Memoization in Recursion

Python Dictionaries

Python dictionaries are unordered collections of key-value pairs. Keys must be immutable (e.g., strings, numbers, tuples), while values can be of any data type.

Key Features:

Key-Value Pairs: Data is stored as key-value pairs, allowing for efficient lookups using keys.
Mutability: Dictionaries are mutable, meaning you can add, remove, or modify elements after creation.
Unordered: Prior to Python 3.7, dictionaries were unordered. While they appear ordered in later versions, relying on this order is not recommended for code portability.
Hashing: Dictionaries utilize hashing for efficient key lookups. This means that accessing a value by its key is typically very fast, O(1) on average.

Creating Dictionaries:

There are several ways to create dictionaries:

Using curly braces {}:

my_dict = {"name": "Alice", "age": 30, "city": "[New York](./../new-york/)"}

Using the dict() constructor:

my_dict = dict(name="Bob", age=25, city="London")

From a list of tuples:

my_dict = dict([("name", "Charlie"), ("age", 35), ("city", "Paris")]])

Accessing Elements:

Elements are accessed using their keys:

print(my_dict["name"]])  # Output: Alice (or Bob, or Charlie, depending on which creation method above was used)

If a key doesn’t exist, a KeyError is raised. Use the get() method to avoid this:

print(my_dict.get("country", "Unknown")) # Output: Unknown (or the country if it exists)

Adding and Modifying Elements:

my_dict["occupation"]] = "Engineer" #Adding a new key-value pair
my_dict["age"]] = 31 #Modifying an existing key-value pair

Removing Elements:

del my_dict["city"]] # Removes the key-value pair with key "city"
popped_value = my_dict.pop("age") #Removes and returns the value associated with the key "age"
my_dict.popitem() #Removes and returns an arbitrary key-value pair

Iterating through Dictionaries:

#Iterating through keys
for key in my_dict:
    print(key)

#Iterating through values
for value in my_dict.values():
    print(value)

#Iterating through key-value pairs
for key, value in my_dict.items():
    print(f"Key: {key}, Value: {value}")

Dictionary Methods:

Dictionary Methods (This will be a separate note)

Common Use Cases: Dictionaries are frequently used to represent structured data, such as configurations, data from JSON or other APIs, and more.

Dictionary vs. Lists and Tuples (This will be a separate note)

Example:

person = {
    "name": "John Doe",
    "age": 30,
    "address": {
        "street": "123 Main St",
        "city": "Anytown",
        "zip": "12345"
    },
    "phone_numbers": ["555-1234", "555-5678"]]
}

print(person["address"]]["city"]]) # Accessing nested dictionaries

Python Dictionaries

Carson West

Memoization in Recursion

Python Dictionaries