Tuples & Dictionaries

Overview

Teaching: 10 min
Exercises: 0 min

Questions

• How can I add semantic value to my collections of multiple values?

Objectives

• Identify lists, tuples and dictionaries

• Write programs that create and modify dictionaries

• Select the best data collection type for a given purpose.

Tuples are “immutable” lists

• Sometimes it is useful to “bind” different pieces of data together.
• Tuples can be indexed like lists

name = ('Paul', 'Wilson')
first_name = name[0]
last_name = name[1]
print(first_name,last_name)

• Individual entries in tuples cannot be changed

name = ('Paul', 'Wilson')
name[1] = 'Nagus-Wilson'

TypeError                                 Traceback (most recent call last)
<ipython-input-85-8f02ace9e6af> in <module>()
      1 name = ('Paul','Wilson')
----> 2 name[1] = 'Nagus-Wilson'

TypeError: 'tuple' object does not support item assignment

Immutability preserves order

• Lists of tuples are better than parallel lists
• Can’t accidentally change data that is presumed to correspond

first_names = ['Paul', 'Patrick', 'Kalin']
last_names = ['Wilson', 'Shriwise', 'Kiesling']
last_names[1] = 'Nagus-Wilson'
print(first_names)
print(last_names)
names = [('Paul','Wilson'), ('Patrick','Shriwise'), ('Kalin','Kiesling')]
print(names[0])

Dictionaries add meaningful labels

• Once you start binding data together, it is often useful to add semantic meaning
• Dictionaries allow you to label the entries that are bound together
  • Be sure to choose meaningful names!
• Dictionaries are mutable, you can change them
  • Because of meaningful labels, this is less dangerous

name = {'first': 'Paul', 'last': 'Wilson'}
print(name['first'], name['last'])
name['last'] = 'Nagus-Wilson'
print(name['first'], name['last'])

Paul Wilson
Paul Nagus-Wilson

Entries can be added to a dictionary

• As long as the variable is already of a dictionary type, new entries can be added as if they were already there
• Only one item can exist for each unique key
  • Assigning a new value to an existing key overwrites the old value

my_name = {'first': 'Paul', 'last': 'Wilson'}
my_name['middle'] = 'Philip'
print(my_name)
my_name['last'] = 'Nagus-Wilson'
print(my_name)
your_name['first'] = 'Henry'

{'first': 'Paul', 'last': 'Wilson', 'middle': 'Philip'}
{'first': 'Paul', 'last': 'Nagus-Wilson', 'middle': 'Philip'}

--------------------------------------------------------------------------
NameError                                 Traceback (most recent call last)
<ipython-input-97-cc04cabb3603> in <module>()
      1 my_name = {'first': 'Paul', 'last': 'Wilson'}
      2 my_name['middle'] = 'Philip'
----> 3 your_name['first'] = 'Henry'

NameError: name 'your_name' is not defined

Use del to remove items from a dictionary entirely.

my_name = {'first': 'Paul', 'middle': 'Philip', 'last': 'Wilson'}
print(my_name)
del my_name['middle']
print(my_name)

{'first': 'Paul', 'middle': 'Philip', 'last': 'Wilson'}
{'first': 'Paul', 'last': 'Wilson'}

Various ways to access all the entries in a dictionary

• The names of each entry are called keys
• The values of each entry are called values

name = {'first': 'Paul', 'last': 'Wilson'}
print(name.keys())
print(name.values())

dict_keys(['first', 'last'])
dict_values(['Paul', 'Wilson'])

All collection types can be nested

• Lists, tuples and dictionaries may all contain lists, tuples and dictionaries

instructors = [{'first':'Paul', 'middle': 'Philip', 'last':'Wilson'},       # list of dictionaries
               {'first':'Kalin','last':'Kiesling'},
               {'first':'Patrick','last':'Shriwise'}]
axes_tics = {'x': [0,0.1,0.2,0.3,0.4,0.5],              # dictionary of lists
             'y': [0,10,20,30,40,50]}
curve_points = [(0,0), (2,3), (4,5), (6,-3), (8,-10)]   # list of tuples
shapes = { 'shape_01': [(0,0), (3,4), (6,-3), (10,-6)], # dictionary of lists of tuples
           'other_shape': [(12,4.5), (15,10), (4,78)] }
print(shapes)

• Defining collections as above looks cumbersome. Often collections are defined more programmatically, a little at a time, rather than in a single big block.

Choosing the best data structure

• Best Practice: Write programs for people and not for computers!
• The best choice of data structure depends on how you will use it
• Focus on clarity before performance
• Good data structure choices can make your code easier to follow

Lists & Tuples vs Dictionaries

• Does the data have a natural order?
  • Yes → consider a list, dictionaries can be sorted by their keys, but order is not inherent
  • All access to list data is either by looping through it in order, or by referring to an entry by it’s ordinal place in the list
  • All access to dictionary data is either by looping through it, perhaps in some arbitrary order, or by referring to an entry by it’s semantic meaning
• Does the addition of keys add semantic value?
  • Yes → probably benefit from a dictionary
  • No → fabricating keys that don’t have semantic value can be counter-productive
    • If the order of entries IS the semantic value, then use a list

Lists vs Tuples

• Do you want to clearly indicate that certain data has an immutable relationship?
  • Yes → choose a tuple; immutability provides a weak form of semantics since order is fixed

Key Points

• A tuple is a list that can never be changed.

• Use an item’s index to fetch it from a tuple.

• Dictionaries are lists in which the semantic meaning of each entry is more important than its order.

• New entries can be added to an existing dictionary by assignment.

• Dictionary keys are unique - only one item can exist per key

• Use del to remove items from a list entirely

• You can access all the keys and all the values of a dictionary

• Collections (lists, tuples, dictionaries) may be nested arbitrarily

• Code clarity & maintainability should guide choice of collection type