MicroPython ‘dictionary’ Data Type

Contents

• Introduction
• Dictionary Definition
• Accessing the Dictionary
  • Adding, Updating and Deleting Entries to a Dictionary
  • Dictionary Membership
• Dictionary Functions
• Dictionary Methods
• MicroPython Tutorial Links

Introduction

MicroPython is a “slim” version of Python specifically designed with a small footprint to efficiently run on memory constrained microcontrollers.

Computer languages have a built-in set of data types along with user capability to define custom types. MicroPython is no exception. The built-in data types for MicroPython:

• Numeric
• Boolean
• Sequence Type
• Set
• Dictionary

The python dictionary can also be considered a collection type

There are four collection data types in the Python programming language:

• List is a collection which is ordered and changeable.
• Tuple is a collection which is ordered and unchangeable.
• Set is a collection which is unordered, unchangeable and unindexed.
• Dictionary is a collection which is ordered^[1] and changeable.

Dictionary Definition

A MicroPython dictionary is similar to a MicroPython list. The main difference is the manner used to access elements with list elements by index and dictionary elements by key.

• Dictionaries and lists are mutable. This means that existing elements can be altered (changed).
• Dictionaries and lists are dynamic. They can grow or shrink in size.
• Dictionaries and lists can be nested. A list can be an element in another list. An element within a dictionary may be another dictionary or even a list. A dictionary might also be a dictionary of other dictionaries.
• While list elements are accessed by index (their position in the list), dictionary elements are accessed by keys.

A dictionary consists of a collection of key-value pairs. Each key-value pair maps the key to its associated value.

A dictionary can be defined by enclosing a comma-separated list of key-value pairs in curly braces { }. A colon : separates each key from its associated value. A dictionary can also be created with the dictionary function (constructor) dict().

# Different ways to define dictionaries.

# Direct assignment
d1 = {'Color' : 'blue', 'Doors' : 4}
print('d1 =', d1)

# Convert list to dictionary with dict()
d2 = dict([('Color', 'red'), ('Doors', 2)])
print('d2 =', d2)

# Another way to use dict()
d3 = dict(Color = 'brown', Doors = 3)
print('d3 =', d3)

# Empty dictionary
d4 = {}
print('d4 =', d4)

# Dictionary of dictionaries
all = {1 : d1,
       2 : d2,
       3 : d3}
print('all =', all)
          

d1 = {'Color': 'blue', 'Doors': 4}
d2 = {'Color': 'red', 'Doors': 2}
d3 = {'Color': 'brown', 'Doors': 3}
d4 = {}
all = {3: {'Color': 'brown', 'Doors': 3}, 
       1: {'Color': 'blue', 'Doors': 4},
       2: {'Color': 'red', 'Doors': 2}}
          

Accessing the Dictionary

As noted above dictionary entries are not accessed with an index. Rather, by using the key enclosed in square brackets [ ] it will reference the associated value. An error (exception) will be raised if the key doesn't exist within the dictionary. A MicroPython tutorial on exception handling can be found here.

          # Accessing dictionary elements.

# Defining some dictionaries
d1 = {'Color' : 'red', 'Doors' : 4}
d2 = dict([('Color', 'green'), ('Doors', 2)])
d3 = dict(Color = 'brown', Doors = 3)

# Get value from each dictionary
# where the key = 'Color'.
print(d1['Color'], d2['Color'], d3['Color'])
print()

# Attempting to access a dictionay key
# that doesn't exist will throw an error.
print(d1['Tyres'])

          

red green brown

Traceback (most recent call last):
  File "main.py", line 15, in <module>
KeyError: Tyres

          

The request for the value of key 'Tyres' from dictionary d1 returns a KeyError exception as this key doesn't exist in the dictionary.

The following code snippet is a much more in-depth dictionary example where all elements of a dictionary are also dictionaries. Additionally, each nested dictionary also contains a list.

# Example of nested dictionaries.

# Each value of the dictionary 'towns' is another dictionary,
# i.e. dictionaries nested within a parent dictionary.

towns = {'Hampton' : {'country' : 'UK', 'av_age' : 35.9, 'climate' : ['26', 'humid']},
         'Clayton' : {'country' : 'USA', 'av_age' : 29.3,'climate' : ['19', 'dry']},
         'Sanyun'  : {'country' : 'Korea', 'av_age' : 18.4,'climate' : ['12', 'wet']}}

# Return some statistics from the 'towns' dictionary      
print("Average age of Clayton's population is", towns['Clayton']['av_age']) 
print("Sanyun's average temperature is", towns['Sanyun']['climate'][0])

          

Average age of Clayton's population is 29.3
Sanyun's average temperature is 12
          

# Adding & updating entries in a dictionary

# Define a dictionary
dict1 = {'Color' : 'red', 'Doors' : 4}
print('Before:', dict1)
print()

# Add the key 'tyres' to the dictionary
dict1['Tyres'] = 'Dunlop'

# Change the value of the key 'color'
# from 'red' to 'yellow'
dict1['Color'] = 'yellow'

# Verify the changes
print('After:', dict1)

            

Before: {'Color': 'red', 'Doors': 4}

After: {'Color': 'yellow',
        'Doors': 4,
        'Tyres': 'Dunlop'}
            

# Delete a dictionary entry

dict1 = {'Color' : 'red', 'Doors' : 4}

del dict1['Color']
print(dict1)

            

{'Doors': 4}
            

# Using the operators 'in' and 'not in'
# to guard against an exception being
# raised when accessing a dictionary
# with a key that doesn't exist.

# Define a dictionary
dict1 = {'Color' : 'red', 'Doors' : 4}

# Use operator 'in' to check
# that key 'Tyre' exists before attempting
# to access its associated value.
if ('Tyre' in dict1):
    print("'Tyre' is", dict1['Tyre'])
else:
    print("No entry for 'Tyre' found")

# Use operator 'not in' to check whether
# the key 'Color' exists in the dictionary.
if ('Color' not in dict1):
    print("No entry for 'Color' found")
else:
    print("'Color' is", dict1['Color'])
            

No entry for 'Tyre' found
The value of 'Color' is red
            

Dictionary Functions

Dictionary Methods