TypeError: Object of type ndarray is not JSON serializable

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# TypeError: Object of type ndarray is not JSON serializable

The Python "TypeError: Object of type ndarray is not JSON serializable" occurs when we try to convert a NumPy ndarray object to a JSON string.

To solve the error, use the tolist() method on the array to convert it to a Python list before serializing it to JSON.

Here is an example of how the error occurs.

main.py

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import json
import numpy as np


arr = np.array([1, 2, 3, 4])

# ⛔️ TypeError: Object of type ndarray is not JSON serializable
json_str = json.dumps({'nums': arr})

object of type ndarray is not json serializable

We tried passing a NumPy ndarray object to the json.dumps() method but the method doesn't handle NumPy arrays by default.

# Convert the array to a Python list to solve the error

To solve the error, use the tolist() method on the array to convert it to a Python list.

main.py

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import json
import numpy as np


arr = np.array([1, 2, 3, 4])

# ✅ used tolist()
json_str = json.dumps({'nums': arr.tolist()})

print(json_str)  # 👉️ {"nums": [1, 2, 3, 4]}
print(type(json_str))  # 👉️ <class 'str'>

convert array to python list to solve the error

We can use a native Python list instead of a NumPy ndarray when serializing to JSON.

The json.dumps() method converts a Python object to a JSON formatted string.

If you need to convert the JSON string back to a NumPy array, use the json.loads() method.

main.py

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import json
import numpy as np


arr = np.array([1, 2, 3, 4])

# ✅ used tolist()
json_str = json.dumps({'nums': arr.tolist()})

my_dict = json.loads(json_str)

new_arr = np.array(my_dict['nums'])
print(new_arr)  # 👉️ [1 2 3 4]

use json loads to convert json string to numpy array

The json.loads() method parses a JSON string into a native Python object.

We accessed the Python list and used the np.array method to convert it to a NumPy array.

# Extend from the `JSONEncoder` class to solve the error

Alternatively, you can extend from the JSONEncoder class and handle the conversions in a default method.

main.py

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import json
import numpy as np


class NpEncoder(json.JSONEncoder):
    def default(self, obj):
        if isinstance(obj, np.integer):
            return int(obj)
        if isinstance(obj, np.floating):
            return float(obj)
        if isinstance(obj, np.ndarray):
            return obj.tolist()
        return json.JSONEncoder.default(self, obj)


arr = np.array([1, 2, 3, 4])

json_str = json.dumps({'nums': arr}, cls=NpEncoder)

print(json_str)  # 👉️ {"nums": [1, 2, 3, 4]}
print(type(json_str))  # 👉️ <class 'str'>

extend the json encoder class to solve the error

We extended from the JSONEncoder class.

The JSONEncoder class supports the following objects and types by default.

Python	JSON
dict	object
list, tuple	array
str	string
int, float, int and float derived Enums	number
True	true
False	false
None	null

Notice that the JSONEncoder class doesn't support NumPy ndarray to JSON conversion by default.

We can handle this by extending from the class and implementing a default() method that returns a serializable object.

main.py

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import json
import numpy as np


class NpEncoder(json.JSONEncoder):
    def default(self, obj):
        if isinstance(obj, np.integer):
            return int(obj)
        if isinstance(obj, np.floating):
            return float(obj)
        if isinstance(obj, np.ndarray):
            return obj.tolist()
        return json.JSONEncoder.default(self, obj)

If the passed-in object is an instance of np.integer, we convert the object to a Python int() and return the result.

If the passed-in object is an instance of np.floating, we convert it to a Python float and return the result.

If the object is an instance of np.ndarray, we convert it to a Python list and return the result.

In all other cases, we let the base class's default method do the serialization.

To use a custom JSONEncoder, specify it with the cls keyword argument in your call to the json.dumps() method.

main.py

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import json
import numpy as np


class NpEncoder(json.JSONEncoder):
    def default(self, obj):
        if isinstance(obj, np.integer):
            return int(obj)
        if isinstance(obj, np.floating):
            return float(obj)
        if isinstance(obj, np.ndarray):
            return obj.tolist()
        return json.JSONEncoder.default(self, obj)


arr = np.array([1, 2, 3, 4])

# ✅ provide cls keyword argument
json_str = json.dumps({'nums': arr}, cls=NpEncoder)

print(json_str)  # 👉️ {"nums": [1, 2, 3, 4]}
print(type(json_str))  # 👉️ <class 'str'>

If you don't provide the cls kwarg, the default JSONEncoder is used.

# Using the `default` keyword argument to solve the error

You can also use the default keyword argument in the call to the json.dumps() method.

main.py

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import json
import numpy as np


arr = np.array([1, 2, 3, 4])


def json_serializer(obj):
    if isinstance(obj, np.ndarray):
        return obj.tolist()
    return obj


json_str = json.dumps({'nums': arr}, default=json_serializer)

print(json_str)  # 👉️ {"nums": [1, 2, 3, 4]}

using default keyword argument to solve the error

The json.dumps() method converts a Python object to a JSON formatted string.

The default keyword argument can be set to a function that gets called for objects that can't otherwise be serialized.

We simply convert the ndarray object to a list by using the tolist() method.

The json_serializer function takes an object as a parameter and checks if the object is a ndarray.

If the condition is met, we use the tolist() method to convert the array to a list, otherwise, the value is returned as is.

# Using `pandas` to solve the error

If you use the pandas module, you can also use the to_json method to solve the error.

main.py

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import numpy as np

import pandas as pd

arr = np.array([1, 2, 3, 4])


json_str = pd.Series(arr).to_json(orient='values')
print(json_str)  # 👉️ [1,2,3,4]

The Series.to_json method converts the object to a JSON string.

The orient argument determines the expected JSON string format.

The values option is used to only use the array's values in the JSON string.

# TypeError: Object of type DataFrame is not JSON serializable

The Python "TypeError: Object of type DataFrame is not JSON serializable" occurs when we try to serialize a DataFrame object to JSON using the json.dumps method.

To solve the error, use the to_json() method instead, e.g. df.to_json().

Here is an example of how the error occurs

main.py

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import json
import pandas as pd

df = pd.DataFrame(
    {
        "Name": [
            "Alice",
            "Bob",
            "Carl",
        ],
        "Age": [29, 30, 31],
    }
)

# ⛔️ TypeError: Object of type DataFrame is not JSON serializable
print(json.dumps(df))

We tried passing a DataFrame object to the json.dumps() method but the method doesn't handle DataFrame objects by default.

# Use the `to_json()` method to solve the error

To solve the error, use the to_json() method on the DataFrame object.

main.py

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import pandas as pd

df = pd.DataFrame(
    {
        "Name": [
            "Alice",
            "Bob",
            "Carl",
        ],
        "Age": [29, 30, 31],
    }
)

# 👇️ '{"Name":{"0":"Alice","1":"Bob","2":"Carl"},"Age":{"0":29,"1":30,"2":31}}'
print(df.to_json())

# 👇️ <class 'str'>
print(type(df.to_json()))

The to_json() method converts the DataFrame object to a JSON string.

# Convert the `DataFrame` to a `dict` to solve the error

Alternatively, you can try to convert the DataFrame to a dict object before serializing to JSON.

main.py

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import json
import pandas as pd

df = pd.DataFrame(
    {
        "Name": [
            "Alice",
            "Bob",
            "Carl",
        ],
        "Age": [29, 30, 31],
    }
)

# 👇️ '{"Name": {"0": "Alice", "1": "Bob", "2": "Carl"}, "Age": {"0": 29, "1": 30, "2": 31}}'
print(json.dumps(df.to_dict()))

# 👇️ <class 'str'>
print(type(json.dumps(df.to_dict())))

The to_dict method converts the DataFrame to a dictionary, which we can then serialize to JSON.

The JSONEncoder class supports the following objects and types by default.

Python	JSON
dict	object
list, tuple	array
str	string
int, float, int and float derived Enums	number
True	true
False	false
None	null

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TypeError: Object of type ndarray is not JSON serializable

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