{"id":39,"date":"2005-10-15T07:40:28","date_gmt":"2005-10-15T07:40:28","guid":{"rendered":"http:\/\/69.195.124.246\/~wisecon1\/blog\/?p=39"},"modified":"2005-10-15T07:40:28","modified_gmt":"2005-10-15T07:40:28","slug":"starting_to_thi","status":"publish","type":"post","link":"https:\/\/wisecontradictions.com\/blog\/?p=39","title":{"rendered":"Starting to think like a Computer Scientist"},"content":{"rendered":"

I am in day 2 of programming school and am working my way through "How to Think Like a Computer Scientist<\/a>" (python edition) by Downey, Elkner and Meyers.  This book’s available for *free* as in free beer.  It’s well written and fun to read. <\/p>\n

Learning to think like a computer scientist is practical.  In the author’s words: "The single most important skill for a computer scientist is problem solving. Problem solving means the ability to formulate problems, think creatively about solutions, and express a solution clearly and accurately." <\/p>\n

<\/p>\n

\nLike any new language, there are many new words to learn, but today I
\nlearned an important distinction in the way that computer scientists
\nthink about languages.  I am writing this post in English–a "natural"
\nlanguage that we use for speaking and writing.  Comparatively, Python
\nis a "formal" language designed by people to express computations and
\nthat means it has really strict rules about syntax.  In formal
\nprogramming languages, there are no metaphors, no redundancy, no
\ncontextual clues.  The statements must conform to the computer
\nlanguages’ rules or the interpreter–the high level program that reads
\nall other programs–can’t act on them.  Fortunately, the computer is
\nvery good at saying "I don’t understand."  \n<\/p>\n

\nOne of the things I already like about programming is that you’re able
\nto tinker and get immediate feedback. This is obvious to anyone that
\nprograms, but neat for someone who’s relatively new at it.  I wonder if
\nthe reason that so many programmers are self taught is because formal
\nlanguages lend themselves to self teaching since the interpreter
\nprovides the feedback. For example:<\/p>\n

\nThe first time I asked the python interpreter to multiply 2 * apple, it said:<\/p>\n

\nNameError: name ‘apple’ is not defined\"Instantfeedback\"<\/a><\/p>\n

\nWhich meant that I hadn’t defined "apple."  So I went back and said:<\/p>\n

\napple = 6<\/p>\n

\nand then the interpreter was able to do the math.  This is just a line, but a program is more than that.<\/p>\n

\nPrograms are collections of statements that specify how to perform a
\ncomputation–whether that’s doing math, or putting text together.
\nAccording to the authors, programs can be broken down to these basic
\nsteps:<\/p>\n