python json 12: numpy转换为json数据

📌 相关文章

📜 python json 12: numpy转换为json数据

📅 最后修改于: 2020-09-06 08:44:02 🧑 作者: Mango

当直接编码/序列化与NumPy阵列成JSON格式，一般会遇到Object of type ndarray is not JSON serializable的错误。因此，我们学习将NumPy数组与JSON格式的数据转换。

1. JSON Encoder

此方法我们已经有过多次的介绍，详情如下，我们在此看一看如何将numpy的ndarray格式转换为json。

Set转json：https://www.imangodoc.com/4773.html
Datetime转json：https://www.imangodoc.com/4734.html
python自定义对象转json：https://www.imangodoc.com/4541.html

import json
from json import JSONEncoder
import numpy

class NumpyArrayEncoder(JSONEncoder):
    def default(self, obj):
        if isinstance(obj, numpy.ndarray):
            return obj.tolist()
        return JSONEncoder.default(self, obj)

numpyArrayOne = numpy.array([[11, 22, 33], [44, 55, 66], [77, 88, 99]])

# Serialization
numpyData = {"array": numpyArrayOne}
encodedNumpyData = json.dumps(numpyData, cls=NumpyArrayEncoder)  # use dump() to write array into file
print("Printing JSON serialized NumPy array")
print(encodedNumpyData)

# Deserialization
print("Decode JSON serialized NumPy array")
decodedArrays = json.loads(encodedNumpyData)

finalNumpyArray = numpy.asarray(decodedArrays["array"])
print("NumPy Array")
print(finalNumpyArray)

打印输出：

Printing JSON serialized NumPy array
{"array": [[11, 22, 33], [44, 55, 66], [77, 88, 99]]}

Decode JSON serialized NumPy array
NumPy Array
[[11 22 33]
 [44 55 66]
 [77 88 99]]

2. 将Numpy编码为JSON写入文件，并解码

我们将执行以下操作：

将两个NumPy数组转换为JSON并将其写入JSON文件
读取JSON文件，该文件包含JSON序列化的NumPy数组，并将其转换为实际的NumPy数组。

import numpy
from json import JSONEncoder
import json

class NumpyArrayEncoder(JSONEncoder):
    def default(self, obj):
        if isinstance(obj, numpy.ndarray):
            return obj.tolist()
        return JSONEncoder.default(self, obj)

numpyArrayOne = numpy.array([[11 ,22, 33], [44, 55, 66], [77, 88, 99]])
numpyArrayTwo = numpy.array([[51, 61, 91], [121 ,118, 127]])

# Serialization
numpyData = {"arrayOne": numpyArrayOne, "arrayTwo": numpyArrayTwo}
print("serialize NumPy array into JSON and write into a file")
with open("numpyData.json", "w") as write_file:
    json.dump(numpyData, write_file, cls=NumpyArrayEncoder)
print("Done writing serialized NumPy array into file")

# Deserialization
print("Started Reading JSON file")
with open("numpyData.json", "r") as read_file:
    print("Converting JSON encoded data into Numpy array")
    decodedArray = json.load(read_file)

    finalNumpyArrayOne = numpy.asarray(decodedArray["arrayOne"])
    print("NumPy Array One")
    print(finalNumpyArrayOne)
    finalNumpyArrayTwo = numpy.asarray(decodedArray["arrayTwo"])
    print("NumPy Array Two")
    print(finalNumpyArrayTwo)

打印输出如下：

serialize NumPy array into JSON and write into a file
Done writing serialized NumPy array into file
Started Reading JSON file
Converting JSON encoded data into Numpy array
NumPy Array One
[[11 22 33]
 [44 55 66]
 [77 88 99]]
NumPy Array Two
[[ 51  61  91]
 [121 118 127]]

3. 多种数据类型混合

即需要写入Json的数据包含整形、浮点型、ndarray等多种数据类型。

import json
from json import JSONEncoder
import numpy as np

class NumpyArrayEncoder(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(NumpyArrayEncoder, self).default(obj)

# Serialization
numPyData = {"id": 25, "floatSample": np.float32(1.2), "intSample":np.int32(42), "arangeSample": np.arange(12)}
encodedNumpyData = json.dumps(numPyData, cls=NumpyArrayEncoder)  # use dump() to write array into file
print("Printing JSON serialized NumPy array")
print(encodedNumpyData)

# Deserialization
print("Decode JSON serialized NumPy array")
decodedArrays = json.loads(encodedNumpyData)

numPyFloat = np.asarray(decodedArrays["floatSample"])
print("numPy Float")
print(numPyFloat)

numPyInt = np.asarray(decodedArrays["intSample"])
print("numPy Integer")
print(numPyInt)

numPyArange = np.asarray(decodedArrays["arangeSample"])
print("numPy arange")
print(numPyArange)

打印输出：

Printing JSON serialized NumPy array
{"id": 25, "floatSample": 1.2000000476837158, "intSample": 42, "arangeSample": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11]}
Decode JSON serialized NumPy array
numPy Float
1.2000000476837158
numPy Integer
42
numPy arange
[ 0  1  2  3  4  5  6  7  8  9 10 11]

4. 使用Pandas

关于pandas及其丰富的用法，请参阅我们之前的相关介绍https://www.imangodoc.com/599.html

在此我们只介绍如何借助pandas转换数据为json格式。可以使用to_json功能，pandas.Series.to_json转换对象为JSON字符串。

import pandas as pd
import numpy

numpyArray = numpy.array([[51, 61, 91], [121, 118, 127]])

df = pd.DataFrame(numpyArray, index=['row 1', 'row 2'], columns=['col 1', 'col 2', 'col 3'])
df = df.to_json(orient='index')

print("Json Encoded Array")
print(df)