Why doesn't dict.copy() update the original dictionary?

General Discussions
,
#1

Why does updating a “shallow” copy of a dictionary not update the “original” dictionary?

While reading the documentation for dict.copy(), it mentions that it creates a shallow copy of the dictionary. The book I am following (Beazley’s Python Reference) also states that the m.copy() method creates a shallow copy of the items in a mapping object and places them in a new mapping object.

Consider the following example:

>>> original = dict(a=1, b=2)
>>> new = original.copy()
>>> new.update({'c': 3})
>>> original
{'a': 1, 'b': 2}
>>> new
{'a': 1, 'c': 3, 'b': 2}

I assumed that this would update the original dictionary (adding 'c': 3), since I made a shallow copy. This behavior is similar to lists:

>>> original = [1, 2, 3]
>>> new = original
>>> new.append(4)
>>> new, original
([1, 2, 3, 4], [1, 2, 3, 4])

This works as expected. Since both are shallow copies, why does dict.copy() not behave as I expect? Is my understanding of shallow vs deep copying flawed? Or is there a reason for this discrepancy in behavior with Python copy dictionary operations?

#2

Hey All!

Shallow copy only copies the dictionary structure, not the values. When you use dict.copy() in Python, it creates a shallow copy of the dictionary. This means it only copies the references to the objects inside the dictionary, not the actual objects themselves. So, when you update the shallow copy by adding new key-value pairs, it doesn’t affect the original dictionary because the shallow copy has its own reference to those keys.

For example:

original = dict(a=1, b=2)  
new = original.copy()  
new.update({'c': 3})  

print(original)  # {'a': 1, 'b': 2}  
print(new)       # {'a': 1, 'b': 2, 'c': 3}

Here, new is a separate shallow copy of original. Changes in new don’t reflect in the original dictionary. That’s how python copy dictionary works with shallow copies.

#3

To add on to @joe-elmoufak’s point, the behavior of dict.copy() highlights the difference between shallow and deep copies when copying a Python dictionary.

  • A shallow copy (created with dict.copy()) only duplicates the outer dictionary structure. If the dictionary contains mutable objects like lists or nested dictionaries, those objects are not copied, only their references are.
  • A deep copy (created with copy.deepcopy()) copies both the dictionary and its nested objects, ensuring that changes in the copy don’t affect the original.

Here’s an example with a nested dictionary:

import copy  
original = {'a': [1, 2], 'b': [3, 4]}  
new = copy.deepcopy(original)  
new['a'].append(5)  

print(original)  # {'a': [1, 2], 'b': [3, 4]}  
print(new)       # {'a': [1, 2, 5], 'b': [3, 4]}

If you’re working with nested or complex dictionaries in Python, always use copy.deepcopy() for a clean duplicate. This is especially important when performing operations on mutable values inside a python copy dictionary.

#4

Hello Everyone!

@vindhya.rddy’s example brings up another key detail about mutable values inside dictionaries. Even though a shallow copy (dict.copy()) creates a new dictionary structure, it doesn’t copy the inner mutable values (like lists or nested dictionaries). So, if you modify a value (not the dictionary itself), it will reflect in both the original and the copy.

Here’s an example to clarify:

original = {'a': [1, 2], 'b': [3, 4]}  
new = original.copy()  
new['a'].append(3)  

print(original)  # {'a': [1, 2, 3], 'b': [3, 4]}  
print(new)       # {'a': [1, 2, 3], 'b': [3, 4]}

In this case, the list [1, 2] under key 'a' is shared between original and new. When we append 3, both dictionaries reflect the change. This behavior is specific to shallow copies in Python dictionaries. To avoid this, you can use copy.deepcopy() to make a deep copy where the nested values are also duplicated.

So when deciding on a python copy dictionary method, choose between dict.copy() and copy.deepcopy() based on your needs—shallow for structure-only copies and deep for completely independent duplicates."