Python - Dictionary Copying: Shallow and Deep Copy

For effective data management, it is important to know how to copy dictionaries properly. This concept can be illustrated with a simple dictionary of European capitals.

Shallow Copy

The simplest way to copy a dictionary is using what we call a "shallow copy". You can create a shallow copy in two ways. The first method uses the dict.copy() method:

Shallow copies create a new dictionary, but they don't create copies of the nested objects if your dictionary contains any. In our simple capitals example, this isn't a problem because we only have strings, which are immutable.

Now, consider a more complex scenario involving nested dictionaries:

In such cases, a shallow copy might not be sufficient, and this is where deep copying comes into play.

Deep Copy: The Complete Clone

When you need a true, independent copy of your dictionary - inner contents and all - deep copy comes to the rescue.

To create a deep copy, we need to import Python's copy module and use its deepcopy function:

The deep copy creates a completely independent copy of the original dictionary, including all nested objects. This means you can modify any level of the new dictionary without affecting the original one.

To illustrate the difference, we will observe what happens when when we modify our dictionaries:

Remember that shallow copies are usually sufficient for simple dictionaries with immutable values like strings and numbers. However, when working with nested data structures, consider using deep copy to ensure complete independence between the original and copied data.

In this example, when we modify the nested list in the shallow copy, the change is also reflected in the original dictionary because both dictionaries reference the same nested list. However, the deep copy remains unchanged because it created independent copies of all nested objects.

The decision to use shallow or deep copying typically hinges on your particular requirements: shallow copies are faster and use less memory, whereas deep copies ensure full data independence at the cost of higher memory usage and processing resources.

Use of the Assignment Operator: Reference Copy

We will examine what happens when the assignment operator (=) is used with dictionaries:

When using the assignment operator (=), Python doesn't create a new dictionary. Instead, it creates a new reference to the same dictionary object in memory. This means both variables (capitals and new_capitals) point to exactly the same dictionary. Any changes made using either variable will affect the dictionary that both variables reference.

This is usually referred to as a "reference copy" or "aliasing," not a true copy of the data. If you’re not careful, this can lead to some surprising outcomes. That’s why it’s important to use proper copying methods (shallow or deep) when you need a completely independent version of a dictionary.

Comparative Table of Different Dictionary Copying Methods

Feature	Reference Copy	Shallow Copy	Deep Copy
Syntax	dict2 = dict1	dict2 = dict1.copy() or dict2 = dict(dict1)	import copy dict2 = copy.deepcopy(dict1)
Definition	Creates a new reference to the same object	Creates a new dictionary with references to the same nested objects	Creates a completely new dictionary with new copies of all nested objects
Nested Objects	Changes affect both dictionaries	Changes to nested objects affect both dictionaries	Changes to nested objects are completely independent
Performance	Fastest	Moderate speed	Slowest
Use Case	When you need just another reference to the same dictionary	When dictionary contains only immutable objects (strings, numbers, tuples)	When dictionary contains mutable objects (lists, dictionaries) and you need full independence
Changes to Original	Affects both dictionaries	Affects only top-level elements	Doesn't affect original dictionary at all
Memory Usage	Lowest (single object)	Medium (new dictionary, same nested objects)	Highest (complete copy of all objects)

FAQS on Dictionary Copying in Python

How do I make a shallow copy of a dictionary?

You've got three cool ways to make a shallow copy:

• Using the dict.copy() method: new_dict = old_dict.copy()
• Using dict() constructor: new_dict = dict(old_dict)

They do the same thing, so pick whatever feels more natural to you!

What is the difference between a shallow copy and a deep copy of a dictionary in Python?

A shallow copy (created with dict.copy() or via the dict() constructor) duplicates only the top-level structure of the dictionary. However, any nested objects, such as lists or other dictionaries, remain references to the same original objects.

A deep copy (created with copy.deepcopy()) recreates all nested objects, ensuring that no references point back to the original dictionary’s contents.

Can I perform a shallow copy using list slicing on a dictionary?

No. Python’s slicing syntax (e.g., some_list[:]) applies to sequence types like lists, tuples, or strings, not dictionaries. For shallow dictionary copying, you can use dict.copy(), the dict() constructor, or other methods like {k: v for k, v in original_dict.items()}.

Will using the assignment operator (=) create a copy of my dictionary?

No. Using the assignment operator on a dictionary only creates a new reference to the same dictionary object in memory. Any changes made through one reference will be visible in the other. If you actually need a copy, you must use an explicit copy method, such as dict.copy() or copy.deepcopy().

What is the most efficient way to copy a dictionary in Python?

For a shallow copy, dict.copy() is the most efficient method. For a deep copy, use copy.deepcopy(), but be aware that it is slower due to the recursive copying of nested objects.