#                                                    strings.py

# A string is an ordered sequence of characters.

# String is a data structure and just like integer is a data structure.
# Integer is a very simple data structure whereas string is a more 
# complex data structure.  Every time you encounter a new data structure
# in any language that you learn, figure out four things:
#
#    1. How do you create an instance of that data structure and give
#       a name to it?
#
#       Ex. sports = "basketball"
#
#    2. How do you view an element of the data structure?  This is what
#       we call 'read access'.
#
#       Ex. letter = sports[0]        # to access the first character
#           print sports[1]           # to access the second character
#
#    3. How do you change an element in the data structure, if possible?
#       For example, if we want to modify the contents of sports so that
#       it holds "Baseball" instead of "baseball", we would have to assign
#       a new character in that location of the sports string by using an
#       assignment operator like this:
#
#           sports[0] = 'B'
#
#       but modifying an element in place in string is NOT allowed in
#       Python.  So, we call string an immutable data structure in Python.
#       The best you can do is to create a new string with a 'B' in the
#       first location and reassign the whole string to be the new value 
#       of the variable sports.  When we study lists later, we will try
#       to modify an element in a list in place.  Stay tuned.
#       Changing the value of a variable is called 'write access', and
#       there are two forms of write access we can think of when we deal
#       with a string.
#       (1) changing a character in the string, e.g., by doing something
#           like:
#
#                sports[0] = 'B'
#
#           but that is not allowed with a string because string is
#           immutable.
#       (2) setting a new string to be the value of the variable, e.g.,
#
#                sports = Baseball
#
#           which is allowed in Python.
#
#    4. How do you destroy the data structure when we are done using it.
#       In a language such as C or C++ you would have to worry about that,
#       but in Python, you don't need to.  So, actually there are only
#       3 things to worry about when you encounter a new data structure
#       in Python.  Sometimes, only 2 as with strings.


# Let's see some strings and related functions that we can use to manipulate
# strings.


# Define a variable with the string value 'banana" as its initial value
#
fruit = "banana"


# String is a compound value and we can access individual pieces in it.

# Here we are accessing the second character in fruit.
#
letter = fruit[1]     

print "letter = ", letter

# Indices in Python are 0-based as in most other programming languages
# So, fruit[1] is accessing the second character in the string.
#
print "fruit[0] = ", fruit[0]

# Length of a string
#
print "len(fruit) = ", len(fruit)


# More looping using strings
#
print "printing fruit using a while loop"

i = 0
while i < len(fruit):
    print fruit[i]
    i = i + 1


# Exercise: Create a function that takes one string argument and prints the
#    letters backward.


# We have learned one kind of a loop in Python so far: the 'while' loop.
# Well, there is another looping construct in Python: the 'for' loop.  
# As you can see below, it has a very simple intuitive form.  This loop
# is often referred to as the 'for-each' loop because that is what it 
# really means.  So, the example below can be read as 
#
#    'for each letter referred to as c in the string 
#     fruit, print the character c'
#
# thus printing each letter in the string to the standard output device,
# i.e., the computer screen.
#
print "printing fruit using a for loop"

for c in fruit:
    print c


# Here is a simple yet fun thing to do.  I think you can figure out what
# this does.
#
prefixes = "JKLMNOPQ"
suffix = "ack"
for letter in prefixes:
    print letter + suffix


# Slicing a string - by using the ':' operator we can specify a range
# within the string.
#
s = "Peter, Paul, and Mary"

print "s[0:5] = ", s[0:5]       # 0 to 5, but 0 inclusive, 5 exclusive
print "s[7:11] = ", s[7:11]
print "s[17:21] = ", s[17:21]

print

print "s[:3] = ", s[:3]         # 0 to 3, but 0 inclusive, 3 exclusive
print "s[17:] = ", s[17:]       # 17 to the end, with 17 inclusive


# Comparing strings - we can use the usual comparison operators that we use
# for numbers to compare two strings.
#

word = "apple"

if word == "banana":
    print "Yes, we have a banana!"
else:
    print "No, we don't have a banana!"

if word < "banana":
    print "Your word, " + word + ", comes before banana."
elif word > "banana":
    print "Your word, " + word + ", comes after banana."
else:
    print "Yes, we have a banana!"


# Finding a letter in a string - we can define a function that does that
# like this:
#
def find(str, ch):
    index = 0
    while index < len(str):
        if str[index] == ch:
            return index
        index = index + 1
    return -1

print "find(\"apple\", 'l') = ", find("apple", 'l')
print "find(\"apple\", 'p') = ", find("apple", 'p')


# Counting - count the occurrences of a letter in a string.
#
def count(str, ch):
    count = 0
    for char in str:
        if char == ch:
            count = count + 1
    return count

print "count(\"apple\", 'p') = ", count("apple", 'p')


print
print

# Built-in string module
#
import string

# To see what things are included in the module:
#
print "dir(string) . . . . . . . . "
print dir(string)

# Two of those are digits and find:
#
print
print "string.digits = ", string.digits
print "string.find = ", string.find

print
print

# If you want to find the documentation on 'find', try this.  Similarly
# you can find documentation on other functions as well.
#
print "string.find.__doc__"
print string.find.__doc__

# Based on the information obtained from the documentation, we can now
# call find:
#
print "string.find(\"banana\", \"nan\") = ", string.find("banana", "nan")


# Exercise 1:
#
# See Section 8.13 of [Downey] to see more exercise problems.