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HOW PYTHON IS DIFFERENT
Comments for those with prior programming experience
Bruce Sherwood, Fall 2006; revised Fall 2009
(For more formal comparisons, see Google)

In many respects Python is like any other algorithmic programming language (C, Pascal, Java, etc.) and unlike, say, Lisp. There are a few features of Python that an experienced programmer doesn't expect because they are embedded in a seemingly familiar environment yet are quite different from most algorithmic languages. This document attempts to point out the most important ones.

DYNAMIC TYPING
When you say "z1 = Zork(cost=23)" you create a Zork object and stick a label on it, "z1". There is no need (and no way) to declare "z1" to be of type "Zork" before labeling this instance of the class "Zork" with the label "z1".

If you now say "z2 = z1" you have not created any new object, you have merely stuck a second label "z2" on the existing Zork object. Note carefully that this does NOT create a second instance of the class "Zork". If you alter z1.cost it is just the same as altering z2.cost. Making a second, independent copy of an object is a fairly unusual thing to do in Python, but there exist special methods for doing this.

If you now say "z1 = 3.7" the label "z1" no longer refers to the Zork object, and a reference counter on the Zork object is decremented. You can still refer to the object with expressions such as "z2.cost". If you then say "z2 = 28.7/3.4" there is no longer any way to refer to the Zork object. The Zork object reference count is decremented again, to zero, and the object is now marked as eligible to be deleted by the garbage collection routine, since there is no longer any way to refer to it.

This label behavior only applies to objects that are "mutable" (can be changed; see next section). In contrast, if you say "a = b = 5" and then say "b = 2", "a" still has the value 5.

Special case for VPython: Humanly visible objects such as boxes or spheres in a graphics scene have an extra reference count so that even if there are no labels on these objects, they are not deletable because a human viewer counts as a reference. To delete a visual object it is first necessary to set the visible attribute to False.

MUTABLE AND IMMUTABLE
An important Python structure is a list: mylist = [3, 'dog', 4.7, Zork(cost=23), box()]. The 'dog' in this list can be referred to as mylist[1], the elements being numbered starting with zero. If you say mylist[1] = 42 you've changed 'dog' to 42 in the list. The ability to change elements in a list means that lists are "mutable".

A different list-like structure is a tuple: mytup = (3, 'dog', 4.7) is created using parens instead of square brackets. You can read an element, so mytup[1] refers to 'dog', but you cannot change an element. A tuple is "immutable". The only way to achieve the effect is something like this:  mytup = (mytup[0], 42, mytup[2]), which creates a new tuple.

Lists and tuples are examples of what are called "sequences" in Python. A third important kind of sequence is a dictionary, which is a container of elements with keywords, and you index in not by position but by keyword (as a string).

"FOR" LOOPS
A particularly delightful and powerful feature of Python is that you can loop over any sequence. Suppose for example you have created objects for the planets. You can loop over them like this:

for planet in [Mercury, Venus, Earth, Mars, Jupiter, Saturn, Uranus, Neptune, Pluto]:
            print planet.pos, planet.mass, planet.radius

This could also be written like this:

planets = [Mercury, Venus, Earth, Mars, Jupiter, Saturn, Uranus, Neptune, Pluto]
for planet in planets:
            print planet.pos, planet.mass, planet.radius

INTEGER DIVISION
As in many languages including C, 3/4 normally evaluates as zero rather than 0.75. There is a slow migration path for Python eventually to treat 3/4 as 0.75 rather than zero. You can invoke this behavior now by making the following statement the first statement in the program:

from  __future__  import division

Note carefully that there are TWO underlines before "future" and TWO underlines after "future".

IDLE VS SHELL
If you run Python directly, or operate in the "shell" window of IDLE, the editor that comes with Python, you can execute statements interactively. Many experienced programmers find this a useful mode.

Some people much prefer to write whole programs, even small ones, because it is easier to revise and easier to understand what state of module import one is in. There are two features in IDLE that can be set in the Configure IDLE menu option (if not already set at install time) which make edit/compile/run/revise cycles almost as immediate as the shell window. One feature is to specify that whenever you press F5 to run, the current version of your file is automatically saved to disk ("autosave"; note that there is nearly infinite un-do available). The other is an option to specify that at startup IDLE should open an edit window rather than the shell window (you can always open a shell window later, and one is created when you run a program, because that's where text output goes). The first time you press F5 to run, you will be asked to specify where to save the file, but with autosave turned on you won't be asked again.

The effect is that when you start IDLE you're ready to enter a program, and after the initial save, the programming cycle is extremely simple: just press F5 to save and run. One-touch testing.

(As of Fall 2009 the VIDLE variant of IDLE lets you specify that you don't need to save the file even the first time. If you exit VIDLE without saving the file to a permanent location, you're invited to do the save. With this restoration of a feature that used to be present in IDLE, you can now write little test routines without the distraction of saving the file. It is expected that the standard IDLE distributed with future versions of Python will incorporate the recent improvements currently available in VIDLE.)

For a more powerful interactive environment, you might be interested in ipython.