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What is deserialize and serialize in JSON?

I have seen the terms "deserialize" and "serialize开发者_运维问答" with JSON. What do they mean?


JSON is a format that encodes objects in a string. Serialization means to convert an object into that string, and deserialization is its inverse operation (convert string -> object).

When transmitting data or storing them in a file, the data are required to be byte strings, but complex objects are seldom in this format. Serialization can convert these complex objects into byte strings for such use. After the byte strings are transmitted, the receiver will have to recover the original object from the byte string. This is known as deserialization.

Say, you have an object:

{foo: [1, 4, 7, 10], bar: "baz"}

serializing into JSON will convert it into a string:

'{"foo":[1,4,7,10],"bar":"baz"}'

which can be stored or sent through wire to anywhere. The receiver can then deserialize this string to get back the original object. {foo: [1, 4, 7, 10], bar: "baz"}.


Serialize and Deserialize

In the context of data storage, serialization (or serialisation) is the process of translating data structures or object state into a format that can be stored (for example, in a file or memory buffer) or transmitted (for example, across a network connection link) and reconstructed later. [...]

The opposite operation, extracting a data structure from a series of bytes, is deserialization.

– wikipedia.org

JSON

JSON (JavaScript Object Notation) is an open standard file format and data interchange format that uses human-readable text to store and transmit data objects consisting of attribute–value pairs and arrays (or other serializable values). It is a common data format with diverse uses in electronic data interchange, including that of web applications with servers.

JSON is a language-independent data format. It was derived from JavaScript, but many modern programming languages include code to generate and parse JSON-format data. JSON filenames use the extension .json.

– wikipedia.org

Explained using Python

In Python serialization does nothing else than just converting the given data structure into its valid JSON pendant (e.g., Python's True will be converted to JSON's true and the dictionary itself will be converted to a string) and vice versa for deserialization.

Python vs. JSON

You can easily spot the difference between Python and JSON representations in a side-by-side comparison. For example, by examining their Boolean values. Have a look at the following table for the basic types used in both contexts:

Python JSON
True true
False false
None null
int, float number
str (with single ', double " and tripple """ quotes) string (only double " quotes)
dict object
list, tuple array

Code Example

Python builtin module json is the standard way to do serialization and deserialization:

import json

data = {
    'president': {
        "name": """Mr. Presidente""",
        "male": True,
        'age': 60,
        'wife': None,
        'cars': ('BMW', "Audi")
    }
}

# serialize
json_data = json.dumps(data, indent=2)

print(json_data)
# {
#   "president": {
#     "name": "Mr. Presidente",
#     "male": true,
#     "age": 60,
#     "wife": null,
#     "cars": [
#       "BMW",
#       "Audi"
#     ]
#   }
# }

# deserialize
restored_data = json.loads(json_data) # deserialize

Sources: realpython.com, geeksforgeeks.org


Explanation of Serialize and Deserialize using Python

In python, pickle module is used for serialization. So, the serialization process is called pickling in Python. This module is available in Python standard library.

Serialization using pickle

import pickle

#the object to serialize
example_dic={1:"6",2:"2",3:"f"}

#where the bytes after serializing end up at, wb stands for write byte
pickle_out=open("dict.pickle","wb")
#Time to dump
pickle.dump(example_dic,pickle_out)
#whatever you open, you must close
pickle_out.close()

The PICKLE file (can be opened by a text editor like notepad) contains this (serialized data):

€}q (KX 6qKX 2qKX fqu.

Deserialization using pickle

import pickle

pickle_in=open("dict.pickle","rb")
get_deserialized_data_back=pickle.load(pickle_in)

print(get_deserialized_data_back)

Output:

{1: '6', 2: '2', 3: 'f'}

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