Update Nested Dictionary - Python

A nested dictionary in Python is a dictionary that contains another dictionary (or dictionaries) as its value. Updating a nested dictionary involves modifying its structure or content by:

• Adding new key-value pairs to any level of the nested structure.
• Modifying existing values associated with specific keys.
• Removing key-value pairs from any level within the nested structure.

Direct Assignment

Direct assignment is the most straightforward method to update a nested dictionary. We access the nested key directly and assign a new value to it.

Example:

# Initial nested dictionary
d = {
    "name": "Bob",
    "age": 20,
    "grades": {
        "math": "A",
        "science": "B"
    }
}

# Updating the science grade to 'A'
d["grades"]["science"] = "A"

print(d)

{'name': 'Bob', 'age': 20, 'grades': {'math': 'A', 'science': 'A'}}

Explanation:

• Accessing Nested Keys: student["grades"]["science"] accesses the science grade within the grades dictionary.
• Assigning New Value: By setting it equal to "A", we update the existing grade from "B" to "A".

Nested Dictionary Structure:

Below are all the primary methods to update nested dictionaries:

Using the .update() Method (For shallow Nested)

The .update() method allows us to update multiple key-value pairs at once. It can be used on the nested dictionary to add new entries or modify existing. It is used for simple updates to shallow or moderately nested dictionaries.

Example:

# Initial nested dictionary
d = {
    "name": "Bob",
    "age": 20,
    "grades": {
        "math": "A",
        "science": "B"
    }
}

# Adding a new subject 'history' with grade 'A-'
d["grades"].update({"history": "A-"})

print(d)

{'name': 'Bob', 'age': 20, 'grades': {'math': 'A', 'science': 'B', 'history': 'A-'}}

Explanation:

• Using .update(): The update() method takes a dictionary as an argument and adds its key-value pairs to the target dictionary.
• Adding New Entry: Here, {"history": "A-"} is added to the grades dictionary.

Using setdefault()

setdefault() method is useful for ensuring that a key exists in the dictionary. If the key doesn't exist, it initializes it with a default value. This method can be chained to handle multiple nested levels. It can also be used when we need to initialize a default value for a key that may not exist.

Example:

# Initial nested dictionary
d = {
    "name": "Bob",
    "age": 20,
    "grades": {
        "math": "A",
        "science": "B"
    }
}

# Ensuring 'contact' dictionary exists and adding 'email'
d.setdefault("contact", {}).setdefault("email", "[email protected]")

print(d)

{'name': 'Bob', 'age': 20, 'grades': {'math': 'A', 'science': 'B'}, 'contact': {'email': '[email protected]'}}

Explanation:

• First setdefault("contact", {}): Checks if the key "contact" exists. If not, initializes it as an empty dictionary.
• Second setdefault("email", "[email protected]"): Within the "contact" dictionary, checks for the key "email". If absent, sets it to "[email protected]".

Using defaultdict (For Deeply Nested)

The defaultdict from Python's collections module automatically initializes nested dictionaries, eliminating the need to check for key existence manually. It's ideal for deeply nested or dynamically growing dictionaries.

Example:

from collections import defaultdict

# Creating a nested defaultdict
d = defaultdict(dict)

# Adding grades
d["grades"]["math"] = "A"
d["grades"]["science"] = "B"

# Adding contact information
d["contact"]["email"] = "[email protected]"

print(dict(d))

{'grades': {'math': 'A', 'science': 'B'}, 'contact': {'email': '[email protected]'}}

Explanation:

• defaultdict(dict): Initializes a dictionary where each value is another dictionary by default.
• Automatic Initialization: When accessing student["grades"] or student["contact"], if these keys don't exist, they are automatically created as empty dictionaries.

Using Dictionary Unpacking (Python 3.5+)

Dictionary unpacking allows us to merge dictionaries or update specific parts by unpacking them into a new dictionary. This method is useful when merging or updating shallow dictionaries with clear input data and situations where immutability of the original dictionaries is preferred.

Example:

# Initial nested dictionary
d1 = {
    "name": "Bob",
    "age": 20,
    "grades": {
        "math": "A",
        "science": "B"
    }
}

# New grades to update
d2 = {
    "science": "A",
    "history": "A-"
}

# Updating grades using dictionary unpacking
d1["grades"] = {**d1["grades"], **d2}

print(d1)

{'name': 'Bob', 'age': 20, 'grades': {'math': 'A', 'science': 'A', 'history': 'A-'}}

Explanation:

• **d1["grades"] and **d2: Unpacks both dictionaries.
• Merging Dictionaries: Keys in d2 overwrite those in student["grades"] if they exist; otherwise, they are added.
• Assigning Back: The merged dictionary is assigned back to student["grades"].

Using the Merge (|) Operator (Python 3.9+)

Python 3.9 introduced the merge (|) operator for dictionaries, allowing us to combine dictionaries to create a new dictionary. This operator can be used to update nested dictionaries by merging inner dictionaries.

Example:

# Initial nested dictionary
d1 = {
    "name": "Bob",
    "age": 20,
    "grades": {
        "math": "A",
        "science": "B"
    }
}

# New grades to update
d2 = {
    "science": "A",
    "history": "A-"
}

# Updating grades using the merge operator
d1["grades"] = d1["grades"] | d2

print(d1)

Output:

{'name': 'Bob', 'age': 20, 'grades': {'math': 'A', 'science': 'A', 'history': 'A-'}}

Explanation:

• d1["grades"] | d2: Merges d2 into d1["grades"] with d2 taking precedence.
• Assigning Back: The merged dictionary replaces the original d1["grades"].