Python Copy and Nested Dictionaries – Deep Dive for Practical Usage

Introduction – Why Copy and Nest Dictionaries?

Python dictionaries are flexible and powerful, allowing not only flat key-value pairs but also nested structures and safe copying techniques.

• Copying is important to prevent unintended modifications.
• Nested dictionaries are useful for structured data like JSON, user profiles, config files, or APIs.

In this guide, you’ll learn:

• How to properly copy dictionaries (shallow vs deep)
• How nested dictionaries work and how to access their contents
• Real-world use cases and best practices

1. Copying a Dictionary

Using copy() – Shallow Copy

original = {"name": "Alice", "age": 30}
copy_dict = original.copy()
copy_dict["age"] = 31

print(original)
print(copy_dict)

Explanation:

• copy() creates a new dictionary with the same top-level key-value pairs.
• Changing copy_dict["age"] does not affect original.

Shallow Copy Limitation with Nested Values

original = {"name": "Alice", "details": {"age": 30}}
copy_dict = original.copy()
copy_dict["details"]["age"] = 31

print(original)  # 'age' is also changed here

Explanation:

• Both dictionaries point to the same inner dictionary ("details").
• This is a shallow copy—only the outermost dictionary is copied.

Using copy.deepcopy() – Deep Copy

import copy

original = {"name": "Alice", "details": {"age": 30}}
deep_copy = copy.deepcopy(original)
deep_copy["details"]["age"] = 31

print(original)     # Age remains 30
print(deep_copy)    # Age updated only in copy

Explanation:

• deepcopy() recursively copies all nested objects.
• Safest way to work with deeply nested dictionaries.

2. Working with Nested Dictionaries

Creating a Nested Dictionary

users = {
    "user1": {"name": "Alice", "age": 30},
    "user2": {"name": "Bob", "age": 25}
}

Explanation:

• Each value is itself a dictionary.
• Great for structured or tabular data.

Accessing Nested Values

print(users["user1"]["name"])  # Output: Alice

Explanation:

• Access outer key "user1", then inner key "name".

Adding/Updating Nested Entries

users["user3"] = {"name": "Carol", "age": 28}
users["user1"]["age"] = 31

Explanation:

• Adds a new user and updates an existing one.

Looping Through Nested Dictionary

for user_id, info in users.items():
    print(f"{user_id} → {info['name']}, Age: {info['age']}")

Explanation:

• Iterates through keys and accesses inner dictionary values.

Best Practices

• Use copy.deepcopy() for safe copying of nested dictionaries.
• Check for key existence with in or .get() before accessing nested keys.
• For deeply nested structures, consider using defaultdict or data validation logic.
• Don’t modify nested dictionaries without understanding reference behavior.

Summary – Recap & Next Steps

Python dictionaries can store complex, nested data structures. Knowing how to copy safely and navigate nested keys is crucial for working with configurations, user profiles, and JSON responses.

Key Takeaways:

• copy() creates a shallow copy; deepcopy() copies all nested levels.
• Nested dictionaries are dictionaries within dictionaries.
• Access nested data using multiple keys: dict["outer"]["inner"].

Real-World Relevance:
Nested dictionaries are essential in API parsing, database rows, form submissions, ML model configs, and multi-level permissions.

FAQ Section – Python Copy and Nested Dictionaries

What is the difference between copy() and deepcopy()?

copy() copies only the top-level dictionary (shallow). deepcopy() copies all levels recursively.

How do I access a value in a nested dictionary?

Use chained keys:

dict["outer"]["inner"]

Can I safely copy a nested dictionary using copy()?

No. Use copy.deepcopy() for complete independence.

How do I add a new entry to a nested dictionary?

Add like this:

dict["outer"] = {"key": "value"}

What happens if a nested key doesn’t exist?

It raises a KeyError. Use:

dict.get("outer", {}).get("inner")