fix unhashable type set error in python

How to Fix – TypeError unhashable type ‘set’

In Python, a TypeError is raised when an operation or function is applied to an object of inappropriate type. One such error is the “TypeError: unhashable type: ‘set'” error. This error occurs when we try to use a set as a key in a dictionary or as an element in another set. In this tutorial, we will discuss the reasons behind this error and how to fix it.

fix unhashable type set error in python

Understanding the TypeError: unhashable type: 'set' error

In Python, hashable types are those which have a hash value that remains constant throughout its lifetime. Hash values are unique identifiers assigned to objects by Python’s built-in hash() function. These hash values are used to quickly compare and access objects in dictionaries and sets.

On the other hand, unhashable types are those which do not have a constant hash value and cannot be used as keys in dictionaries or elements in sets. Examples of unhashable types include lists, sets, and dictionaries themselves.

To illustrate the difference between hashable and unhashable types, consider the following example:

# Hashable type (tuple)
my_tuple = (1, 2, 3)
print(hash(my_tuple))

Output:

529344067295497451
# Unhashable type (set)
my_set = {1, 2, 3}
print(hash(my_set))

Output:

---------------------------------------------------------------------------

TypeError                                 Traceback (most recent call last)

Cell In[7], line 3
      1 # Unhashable type (set)
      2 my_set = {1, 2, 3}
----> 3 print(hash(my_set))

TypeError: unhashable type: 'set'

In the above example, we create a tuple my_tuple and a set my_set containing the same elements. When we try to hash the tuple using the built-in hash() function, we get a unique hash value. However, when we try to hash the set, we get a TypeError because sets are unhashable in Python. This means that we cannot use sets as keys in dictionaries or elements in other sets.

The TypeError: unhashable type: 'set' error occurs when we try to use a set in a place that requires a hashable type, for example, as a key in a dictionary or a value in another set. This error occurs because sets are mutable, which means that their contents can be changed. In Python, only immutable objects can be used as keys in a dictionary or as elements in a set.

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Let’s look at examples of the common scenarios where this error occurs.

# using a set as a key in a dictionary
my_set = {1, 2, 3}
my_dictionary = {
    "Name": "Jim",
    my_set: "Yes"
}
print(my_dictionary)

Output:

---------------------------------------------------------------------------

TypeError                                 Traceback (most recent call last)

Cell In[8], line 3
      1 # using a set as a key in a dictionary
      2 my_set = {1, 2, 3}
----> 3 my_dictionary = {
      4     "Name": "Jim",
      5     my_set: "Yes"
      6 }
      7 print(my_dictionary)

TypeError: unhashable type: 'set'

In the above example, we’re trying to use the set my_set as a key in the dictionary my_dictionary. You can see that we get the TypeError: unhashable type: 'set'.

# using a set as a an element in another set
set1 = {1, 2, 3}
set2 = {4, 5}

# add set2 as an element in set1
set1.add(set2)

Output:

---------------------------------------------------------------------------

TypeError                                 Traceback (most recent call last)

Cell In[9], line 6
      3 set2 = {4, 5}
      5 # add set2 as an element in set1
----> 6 set1.add(set2)

TypeError: unhashable type: 'set'

In the above example, we’re trying to add the set set2 as an element to the set set1. Since sets are unhashable types, we get the error TypeError: unhashable type: 'set'.

Fixing the Error

To fix the TypeError: unhashable type: 'set', use a hashable type like a frozen set or a tuple instead of a set. For example, if you’re trying to use a set as a key in a dictionary, use a frozen set (or a tuple) instead. Similarly, if you’re trying to use a set as an element in another set, you can use a tuple or a frozen set instead.

A frozenset is an immutable set in Python. It is similar to a set, but once a frozenset is created, you cannot add or remove elements from it. However, you can perform set operations like union, intersection, and difference on frozenset objects.

Note that you can create a frozenset from a set using the frozenset() constructor.

Let’s revisit the examples from above and fix those errors.

# using a frozenset as a key in a dictionary
my_frozen_set = frozenset({1, 2, 3})
my_dictionary = {
    "Name": "Jim",
    my_frozen_set: "Yes"
}
print(my_dictionary)

Output:

{'Name': 'Jim', frozenset({1, 2, 3}): 'Yes'}

In the above example, we replaced the set my_set with the fronzenset, my_frozen_set as a key in the dictionary. We don’t get an error on executing the above code. Notice that you can still use a set as a value in a dictionary but the keys must be hashable types.

# using a frozenset as a an element in another set
set1 = {1, 2, 3}
set2 = frozenset({4, 5})

# add set2 as an element in set1
set1.add(set2)

print(set1)

Output:

{frozenset({4, 5}), 1, 2, 3}

In the above example, we added a fronzen set instead of a set to set1. You can see that we don’t get the error now.

In summary, you can take the following steps to fix the TypeError: unhashable type: 'set' error.

  1. Identify the code that is causing the error.
  2. Check if you are using a set as a key in a dictionary or as an element in a set.
  3. If you are using a set as a key in a dictionary or as a value in another set, consider using a frozenset or a tuple instead. Frozensets and Tuples are immutable and can be hashed.

Conclusion

The “TypeError: unhashable type: ‘set'” error occurs when we try to use a set as a key in a dictionary or as an element in a set. This error can be fixed by converting the set into an immutable object such as a frozenset or a tuple. By following the steps mentioned in this tutorial, you can easily fix this error and make your code more efficient and error-free.

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Author

  • Piyush Raj

    Piyush is a data professional passionate about using data to understand things better and make informed decisions. He has experience working as a Data Scientist in the consulting domain and holds an engineering degree from IIT Roorkee. His hobbies include watching cricket, reading, and working on side projects.

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