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In-memory data serialization example

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Jul 23, 2017 am 10:07 AM

javascriptjsonpickle

1. Purpose

We need to serialize the data in memory, that is, when writing to a file, the type written can only be a string or binary type. But if we want to serialize more complex data types, such as lists, dictionaries or functions, we have to use json or pickle.

2. json serialization

1. Serialization of dumps and deserialization of loads

dumps converts the data type into a string

import json

info = {
    &#39;name&#39;: &#39;The Count of Monte Cristo&#39;,
    &#39;type&#39;: &#39;Movie&#39;
}

data = json.dumps(info)
print(data)
print(type(data))

# 输出
{"name": "The Count of Monte Cristo", "type": "Movie"}
<class &#39;str&#39;>

loads converts the string into a data type

import json

get_info = json.loads(data)
print(get_info[&#39;name&#39;])
print(get_info)
print(type(get_info))

#输出
The Count of Monte Cristo
{&#39;name&#39;: &#39;The Count of Monte Cristo&#39;, &#39;type&#39;: &#39;Movie&#39;}
<class &#39;dict&#39;>

2.dump serialization and load deserialization

dump converts the data Convert the type to a string and store it in the file

import json

info = {
    &#39;name&#39;: &#39;The Count of Monte Cristo&#39;,
    &#39;type&#39;: &#39;Movie&#39;
}

with open("test.txt", "w", encoding="utf-8") as f:
    json.dump(info, f)  # 第一个参数是内存中的数据对象，第二个参数是文件句柄

#写入文件中的内容
{"name": "The Count of Monte Cristo", "type": "Movie"}

loadConvert the file opening from a string to a data type

import json


with open("test.txt", "r", encoding="utf-8") as f:
    data_from_file = json.load(f)

print(data_from_file[&#39;name&#39;])
print(data_from_file)
print(type(data_from_file))

#输出
The Count of Monte Cristo
{&#39;name&#39;: &#39;The Count of Monte Cristo&#39;, &#39;type&#39;: &#39;Movie&#39;}
<class &#39;dict&#39;>

3.json serializes a function

import json

def test(name):
    print("hello,{}".format(name))

info = {
    &#39;name&#39;: &#39;The Count of Monte Cristo&#39;,
    &#39;type&#39;: &#39;Movie&#39;,
    &#39;func&#39;: test
}

data = json.dumps(info)

#输出
 File "G:/python/untitled/study6/json&pickle模块.py", line 22, in <module>
    data = json.dumps(info)
  File "G:\python\install\lib\json\__init__.py", line 230, in dumps
    return _default_encoder.encode(obj)
  File "G:\python\install\lib\json\encoder.py", line 198, in encode
    chunks = self.iterencode(o, _one_shot=True)
  File "G:\python\install\lib\json\encoder.py", line 256, in iterencode
    return _iterencode(o, 0)
  File "G:\python\install\lib\json\encoder.py", line 179, in default
    raise TypeError(repr(o) + " is not JSON serializable")
TypeError: <function test at 0x0000021B13C57F28> is not JSON serializable

1. JSON can only handle simple data types, such as dictionaries, lists, strings, etc. It cannot handle complex data types such as functions.

2, json is common to all languages, and all languages support json. If we need python to interact with other languages for data, then use json format

3. Pickle serialization

The usage of pickle is the same as above, but the data type after pickle serialization is binary, and pickle can only be used in python use.

1.dumps && loads

import pickle


def test(name):
    print("hello,{}".format(name))

info = {
    &#39;name&#39;: &#39;The Count of Monte Cristo&#39;,
    &#39;type&#39;: &#39;Movie&#39;,
    &#39;func&#39;: test
}

data = pickle.dumps(info)
print(data)
print(type(data))

#输出
b&#39;\x80\x03}q\x00(X\x04\x00\x00\x00nameq\x01X\x19\x00\x00\x00The Count of Monte Cristoq\x02X\x04\x00\x00\x00typeq\x03X\x05\x00\x00\x00Movieq\x04X\x04\x00\x00\x00funcq\x05c__main__\ntest\nq\x06u.&#39;

<class &#39;bytes&#39;>

import pickle

get_data = pickle.loads(data)
get_data[&#39;func&#39;](&#39;cat&#39;)
print(get_data)

#输出
hello,cat
{&#39;name&#39;: &#39;The Count of Monte Cristo&#39;, &#39;type&#39;: &#39;Movie&#39;, &#39;func&#39;: <function test at 0x00000235350A7F28>}

2. dump && load

import pickle


def test(name):
    print("hello,{}".format(name))

info = {
    &#39;name&#39;: &#39;The Count of Monte Cristo&#39;,
    &#39;type&#39;: &#39;Movie&#39;,
    &#39;func&#39;: test
}

with open(&#39;test.txt&#39;, &#39;wb&#39;) as f:
    pickle.dump(info, f)

# 写入test.txt文件中的内容

�}q (X   typeqX   MovieqX   funcqc__main__
test
qX   nameqX   The Count of Monte Cristoqu.

import pickle

with open(&#39;test.txt&#39;, &#39;rb&#39;) as f:
    get_data = pickle.load(f)
print(get_data)

# 输出

{&#39;name&#39;: &#39;The Count of Monte Cristo&#39;, &#39;func&#39;: <function test at 0x000001BA2AB4D510>, &#39;type&#39;: &#39;Movie&#39;}

Summary:

JSON values support simple data types, and pickle supports all data types.
pickle can only support serialization and deserialization of python itself, and cannot be used for data interaction with other languages, while json can.
pickle serializes the entire data object, so when deserializing a function, the logic in the function body changes and follows the original function body.

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