Lists

On Monday, we began talking about Python -- the programming language we are going to use in this AI course.
We talked about installing it, running programs with it, variables, conditionals, File I/O, and strings.

Today, we begin by looking at Python lists... Lists can be declared using square brackets like:

my_list = ['YO', 1.2, 7, "HI", ["scary nested list", "watch out!"]]
my_empty_list = [] # or list()

We can access parts of a list in a variety of ways:

b = my_list[0] # b is now: 'YO'
c = my_list[4][1] # c is now: 'watch out!'
d = my_list[1:3] # d is [1.2, 7]
e = my_list[2:] # e is [7, 'HI', ['scary nested list', 'watch out!']]

Lists can also be easily manipulated to make new lists:

my_list.append("an end") #my_list now 
    #['YO', 1.2, 7, 'HI', ['scary nested list', 'watch out!'], 'an end']
my_list.insert(2, 3) # my_list now
    #['YO', 1.2, 3, 7, 'HI', ['scary nested list', 'watch out!'], 'an end']
a = [1, 2, 3] + [4, 5] #a is [1, 2, 3, 4, 5]

Example Using Lists and Command Line

import sys
if(len(sys.argv)) != 2: 
   #notice sys.argv is a list of command-line args and we found its length
   print "Please supply a filename"
   raise SystemExit(1) # throw an error and exit
f = open(sys.argv[1]) #program name is argv[0]
lines = f.readlines() # reads all lines into list one go
f.close()

#convert inputs to list of ints
ivalues = [int(line) for line in lines]

# print min and max
print "The min is ", min(ivalues)
print "The max is", max(ivalues)

Tuples

You can pack a collection of objects into a single object in Python using a tuple

a = ( 1, "hello", 3)
b = ( some, where)
c = "6 scared of 7", "as 7 8 9" #notice can omit paren's
d = () # 0-tuple
e = 'yo', #one tuple 
f = ('yo',) #same one tuple
g = (d,) # g is ((),)

Can access parts of tuple with the same notation as lists a[1] gives 'hello' for instance. Or we can do things like:
```
c = (4, 5)
a, b = c
```
Tuples cannot be appended or inserted to, but save memory.

Sets

A set is used to contain an unordered collection of objects.

Sets can created, viewed, and check for membership using statements like:

my_set = set([3, 9, 2, 6])
another_set = set("goodness") # set of unique chars
print another_set # set(['e', 'd', 'g', 'o', 'n', 's'])
if 'e' in another_set:
    print "it's in there"

Sets support various operations:

a = my_set; b = another_set;
c = a | b # union of sets
c = a & b # intersection of sets
c = a - b # difference of sets
c = a ^ b # symmetric difference of sets
another_set.add('y') # adds a single element to set
another_set.update([6,7,8]) # add multiple elements
my_set.remove(3) # removes the number 3 from my_set

A frozenset is like a set but cannot be changed

Dictionaries

Python's notion of an associative array (a table of key-value pairs) is called a dictionary.

Dictionary literal make use of curly braces:

person = {
    "name" : "bob",
    "age" : 27,
    "sex" : "Male"
}
empty_dict = {} #an empty dictionary # or use dict()

We can access and modify elements of a dictionary with statements like:

name= person["name"]
person["age"] = 28
person["address"] = "somewhere" #this would add a key-value pair
del person["age"] # removes key value associated with 'age'

Membership of a key in a dictionary can be tested with 'in':

if "name" in person:
   name = person["name"]
else:
   name = "no one"
#the above conditional can be shortened to:
name = person.get("name", "no one")

The list of keys in a dictionary can be gotten with:

keys = list(person) #keys is ['address', 'name',  'sex'] 
#could also do person.keys() 
#person.values() would get list of values
#person.len() gives the number of keys in dictionary

Iteration and Looping

Python supports while loops like most languages:

while condition:
    statement1
    statement2
    ...

Python for loops always behave as a foreach over a sequence:

for n in [1,2,3,4,5,6,7,8,9]:
    print "2 to the %d  is %d" % (n, 2**n)

To make this less cumbersome, Python allows you to declare ranges such as range(1, 10):
```
for n in range(1,10):
    print "2 to the %d  is %d" % (n, 2**n) # same as before
```

The syntax for ranges is: range(start_inclusive, end_exclusive [, stride]):

a = range(5) # can omit start to get a = 0, 1, 2, 3, 4
b = range(1,8) # b = 1, 2, 3, 4, 5, 6, 7
c = range(0, 13, 2) # c = 0, 2, 4, 6, 8, 10, 12
d = range(7, 2, -1) # d = 7, 6, 5, 4, 3

In Python 2, range actually creates a list which can be quite memory intensive for big ranges. If you didn't want a list but just something to iterate over you used xrange. In Python 3, xrange is no more and range() have the default behavior of xrange.

Examples of things can iterate over with for

As we've seen in some of our earlier examples, for can be used with strings, lists, dictionaries, file objects, etc:

a = "Get rich quick"
for b in a:
    print b

c = ["now", "I", "know"]
for d in c:
    print c

person = {
    "name" : "bob",
    "age" : 27,
    "sex" : "Male"
}
for key in person:
    print key, person[key]

f = open("my_file.txt")
for line in f
    print line

Functions

The keyword def is used to create functions in Python:

def smaller_value( a, b):
   if a < b: return a # notice single line if can be same line
   else: return b

Function invocation is similar to most languages:
```
print smaller_value(8, 4)
```

Functions can be recursive and are allowed to take as arguments and return tuples, lists, etc:

def reverse_list(list):
    if list == []: return []
    return reverse_list(list[1:]) + [list[0]]
print reverse_list([1, 2, 3, 4]) # prints [4, 3, 2, 1]

def divide(a,b):
   q = a // b
   r = a - q*b
   return (q, r)
quotient, remainder = divide(2373, 16)

We can also supply default values to functions:

def expify(a, b=2):
   return b**a #if don't give a second argument b will be 2

More Python

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