I am trying to send a simple dictionary to a json file from python, but I keep getting the “TypeError: 1425 is not JSON serializable” message.

import json
alerts = {'upper':[1425],'lower':[576],'level':[2],'datetime':['2012-08-08 15:30']}
afile = open('test.json','w')
afile.write(json.dumps(alerts,encoding='UTF-8'))
afile.close()

If I add the default argument, then it writes, but the integer values are written to the json file as strings, which is undesirable.

afile.write(json.dumps(alerts,encoding='UTF-8',default=str))

I found my problem. The issue was that my integers were actually type numpy.int64.

It seems like there may be a issue to dump numpy.int64 into json string in Python 3 and the python team already have a conversation about it. More details can be found here.

There is a workaround provided by Serhiy Storchaka. It works very well so I paste it here:

def convert(o):
    if isinstance(o, numpy.int64): return int(o)  
    raise TypeError

json.dumps({'value': numpy.int64(42)}, default=convert)

This solved the problem for me:

def serialize(self):
    return {
        my_int: int(self.my_int), 
        my_float: float(self.my_float)
    }

Just convert numbers from int64 (from numpy) to int.

For example, if variable x is a int64:

int(x)

If is array of int64:

map(int, x)

as @JAC pointed out in the comments of the highest rated answer, the generic solution (for all numpy types) can be found in the thread Converting numpy dtypes to native python types.

Nevertheless, I´ll add my version of the solution below, as my in my case I needed a generic solution that combines these answers and with the answers of the other thread. This should work with almost all numpy types.

def convert(o):
    if isinstance(o, np.generic): return o.item()  
    raise TypeError

json.dumps({'value': numpy.int64(42)}, default=convert)

This might be the late response, but recently i got the same error. After lot of surfing this solution helped me.

alerts = {'upper':[1425],'lower':[576],'level':[2],'datetime':['2012-08-08 15:30']}
def myconverter(obj):
        if isinstance(obj, np.integer):
            return int(obj)
        elif isinstance(obj, np.floating):
            return float(obj)
        elif isinstance(obj, np.ndarray):
            return obj.tolist()
        elif isinstance(obj, datetime.datetime):
            return obj.__str__()

Call myconverter in json.dumps() like below. json.dumps(alerts, default=myconverter).

Alternatively you can convert your object into a dataframe first:

df = pd.DataFrame(obj)

and then save this dataframe in a json file:

df.to_json(path_or_buf='df.json')

Hope this helps

You have Numpy Data Type, Just change to normal int() or float() data type. it will work fine.

Same problem. List contained numbers of type numpy.int64 which throws a TypeError. Quick workaround for me was to

mylist = eval(str(mylist_of_integers))
json.dumps({'mylist': mylist})

which converts list to str() and eval() function evaluates the String like a Python expression and returns the result as a list of integers in my case.

Use the below code to resolve the issue.

import json
from numpyencoder import NumpyEncoder
alerts = {'upper':[1425],'lower':[576],'level':[2],'datetime':['2012-08-08 
15:30']}
afile = open('test.json','w')
afile.write(json.dumps(alerts,encoding='UTF-8',cls=NumpyEncoder))
afile.close()