TypeError: Object of type int64 is not JSON serializable

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# TypeError: Object of type int64 is not JSON serializable

The Python "TypeError: Object of type int64 is not JSON serializable" occurs when we try to convert a NumPy int64 object to a JSON string.

To solve the error, convert the NumPy int to a Python integer before converting it to JSON, e.g. int(my_numpy_int).

Here is an example of how the error occurs.

main.py

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import json
import numpy as np

salary = np.power(100, 4, dtype=np.int64)

# ⛔️ TypeError: Object of type int64 is not JSON serializable
json_str = json.dumps({'salary': salary})

print(json_str)

typeerror object of type int64 is not json serializable

We tried passing a numpy int64 object to the json.dumps() method but the method doesn't handle numpy integers by default.

# Use the built-in `int` or `float` classes to solve the error

To solve the error, use the built-in int() (or float) constructor to convert the numpy integer to a native Python integer before serializing it.

main.py

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import json
import numpy as np

salary = np.power(100, 4, dtype=np.int64)

# 👇️ convert to int
json_str = json.dumps({'salary': int(salary)})

print(json_str) # 👉️ '{"salary": 100000000}'

print(type(json_str))  # 👉️ <class 'str'>

use built in int or float classes to solve the error

The default JSON encoder handles int and float values, so we can use a native Python int instead of a numpy int when serializing to JSON.

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

# Extending 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

salary = np.power(100, 4, dtype=np.int64)

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)


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

print(json_str)  # 👉️ '{"salary": 100000000}'
print(type(json_str))  # 👉️ <class 'str'>

extending 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 int64 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

Copied!
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

Copied!
import json
import numpy as np

salary = np.power(100, 4, dtype=np.int64)

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)


# ✅ pass cls kwarg
json_str = json.dumps({'salary': salary}, cls=NpEncoder)

print(json_str)  # 👉️ '{"salary": 100000000}'
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

Copied!
import json
import numpy as np

salary = np.power(100, 4, dtype=np.int64)

json_str = json.dumps({'salary': salary}, default=int)

print(json_str)  # 👉️ '{"salary": 100000000}'
print(type(json_str))  # 👉️ <class 'str'>

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 numpy.int64 object to an integer by passing it to the int class.

You can also define a custom JSON serializer function.

main.py

Copied!
import json
import numpy as np

salary = np.power(100, 4, dtype=np.int64)


def json_serializer(obj):
    if isinstance(obj, np.int64):
        return int(obj)

    return obj


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

print(json_str)  # 👉️ '{"salary": 100000000}'
print(type(json_str))  # 👉️ <class 'str'>

We set the default keyword argument to the custom json_serializer function.

The function uses the isinstance() function to check if the value is of type numpy.int64.

If the value is of type numpy.int64, we convert it to an integer and return the result.

Otherwise, the value is returned as is.

# TypeError: Object of type float32 is not JSON serializable

The Python "TypeError: Object of type float32 is not JSON serializable" occurs when we try to convert a numpy float32 object to a JSON string.

To solve the error, convert the numpy float to a Python float before converting it to JSON, e.g. float(my_numpy_float).

Here is an example of how the error occurs.

main.py

Copied!
import json
import numpy as np

salary = np.power(100, 2.75, dtype=np.float32)

# ⛔️ TypeError: Object of type float32 is not JSON serializable
json_str = json.dumps({'salary': salary})

object of type float32 is not json serializable

We tried passing a NumPy float32 object to the json.dumps() method but the method doesn't handle NumPy floats by default.

# Use the built-in `float` or `str` constructor to convert the numpy float

To solve the error, use the built-in float() (or str()) constructor to convert the numpy float to a native Python float before serializing it.

main.py

Copied!
import json
import numpy as np

salary = np.power(100, 2.75, dtype=np.float32)

print(salary)  # 👉️ 316227.78

# ✅ convert to float
json_str = json.dumps({'salary': float(salary)})

print(json_str)  # 👉️ '{"salary": 316227.78125}'
print(type(json_str))  # 👉️ <class 'str'>

We used the built-in float() constructor to convert the NumPy float32 value to a native Python float.

Note that if you are worried about losing precision, you can use the str() constructor to convert the value to a string instead.

The default JSON encoder handles float and str values, so we can use a native Python float instead of a NumPy float32 when serializing to JSON.

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

# Create a custom class to handle the conversion

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

main.py

Copied!
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):
            # 👇️ alternatively use str()
            return float(obj)
        if isinstance(obj, np.ndarray):
            return obj.tolist()
        return json.JSONEncoder.default(self, obj)


salary = np.power(100, 2.75, dtype=np.float32)

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

print(json_str)  # 👉️ {"salary": 316227}
print(type(json_str))  # 👉️ <class 'str'>

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 float32 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

Copied!
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.

Note that you can use the str() constructor instead of float() if you worry about losing precision.

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

Copied!
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)


salary = np.power(100, 2.75, dtype=np.float32)

# ✅ pass cls kwarg
json_str = json.dumps({'salary': salary}, cls=NpEncoder)

print(json_str)  # 👉️ {"salary": 316227}
print(type(json_str))  # 👉️ <class 'str'>

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

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TypeError: Object of type int64 is not JSON serializable

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