# Collection Types

'''
LISTS

- Ordered
- Mutable
- Can contain any type of data
'''

# Empty
lis0 = []

# Declaration
lis1 = [1,2,3]

# Indexing
elem1 = lis1[0]

'''
TUPLES

- Ordered
- Immutable
- Can contain any type of data
- Near-identical in function to lists, more efficient
'''

# Empty
tup0 = ()

# Declaration
tup1 = (1,2,3)
tup1 = 1,2,3

# Indexing
elem2 = tup1[0]

'''
ARRAYS

- Ordered
- Mutable
- Can contain only one pre-specified type of data
- Similar to lists but more efficient
'''

'''
SETS

- Unordered
- Mutable
- Contains unique items
- Implements most operations for mathematical sets
'''

set1 = set(['a','b','c'])
set2 = set(['c','d','e'])
set3 = set(['a','b'])

# Union
s4 = set1 | set2

# Intersection
s5 = set1 & set2

# Subtraction
s6 = set1 - set3

# Subset
if set3 <= set1:
    print "Subset"

# Proper Subset
if set3 <= set1:
    print "Proper subset"

'''
DICTIONARIES

- Set of key-to-value mappings
- Mutable
- Can contain any type of data as values
- Can use many types of data as keys
  (only tuples work in the realm of collection types)
'''

# Empty
dict0 = {}

# Declaration
dict1 = {'a':1, 'b':2, 'c':3}

# Indexing
elem3 = dict1['b']

# Test for key pair
if dict1.has_key('c'):
    print "Got a C"