在创建NumPy数组后,并将其保存为Django上下文变量,我在加载网页时收到以下错误:
array([ 0, 239, 479, 717, 952, 1192, 1432, 1667], dtype=int64) is not JSON serializable
这是什么意思?
在创建NumPy数组后,并将其保存为Django上下文变量,我在加载网页时收到以下错误:
array([ 0, 239, 479, 717, 952, 1192, 1432, 1667], dtype=int64) is not JSON serializable
这是什么意思?
当前回答
我有一个类似的问题,嵌套字典与一些numpy。ndarray在里面。
def jsonify(data):
json_data = dict()
for key, value in data.iteritems():
if isinstance(value, list): # for lists
value = [ jsonify(item) if isinstance(item, dict) else item for item in value ]
if isinstance(value, dict): # for nested lists
value = jsonify(value)
if isinstance(key, int): # if key is integer: > to string
key = str(key)
if type(value).__module__=='numpy': # if value is numpy.*: > to python list
value = value.tolist()
json_data[key] = value
return json_data
其他回答
使用NumpyEncoder它将处理json转储成功。NumPy数组不是JSON序列化的
import numpy as np
import json
from numpyencoder import NumpyEncoder
arr = array([ 0, 239, 479, 717, 952, 1192, 1432, 1667], dtype=int64)
json.dumps(arr,cls=NumpyEncoder)
如果你在字典中嵌套了numpy数组,我发现了最好的解决方案:
import json
import numpy as np
class NumpyEncoder(json.JSONEncoder):
""" Special json encoder for numpy types """
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()
return json.JSONEncoder.default(self, obj)
dumped = json.dumps(data, cls=NumpyEncoder)
with open(path, 'w') as f:
json.dump(dumped, f)
多亏了这个家伙。
你可以使用Pandas:
import pandas as pd
pd.Series(your_array).to_json(orient='values')
可以做简单的for循环检查类型:
with open("jsondontdoit.json", 'w') as fp:
for key in bests.keys():
if type(bests[key]) == np.ndarray:
bests[key] = bests[key].tolist()
continue
for idx in bests[key]:
if type(bests[key][idx]) == np.ndarray:
bests[key][idx] = bests[key][idx].tolist()
json.dump(bests, fp)
fp.close()
下面是一个为我工作的实现,并删除了所有的nan(假设这些是简单的对象(list或dict)):
from numpy import isnan
def remove_nans(my_obj, val=None):
if isinstance(my_obj, list):
for i, item in enumerate(my_obj):
if isinstance(item, list) or isinstance(item, dict):
my_obj[i] = remove_nans(my_obj[i], val=val)
else:
try:
if isnan(item):
my_obj[i] = val
except Exception:
pass
elif isinstance(my_obj, dict):
for key, item in my_obj.iteritems():
if isinstance(item, list) or isinstance(item, dict):
my_obj[key] = remove_nans(my_obj[key], val=val)
else:
try:
if isnan(item):
my_obj[key] = val
except Exception:
pass
return my_obj