Python's Data Structures: Dictionary
CSCI 1470

by K. Yue

1. Dictionary Review

• Review: go to Type.html (section 3.8).

2. Dictionary Basics

• Python's dict:
  1. dicts are mutable.
  2. store key-value pairs.
  3. keys are unique.
  4. keys are immutable.
  5. Values can be mutable.
  6. Efficient storage for fast retrieval. Implemented as hash tables.
• Since Python 3.7, dictionaries maintain the order in which items are inserted.

Example:

dict_basic_1.py:

#
#   Python dict basic
#
person_1 = {
    "name": "Jane",
    "dob": "12/08/1997",
    "city": "Houston"
}

print(f"person_1: {person_1}")

print(f"id(person_1): {id(person_1)}")
person_1['school'] = 'uhcl'
print(f"person_1 after 'person_1['school'] = 'uhcl'': {person_1}")
print("dicts are mutable.")
print(f"id(person_1): {id(person_1)}")

print("""
#   keys are unique.
person_2 = {
    "name": "Jane",
    "name": "Johnson",
    "dob": "12/08/1997",
    "city": "Houston"
}
""")
#   keys are unique.
person_2 = {
    "name": "Jane",
    "name": "Johnson",
    "dob": "12/08/1997",
    "city": "Houston"
}
print(f"person_2: {person_2}")

def hello():
    print("hello")
def bye():
    print("bye")  

print("""
#  keys can be any mutable.
dict_1 = {
    hello: 1,
    bye: 2,
    "hello": 3,
    4: 4
}
""")
#  keys can be any immutable.
dict_1 = {
    hello: 1,
    bye: 2,
    "hello": 3,
    4: 4
}
print(f"dict_1: {dict_1}")
print(f"dict_1[hello]: {dict_1[hello]}")
print(f"dict_1['hello']: {dict_1['hello']}")
print(f"dict_1[4]: {dict_1[4]}")

#   Keys cannot be mutable.
print("""
#   Keys cannot be mutable.
list_1 = [1,2,3]
dict_2 = {
    "hey": 1,
    list_1: 2
}
Traceback (most recent call last):
  File "...", line 63, in <module>
    dict_2 = {
TypeError: unhashable type: 'list'
""")

print("""
#   values can be mutable.
list_1 = [1,2,3]
dict_2 = {
    "hey": 1,
    "ho": list_1
}
""")

#   values can be mutable.
list_1 = [1,2,3]
dict_2 = {
    "hey": 1,
    "ho": list_1
}
print(f"list_1: {list_1}")
print(f"dict_2: {dict_2}")

# 
list_1.append(4)
print("After 'list.append(4)':")
print(f"   list_1: {list_1}")
print(f"   dict_2: {dict_2}")

dict_2['ho'].append(7)
print("After 'dict_2['ho'].append(7):")
print(f"   list_1: {list_1}")
print(f"   dict_2: {dict_2}")

3. Modifying dicts

• There are many methods for modifying dicts.
  • del dict_a[key]: the del statement can be used to delete an item of a mutable object (dicts are mutable).
  • dict_a[key] = value: can be used to add or update a key value.
  • dict_a.extend(dict_b): can be used to add the items in dict_b to dict_a.

Example:

dict_more_1.py:

#
#   Python dict: more.
#
person_1 = {
    "name": "Jane",
    "dob": "12/08/1997",
    "city": "Houston"
}

print(f"person_1: {person_1}")
person_1['city'] = 'Galveston';
print(f"person_1 after 'person_1['city'] = 'Galveston'': {person_1}")

print(f"person_1['city']: {person_1['city']}")

print("""
print(f"person_1['state']: {person_1['state']}")
Traceback (most recent call last):
  File "...\dict_more_1.py", line 16, in <module>
    print(f"person_1['state']: {person_1['state']}")
KeyError: 'state'
""")

print("Use the error-safe method get(), which returns a user-specified value if the key cannot be found.")

print(f"person_1.get('city', 'unknown'): {person_1.get('city', 'unknown')}")
print(f"person_1.get('state', 'unknown'): {person_1.get('state', 'unknown')}")

print()
print("Replacing the name key by first and last name.")

del person_1['name']
print("del person_1['name']")
print(f"person_1 : {person_1}")

print("""
person_1['first name'] = 'Jane'
person_1['last name'] = 'Johnson'
""")

person_1['first name'] = 'Jane'
person_1['last name'] = 'Johnson'
print(f"person_1: {person_1}")
print(f"len(person_1): {len(person_1)}")

uhcl = {
    'University abbreviation': 'uhcl',
    'University name': 'University of Houston-Clear Lake',
    'Univesrity state': 'Texas'
}
print(f"uhcl: {uhcl}")
print(f"person_1: {person_1}")
person_1.update(uhcl)
print(f"uhcl: {uhcl}")
print(f"person_1: {person_1}")
 

4. Iterating dicts

• dict methods for faciliating iteration.
  1. dict_1.keys(): Returns a view object of all keys.
  2. dict_1.values(): Returns a view object of all values.
  3. dict_1.items(): Returns a view object of all key-value pairs.
• view objects are dynamic and live. They are views/windows on the underlying dict.

Example:

dict_iter_1.py

#
#   Python dict: iteration
#
person_1 = {
    'name': 'Jane',
    'dob': '12/08/1997',
    'city': 'Houston',
   'university': 'UHCL'
}

print("""dict methods for iteration.
    dict_1.keys(): Returns a view object of all keys.
    dict_1.values(): Returns a view object of all values.
    dict_1.items(): Returns a view object of all key-value pairs.
""")

print(f"person_1: {person_1}")
print(f"person_1.keys(): {person_1.keys()}")
print(f"person_1.values(): {person_1.values()}")
print(f"person_1.items(): {person_1.items()}")

print("""view objects are dynamic and live.
They are views/windows on the underlying dict.
""")
print("keys = person_1.keys()")
keys = person_1.keys()

print(f"keys: {keys}")
print("person_1['hobbies'] = {'primary': 'music', 'others': ['games', 'woodwork']}")
person_1['hobbies'] = {'primary': 'music', 'others': ['games', 'woodwork']}
print(f"person_1: {person_1}")
print(f"keys: {keys}")

#   iterations to pretty print a dict.
print()
print(f"person_1: {person_1}")

print("""
print('{')
for key in person_1.keys():
    print(f"    {key}: {person_1[key]}")
print('}')
""")
print('{')
for key in person_1.keys():
    print(f"    {key}: {person_1[key]}")
print('}')

print("""
print('{')
for key, value in person_1.items():
    print(f"    {key}: {value}")
print('}')
""")
print('{')
for key, value in person_1.items():
    print(f"    {key}: {value}")
print('}')

print("""
import pprint
pprint.pp(person_1, indent=4)
""")

import pprint
pprint.pp(person_1, indent=4)

print()
print("pprint.pp(person_1, indent=4, sort_dicts=True)")
pprint.pp(person_1, indent=4, sort_dicts=True)

print("""
#   simple summing use cases.
sales_by_region = {
    'North': 1120,
    'South': 2100,
    'East': 3219,
    'West': 4050}
total_sales = 0
for sales_amount in sales_by_region.values():
    total_sales += sales_amount
print(f"Total sales across all regions: {total_sales}")""")
#   simple summing use cases.
sales_by_region = {
    'North': 1120,
    'South': 2100,
    'East': 3219,
    'West': 4050}
total_sales = 0
for sales_amount in sales_by_region.values():
    total_sales += sales_amount
print(f"Total sales across all regions: {total_sales}")

# version #2:
print('print(f"Total sales across all regions: {sum(sales_by_region.values())}")')
print(f"Total sales across all regions: {sum(sales_by_region.values())}")

5. Nested Data Structures (dict)

• Nested data structures involve placing one data structure inside another, enabling the organization of complex and hierarchical data. 
• Lists and dictionaries are frequently used in nested data structures.

Example:

nested_ds_1.py:

#
#   Nested data structures.
#

#   Each item in score_1 contains the scores of three homework assignments.
scores_1 = [
   [96, 89, 97],
   [88, 84, 83],
   [64, 57, 72]
]
print("""
#   Each item in score_1 is the score of three homework assignments.
scores_1 = [
   [96, 89, 97],
   [88, 84, 83],
   [64, 57, 72]
]
""")

#   print the individual scores of each student.
for item in scores_1:
    print(f"student score: ", end="")
    for score in item:
        print(score, end=" ")
    print()

print()   
#   putting a comma between scores.
for item in scores_1:
    print(f"student scores: ", end="")
    for pos, score in enumerate(item):
        if pos == len(item)-1:
            print(score)
        else:
            print(f"{score}, ", end="")

print()            
#   Second version using list comprehensions.
for item in scores_1:
    print(f"student scores: ", end="")
    str_item = [str(score) for score in item]
    print(", ".join(str_item))
   
print()   
#   add student #
for student_num, item in enumerate(scores_1):
    print(f"student #{student_num + 1} scores: ", end="")
    for pos, score in enumerate(item):
        if pos == len(item)-1:
            print(score)
        else:
            print(f"{score}, ", end="")

#   Each item in score_2 contains a dict with the name of the student as the key and the scores of three homework assignments as the value.
scores_2 = {
   "Joe": [96, 89, 97],
   "Jane": [88, 84, 83],
   "Jenny": [64, 57, 72]
}

print() 
for student in scores_2.keys():
    print(f"{student}'s scores: ", end="")
    for pos, score in enumerate(scores_2[student]):
        if pos == len(item)-1:
            print(score)
        else:
            print(f"{score}, ", end="")

scores_3 = {
   "Joe": {"HW1": 96, "HW2": 89, "HW3": 97, "HW4": 84},
   "Jane": {"HW1": 88, "HW2": 84, "HW3": 83},
   "Jenny": {"HW1": 64, "HW2": 57, "HW4": 72}
}

print() 
for student in scores_3.keys():
    print(f"{student}'s scores: ", end="")
    for pos, assignment_name in enumerate(scores_3[student].keys()):
        if pos == len(scores_3[student].keys())-1:
            print(f"{assignment_name}: {scores_3[student][assignment_name]}")
        else:
            print(f"{assignment_name}: {scores_3[student][assignment_name]}, ", end="")