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Updated on 2025-03-01

Python error TypeError: unhashable type: '' Solution

introduction

In Python programming, especially when processing data, we often use numpy arrays. However, when we try to use the numpy array as a key or element of a collection of dictionary, we encounter TypeError: unhashable type: ''. This error indicates that we are trying to use a non-hashable type (such as) as a key in the hash table. This article will explore the cause of this error and provide several possible solutions.

1. Problem description

1.1 Error report example

Assuming we have the following code, it tries tonumpyArrays are used as keys for dictionaries:

import numpy as np
# Create a numpy arraymy_array = ([1, 2, 3])
# Try to use numpy array as key for dictionarymy_dict = {my_array: "value"}

Running the above code will throw the following error:

TypeError: unhashable type: ''

1.2 Error report analysis

This error indicatesmy_arrayIt's oneobject, andObjects are not hashable and therefore cannot be used as keys for dictionaries.

1.3 Solutions

To solve this problem, we need to make sure we are not trying to use non-hashable types as keys for dictionaries. We cannumpyConvert an array to a hashable type, or use other methods to process the data.

2. Solution

2.1 Method 1: Convert to hashable type

WillnumpyThe array is converted to a hashable type, such as a list or tuple, and then used as a key for the dictionary.

import numpy as np
# Create a numpy arraymy_array = ([1, 2, 3])
# Convert numpy array to listmy_list = list(my_array)
# Use list as key for dictionarymy_dict = {my_list: "value"}

2.2 Method 2: Use other data structures

Use other data structures, e.g.pandasDataFrame is used to process data, not directlynumpyArray.

import numpy as np
import pandas as pd
# Create a numpy arraymy_array = ([1, 2, 3])
# Convert numpy array to pandas DataFramemy_dataframe = (my_array)
# Use a hashable property of DataFrame as the key of the dictionarymy_dict = {my_dataframe.columns[0]: "value"}

2.3 Method 3: Use Tuples

ifnumpyArrays are fixed-sized and can be converted to tuples because tuples are hashable.

import numpy as np
# Create a numpy arraymy_array = ([1, 2, 3])
# Convert numpy array to tuplemy_tuple = tuple(my_array)
# Use tuples as keys for dictionariesmy_dict = {my_tuple: "value"}

2.4 Method 4: Use hash function

Use custom hash functions to calculatenumpyThe hash value of the array and use it as a key for the dictionary.

import numpy as np
def array_hash(array):
    return hash(tuple(map(tuple, array)))
# Create a numpy arraymy_array = ([[1, 2], [3, 4]])
# Use hash function to calculate hash valuemy_hash = array_hash(my_array)
# Use hash as a key for the dictionarymy_dict = {my_hash: "value"}

3. Other solutions

In addition to the above methods, there are some other solutions to try:

  • usehashableFunction to check whether an object is hashable.
  • usefunctoolsIn the moduletotal_orderingDecorator to create hashable custom objects.
  • usecollectionsIn the modulenamedtupleto create hashable tuples.

4. Summary

In this article, we explore the possible causes of TypeError: unhashable type: '' error and give several solutions. If you encounter this error, you can try the above method to solve the problem. Remember, always make sure that the object is hashable before using it as a key to the dictionary.

Next time you encounter a similar error, you can first check whether your code is correctly used to have a hashedable object, and then take corresponding solutions based on the cause of the error. Hope this information will help you quickly resolve any problems you encounter!

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