blocks|key|499545|text|我找到我的问题了。问题是我的整数实际上是numpy.int64类型。|type|unstyled|depth|inlineStyleRanges|offset|length|style|CODE|entityRanges|data|499546|entityMap|0|LINK|mutability|MUTABLE|url|https://docs.scipy.org/doc/numpy-1.10.0/user/basics.types.html^0|K|B|K|B|0|0^^$0|@$1|2|3|4|5|6|7|N|8|@$9|O|A|P|B|C]]|D|@$9|Q|A|R|1|S]]|E|$]]|$1|F|3|-4|5|6|7|T|8|@]|D|@]|E|$]]]|G|$H|$5|I|J|K|E|$L|M]]]]

I found my problem. The issue was that my integers were actually type <a href="https://docs.scipy.org/doc/numpy-1.10.0/user/basics.types.html" rel="noreferrer"><code>numpy.int64</code></a>.

blocks|key|499605|text|似乎在Python3中将numpy.int64转储到json字符串可能会有问题，Python团队已经就此进行了讨论。更多细节可以在here上找到。|type|unstyled|depth|inlineStyleRanges|entityRanges|offset|length|data|499606|Serhiy+Storchaka提供了一种解决方法。它工作得很好，所以我把它粘贴在这里：|499607|def+convert(o):
++++if+isinstance(o,+numpy.int64):+return+int(o)++
++++raise+TypeError

json.dumps({'value':+numpy.int64(42)},+default=convert)|code-block|syntax|javascript|499608|entityMap|0|LINK|mutability|MUTABLE|url|https://bugs.python.org/issue24313^0|1T|4|0|0|0|0^^$0|@$1|2|3|4|5|6|7|S|8|@]|9|@$A|T|B|U|1|V]]|C|$]]|$1|D|3|E|5|6|7|W|8|@]|9|@]|C|$]]|$1|F|3|G|5|H|7|X|8|@]|9|@]|C|$I|J]]|$1|K|3|-4|5|6|7|Y|8|@]|9|@]|C|$]]]|L|$M|$5|N|O|P|C|$Q|R]]]]

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 <a href="https://bugs.python.org/issue24313" rel="noreferrer">here</a>.

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

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

json.dumps({'value': numpy.int64(42)}, default=convert)
</code></pre>

blocks|key|283159|text|正如@JAC在最高评分答案的评论中指出的那样，通用解决方案(适用于所有numpy类型)可以在线程Converting+numpy+dtypes+to+native+python+types中找到。|type|unstyled|depth|inlineStyleRanges|entityRanges|offset|length|data|283160|然而，我将在下面添加我的解决方案版本，因为在我的情况下，我需要一个通用的解决方案，将这些答案与其他线程的答案结合起来。这应该适用于几乎所有的numpy类型。|283161|def+convert(o):
++++if+isinstance(o,+np.generic):+return+o.item()++
++++raise+TypeError

json.dumps({'value':+numpy.int64(42)},+default=convert)|code-block|syntax|javascript|283162|entityMap|0|LINK|mutability|MUTABLE|url|https://stackoverflow.com/questions/9452775/converting-numpy-dtypes-to-native-python-types^0|1C|1A|0|0|0|0^^$0|@$1|2|3|4|5|6|7|S|8|@]|9|@$A|T|B|U|1|V]]|C|$]]|$1|D|3|E|5|6|7|W|8|@]|9|@]|C|$]]|$1|F|3|G|5|H|7|X|8|@]|9|@]|C|$I|J]]|$1|K|3|-4|5|6|7|Y|8|@]|9|@]|C|$]]]|L|$M|$5|N|O|P|C|$Q|R]]]]

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 <a href="https://stackoverflow.com/questions/9452775/converting-numpy-dtypes-to-native-python-types">Converting numpy dtypes to native python types</a>. 

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.

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

json.dumps({'value': numpy.int64(42)}, default=convert)
</code></pre>

blocks|key|499784|text|只需将数字从int64+(从numpy)转换为int即可。|type|unstyled|depth|inlineStyleRanges|offset|length|style|CODE|entityRanges|data|499785|例如，如果变量x是一个int64：|499786|int(x)|code-block|syntax|javascript|499787|如果是int64数组：|499788|map(int,+x)|499789|entityMap^0|6|5|N|3|0|7|1|0|0|0|0^^$0|@$1|2|3|4|5|6|7|S|8|@$9|T|A|U|B|C]|$9|V|A|W|B|C]]|D|@]|E|$]]|$1|F|3|G|5|6|7|X|8|@$9|Y|A|Z|B|C]]|D|@]|E|$]]|$1|H|3|I|5|J|7|10|8|@]|D|@]|E|$K|L]]|$1|M|3|N|5|6|7|11|8|@]|D|@]|E|$]]|$1|O|3|P|5|J|7|12|8|@]|D|@]|E|$K|L]]|$1|Q|3|-4|5|6|7|13|8|@]|D|@]|E|$]]]|R|$]]

<h1>Just convert numbers from <code>int64</code> (from numpy) to <code>int</code>.</h1>

For example, if variable <code>x</code> is a int64:

<pre><code>int(x)
</code></pre>

If is array of int64:

<pre><code>map(int, x)
</code></pre>

blocks|key|499916|text|这可能是较晚的响应，但最近我收到了相同的错误。在大量的冲浪之后，这个解决方案对我很有帮助。|type|unstyled|depth|inlineStyleRanges|entityRanges|data|499917|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__()|code-block|syntax|javascript|499918|在json.dumps()中调用myconverter，如下所示。json.dumps(alerts,+default=myconverter).|offset|length|style|CODE|499919|entityMap^0|0|0|1|C|G|B|X|14|0^^$0|@$1|2|3|4|5|6|7|O|8|@]|9|@]|A|$]]|$1|B|3|C|5|D|7|P|8|@]|9|@]|A|$E|F]]|$1|G|3|H|5|6|7|Q|8|@$I|R|J|S|K|L]|$I|T|J|U|K|L]|$I|V|J|W|K|L]]|9|@]|A|$]]|$1|M|3|-4|5|6|7|X|8|@]|9|@]|A|$]]]|N|$]]

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

<pre><code>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__()
</code></pre>

Call <code>myconverter</code> in <code>json.dumps()</code> like below. <code>json.dumps(alerts, default=myconverter).</code>

blocks|key|282990|text|这为我解决了这个问题：|type|unstyled|depth|inlineStyleRanges|entityRanges|data|282991|def+serialize(self):
++++return+{
++++++++my_int:+int(self.my_int),+
++++++++my_float:+float(self.my_float)
++++}|code-block|syntax|javascript|282992|entityMap^0|0|0^^$0|@$1|2|3|4|5|6|7|I|8|@]|9|@]|A|$]]|$1|B|3|C|5|D|7|J|8|@]|9|@]|A|$E|F]]|$1|G|3|-4|5|6|7|K|8|@]|9|@]|A|$]]]|H|$]]

This solved the problem for me:

<pre><code>def serialize(self):
 return {
 my_int: int(self.my_int), 
 my_float: float(self.my_float)
 }
</code></pre>

blocks|key|499699|text|或者，您可以先将对象转换为dataframe：|type|unstyled|depth|inlineStyleRanges|entityRanges|data|499700|df+=+pd.DataFrame(obj)|code-block|syntax|javascript|499701|然后将此dataframe保存到json文件中：|offset|length|style|CODE|499702|df.to_json(path_or_buf='df.json')|499703|希望这能有所帮助|499704|entityMap^0|0|0|4|9|G|4|0|0|0^^$0|@$1|2|3|4|5|6|7|S|8|@]|9|@]|A|$]]|$1|B|3|C|5|D|7|T|8|@]|9|@]|A|$E|F]]|$1|G|3|H|5|6|7|U|8|@$I|V|J|W|K|L]|$I|X|J|Y|K|L]]|9|@]|A|$]]|$1|M|3|N|5|D|7|Z|8|@]|9|@]|A|$E|F]]|$1|O|3|P|5|6|7|10|8|@]|9|@]|A|$]]|$1|Q|3|-4|5|6|7|11|8|@]|9|@]|A|$]]]|R|$]]

Alternatively you can convert your object into a dataframe first:

<pre><code>df = pd.DataFrame(obj)
</code></pre>

and then save this <code>dataframe</code> in a <code>json</code> file:

<pre><code>df.to_json(path_or_buf='df.json')
</code></pre>

Hope this helps

blocks|key|283224|text|使用以下代码来解决此问题。|type|unstyled|depth|inlineStyleRanges|entityRanges|data|283225|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()|code-block|syntax|javascript|283226|entityMap^0|0|0^^$0|@$1|2|3|4|5|6|7|I|8|@]|9|@]|A|$]]|$1|B|3|C|5|D|7|J|8|@]|9|@]|A|$E|F]]|$1|G|3|-4|5|6|7|K|8|@]|9|@]|A|$]]]|H|$]]

Use the below code to resolve the issue.
<pre><code>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()
</code></pre>

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.

<pre><code>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()
</code></pre>

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

<pre><code>afile.write(json.dumps(alerts,encoding='UTF-8',default=str))
</code></pre>

"TypeError: (Integer) is not JSON serializable" when serializing JSON in Python?

Python

JSON

我试图从python向json文件发送一个简单的字典，但我一直收到"TypeError: 1425is not JSON serializable“消息。import jsonalerts = {'upper':[1425],'lower':[576],'level':[2],'datetime':['2012-08-08 15:30']}afile = open('test.json','w')

问在Python中序列化TypeError时“JSON：(Integer)不是JSON序列化的”？
EN

回答 8

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问在Python中序列化TypeError时“JSON：(Integer)不是JSON序列化的”？EN

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问在Python中序列化TypeError时“JSON：(Integer)不是JSON序列化的”？
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