Skip to main content

Scheme!

I had a buddy ask me about learning the Scheme programming language... so I figured I'd write a blog post about it!

First a very short history.
A long time ago (in 1958) there was born a language called Lisp.  Lisp is actually the second oldest high level language but that's a different post.  Lisp split into two main branches Common Lisp and Scheme.
Common Lisp is quite large and has lots of features including a full OO system.  Scheme on the other hand is as stripped down as is practical.  For comparison the Common Lisp spec has ~1100 pages while the Scheme R5RS spec has 50 pages.

That being said Scheme has low level primitives which allow you to build high level primitives.
There are lots of great resources out there for learning Scheme and I'm going to list a few here.

Textbooks:



Free textbooks:

Websites:
As for implementations (of which there are many) I think I must recommend either racket or guile.  Racket is a very full featured Scheme including many libraries and a GUI environment where as guile is a smaller scheme used in the Gnome project.

As always the best way to learn a language is to use it.  Scheme is quite a bit different than your standard imperative languages but once your learn it you will have yet another tool in your programming toolbox.

Comments

Popular posts from this blog

Duck typing considered harmful.

I've had a chance to work on a fairly large chunk of Python at this point and have decided that Python (like Perl) is completely untenable at scale.  <rant><rave><drool>  but wait!  I have reasons! Programmers spend most of their time reading code.  We read massive amounts of code.  After we read massive amounts of code we write one... or change one... To make a change to a piece of code you first have to understand what it does and how it interacts with the system around it.  Then we start reading massive amounts of code again.  Anything you can do to minimize the amount of code a programmer has to understand to make a change becomes a huge gain in productivity. Duck typing causes the amount of code you need to read to make a change to grow very large. For example lets look at two functions, one in C++ and one in Python. First in C++ int function(type1 arg1, type2 arg2) {   return arg1->method(arg2); } In this fun...

Publications by Jeff Vitter

Jeff Vitter is the provost and executive vice chancellor and the Roy A. Roberts Distinguished Professor at the University of Kansas. I just stumbled across his page and found a great book on external memory algorithms and data structures external memory algorithms and data structures. IE: algorithms and data structures to use when your dataset is too large to fit in main memory. He has many other papers on his site including several on external memory graph algorithms. Here's the link... http://www.ittc.ku.edu/~jsv/Papers/catalog/

Types of arrays

Arrays are one of the earliest data structures.  They are essentially just a block of memory which is accessed by offset.  Despite their simplicity there are still several broad categories each with their own sets of algorithms. Is the array a fixed size or can it grow as you add elements to it? A fixed size array is called a static array and one that can grow is called a dynamic array. Are the element all of the same type or can they be different? If they must all be the same type then the array are called homogeneous.  Otherwise it is a heterogeneous array. Finally, how many dimensions (subscripts) does the array have? For example, a 2 dimensioned array is a matrix. The number of dimensions doesn't change the structure of the array but changes the way elements are accessed.