Effective Handling of “TypeError: Unhashable Type” in Python

The “TypeError: unhashable type” is a common error encountered by Python developers. It occurs when you attempt to use an unhashable object, such as a mutable data type, as a key in a dictionary or an element in a set. In this guide, we’ll delve into the causes of this error and provide effective solutions to handle it.

Understanding the “TypeError: Unhashable Type”

In Python, hashable objects are those that have a hash value that remains constant during their lifetime. Immutable types like strings, numbers, and tuples are hashable, whereas mutable types like lists and dictionaries are not. When you attempt to use an unhashable object in a context that requires hashable objects, Python raises the “TypeError: unhashable type” error.

Common Scenarios

The “TypeError: unhashable type” error can occur in various situations:

  • Using a list or dictionary as a key in a dictionary.
  • Attempting to add a list to a set.
  • Trying to create a set of dictionaries.

Effective Handling of the Error

Let’s explore strategies to effectively handle the “TypeError: unhashable type” error:

1. Use Immutable Types as Keys

To avoid the error, use immutable types (strings, numbers, tuples) as keys in dictionaries or elements in sets. Immutable objects remain constant and can be safely used as hashable keys.

2. Convert to Immutable Types

If you have unhashable objects that need to be used as keys, consider converting them to immutable types. For example, you can convert a list to a tuple before using it as a dictionary key.

3. Create a Hashable Wrapper

If you need to use mutable objects as keys, consider creating a wrapper class that ensures immutability. Override the __hash__() method in the wrapper to return a hashable value.

4. Use Data Transformation

If the unhashable object contains data that needs to be stored, transform it into a hashable format, such as a tuple or a frozenset.

5. Review Your Data Structure

Reevaluate your data structure choices. If you find yourself needing to use mutable objects as keys frequently, it might be worth considering a different approach that utilizes hashable types.

Exploring LSI Keywords

Deepen your understanding of handling “TypeError: unhashable type” in Python:

  • Python unhashable type error solutions
  • Avoiding unhashable type errors in Python
  • Using immutable keys in Python dictionaries
  • Creating hashable wrapper classes in Python

Practical Application: Converting Lists to Tuples

Suppose you have a list of student names that you want to use as keys in a dictionary:

student_list = [‘Alice’, ‘Bob’, ‘Charlie’]

To avoid the “TypeError: unhashable type” error, convert the list to a tuple:

student_tuple = tuple(student_list)

Now, you can safely use student_tuple as keys in a dictionary.


  • Can I make a custom object hashable?

Yes, you can make a custom object hashable by implementing the __hash__() method and ensuring that the object’s state remains constant.

  • Why are mutable objects not hashable?

Mutable objects can change their state, leading to inconsistent hash values. This can cause issues in data structures that rely on hash values, like dictionaries and sets.

  • How do I know which objects are hashable?

In Python, built-in immutable types like strings, numbers, and tuples are hashable. You can check if an object is hashable using the hash() function.

  • Can I use a dictionary as a value in another dictionary?

Yes, you can use a dictionary as a value in another dictionary, as long as the keys of the inner dictionary are hashable.

  • What’s the performance impact of hashable vs. unhashable types?

Hashable types are generally more efficient for dictionary and set operations, as hash values allow for faster lookups and comparisons.


Handling the “TypeError: unhashable type” error in Python involves understanding the concept of hashable objects and making appropriate choices when using data structures like dictionaries and sets. By applying the effective strategies discussed in this guide, you’ll be equipped to navigate and resolve this error, ensuring the stability and reliability of your Python code. Remember to prioritize the use of immutable types as keys and consider data transformation or wrapper classes when working with unhashable objects.

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