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:start and :end with parse-integer

parse-integer takes :start and :end arguments, so you don’t have to extract integer subsequences from strings to pass them to parse-integer. For example, to parse date strings that look like “2011-10-01” into year, month, and date integers, you can do this:

(defun parse-date (string)
  "Parse a date string in the form YYYY-MM-DD and return the
   year, month, and day as multiple values."
  (values (parse-integer string :start 0 :end 4)
          (parse-integer string :start 5 :end 7)
          (parse-integer string :start 8 :end 10)))
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Converting characters to integers

If you have the character #\7 and you want the integer 7, you might be tempted to use (parse-integer (string char)) or even this ASCII-oriented technique:

(- (char-int char) (char-int #\0))

While the former is specified to give the right answer, the latter will only work by coincidence. The spec does discuss character ordering, but it makes no guarantees about the values returned by char-int or char-code.

What to use, then? digit-char-p not only returns a true value if its first argument represents a digit, the true value it returns is the integer value of that digit:

* (digit-char-p #\7)
7

It also works with other radixes:

* (digit-char-p #\a 16)
10

If the character is not a digit, digit-char-p returns nil.

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Multi-line format control strings

You can break up long format control strings with ~ at the end of a line. For example:

* (format t "It was the best of times, ~
             it was the worst of times.")
It was the best of times, it was the worst of times.

The ~, newline, and all whitespace following the newline are removed from the output, so you can align the continued control string with the previous line.

The : and @ modifiers have additional meaning:

With a :, the newline is ignored, but any following whitespace is left in place. With an @, the newline is left in place, but any following whitespace is ignored.

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PAIP lessons

Paradigms of AI Programming is a great book for learning Common Lisp. Peter Norvig wrote a retrospective on the book and included this list of 52 important lessons:

  • Use anonymous functions. [p. 20]
  • Create new functions (closures) at run time. [p. 22]
  • Use the most natural notation available to solve a problem. [p. 42]
  • Use the same data for several programs. [p. 43]
  • Be specific. Use abstractions. Be concise. Use the provided tools. Don’t be obscure. Be consistent. [p. 49]
  • Use macros (if really necessary). [p. 66]
  • There are 20 or 30 major data types; familiarize yourself with them. [p. 81]
  • Whenever you develop a complex data structure, develop a corresponding consistency checker. [p. 90]
  • To solve a problem, describe it, specify it in algorithmic terms, implement it, test it, debug and analyze it. Expect this to be an iterative process. [p. 110]
  • AI programming is largely exploratory programming; the aim is often to discover more about the problem area. [p. 119]
  • A general problem solver should be able to solve different problems. [p. 132]
  • We must resist the temptation to belive that all thinking follows the computational model. [p. 147]
  • The main object of this book is to cause the reader to say to him or herself “I could have written that”. [p. 152]
  • If we left out the prompt, we could write a complete Lisp interpreter using just four symbols. Consider what we would have to do to write a Lisp (or Pascal, or Java) interpreter in Pascal (or Java). [p. 176]
  • Design patterns can be used informally, or can be abstracted into a formal function, macro, or data type (often involving higher-order functions). [p. 177]
  • Use data-driven programming, where pattern/action pairs are stored in a table. [p. 182]
  • Sometimes “more is less”: its easier to produce more output than just the right output. [p. 231]
  • Lisp is not inherently less efficient than other high-level languages - Richard Fateman. [p. 265]
  • First develop a working program. Second, instrument it. Third, replace the slow parts. [p. 265]
  • The expert Lisp programmer eventually develops a good “efficiency model”. [p. 268]
  • There are four general techniques for speeding up an algorithm: caching, compiling, delaying computation, and indexing. [p. 269]
  • We can write a compiler as a set of macros. [p. 277]
  • Compilation and memoization can yield 100-fold speed-ups. [p. 307]
  • Low-level efficiency concerns can yield 40-fold speed-ups. [p. 315]
  • For efficiency, use declarations, avoid generic functions, avoid complex argument lists, avoid unnecessary consing, use the right data structure. [p. 316]
  • A language that doesn’t affect the way you think about programming is not worth knowing - Alan Perlis. [p. 348]
  • Prolog relies on three important ideas: a uniform data base, logic variables, and automatic backtracking. [p. 349]
  • Prolog is similar to Lisp on the main points. [p. 381]
  • Object orientation = Objects + Classes + Inheritance - Peter Wegner [p. 435]
  • Instead of prohibiting global state (as functional programming does), object-oriented programming breaks up the unruly mass of global state and encapsulates it into small, manageable pieces, or objects. [p. 435]
  • Depending on your definition, CLOS is or is not object-oriented. It doesn’t support encapsulation. [p. 454]
  • Prolog may not provide exactly the logic you want [p. 465], nor the efficiency you want [p. 472]. Other representation schemes are possible.
  • Rule-based translation is a powerful idea, however sometimes you need more efficiency, and need to give up the simplicity of a rule-based system [p. 509].
  • Translating inputs to a canonical form is often a good strategy [p. 510].
  • An “Expert System” goes beyond a simple logic programming system: it provides reasoning with uncertainty, explanations, and flexible flow of control [p. 531].
  • Certainty factors provide a simple way of dealing with uncertainty, but there is general agreement that probabilities provide a more solid foundation [p. 534].
  • The strategy you use to search for a sequence of good moves can be important [p. 615].
  • You can compare two different strategies for a task by running repeated trials of the two [p. 626].
  • It pays to precycle [p. 633].
  • Memoization can turn an inefficient program into an efficient one [p. 662].
  • It is often easier to deal with preferences among competing interpretations of inputs, rather than trying to strictly rule one interpretation in or out [p 670].
  • Logic programs have a simple way to express grammars [p. 685].
  • Handling quantifiers in natural languiage can be tricky [p. 696].
  • Handling long-distance dependencies in natural language can be tricky [p. 702].
  • Understanding how a Scheme interpreter works can give you a better appreciation of how Lisp works, and thus make you a better programmer [p. 753].
  • The truly amazing, wonderful thing about call/cc is the ability to return to a continuation point more than once. [p. 771].
  • The first Lisp interpreter was a result of a programmer ignoring his boss’s advice. [p. 777].
  • Abelson and Sussman (1985) is probably the best introduction to computer science ever written [p. 777].
  • The simplest compiler need not be much more complex than an interpreter [p. 784].
  • An extraordinary feature of ANSI Common Lisp is the facility for handling errors [p. 837].
  • If you can understand how to write and when to use once-only, then you truly understand macros [p. 853].
  • A word to the wise: don’t get carried away with macros [p. 855].
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Stylish Common Lisp

The Tutorial on Good Lisp Programming Style by Peter Norvig and Kent Pitman is full of useful tips for Common Lisp programmers.

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Touching a file

To create an empty file, like the Unix touch command does, you might try something like this:

;; BOGUS
(close (open "foo.txt" :direction :output 
             :if-does-not-exist :create 
             :if-exists :append))

open has a :direction option specifically for this purpose, though:

(open "foo.txt" :direction :probe :if-does-not-exist :create)

If “foo.txt” does not exist, it will be created. The stream returned is already closed. The spec says this:

[:probe causes] the creation of a “no-directional” file stream; in effect, the file stream is created and then closed prior to being returned by open.

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Reading floats

When the reader sees a number like “3.0” with no exponent marker, the reader will convert it into a single-float by default. You can change what float type is used for conversion by changing *read-default-float-format* to another float type.

For example:

* (/ 22.0 7.0)
3.142857

* (setf *read-default-float-format* 'double-float)
DOUBLE-FLOAT

* (/ 22.0 7.0)
3.142857142857143

The printer will also omit exponent markers if the float type of the number being printed matches *read-default-float-format*.

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Redirecting output

Got a function that writes to *standard-output* but you really want to redirect it somewhere else? You can bind the *standard-output* special variable in all the macros that create temporary streams.

For example, to return the output as a string:

* (with-output-to-string (*standard-output*) 
    (print-marketing-report))
"Source,Hits
twitter,243
google,805
direct,47
"

To write it out to a file:

* (with-open-file (*standard-output* #p"file.txt" :direction :output)
    (print-marketing-report))
NIL
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Swapping places

The naive way to swap the values of two places, a and b, is something like this:

;; BOGUS
(setf temp a)
(setf a b)
(setf b temp)

psetf (parallel setf) can do it in one form:

(psetf a b b a)

But rotatef is best:

(rotatef a b)
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Pluralization

The ~P format directive can do simple pluralization.

* (format nil "You have ~D goat~:P." 42)
"You have 42 goats."

* (format nil "You have ~D goat~:P." 1)
"You have 1 goat."

* (format nil "You have ~D fl~@:P." 42)
"You have 42 flies."

* (format nil "You have ~D fl~@:P." 1)
"You have 1 fly."

Irregular plurals are more complicated:

(format nil "You have ~D ~:*~[mice~;mouse~:;mice~]." n)

(Thanks to stassats for the flies and mice.)