLE can be implemented by holding a lock over the shared resource without much disruption. The drawing color on the other hand is set outside of the loop, so if we had locked the graphics state with a lock, then these functions would be serialized despite being called from different processes. The solution to this problem is to make graphics context a dynamic slot that is accessed with WITH-DRAWING-OPTIONS.

Summary

I hope that I've convinced you that dynamic variables are cool (I'm sure that majority of readers here are already convinced), and that dynamic slots are even cooler :-). Watch forward to the upcoming McCLIM release!

If you like technical writeups like this, please consider supporting me on Patreon.

22 Oct 2024 12:00am GMT

[BULLETIN: Quicklisp now has the latest version of FSet.]

Sycamore, primarily by Neil Dantam, is a functional collections library that is built around the same weight-balanced binary tree data structure (with leaf vectors) that FSet uses. While the README on that page comments briefly on the differences between Sycamore and FSet, I don't feel that it does FSet justice. Here is my analysis.

Dantam claims that his library is 30% to 50% faster than FSet on common operations. While I haven't done comprehensive micro-benchmarking, a couple of quick tests indicates that this claim is plausible. A look through the internals of the implementation confirms that it is clean and tight, and I must commend him. There may be some techniques in here that I could usefully borrow.

Most of the performance difference is necessitated by two design choices that were made differently in the two libraries. One of these Dantam mentions in his comparison: FSet's use of a single, global ordering relation implemented as a CLOS generic function, vs. Sycamore's more standard choice of requiring a comparison function to be supplied when a collection is created. The other one he doesn't mention: the fact that FSet supports a notion of equivalent-but-unequal values, which are values that are incomparable - there's no way, or at least no obvious way, to say which is less than the other, and yet we want to treat them as unequal. The simplest example is the integer 1 and the single-float 1.0, which have equal numerical values (and cl:= returns true on them), but which are nonetheless not eql. (I have a previous blog post that goes into a lot more detail about equality and comparison.) Since Sycamore expects the user-supplied comparison function to return an integer that is negative, zero, or positive to indicate the ordering of its arguments, there's no encoding for the equivalent-but-unequal case, nor is there any of the code that would be required to handle that case.

Both of these decisions were driven by my goal for the FSet project. I didn't just want to provide a functional collections library that could be called occasionally when one had a specific need for such a data structure. My ambition was much grander: to make functional collections into a reasonable default choice for the vast majority of programming situations. I wanted FSet users (including, of course, myself) to be able to use functional collections freely, with very little extra effort or thought. While Lisp by itself reaches a little bit in this direction - lists can certainly be used functionally - lists used as functional collections run into severe time complexity problems as those collections get large. I wanted the FSet collections to be as convenient and well-supported as lists, but without the time complexity issues.

- Or rather, I wanted them to be even more convenient than lists. Before writing FSet, I had spent years working in a little-known proprietary language called Refine, which happened to be implemented on top of Common Lisp, so it was not unusual to switch between the two languages. And I had noticed something. In contrast to CL, with its several different predefined equality predicates and with its functions that take :test arguments to specify which one to use, Refine has a single notiion of equality. The value space is cleanly divided between immutable types, which are compared by value - along with numbers, these include strings, sets, maps, and seqs - and mutable objects, which are always compared by identity. And it worked! I found I did not miss the ability to specify an equality predicate when performing an operation such as "union". It was just never needed. Get equality right at the language level, and the problem goes away.

Although FSet's compare generic function isn't just for equality - it also defines an ordering that is used by the binary trees - I thought it would probably turn out to be the case that a single global ordering, implemented as a generic function and therefore extensible, would be fine the vast majority of the time. I think experience has borne this out. And just as you can mix types in Lisp lists - say, numbers and symbols - without further thought, so you can have any combination of types in an FSet set, effortlessly. (A project I'm currently working on actually takes considerable advantage of this capability.)

As for supporting equivalent-but-unequal values, this desideratum flows directly from the principle of least astonishment. While it might not be too surprising for a set or map implementation to fail distinguish the integer 1 from the float 1.0, it certainly would be very surprising, and almost certainly a source of bugs in a compiler that used it, for it to fail to distinguish two uninterned symbols with the same name. (I saw a macro expansion recently that contained two distinct symbols that both printed as #:NEW. It happens.) A compiler using Sycamore for a map on symbols would have to supply a comparison function that accounted for this; it couldn't just compare the package name and symbol name. (You'd have to do something like keep a weak hash table mapping symbols to integers, assigned in the order in which the comparison function encountered them. It's doable, but FSet protects you from this madness.)

Along with those deep semantic design choices, I've spent a lot of time on developing a wide and featureful API for FSet (an effort that's ongoing). FSet has many features that Sycamore lacks, including:

• seqs, a binary-tree sequence implementation that holds arbitrary Lisp objects (Sycamore ropes hold only characters, which is certainly an important special case, but why restrict ourselves?)
• default values for maps and seqs (the value to return when the key is outside the domain is associated with the collection, not supplied at the call site; this turns out to be a significant convenience)
• generic functions that operate on both lists and FSet collections, to shadow the CL builtins
  
• the powerful map-union and map-intersection operations (I'll blog about these in the future)
• more ways to iterate over the collections (the FSet tutorial has a good summary, about 3/4 of the way down)
• speaking of the tutorial, FSet has lots more documentation

Let me digress slightly to give an example of how FSet makes programming more elegant and convenient. Joe Marshall just put up a blog post comparing Go(lang) with Common Lisp, which is worth a read on its own; I'm just going to grab a code snippet from there to show a little bit of what programming with FSet is like. Here's Joe's code:

 (defun collate (items &key (key #'identity) (test #'eql) (merger (merge-adjoin #'eql)) (default nil))
   (let ((table (make-hash-table :test test)))
     (dolist (item items table)
       (let ((k (funcall key item)))
         (setf (gethash k table) (funcall merger (gethash k table default) item))))))

 (defun merge-adjoin (test)
   (lambda (collection item)
     (adjoin item collection :test test)))

And here's what I would write using FSet:

(Well, I would probably move result outside the dolist form to make it clearer what the return value is, but let's go with Joe's stylistic choice here.)

For those who haven't used FSet: the form (map :default (set)) creates a map whose default is the empty set, meaning that lookups on that map will return the empty set if the key is not in the map. This saves the includef form from having to handle that possibility.

My version makes assumptions, it's true, about how you want to collect the items with a given key; it doesn't give you other choices. It could, but what would be the point? It's already using a general set with better time complexity than lists, and saving you from having to write anything like merge-adjoin. The extensible global equivalence relation means you're not going to need to supply a :test either.

I think the FSet-enhanced code is cleaner, more elegant, and therefore clearer than the plain-CL version. Don't you agree? Maybe you wouldn't say it's a huge improvement, okay, but it's a small example; in a larger codebase, I would argue, these small improvements add up.

* * * * *

To summarize: if you just want a library you can call in a few places for specific purposes, Sycamore might work better for you (but think hard if you're writing a comparator for symbols). FSet can certainly be used that way, but it can be much more. If you want to see one way in which Common Lisp can be made into a better language, without giving up anything that we love about it, I urge you to give FSet a try.

FSet has changed the way I write Lisp programs. - an FSet user

(UPDATE: the magnitude of the performance difference between FSet and Sycamore surprised me, and inspired me to do some profiling of FSet. It turned out that I could get a 20% speedup on one micro-benchmark simply by adding some inline declarations. Mea culpa, mea culpa, mea maxima culpa; I should have done this years ago. With that change, the generic function overhead appears to be the only significant cause of the remaining ~20% performance difference. I tried creating a Sycamore set using a thin wrapper around fset:compare, and the resulting performance was very similar to that of FSet with its new inlines.)

18 Oct 2024 5:35am GMT

It's no secret that I'm an aficionado of Lisp. It's my go to language, especially when I don't know what I'm doing. I call it research and prototyping, but it's really just playing around until something works.

We had a need for some auditing of some of our databases at work. They ought to agree with each other and with what GitHub and CircleCI think. It took a couple of weeks part time to prototype a solution in Common Lisp. It showed that the databases were in 99% agreement and found the few points of disagreement and anomalies that we ought to fix or look out for.

I want to integrate this information into a dashboard on one of our tools. I prototyped this by spinning up a Common Lisp microservice that returns the information in JSON format.

But management prefers that new services are written in golang. It would be easier for me to rewrite the service in golang than to try to persuade others to use Common Lisp. It also gives me the opportunity to compare the two languages head to head on a real world problem.

No, this is not a fair comparison. When I wrote the Lisp code I was exploring the problem space and prototyping. I'm much more experienced with Lisp than with golang. The golang version has the advantage that I know what I want to do and how to do it. In theory, I can just translate the Common Lisp code into golang. But then again, this is a "second system" which is not a prototype and has slightly larger scope and fuller requirements. So this cannot be a true head to head comparison.

The first point of comparison is macros (or lack thereof). I generally don't use a lot of macros in Common Lisp, but they come in handy when I do use them. One macro I wrote is called audit-step, which you can wrap around any expresion and it prints out a message before and after the expression is evaluated. The steps are numbered in sequence, and nested steps get nested numbers (like step 2.3.1). If you wrap the major function bodies with this macro, you get a nice trace of the call sequence in the log.

Golang doesn't have macros, but it has first class functions. It's easy enough to write a function that takes a function as an argument and wraps it to output the trace messages. In fact, the macro version in Common Lisp just rewrites the form into such a function call. But the macro version hides a level of indentation and a lambda. In golang, my major functions all start with

func MajorFunction (args) int {
        return AuditStep("MajorFunction", "aux message", func() int {
                // body of MajorFunction
                // Actual code goes here.
        })    
}

The bodies of all my major functions are indented by 16 spaces, which is a little much.

I like higher order functions. I can write one higher order function and parameterize it with functions that handle the specific cases. In my auditing code, one such workhorse function is called collate. It takes a list of objects and creates a table that maps values to all objects in the list that contain that value. To give an example, imaging you have a list of objects that all have a field called foo. The foo field is a string. The collate function can return a table that maps strings to all objects that have that string in the foo field.

collate is very general. It takes a list of objects and four keyword arguments. The :key argument is a function that extracts the value to collate on. The :test argument is a function that compares two keys (it defaults to eql if not specified). The :merger argument is a function to add the mapped object to its appropriate collection in the table (it defaults to adjoin). The :default argument specifies the initial value of a collection in the table (it defaults to nil).

The :merger function is the most interesting. It takes the key and the object and the current value of the table at that key. It returns the new value of the table at that key. The default merger function is adjoin, which adds the object to the collection at the key if it is not already there. But you can specify a different merger function. For example, if you want to count the number of objects at each key, you can specify a merger function that increments a counter.

The functional arguments to the collate function are often the results of other higher order functions. For example, the :key argument is often the result of composing selector functions. The :merger argument is often the result of composing a binary merge function with a unary transformer function. The transformer function is often the result of composing a number of primitive selectors and transformers.

In Common Lisp, it is quite easy to write these higher order functions. We can compose two unary functions with the compose2 function:

(defun compose2 (f g)
  (lambda (x) (funcall f (funcall g x)))

and then compose as many functions as we like by fold-left of compose2 starting with the identity function:

(defun compose (&rest fs)
  (fold-left #'compose2 #'identity fs))

We can compose a binary function with a unary function in three ways: we can pipe the output of the binary function into the unary function, or we can pipe the output of the unary function into one or the other of the inputs of the binary function.

(defun binary-compose-output (f g)
  (lambda (x y) (funcall f (funcall g x y))))

(defun binary-compose-left (f g)
  (lambda (x y) (funcall f (funcall g x) y)))

(defun binary-compose-right (f g)
  (lambda (x y) (funcall f x (funcall g y))))

The collate function can now assume that a lot of the work is done by the :key and :merger functions that are passed in. It simply builds a hash table and fills it:

(defun collate (item &key (key #'identity) (test #'eql) (merger (merge-adjoin #'eql)) (default nil))
  (let ((table (make-hash-table :test test)))
    (dolist (item items table)
      (let ((k (funcall key item)))
        (setf (gethash k table) (funcall merger (gethash k table default) item))))))

(defun merge-adjoin (test)
  (lambda (collection item)
    (adjoin item collection :test test)))

So suppose, for example, that we have a list of records. Each record is a three element list. The third element is a struct that contains a string. We want a table mapping strings to the two element lists you get when you strip out the struct. This is easily done with collate:

(collate records
  :key (compose #'get-string #'third)
  :test #'equal      ; or #'string= if you prefer
  :merger (binary-compose-right (merge-adjoin #'equal) #'butlast))

The audit code reads lists of records from the database and from GitHub and from CircleCI and uses collate to build hash tables we can use to quickly walk and validate the data.

Translating this into golang isn't quite so easy. Golang has first class function, true, but golang is a statically typed language. This causes two problems. First, the signature of the higher order functions includes the types of the arguments and the return value. This means you cannot just slap on the lambda symbol, you have to annotate each argument and the return value. This is far more verbose. Second, higher order functions map onto parameterized (generic) types. Generic type systems come with their own little constraint language so that the computer can figure out what concrete types can correctly match the generic types. This makes higher order functions fairly unweildy.

Consider compose2. The functions f and g each have an input and output type, but the output type of g is the input type of f so only three types are involved

func Compose2[T any, U any, V any](f func(U) V, g func(T) U) func(T) V {
        return func(x T) V {
                return f(g(x))
        }
}

If want to compose three functions, we can write this:

func Compose3[T any, U any, V any, W any](f func(V) W, g func(U) V, h func(T) U) func(T) W {
        return func(x T) W {
                return f(g(h(x)))
        }
}

The generic type specifiers take up as much space as the code itself.

I don't see a way to write an n-ary compose function. It would have to be dynamically parameterized by the intermediate types of all the functions it was composing.

For the collate function, we can write this:

func Collate[R any, K comparable, V any](
        list *Cons[R],
        keyfunc func(R) K,
        merger func(V, R) V,
        defaultValue V) map[K]V {
        answer := make(map[K]V)
        for list != nil {
                key := keyfunc(list.Car)
                probe, ok := answer[key]
                if !ok {
                        probe = defaultValue
                }
                answer[key] = merger(probe, list.Car)
                list = list.Cdr
        }
        return answer
}

We have three types to parameterize over: the type of the list elements (i.e. the record type) R, the type of the key K, and the type of the value V. The key type is needs to be constrained to be a valid key in a map, so we use the comparable constraint. Now that we have the types, we can annotate the arguments and return value. The list we are collating is a list of R elements. The key function takes an R and returns a K. The merger takes an existing value of type V and the record of type R and returns a new value of type V.

The magic of type inference means that I do not have to annotate all the variables in the body of the function, but the compiler cannot read my mind and infer the types of the arguments and return value. Golang forces you to think about the types of arguments and return values at every step of the way. Yes, one should be aware of what types are being passed around, but it is a burden to have to formally specify them at every step. I could write the Common Lisp code without worrying too much about types. Of couse the types would have to be consistent at runtime, but I could write the code just by considering what was connected to what. In golang, the types are in your face at every function definition. You not only have to think about what is connected to what, you have to think about what sort of thing is passed through the connection.

I'm sure that many would argue that type safety is worth the trouble of annotation. I don't want to argue that it isn't. But the type system is cumbersome, awkward, and unweildy, especially when you are trying to write higher order functions.

It is taking me longer to write the golang version of the audit service than it did to write the Common Lisp version. There are several reasons. First, I am more experienced with Common Lisp than golang, so the right Common Lisp idioms just come to mind. I have to look up many of the golang idioms. Second, the golang code is trying to do more than the Common Lisp code. But third, golang itself introduces more friction than Common Lisp. Programs have to do more than express the algorithm, they have to satisfy the type system.

There are more points of comparison between the two languages. When I get frustrated enough, I'll probably write another post.

17 Oct 2024 2:17am GMT

New projects:

• adp-github - ADP extension to generate github markdown files. - MIT
• adp-plain - Add Documentation, Please... using plain text. An extension of ADP to generate files with barely additional features. - MIT
• allioli - Alliolification - MIT
• alternate-asdf-system-connections - Allows for ASDF system to be connected so that auto-loading may occur. This is a fork of asdf-system-connections and incorporates a load-system-driven mechanism for loading dependencies and also loads the dependencies of the connections. - MIT
• cbor - CBOR encoder/decoder - MIT
• charje.documentation - Documentation is an opinionated yet customizable docstring parsing library. - AGPL V3 or any later version
• chipi - House automation bus in Common Lisp - Apache-2
• cl-aseprite - Aseprite file format parser - GPLv3
• cl-astar - A heavily optimized yet flexible A* pathfinding algorithm implementation - MIT
• cl-ceigen-lite - A Common Lisp wrapper around CEIGEN-LITE - which is itself a C wrapper around the C++ Eigen library. - MIT
• cl-cf - Computations using continued fractions - GPL-3
• cl-concord - CONCORD implementation based on Common Lisp - LGPL
• cl-duckdb - CFFI wrapper around the DuckDB C API - MIT License
• cl-fastcgi - FastCGI wrapper for Common Lisp - BSD License
• cl-flx - Rewrite emacs-flx in Common Lisp - MIT
• cl-frugal-uuid - Common Lisp UUID library with zero dependencies - MIT License
• cl-gog-galaxy - A wrapper for the GOG Galaxy SDK - zlib
• cl-lc - List comprehensions - MIT
• cl-naive-ptrees - Functions to make it easier to work with plist(s) and plist trees. Works with plist(s) pairs as units and not as individual list items. - MIT
• cl-qoa - An implementation of the Quite Okay Audio format. - zlib
• cl-reddit - Reddit client api library - BSD
• cl-resvg - An up-to-date bindings library for the resvg SVG rendering library - zlib
• cl-trivial-clock - Common Lisp library to get accurate wall-clock times on multiple platforms - MIT License
• clack-cors - A Clack middleware to set CORS related HTTP headers. - Unlicense
• clack-prometheus - Clack middleware to serve stats in Prometheus format. - Unlicense
• clith - Common Lisp wITH macro. A general WITH macro. - MIT
• clj-arrows - Implements Clojure-styled threading/transformation macros. - MIT
• clos-encounters - A collection of OOP patterns benefiting from the CLOS MOP. - Unlicense
• coalton - An efficient, statically typed functional programming language that supercharges Common Lisp. - MIT
• cocoas - A toolkit library to help deal with CoreFoundation, Cocoa, and objc - zlib
• com.danielkeogh.graph - A fast an reliable graph library. - MIT
• fast-mpsc-queue - Multi-Producer Single-Consumer queue implementation. - MIT
• file-finder - File finder. Enable rapid file search, inspection and manipulation. - GPL3+
• golden-utils - A utility library. - MIT
• hiccl - HTML generator for Common Lisp - MIT
• hsx - Hypertext S-expression - MIT
• hunchentoot-stuck-connection-monitor - Monitors hunchentoot connections and logs the connections stuck in the same state for a long time (due to slow or inactive clients and network stream timeouts that hunchentoot tries to utilize not working properly). Offers an option to shutdown the stuck connections sockets manually or automatically, thus unblocking the connection threads and preventing thread and socket leak. See https://github.com/edicl/hunchentoot/issues/189 - BSD-2-Clause
• incless - A portable and extensible Common Lisp printer implementation (core) - BSD
• inravina - A portable and extensible Common Lisp pretty printer. - MIT
• invistra - A portable and extensible Common Lisp FORMAT implementation - BSD
• knx-conn - KNXnet/IP implementation in Common Lisp - GNU GPL, version 3
• machine-state - Retrieve machine state information about CPU time, memory usage, etc. - zlib
• myweb - simple web server written in common lisp for educational reasons - LGPLv3
• noisy - Perlin noise for arbitrary numbers of dimensions. - MIT
• nontrivial-gray-streams - A compatibility layer for Gray streams including extensions - MIT
• open-with - Open a file in a suitable external program - zlib
• openai-openapi-client - Openai API client - AGPLv3+
• openrpc - CI for Common Lisp OpenRPC library. - BSD
• parse-number-range - Parses LOOP's convenient "for-as-arithmetic" syntax into 5 simple values: from, to, limit-kind (:inclusive, :exclusive or nil if unbounded), by (step) and direction (+ or -)). Further related utilities are provided. Intended for easy implementation of analogous functionality in other constructs. - Public Domain
• precise-time - Precise time measurements - zlib
• pregexp - Portable regular expressions for Common Lisp - MIT-like
• progressons - Display a progress bar on one line. - MIT
• quaviver - A portable and extensible floating point string library - MIT
• quilc - A CLI front-end for the Quil compiler - Apache License 2.0 (See LICENSE.txt)
• qvm - An implementation of the Quantum Abstract Machine. - Apache License 2.0 (See LICENSE.txt)
• random-sampling - Functions to generate random samples with various distributions - zlib
• rs-dlx - Knuth's Algorithm X with dancing links. - Modified BSD License
• scrapycl - The web scraping framework for writing crawlers in Common Lisp. - Unlicense
• smoothers - Statistical methods to create approximating functions that attempt to capture important patterns in the data, while leaving out noise or other fine-scale structures/rapid phenomena. - MS-PL
• trivial-adjust-simple-array - A tiny utility to change array size ensuring it is simple. - MIT
• trivial-system-loader - A system installation/loading abstraction for Common Lisp - MIT
• trivial-toplevel-commands - Trivial Toplevel Commands allows to define toplevel commands available on most implementations in a portable fashion. - BSD-3 Clause
• trivial-toplevel-prompt - Portability library to customize REPL prompts. - BSD-3 Clause
• utf8-input-stream - A UTF-8 string input stream over a binary stream for Common Lisp - MIT
• whereiseveryone.command-line-args - Automatically create a command-line-argument parser for a given Common Lisp function definition. - AGPL v3 or any later version

Updated projects: 3b-bmfont, 3bgl-shader, 3bmd, 3d-math, 3d-spaces, 40ants-asdf-system, 40ants-slynk, access, acclimation, action-list, adhoc, adopt, adp, agnostic-lizard, alexandria, alexandria-plus, anatevka, anypool, april, arc-compat, architecture.builder-protocol, array-utils, arrow-macros, assoc-utils, async-process, atomics, auto-restart, aws-sdk-lisp, babel, bdef, bike, binary-structures, binding-arrows, birch, blackbird, bordeaux-threads, calm, carrier, caveman, ccldoc, cephes.cl, cepl, cerberus, cffi, cffi-object, cffi-ops, chanl, chunga, ci, ci-utils, ciao, cl-6502, cl-algebraic-data-type, cl-all, cl-ansi-term, cl-async, cl-atelier, cl-autowrap, cl-base32, cl-bmas, cl-bmp, cl-bnf, cl-brewer, cl-buchberger, cl-cmark, cl-collider, cl-colors2, cl-confidence, cl-containers, cl-cookie, cl-csv, cl-custom-hash-table, cl-cxx-jit, cl-data-structures, cl-dbi, cl-digraph, cl-dot, cl-enchant, cl-environments, cl-fast-ecs, cl-fbx, cl-fluent-logger, cl-form-types, cl-forms, cl-freetype2, cl-gamepad, cl-github-v3, cl-gltf, cl-gobject-introspection, cl-graph, cl-grip, cl-gserver, cl-hamcrest, cl-hash-util, cl-html-readme, cl-i18n, cl-info, cl-ini, cl-ipfs-api2, cl-kanren, cl-lib-helper, cl-liballegro, cl-liballegro-nuklear, cl-log, cl-markless, cl-marshal, cl-migratum, cl-mixed, cl-modio, cl-mount-info, cl-mpg123, cl-mssql, cl-mustache, cl-mysql, cl-neovim, cl-netpbm, cl-oju, cl-opengl, cl-opensearch-query-builder, cl-opus, cl-patterns, cl-plus-ssl-osx-fix, cl-ppcre, cl-project, cl-protobufs, cl-pslib, cl-pslib-barcode, cl-rashell, cl-readline, cl-sat.minisat, cl-sdl2-image, cl-sdl2-mixer, cl-sdl2-ttf, cl-sendgrid, cl-sentry-client, cl-skkserv, cl-smtp, cl-ssh-keys, cl-steamworks, cl-str, cl-svg, cl-telegram-bot, cl-threadpool, cl-tiled, cl-torrents, cl-tqdm, cl-transducers, cl-transit, cl-unicode, cl-unification, cl-unix-sockets, cl-utils, cl-vectors, cl-vorbis, cl-wavefront, cl-webdriver-client, cl-webkit, cl-webmachine, cl-who, clack, clack-pretend, clad, classimp, clast, clath, clavier, clazy, clerk, clgplot, climacs, clingon, clip, clj-con, clj-re, clobber, clog, clog-ace, clog-collection, clog-plotly, clog-terminal, clohost, closer-mop, clss, cluffer, clunit2, clx, cmd, codata-recommended-values, codex, coleslaw, collectors, colored, com-on, common-lisp-jupyter, commondoc-markdown, compiler-macro-notes, conduit-packages, consfigurator, contextl, croatoan, ctype, cytoscape-clj, damn-fast-priority-queue, dartscluuid, data-frame, data-lens, datafly, dbus, decompress, defenum, definer, definitions, deflate, defmain, deploy, depot, deptree, dexador, dissect, djula, dns-client, doc, docs-builder, dsm, dufy, easter-gauss, easy-audio, easy-macros, easy-routes, eclector, equals, erjoalgo-webutil, erudite, esrap, event-emitter, external-program, external-symbol-not-found, fare-csv, fare-scripts, fast-http, fast-websocket, file-attributes, file-notify, file-select, filesystem-utils, fiveam, fiveam-matchers, flexi-streams, float-features, flow, fn, fset, functional-trees, fuzzy-dates, gadgets, generic-cl, github-api-cl, glfw, glsl-toolkit, harmony, hashtrie, helambdap, http2, hunchentoot, imago, in-nomine, inferior-shell, introspect-environment, ironclad, jose, js, json-mop, jsonrpc, jzon, khazern, lack, lass, lemmy-api, letv, lichat-protocol, lichat-tcp-client, linear-programming, lisp-binary, lisp-chat, lisp-critic, lisp-pay, lisp-stat, lispcord, lla, local-time, log4cl-extras, logging, lru-cache, magicl, maiden, maidenhead, manifolds, math, mcclim, memory-regions, messagebox, method-combination-utilities, mgl-pax, misc-extensions, mito, mk-defsystem, mmap, mnas-package, mnas-string, moira, multiposter, mutility, mutils, named-closure, ndebug, neural-classifier, new-op, nibbles, nibbles-streams, ningle, nodgui, north, numerical-utilities, nytpu.lisp-utils, omglib, ook, open-location-code, openapi-generator, orizuru-orm, overlord, papyrus, parachute, parse-number, pathname-utils, petalisp, phos, picl, plot, plump, plump-sexp, pngload, policy-cond, polymorphic-functions, postmodern, ppath, prometheus-gc, psychiq, purgatory, py4cl, py4cl2, py4cl2-cffi, qlot, qoi, query-fs, quick-patch, quickhull, quri, random-state, reblocks, reblocks-auth, reblocks-file-server, reblocks-lass, reblocks-navigation-widget, reblocks-parenscript, reblocks-prometheus, reblocks-typeahead, reblocks-ui, reblocks-websocket, rove, s-dot2, sandalphon.lambda-list, sb-fastcgi, sc-extensions, sel, select, serapeum, shasht, shop3, si-kanren, sketch, slime, slite, sly, snooze, spinneret, staple, static-vectors, statistics, stepster, stmx, stripe, swank-crew, swank-protocol, sxql, symath, system-locale, taglib, teddy, ten, testiere, tfeb-lisp-hax, tfm, tiny-routes, tooter, trivia, trivial-arguments, trivial-clipboard, trivial-file-size, trivial-gray-streams, trivial-main-thread, trivial-octet-streams, trivial-package-locks, trivial-package-manager, trivial-sanitize, trivial-shell, type-templates, typo, uax-15, uiop, usocket, vellum, vellum-binary, vellum-csv, vellum-postmodern, verbose, vernacular, vom, websocket-driver, winhttp, with-branching, with-contexts, woo, xhtmlambda, xml-emitter, yason, zippy, zpb-ttf.

Removed projects: abstract-arrays, ahungry-fleece, cl-cheshire-cat, cl-darksky, cl-epoch, cl-naive-store, convolution-kernel, dense-arrays, extensible-compound-types, extensible-optimizing-coerce, fast-generic-functions, flac-metadata, freebsd-ffi, listoflist, luckless, one-more-re-nightmare, postmodern-localtime, stumpwm-dynamic-float, stumpwm-sndioctl, unicly.

To get this update, use:

(ql:update-dist "quicklisp")

Sorry this update took so long. My goal is to resume monthly releases.

Enjoy!

15 Oct 2024 8:16pm GMT

Earlier this year, I started working through the online book Ray Tracing In One Weekend (Book 1). I have been following along with it in Common Lisp, and I have been extending it all from 3-dimensional to n-dimensional.

I reproduced 4-dimensional versions of all of the book images which you can see on my weekend-raytracer github page.

Here is the final image. This is a 250-samples-per-pixel, 640x360x10 image plane of three large hyperspheres (one mirrored, one diffuse, one glass) atop a very large, diffuse hypersphere. Also atop this very large hypersphere are a bunch of smaller hyperspheres of varying colors and materials. The image is rendered with some defocus-blur.

Final image of 4-dimensional scene

Caveat: This depends on a patched version of the policy-cond library that is not in the current Quicklisp distribution but should be in the next.

27 Sep 2024 2:37am GMT

I'm a sucker for sage advice much as anyone else, and Kernighan is certainly right on money in the epigraph. Alas there comes a time in programmer's career when you just end up there despite the warning. It could be that you were indeed too clever for your own good, or maybe the code isn't quite yours anymore after each of your colleague's take on it over the years. Or just sometimes, the problem is indeed so hard that it strains your capacity as a coder.

It would usually start with a reasonable idea made into first iteration code. The solution looks fundamentally sound but then as you explore the problem space further it begins to seep nuance, either as manifestation of some real world complexity or your lack of foresight. When I run into this my first instinct is to instrument the code. If the problem is formidable you got to respect it: flailing around blindly modifying things or ugh, doing a rewrite at this stage is almost guaranteed to be a waste of time. It helps to find a promising spot, chisel it, gain a foothold in the problem, and repeat until you crack it. Comfortable debugging tools here can really help to erode the original Kernighan coefficient from 2 to maybe 1.6 or 1.4 where you can still have a chance.

Lisp users are fortunate with the options of interactive debugging, and one facility I reach often for is the plain BREAK. It's easy enough to wrap it into a conditional for particular matches you want to debug. However sometimes you want it to trigger after a particular sequence of events across different positions in code has taken place. While still doable it quickly becomes cumbersome and this state machine starts to occupy too much mental space which is already scarce. So one day, partly as a displacement activity from being intimidated by a Really Hard Problem I wrote down my debugging patterns as a handful of macros.

Enter BRAKE. Its features reflect my personal preferences so are not necessarily your cup of tea but it could be a starting point to explore in this direction. Things it can do:

• act as a simple BREAK with no arguments (duh)
• wrap an s-expression, passing through its values upon continuing
• trigger sequentially based on the specified position for a common tag
• allow for marks that don't trigger the break but mark the position as reached
• provide conditional versions for the expressions above
• print traces of tagged breakpoints/marks

If you compile functions with debug on you hopefully should be able to see the wrapped sexpr's result values.

(use-package '(brake))

(defun fizzbuzz ()
  (loop for n from 100 downto 0
        for fizz = (zerop (mod n 3))
        for buzz = (zerop (mod n 5)) do
        (format t "~a "
                (if (not (or fizz buzz))
                    (format nil "~d" n)
                  (brake-when (= n 0)
                              (concatenate 'string
                                           (if fizz "Fizz" "")
                                           (if buzz "Buzz" "")))))))

These macros try to detect common cases for tagged sequences being either aborted via break or completed to the last step, resetting them after to the initial state. However it is possible for a sequence to end up "abandoned", which can be cleaned up by a manual command.

Say in the example below we want to break when the two first branches were triggered in a specific order. The sequence of 1, 3, 4 will reinitialize once the state 4 is reached, allowing to trigger continuously. At the same time if we blow our stack it should reset to initial when aborting.

(defun ack (m n)
  (cond ((zerop m) (mark :ack 3 (1+ n)))
        ((zerop n) (mark :ack 1 (ack (1- m) 1)))
        (t (brake :ack 4 (ack (1- m) (ack m (1- n)))))))

In addition there are a few utility functions to report on the state of brakepoints, enable or disable brakes based on tags and turn tracing on or off. Tracing isn't meant to replace the semantics of TRACE but to provide a souped up version of debug by print statements everyone loves.

CL-USER> (report-brakes)
Tag :M is DISABLED, traced, with 3 defined steps, current state is initial
Tag :F is DISABLED with 2 defined steps, current state is 0
Tag :ACK is ENABLED with 3 defined steps, current state is initial

Disabling breakpoints without recompilation is really handy and something I find using all the time. The ability to wrap a sexpr was often sorely missed when using BREAK in constructs without implicit body.

Sequencing across threads is sketchy as the code isn't guarded but in many cases it can work, and the appeal of it in debugging races is clear. One of those days I hope to make it more robust while avoiding potential deadlocks but it isn't there yet. Where it already shines tho is in debugging complex iterations, mutually recursive functions and state machines.

15 Sep 2024 3:00pm GMT

Unfortunately, I managed to delete my WordPress database at a time when the most recent backup I had was from 11 years ago.

So… I will hopefully get some newer information uploaded again sometime.

But, most of my content is gone.

Scott Burson pointed out that The Wayback Machine has my content: http://web.archive.org/web/20240901104727/https://nklein.com/

And, Daniel Brooks pointed out that NewsBlur has the stuff from my RSS feeds: https://www.newsblur.com/site/101509/nklein-software

I will eventually get to moving some of that back here properly.

13 Sep 2024 3:46pm GMT