The following chapters introduce fundamental concepts of Scheme. To some extent this introduction is independent from LilyPond, as most of the concepts are general Scheme techniques. However, they are all taken from the LilyPond perspective.
We start with discussing data types, followed by a sequence of discussions of more complex concepts and techniques.
When talking to a computer there's no room for ambiguity. Approaching a computational task with irony is almost bound to fail, as the programming language will always want to know what it really is you are talking about. Therefore in programming languages each value has a type, and this is not different in Scheme. If a function processes a number you have to give it a number, sometimes you even have to make a difference between, say, integer and real numbers, e.g. between
1.0. And so on.
Scheme is extremely flexible and permeable with regard to type. If you have an expression like
(some-procedure arg1 arg2)
then Scheme will not check in any way what types the values
arg2 have. Any type mismatch will only become visible upon the procedure application within the expression:
guile> (+ "1" "2") ERROR: In procedure +: ERROR: Wrong type argument in position 1: "1" ABORT: (wrong-type-arg)
You can compare this behaviour with other programming languages. In “strongly typed” languages like Java or C++ the function interface would already act as a shield against arguments with wrong types. The
"2" wouldn't even reach the
So Scheme doesn't check the type of an argument passed into an expression but doesn't do anything to help with improper types either. This is an important characteristic because instead of the three literal elements the expression could equally consist of expressions themselves whose resulting type will only be known at runtime:
((return-a-procedure) (return-arg1) (return-arg2))
So Scheme is open for very elegant and concise dynamic programming tricks. Admittedly this is still pretty abstract. What you should remember at this point is that the type of an expression's elements is not enforced by Scheme, but that passing arguments of unsuitable type will cause errors during procedure application.
Of course it's no good idea to simply throw values at a procedure and wait for errors to occur or not. In Scheme it is therefore very common to check the type of a value before using it. As a response the program will either reject the value or select suitable code to be executed. This will be discussed in a later chapter on conditionals.
Scheme does not have a (regular) way of revealing the type of something directly (which is part of the open characteristic). The approach taken instead is something like asking “is this object behaving like a certain type, does it have the right properties?” This is achieved using predicates. Predicates are procedures that take an object and return true if the object matches a certain definition or false otherwise. By convention the name of a predicate has a trailing question mark, so for example
number? checks if a given value is a number etc.
guile> (string? "I'm a string") #t guile> (integer? 4.2) #f guile> (boolean? #f) #t guile> (boolean? "true") #f
We will come back to the topic of predicates after having discussed writing procedures, for now we will continue with the discussion of a number of basic data types.
If at some point you might want to get more in-depth information about simple data types you should consult the reference in the Guile manual.