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Subsections

- Examples
- Exercises

# Boolean Expressions

Here is a little example of boolean expressions (you don't have to type it in):

    a = 6
    b = 7
    c = 42
    print 1, a == 6
    print 2, a == 7
    print 3,a == 6 and b == 7
    print 4,a == 7 and b == 7
    print 5,not a == 7 and b == 7
    print 6,a == 7 or b == 7
    print 7,a == 7 or b == 6
    print 8,not (a == 7 and b == 6)
    print 9,not a == 7 and b == 6

With the output being:

    1 1
    2 0
    3 1
    4 0
    5 1
    6 1
    7 0
    8 1
    9 0

What is going on? The program consists of a bunch of funny looking `print` statements. Each `print` statement prints a number and a expression. The number is to help keep track of which statement I am dealing with. Notice how each expression ends up being either 0 or 1. In Python false is written as 0 and true is written as 1. The lines:

    print 1, a == 6
    print 2, a == 7

print out a 1 and a 0 respectively just as expected since the first is true and the second is false. The third print, `print 3,a == 6 and b == 7`, is a little different. The operator `and` means if both the statement before and the statement after are true then the whole expression is true otherwise the whole expression is false. The next line, `print 4,a == 7 and b == 7`, shows how if part of an `and` expression is false, the whole thing is false. The behavior of `and` can be summarized as follows:

expression | result
true and true | true
true and false | false
false and true | false
false and false | false

Notice that if the first expression is false Python does not check the second expression since it knows the whole expression is false.

The next line, `print 5,not a == 7 and b == 7`, uses the `not` operator. `not` just gives the opposite of the expression (The expression could be rewritten as `print 5,a != 7 and b == 7`). Heres the table:

expression | result
not true | false
not false | true

The two following lines, `print 6,a == 7 or b == 7` and `print 7,a == 7 or b == 6`, use the `or` operator. The `or` operator returns true if the first expression is true, or if the second expression is true or both are true. If neither are true it returns false. Here's the table:

expression | result
true or true | true
true or false | true
false or true | true
false or false | false

Notice that if the first expression is true Python doesn't check the second expression since it knows the whole expression is true. This works since `or` is true if at least one half of the expression is true. The first part is true so the second part could be either false or true, but the whole expression is still true.

The next two lines, `print 8,not (a == 7 and b == 6)` and `print 9,not a == 7 and b == 6`, show that parentheses can be used to group expressions and force one part to be evaluated first. Notice that the parentheses changed the expression from false to true. This occurred since the parentheses forced the `not` to apply to the whole expression instead of just the `a == 7` portion.

Here is an example of using a boolean expression:

    list = ["Life","The Universe","Everything","Jack","Jill","Life","Jill"]

    #make a copy of the list.  See the More on Lists chapter to explain what
    #[:] means.
    copy = list[:]
    #sort the copy
    copy.sort()
    prev = copy[0]
    del copy[0]

    count = 0

    #go through the list searching for a match
    while count < len(copy) and copy[count] != prev:
        prev = copy[count]
        count = count + 1

    #If a match was not found then count can't be < len
    #since the while loop continues while count is < len
    #and no match is found
    if count < len(copy):
        print "First Match: ",prev

And here is the output:

    First Match:  Jill

This program works by continuing to check for match `while count < len(copy and copy[count]`. When either `count` is greater than the last index of `copy` or a match has been found the `and` is no longer true so the loop exits. The `if` simply checks to make sure that the `while` exited because a match was found.

The other `trick' of `and` is used in this example. If you look at the table for `and` notice that the third entry is ``false and won't check''. If `count >= len(copy)` (in other words `count < len(copy)` is false) then copy[count] is never looked at. This is because Python knows that if the first is false then they both can't be true. This is known as a short circuit and is useful if the second half of the `and` will cause an error if something is wrong. I used the first expression (`count < len(copy)`) to check and see if `count` was a valid index for `copy`. (If you don't believe me remove the matches `Jill' and `Life', check that it still works and then reverse the order of `count < len(copy) and copy[count] != prev` to `copy[count] != prev and count < len(copy)`.)

Boolean expressions can be used when you need to check two or more different things at once.

# Examples

password1.py

    ## This programs asks a user for a name and a password.
    # It then checks them to make sure the the user is allowed in.

    name = raw_input("What is your name? ")
    password = raw_input("What is the password? ")
    if name == "Josh" and password == "Friday":
        print "Welcome Josh"
    elif name == "Fred" and password == "Rock":
        print "Welcome Fred"
    else:
        print "I don't know you."

Sample runs

    What is your name? Josh
    What is the password? Friday
    Welcome Josh

    What is your name? Bill
    What is the password? Money
    I don't know you.

# Exercises

Write a program that has a user guess your name, but they only get 3 chances to do so until the program quits.

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