Python - TypeError：“int64”类型的对象不是 JSON 可序列化的
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Python - TypeError: Object of type 'int64' is not JSON serializable
提问by dark horse
I have a data frame that stores store name and daily sales count. I am trying to insert this to Salesforce using the Python script below. However, I get the following error:
我有一个存储商店名称和每日销售额的数据框。我正在尝试使用下面的 Python 脚本将其插入 Salesforce。但是，我收到以下错误：
TypeError: Object of type 'int64' is not JSON serializable
Below, there is the view of the data frame.
下面是数据框的视图。
Storename,Count
Store A,10
Store B,12
Store C,5
I use the following code to insert it to Salesforce.
我使用以下代码将其插入 Salesforce。
update_list = []
for i in range(len(store)):
update_data = {
'name': store['entity_name'].iloc[i],
'count__c': store['count'].iloc[i]
}
update_list.append(update_data)
sf_data_cursor = sf_datapull.salesforce_login()
sf_data_cursor.bulk.Account.update(update_list)
Getting the error, when the last line above gets executed. Could anyone assist in fixing this? Thanks..
得到错误，当上面的最后一行被执行时。任何人都可以协助解决这个问题吗？谢谢..
回答by DYZ
jsondoes not recognize NumPy data types. Convert the number to a Python intbefore serializing the object:
json不识别 NumPy 数据类型。int在序列化对象之前将数字转换为 Python ：
'count__c': int(store['count'].iloc[i])
回答by Jie Yang
You can define your own encoder to solve this problem.
你可以定义自己的编码器来解决这个问题。
import json
import numpy as np
class NpEncoder(json.JSONEncoder):
def default(self, 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()
else:
return super(NpEncoder, self).default(obj)
# Your codes ....
json.dumps(data, cls=NpEncoder)
回答by MattCochrane
Another option is that when you create the dataframe use dtype=str
另一种选择是，当您创建数据框使用 dtype=str
For example, if you loaded storefrom a csv file:
例如，如果您store从 csv 文件加载：
import pandas as pd
store = pd.read_csv('store.csv', dtype=str)
Then everything has a type of strwhich can be serialized to json.
那么一切都有一种str可以序列化为json的类型。
回答by shiva
This might be the late response, but recently i got the same error. After lot of surfing this solution helped me.
这可能是迟到的回应，但最近我遇到了同样的错误。经过大量冲浪后，这个解决方案帮助了我。
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 myconverterin json.dumps()like below.
json.dumps('message', default=myconverter)
通话myconverter中 json.dumps()像下面。
json.dumps('message', default=myconverter)
回答by Jason R Stevens CFA
I'll throw in my answer to the ring as a bit more stable version of @Jie Yang's excellent solution.
我将把我的回答作为@Jie Yang优秀解决方案的更稳定版本。
My solution
我的解决方案
numpyencoderand its repository.
from numpyencoder import NumpyEncoder
numpy_data = np.array([0, 1, 2, 3])
with open(json_file, 'w') as file:
json.dump(numpy_data, file, indent=4, sort_keys=True,
separators=(', ', ': '), ensure_ascii=False,
cls=NumpyEncoder)
The breakdown
故障
If you dig into hmallen'scode in the numpyencoder/numpyencoder.pyfile you'll see that it's very similar to @Jie Yang's answer:
如果您深入研究文件中的hmallen代码，numpyencoder/numpyencoder.py您会发现它与@Jie Yang 的回答非常相似：
class NumpyEncoder(json.JSONEncoder):
""" Custom encoder for numpy data types """
def default(self, obj):
if isinstance(obj, (np.int_, np.intc, np.intp, np.int8,
np.int16, np.int32, np.int64, np.uint8,
np.uint16, np.uint32, np.uint64)):
return int(obj)
elif isinstance(obj, (np.float_, np.float16, np.float32, np.float64)):
return float(obj)
elif isinstance(obj, (np.complex_, np.complex64, np.complex128)):
return {'real': obj.real, 'imag': obj.imag}
elif isinstance(obj, (np.ndarray,)):
return obj.tolist()
elif isinstance(obj, (np.bool_)):
return bool(obj)
elif isinstance(obj, (np.void)):
return None
return json.JSONEncoder.default(self, obj)
