📋 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

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🧪 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.

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⚠️ 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.

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✅ 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.

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🧱 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.

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✅ Accessing Nested Values

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

✅ Explanation:

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

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✅ Adding/Updating Nested Entries

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

✅ Explanation:

• Adds a new user and updates an existing one.

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✅ 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.

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💡 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.

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📌 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.

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❓ 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")

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