Starting with Common Lisp in 2020

In my spare time (whenever I get to have some these days) I like to poke around in the world of Lisp.

I do have some experience with various Lisp dialects such as Scheme, Racket and Clojure, so this is not my first introduction to the Lisp family. I’ve been developing in Clojure at my current job and has also used Scheme (Chicken Scheme in particular) and Racket in various small to mid-sized personal and hobby projects. Having spent a fair amount of my time with the various Lisp dialects I wouldn’t say that I’m expert in Lisp, not even close.

We are now in the 2020 year, and this is also the year that Lisp would become 62 years old! That is an impressive age for a programming language. With that said that does not mean that the concepts and ideas developed in Lisp are old.

A thing so common for all languages these days such as if-then-else was first introduced by the creator of Lisp itself - John McCarthy. Another notable thing so common to lots of modern languages such as garbage collection came from Lisp too. The Read-Eval-Print-Loop (REPL) that most of us cannot live without is another good example.

And these are just a few of the things that Lisp gave to the world.

These days Lisp isn’t very popular compared to other languages as it used to be back in the days, but that isn’t to say that Lisp itself is dead. As a matter of fact it is in a pretty good shape - various Common Lisp implementations are actively being maintained – few days ago SBCL 2.0.0 got released for example. Research and innovations are still happening in Racket (check out the Honu project for instance), and Clojure is kicking butts in the JVM world.

So, why spending time with Lisp you might ask?

Is it for the famous Lisp enlightenment everyone is talking about? I don’t know, maybe. Personally, I find programming in Lisp quite fun. Exploring stuff and poking around at the REPL in Common Lisp is a whole different story than most of the REPLs you’ve dealt with. Maybe it is my personal curiousity about programming and computer science that drove me to Lisp.

The language has a long history, so you would find lots of reading materials, research papers and it’s fascinating to know that you can still run such old code in modern Common Lisp implementations.

Have I been enlighted by Lisp? I don’t feel smarter after learning Lisp. I do however feel that I’ve gained more experience as a programmer. And maybe that’s the Lisp enlightment these old Lispers talk about, maybe it’s something else. What I do know however is that learning new paradigms and techniques definitely makes you a better problem solver, so that’s another another reason to try learning some Lisp.

Oh, and I do like the s-expr syntax. That for me is a good enough reason to be excited about Lisp.

In this post I’m going to summarize my experience with Common Lisp so far, and hopefully the things I write here are going to be useful to someone else in his/hers own journey in the world of Lisp.

I also need to mention that even though I have experience with Scheme and Clojure, I’m quite new to Common Lisp. These being Lisp dialects does not mean they are fully compatible with each other. Scheme takes the functional-first approach to solving problems and Clojure is a more modern reincarnation of Lisp which is closer to Scheme being a Lisp-1 dialect, while Common Lisp is the ANSI standardized vision of what Lisp should be.

Also keep in mind that this post is not intended as a tutorial for all things related to Lisp, but rather they document my particular development setup and show various code samples which I’ve found useful, and hopefully others will too.

At the end of this post you will also find additional references to learning materials such as books and documentation, which I’d recommend checking out. These references will be valuable to anyone starting up with Common Lisp as they provide useful information and insight.

Installing Common Lisp

The nice thing about Common Lisp being ANSI standardized language is that you can choose between various implementations.

You need high-performance Lisp compiler - SBCL has got you covered, you need to use the JVM platform - ABCL is there for you. You can check out the various Common Lisp implementations and choose the one that suits you most. My personal choice has been SBCL, but as long as you develop standard compliant code your project be portable to any conforming implementation.

Installing SBCL on my Mac is as simple as the following command.

brew install sbcl

And when I’m working on my Arch Linux system I would install SBCL using the following command.

pacman -S sbcl

You would want to get a copy of the Common Lisp Hyperspec as well. On Macs you can install the HyperSpec using the following command.

brew install hyperspec

Or you can grab the HyperSpec from here instead.

After installing SBCL you can test things up quickly in the REPL and confirm everything has been installed properly.

$ sbcl
This is SBCL 2.0.0, an implementation of ANSI Common Lisp.
More information about SBCL is available at <http://www.sbcl.org/>.

SBCL is free software, provided as is, with absolutely no warranty.
It is mostly in the public domain; some portions are provided under
BSD-style licenses.  See the CREDITS and COPYING files in the
distribution for more information.

Evaluating the following expression from the REPL would return the Lisp implementation type and version.

* (values (lisp-implementation-type)
          (lisp-implementation-version))
"SBCL"
"2.0.0"

Editor setup

I’ve been a long time Emacs user and for me the choice of editor support for Common Lisp is simple - SLIME. Vim users would probably want to pick Vlime.

What follows below are snippets from my Emacs config. I keep these as global settings at the top of my ~/.emacs file.

(server-start)

(setq column-number-mode t)
(global-display-line-numbers-mode)
(global-hl-line-mode 1)
(show-paren-mode 1)
(save-place-mode 1)

;; Disable tabs globally and enable them
(setq indent-tabs-mode nil)

;; We want newlines at end of file
(setq require-final-newline 1)

Config settings for installing packages from MELPA.

(require 'package)
(let* ((no-ssl (and (memq system-type '(windows-nt ms-dos))
                    (not (gnutls-available-p))))
       (proto (if no-ssl "http" "https")))
  (when no-ssl
    (warn "\
Your version of Emacs does not support SSL connections,
which is unsafe because it allows man-in-the-middle attacks.
There are two things you can do about this warning:
1. Install an Emacs version that does support SSL and be safe.
2. Remove this warning from your init file so you won't see it again."))
  ;; Comment/uncomment these two lines to enable/disable MELPA and MELPA Stable as desired
  (add-to-list 'package-archives (cons "melpa" (concat proto "://melpa.org/packages/")) t)
  ;;(add-to-list 'package-archives (cons "melpa-stable" (concat proto "://stable.melpa.org/packages/")) t)
  (when (< emacs-major-version 24)
    ;; For important compatibility libraries like cl-lib
    (add-to-list 'package-archives (cons "gnu" (concat proto "://elpa.gnu.org/packages/")))))
(package-initialize)

I also keep various personal Elisp snippets that I usually throw at ~/.emacs.d/lisp, so I have this as well.

;; For storing custom snippets
(let ((path (expand-file-name "~/.emacs.d/lisp")))
  (if (file-accessible-directory-p path)
      (add-to-list 'load-path path t)))

My theme settings - I use one for day-time coding and another one for late-night work. I’ve found that personally for myself working in light themes during the day works best for my eyes and usually at night I would switch my theme to a darker one.

;; Theme customizations

;; Night theme
(load-theme 'doom-nova t)

;; Daylight theme
;; (load-theme 'solarized-light t)

And then I have my package declarations.

(use-package beacon
  :config
  (beacon-mode 1))

(use-package winner
  :init
  (winner-mode t))

(use-package rainbow-delimiters
  :ensure t
  :init
  (progn
    (add-hook 'prog-mode-hook 'rainbow-delimiters-mode)))

(use-package go-eldoc
  :defer t)

(use-package go-mode
  :init
  (progn
    (setq gofmt-command "goimports")
    (setq indent-tabs-mode t)
    (add-hook 'go-mode-hook 'go-eldoc-setup)
    (add-hook 'before-save-hook 'gofmt-before-save)))

(use-package racket-mode
  :init
  (progn
    (add-hook 'racket-mode-hook
	      (lambda ()
		(define-key racket-mode-map (kbd "C-c r") 'racket-run)))))

(use-package ace-window
  :bind (("M-o" . ace-window)
	 ("C-x o" . ace-window))
  :config
  (setq aw-background nil))

(use-package which-key
  :config
  (which-key-mode t))

(use-package doom-modeline
  :ensure t
  :config
  (doom-modeline-init))

(use-package graphviz-dot-mode
  :init
  (setq graphviz-dot-indent-width 4))

(use-package markdown-mode
  :ensure t
  :commands (markdown-mode gfm-mode)
  :mode (("README\\.md\\'" . gfm-mode)
         ("\\.md\\'" . gfm-mode)
         ("\\.markdown\\'" . markdown-mode))
  :init (setq markdown-command "multimarkdown"))

(use-package ivy
  :bind
  (("C-s" . 'swiper)
   ("M-x" . 'counsel-M-x)
   ("C-x C-f" . 'counsel-find-file)
   ("C-c C-r" . 'ivy-resume))
  :init
  (ivy-mode 1)
  (setq enable-recursive-minibuffers t)
  (setq ivy-display-style 'fancy)
  (setq ivy-count-format "(%d/%d) ")
  (setq magit-completing-read-function 'ivy-completing-read)
  :config
  (use-package ivy-rich)
  (ivy-rich-mode t))

(use-package exec-path-from-shell
  :if (memq window-system '(mac ns x))
  :ensure t
  :config
  (exec-path-from-shell-initialize))

(use-package company
  :defer t
  :config
  (define-key company-active-map (kbd "\C-n") 'company-select-next)
  (define-key company-active-map (kbd "\C-p") 'company-select-previous)
  (define-key company-active-map (kbd "\C-d") 'company-show-doc-buffer)
  (define-key company-active-map (kbd "M-.") 'company-show-location))

(use-package slime-company
  :defer t)

(use-package slime
  :bind (("M-TAB" . company-complete)
	 ("C-c C-d C-s" . slime-describe-symbol)
	 ("C-c C-d C-f" . slime-describe-function))
  :init
  (setq slime-lisp-implementations '((sbcl ("sbcl")))
	slime-default-lisp 'sbcl)
  (setq common-lisp-hyperspec-root
        "/usr/local/share/doc/hyperspec/HyperSpec/")
  (setq common-lisp-hyperspec-symbol-table
        (concat common-lisp-hyperspec-root "Data/Map_Sym.txt"))
  (setq common-lisp-hyperspec-issuex-table
        (concat common-lisp-hyperspec-root "Data/Map_IssX.txt"))
  (slime-setup '(slime-fancy slime-company slime-cl-indent)))

(defun slime-description-fontify ()
  (with-current-buffer "*slime-description*"
    (slime-company-doc-mode)))

(defadvice slime-show-description (after slime-description-fontify activate)
  "Fontify sections of SLIME Description."
  (slime-description-fontify))

Quicklisp

Quicklisp is a package manager for Lisp libraries. You would want to have it, when you need to pull in some external library that your code will use, so now it is a good time to go ahead and install it.

Go ahead and read the installation instructions here. The summarized steps can be found below.

curl -O https://beta.quicklisp.org/quicklisp.lisp
curl -O https://beta.quicklisp.org/quicklisp.lisp.asc
curl -O https://beta.quicklisp.org/release-key.txt
gpg --import release-key.txt
gpg --verify quicklisp.lisp.asc quicklisp.lisp
sbcl --load quicklisp.lisp

Make sure to check out the documentation at Quicklisp for more information and some examples.

Code samples

What follows below are some code snippets I’ve written in Common Lisp. When starting with a new language I usually have a list of problems and tasks that I go through, just to get a rough idea how expressing a solution to a task in the language feels like.

Hash Tables

Hash tables in Common Lisp are the analog of dictionaries in Python or hash maps in other languages. In order to create a new hash table in Common Lisp you would use the MAKE-HASH-TABLE function, e.g.

CL-USER> (defparameter *ht* (make-hash-table))
*HT*

This is how our hash table is represented when printed in the REPL.

CL-USER> *ht*
#<HASH-TABLE :TEST EQL :COUNT 0 {1002179983}>

You can see the number of keys within the hash table and the function used to test for equality of keys (in this case EQL).

Let’s add a few keys to our hash table.

CL-USER> (setf (gethash :a *ht*) 1)
1
CL-USER> (setf (gethash :b *ht*) 2)
2
CL-USER> (setf (gethash :c *ht*) 3)
3
CL-USER> *ht*
#<HASH-TABLE :TEST EQL :COUNT 3 {1002179983}>

SETF is macro used for general-purpose assignment in Common Lisp. When given a place and a value it knows how to properly set the place to the given value.

CL-USER> *ht*
#<HASH-TABLE :TEST EQL :COUNT 3 {1002179983}>

We’ve got 3 keys now, but as you can see you don’t know which are they, just by looking at the above representation of the hash table.

We can however map a function over each key/value pair in a hash table using the MAPHASH function.

CL-USER> (maphash (lambda (k v)
                    (format t "Key ~a has value ~a~%" k v))
                  *ht*)
Key A has value 1
Key B has value 2
Key C has value 3

Let’s add this to a utility function we can call up when we need this later.

(defun hash-table-dump-kvs (table)
  "Dumps the key/value pairs in a given hash table"
  (maphash (lambda (k v)
             (format t "Key ~a: ~a~%" k v))
           table))

HASH-TABLE-KEYS

Common Lisp as mentioned in the beginning of this post is quite an old language and predates the “batteries included” language era. With that said we won’t find a function which returns all keys and/or values within a given hash table as the ANSI standard does not mention such, but that doesn’t mean we cannot implement such functions on our own.

Using MAPHASHas shown previously can implement these utility functions when working with hash tables.

(defun hash-table-keys (ht)
  "Returns a list of all keys in a given hash table"
  (let (result)
    (maphash (lambda (k v)
               (declare (ignore v))
               (push k result))
             ht)
    result))
CL-USER> (hash-table-keys *ht*)
(:C :B :A)

HASH-TABLE-VALUES

Using a similar approach we can implement a function to retrieve the list of values too.

(defun hash-table-values (ht)
  "Returns a list of all values in a given hash table"
  (let (result)
    (maphash (lambda (k v)
               (declare (ignore k))
               (push v result))
             ht)
    result))

Let’s try them out.

CL-USER> (hash-table-values *ht*)
(3 2 1)

Things seems to work as expected. Retrieving the keys/values in a hash table is such a common thing, that you probably don’t want to implement that on your own each time you have to work with hash tables.

Fortunately, this functionality is already part of the Alexandria library, which amongst this contains other helpful utilities.

When I initially started with Common Lisp I wasn’t aware of Alexandria, so I ended up implementing these functions myself, which surprisingly are almost identical. Nevertheless, this is also a good example of how easy it is implement functionality, which may not be covered by the ANSI standard.

In order to use Alexandria you need to load it first.

CL-USER> (ql:quickload :alexandria)
To load "alexandria":
  Load 1 ASDF system:
    alexandria
; Loading "alexandria"
[package alexandria.1.0.0]......................
(:ALEXANDRIA)

And now you can call the functions.

CL-USER> (alexandria:hash-table-keys *ht*)
(:C :B :A)
CL-USER> (alexandria:hash-table-values *ht*)
(3 2 1)

HASH-TABLE-GET-IN

If you’ve done some Clojure programming you would know that hash-maps are very common when it comes to representing data structures. In Clojure you can use the get-in function to retrieve a value in a nested hash-map, e.g.

user=> (get-in {:a {:b {:c 42}}} [:a :b :c])
42

This is really useful and convenient way to access keys in nested hash tables.

In Common Lisp you don’t have that, or at least I haven’t found one. I think this is because Common Lisp does not embrace the idea of using hash tables for almost every data structure to the same level as it is in Clojure, because in Common Lisp you can use proper structures and classes instead. And that’s probably a good thing - classes and structs might be a better choice in representing your data structures than pure hash tables.

Anyways, I still think that get-in is useful on it’s own, so I’ve implemented it in Common Lisp for the fun of it. Actually, we will see more than one implementation of the get-in function.

One thing worth mentioning is that Common Lisp is a multi-paradigm language - you can program in functional style, imperative or object-oriented style. It’s up to you, so pick your poison. Personally I like this kind of freedom that the language allows you to express a solution to a problem in the most suitable way.

Let’s add a few more keys to the *ht* hash table.

CL-USER> (setf (gethash :foo *ht*) (make-hash-table))
#<HASH-TABLE :TEST EQL :COUNT 0 {1002739123}>
CL-USER> (setf (gethash :bar (gethash :foo *ht*)) 42)
42

And here’s the first version of our function to retrieve nested keys.

(defun hash-table-get-in (ht key &rest keys)
  "Get value of a key in nested hash tables - recursive approach"
  (labels ((process (ht keys)
             (if (endp keys)
                 ht
                 (process (gethash (car keys) ht) (cdr keys)))))
    (process (gethash key ht) keys)))

You should note that above function is tail-recursive. However, you should also know that the Common Lisp ANSI standard does not specify that implementations should provide support for tail recursion. Some implementations such as SBCL support tail recursion, while others simply do not, since this is not a strict requirement of the standard.

In any case this doesn’t really matter for our sample hash table as it is not deep enough to overflow our stack and SBCL got our backs covered, since it supports tail recursion.

Here’s another variation of above function, but this time using iteration instead of recursion. The function below uses the DO iteration macro.

(defun hash-table-get-in (ht key &rest keys)
  "Get value of a key in nested hash tables - iterative approach"
  (do ((ht (gethash key ht) (gethash (car keys) ht))
       (keys keys (cdr keys)))
      ((endp keys) ht)))

And last, but not least here’s a solution using REDUCE.

(defun hash-table-get-in (ht key &rest keys)
  "Get value of a key in nested hash tables - REDUCE approach"
  (reduce (lambda (ht x)
	    (gethash x ht))
	  keys
	  :initial-value (gethash key ht)))

Now we have solutions expressed in recursive, iterative and functional style. I’d say having that kind of choice when programming is truly a feature of the language on it’s own.

You can try out above functions in the REPL and confirm they work as expected, e.g.

(hash-table-get-in *ht* :foo :bar)
42

We do have now functions to fetch keys in nested hash tables, but is there a way we can tell what are all the keys in a given hash table? In other words we want to know the key paths we can fetch in a hash table using above functions.

HASH-TABLE-KEY-PATHS

Here’s one possible implementation of a function that returns the list of valid key paths. You can use this function to see which valid keys paths you can use with our HASH-TABLE-GET-IN functions we implemented previously.

(defun hash-table-key-paths (ht)
  "Returns all key paths in a hash table"
  (let ((result nil))
    (labels ((process (ht paths)
               (maphash (lambda (k v)
                          (if (hash-table-p v)
                              (process v (append paths (list k)))
                              (setf result (append result (list (append paths (list k)))))))
                        ht)))
      (process ht nil))
    result))

Above function does the following,

  • Walks over each key/value pair in our hash table and looks up the value
  • If the value is a hash table - note down the key we have so far and traverse into the new hash table
  • When we reach a value, which isn’t a hash table - store the traversed path of keys we have so far

Another possible approach to above function is to completely get rid of the recursion as a whole and use a stack data structure along with iteration.

(defun hash-table-key-paths (ht)
  "Returns all key paths in a given hash table - this time using iteration and a stack"
  (let ((stack (list (list ht nil))) ;; <- use a stack to hold all key paths we need to traverse
        (result nil))                ;; <- holds the final result we will return
    (loop while stack do             ;; <- loop until we exhaust the stack
      (destructuring-bind (table paths) (pop stack) ;; <- grab the hash-table/paths pair from the stack
        (when paths
          (push paths result))
        (maphash (lambda (k v) ;; <- map our lambda to the k/v pairs of the hash table
                   (let ((key-path (append paths (list k)))) ;; <- note down the current path so far
                     (if (hash-table-p v)
                       (push (list v key-path) stack) ;; <- new hash table found, which we need to lookup
                       (push key-path result))))      ;; <- regular value found, store the path so far
                 table))
          finally (return (nreverse result)))))

Let’s try it out.

CL-USER> (hash-table-key-paths *ht*)
((:A) (:B) (:C) (:FOO) (:FOO :BAR))

Perfect, now we know the list of valid key paths we can use with our HASH-TABLE-GET-IN function. We will see yet another implementation of the HASH-TABLE-KEY-PATHS function later on in this post when we talk briefly about graphs and tree traversal. Then we will see another implementation using a Depth-First Search approach.

HASH-TABLE-SELECT-KEYS

Another useful function from Clojure is select-keys.

This one is pretty straight-forward using REDUCE.

(defun hash-table-select-keys (table &rest keys)
  "Returns a new HASH-TABLE with only the keys specified by KEYS"
  (reduce (lambda (acc key)
            (let ((val (gethash key table)))
              (if val
                  (progn (setf (gethash key acc) val) acc)
                  acc)))
          keys
          :initial-value (make-hash-table)))

A minor comment here - in above lambda we can replace the LET and IF forms with an IF-LET macro from Alexandria. I’ve left it out from the code for clarity, but what you would probably want to do is to use IF-LET instead.

Now we can have a new hash table with just a subset of the keys of an existing one, e.g.

CL-USER> (hash-table-select-keys *ht* :a :b)
#<HASH-TABLE :TEST EQL :COUNT 2 {100197CB03}>

GROUP-BY

Another useful bit from the functional world is the group-by function. Check out group-by in Racket and group-by in Clojure for more info.

Using group-by we can group items in equivalence groups. Say for example we want to group all items in a list in groups determined by their length. Here’s how we can implement our own group-by function.

(defun group-by (fun list)
  "Groups items in equivalence groups"
  (reduce (lambda (acc item)
            (let* ((k (funcall fun item))
                   (v (gethash k acc nil)))
              (setf (gethash k acc) (append v (list item)))
              acc))
          list
          :initial-value (make-hash-table)))

And now, let’s try our group-by function.

CL-USER> (hash-table-dump-kvs (group-by #'length
                                        (list "a" "bb" "ccc" "dd" "e")))
Key 1: (a e)
Key 2: (bb dd)
Key 3: (ccc)
NIL

Another example showing how to group items in a list based on whether the item is being an odd number.

CL-USER> (hash-table-dump-kvs (group-by #'oddp
                                        (list 1 2 3 4 5 6 7 8 9 10)))
Key T: (1 3 5 7 9)
Key NIL: (2 4 6 8 10)
NIL

One final word about group-by - you should note that this functionality can already be used as part of the group-by library, which is available in Quicklisp, and contains more features out of the box such as using custom functions to extract the keys and values from items.

I’ve included my implementation of group-by in this post, mainly because it shows a different approach to grouping items using REDUCE.

REPEAT

Often times I find myself needing to repeat some sequence of items a given number of times. In order to do that in Common Lisp we can use the MAKE-LIST function.

CL-USER> (make-list 10 :initial-element :A)
(:A :A :A :A :A :A :A :A :A :A)

Or, if you need to implement one yourself you can use one of the following, although I’d discourage doing that unless you are doing this for the sake of experimenting and practicing.

(defun repeat (n item)
  "Returns a list of ITEMs repeated N times using recursion"
  (labels ((process (i acc)
             (if (>= i n)
                 acc
                 (process (1+ i) (cons item acc)))))
    (process 0 nil)))

And another approach using iteration using with the DOTIMES iteration macro.

(defun repeat (n item)
  "Returns a list of ITEMs repeated N times using iteration"
  (let ((result nil))
    (dotimes (i (1- n))
      (push item result))
    result))

You can use REPEAT like this for example.

CL-USER> (repeat 10 :A)
(:A :A :A :A :A :A :A :A :A)

TAKE & DROP

The TAKE and DROP functions are really useful when we are interested in just a subset of a sequence. Here is how we can implement them.

(defun take (n list)
  "Takes N items from LIST"
  (if (>= n (length list))
      list
      (subseq list 0 n)))

Example usage of TAKE:

CL-USER> (take 3 (list 1 2 3 4 5))
(1 2 3)

Now we have a safer wrapper around SUBSEQ.

And this is how we can write DROP.

(defun drop (n list)
  "Drops N items from LIST and returns the CDR"
  (nthcdr n list))

Example usage of DROP.

CL-USER> (drop 3 (list 1 2 3 4 5))
(4 5)

PARTITION

When you need to partition a list of items into groups we can use the partition function as described below. Here is a recursive approach to implementing this function.

(defun partition (n list)
  "Partitions the given LIST into groups of N items - recursive approach"
  (labels ((process (list acc)
             (cond
               ((endp list) acc)
               (t (process (drop n list) (append acc (list (take n list))))))))
    (process list nil)))

And the iterative approach using DO iteration macro looks like this.

(defun partition (n list)
  "Partitions the given LIST into groups of N items - iterative approach"
  (do ((result nil (append result (list (take n list))))
       (list list (drop n list)))
      ((endp list) result)))

And you can partition a list of values like this for example.

CL-USER> (partition 2 (list 1 2 3 4 5 6))
((1 2) (3 4) (5 6))

However, see what happens if we try partitioning with a number greater than the items we can put in the group.

CL-USER> (partition 4 (list 1 2 3 4 5 6))
((1 2 3 4) (5 6))

The last group contains only two items, since there was nothing left to fill in it. We can improve our first version of the partition function to support padding as well. Here’s how we can do it.

(defun partition (n list &key (pad nil pad-supplied-p))
  "Partitions the given LIST into groups of N items - with padding support"
  (labels ((process (list acc)
             (let ((group (take n list)))
               (cond
                 ((endp list) acc)
                 (pad-supplied-p (let ((padding (make-list (- n (length group))
                                                           :initial-element pad)))
                                   (process (drop n list)
                                            (append acc (list (append group padding))))))
                  (t (process (drop n list)
                              (append acc (list group))))))))
    (process list nil)))

Using the :pad key we can now fill our groups with whatever items is required to make it up for the number of items we initially requested, e.g.

CL-USER> (partition 4 (list 1 2 3 4 5 6) :pad nil)
((1 2 3 4) (5 6 NIL NIL))

DFS

Implementing DFS is one of the things I tend to implement when starting with a new language. It is a good task to practice on.

The solution below is more-or-less a translation of how I would implement this in Scheme for example.

I will use a property list to represent the adjacency list of vertices in my sample graph. Perhaps a better way to represent this would be to use a class, but I have yet to learn about CLOS in my Common Lisp journey, so for now a plist would be more than enough.

(defparameter *g* '(:A (:B :C)
                    :B (:A)
                    :C (:A :D)
                    :D (:C)))

Then we will write this helper function which simply returns the neighbors of a given node.

(defun neighbors (graph node)
  "Returns the neighbors of NODE"
  (getf graph node))

And this is our first implementation of DFS.

(defun dfs (graph root)
  "Traverses the graph in Depth-First Search order starting with ROOT node"
  (labels ((traverse (stack visited)
             (let* ((node (car stack))
                    (neighbors (neighbors graph node))
                    (not-seen (remove-if (lambda (x) (member x visited))
                                         neighbors))
                    (new-visited (cons node visited))
                    (new-stack (append not-seen (cdr stack))))
               (cond
                 ((endp new-stack) (nreverse new-visited))
                 (t (traverse new-stack new-visited))))))
    (traverse (list root) nil)))

And now let’s try it.

CL-USER> (dfs *g* :A)
(:A :B :C :D)
CL-USER> (dfs *g* :D)
(:D :C :A :B)
CL-USER> (dfs *g* :B)
(:B :A :C :D)
CL-USER> (dfs *g* :C)
(:C :A :B :D)

This works fine for our sample graph, but what if we wanted to traverse other data structures? Turns out that with slight modifications to above code we can make our DFS function work just fine with anything that can be traversed.

A minor improvement to our function would be to add support for passing a function, which when given a node it will simply return it’s neighbors.

(defun dfs (neighbors-fn root)
  "DFS walks a tree starting with ROOT using the NEIGHBORS-FN to get the neighbors"
  (labels ((traverse (stack visited)
             (let* ((node (car stack))
                    (neighbors (funcall neighbors-fn node))
                    (not-seen (remove-if (lambda (x) (member x visited)) neighbors))
                    (new-stack (append not-seen (cdr stack)))
                    (new-visited (cons node visited)))
               (cond
                 ((endp new-stack) (nreverse new-visited))
                 (t (traverse new-stack new-visited))))))
    (traverse (list root) nil)))

Using our latest version of DFS we can now pass functions, which would evaluate the list of neighbors for a given node. Using our sample graph from before we can now DFS walk it like this.

CL-USER> (dfs (lambda (node)
                 (neighbors *g* node))
                 :A)
(:A :B :C :D)

And here’s an interesting thing we can do now. Remember the HASH-TABLE-KEY-PATHS function we wrote before?

We can use now implement HASH-TABLE-KEY-PATHS by performing a DFS walk. This is how we can evaluate the list of all possible key paths in a a given hash table using the previously implemented HASH-TABLE-KEYS, HASH-TABLE-GET-IN and DFS functions.

First, let’s write a function that knows how to get the neighbors of a key in a hash table.

(defun hash-table-key-neighbors-fn (ht)
  "Returns a function to query the neighbors of a key in the hash table"
  (lambda (item)
    (let ((value (apply #'hash-table-get-in ht item)))
      ;; If the key we are looking up is associated with a value
      ;; which happens to be another hash-table then we consider
      ;; the neighbors of that key to be the keys of the nested
      ;; hash table.
      (when (hash-table-p value)
        (mapcar (lambda (k)
                  (append item (list k)))
                (hash-table-keys value))))))

And we can write our refactored version of HASH-TABLE-KEY-PATHS using DFS walk.

(defun hash-table-key-paths (ht)
  "Returns all key paths in a given hash table using DFS walk"
  (let ((root-keys (mapcar #'list (hash-table-keys ht)))
        (neighbors-fn (hash-table-key-neighbors-fn ht)))
    (apply #'append
           (mapcar (lambda (x)
                     (dfs neighbors-fn x))
                   root-keys))))

And we can test it to confirm it works as expected.

CL-USER> (hash-table-key-paths *ht*)
((:FOO) (:FOO :BAR) (:C) (:B) (:A))

Macros

Macros is one of the areas in which Lisp truly shines compared to other programming languages. There are whole books written on the subject and I’m still fairly new to advanced macro techniques, but I’m slowly making my way through them.

Clojure programmers are quite familiar with the threading macros, and in Elixir a similar concept exists in the form of the pipe operator. Basically what the thread-macros or pipe operator does is that it allows you to thread an expression through series of transformations. It works in a manner similar to what you do with Unix pipes in the shell.

The code below implements thread-first and thread-last macros. Note that such functionality has already been implemented by libraries available via Quicklisp, so you should probably use them instead. I’ve written the following macros, just so that I can get a better feel of how to implement these on my own.The idea behind the code I’m using below is that we have an initial-form and a series of transformations that we need to REDUCE.

This is how the implementation of thread-first looks like.

(defmacro -> (initial-form &body forms)
  (reduce (lambda (acc form)
            (if (listp form)
                (list* (car form)
                       acc
                       (cdr form))
                (list form acc)))
          forms
          :initial-value initial-form))

And this is the implementation of thread-last.

(defmacro ->> (initial-form &body forms)
  (reduce (lambda (acc form)
            (if (listp form)
                (append form (list acc))
                (list form acc)))
          forms
          :initial-value initial-form))

We can test things out now.

CL-USER> (-> (list 1 2 3) car sqrt)
1.0

Above expression gets expanded to the following.

CL-USER> (macroexpand-1 '(-> (list 1 2 3) car sqrt))
(SQRT (CAR (LIST 1 2 3)))
T

And here’s an example of using thread-last.

CL-USER> (->> (list 1 2 3)
           (mapcar (lambda (x) (* x 2)))
           (reduce #'+))
12

Above example expression gets expanded to the following.

CL-USER> (macroexpand-1 '(->> (list 1 2 3)
                          (mapcar (lambda (x) (* x 2)))
                          (reduce #'+)))
(REDUCE #'+ (MAPCAR (LAMBDA (X) (* X 2)) (LIST 1 2 3)))
T

Wrap up

I still need to work through a lot of areas in the language, which I haven’t touched on - CLOS, the Condition System, images, advanced macro techniques, etc. I’m still quite new to Common Lisp, but I hope to change that by spending more time with it.

I bought a copy of the Practical Common Lisp book by Peter Siebel, which I plan to continue reading and work throught the various projects in it. It is an excellent introductory book, if you already have some programming experience, so if you looking for a good book to get you started with Lisp, I’d recommend this one.

Other books I plan to read once I finish PCL would be the Common Lisp Recipes, as this one seems to be recommended by a lot of experienced Lispers, and there’s also a good list of books on Common Lisp here as well that are worth checking out.

So far I like the language - it gives the freedom of choice in regards to which paradigm you want to program in - functional, imperative or object-oriented. That coupled with the powerful capabilities of the macro system and the whole experesiveness of the language makes it a joy to program in.

And finally, if this post sparked some interested in you in regards to Common Lisp I’d recommend checking these links too, which would be helpful to anyone starting with Common Lisp.

You can also go through the 99 Lisp Problems to practice your skills and you can also see answers to these problems here. If you’ve got some experience with other Lisp dialects then this reference sheet will provide useful bits of information.

Oh, and by the way Lisp is out of this world. Happy hacking!

Written on January 5, 2020