Working With JSON Data in Python

Introduction of JSON in Python :
The full-form of JSON is JavaScript Object Notation. It means that a script (executable) file which is made of text in a programming language, is used to store and transfer the data. Python supports JSON through a built-in package called json. To use this feature, we import the json package in Python script. The text in JSON is done through quoted string which contains value in key-value mapping within { }. It is similar to the dictionary in Python. JSON shows an API similar to users of Standard Library marshal and pickle modules and Python natively supports JSON features. For Example

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# Python program showing 
# use of json package
  
import json
  
# {key:value mapping}
a ={"name":"John",
   "age":31,
    "Salary":25000}
  
# conversion to JSON done by dumps() function
 b = json.dumps(a)
  
# printing the output
print(b)

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Output:

{"age": 31, "Salary": 25000, "name": "John"}

As you can see, JSON supports primitive types, like strings and numbers, as well as nested lists, tuples and objects

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# Python program showing that
# json support different primitive
# types
  
import json
  
# list conversion to Array
print(json.dumps(['Welcome', "to", "GeeksforGeeks"]))
  
# tuple conversion to Array
print(json.dumps(("Welcome", "to", "GeeksforGeeks")))
  
# string conversion to String
print(json.dumps("Hi"))
  
# int conversion to Number
print(json.dumps(123))
  
# float conversion to Number
print(json.dumps(23.572))
  
# Boolean conversion to their respective values
print(json.dumps(True))
print(json.dumps(False))
  
# None value to null
print(json.dumps(None))

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Output:

["Welcome", "to", "GeeksforGeeks"]
["Welcome", "to", "GeeksforGeeks"]
"Hi"
123
23.572
true
false
null

 
Serializing JSON :
The process of encoding JSON is usually called serialization. This term refers to the transformation of data into a series of bytes (hence serial) to be stored or transmitted across a network. To handle the data flow in a file, the JSON library in Python uses dump() function to convert the Python objects into their respective JSON object, so it makes easy to write data to files. See the following table given below.

Python object JSON object
dict object
list, tuple array
str string
int, long, float numbers
True true
False false
None null

 
Serialization Example :
Consider the given example of a Python object.

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var =
      "Subjects": {
                  "Maths":85,
                  "Physics":90
                   }
      }

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Using Python’s context managercontext manager, create a file named Sample.json and open it with write mode.

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with open("Sample.json", "w") as p:
     json.dumps(var, p)

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Here, the dumps() takes two arguments first, the data object to be serialized and second the object to which it will be written(Byte format).
 
Deserializing JSON :
The Deserialization is opposite of Serialization, i.e. conversion of JSON object into their respective Python objects. The load() method is used for it. If you have used Json data from another program or obtained as a string format of Json, then it can easily be deserialized with load(), which is usually used to load from string, otherwise the root object is in list or dict.

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with open("Sample.json", "r") as read_it:
     data = json.load(read_it)

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Deserialization Example :

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json_var ="""
{
    "Country": {
        "name": "INDIA",
        "Languages_spoken": [
            {
                "names": ["Hindi", "English", "Bengali", "Telugu"]
            }
        ]
    }
}
"""
var = json.loads(json_var)

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Encoding and Decoding :
Encoding is defined as converting the text or values into an encrypted form that can only be used by the desired user through decoding it. Here encoding and decoding is done for JSON (object)format. Encoding is also known as Serialization and Decoding is known as Deserialization. Python have a popular package for this operation. This package is known as Demjson. To install it follow the steps below.
For Windows

pip install demjson

For Ubuntu

 sudo apt-get update
 sudo apt-get install python-demjson

Encoding : The encode() function is used to convert the python object into a JSON string representation. Syntax

 
demjson.encode(self, obj, nest_level=0) 

Code 1: Encoding using demjson package

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# storing marks of 3 subjects
var = [{"Math": 50, "physics":60, "Chemistry":70}]
print(demjson.encode(var))

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Output:

 
[{"Chemistry":70, "Math":50, "physics":60}]

 
Decoding: The decode() function is used to convert the JSON oject into python format type. Syntax

 
demjson.decode(self, obj)

Code 2: Decoding using demjson package

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var = '{"a":0, "b":1, "c":2, "d":3, "e":4}'
text = demjson.decode(var)

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Output:

{'a': 0, 'b': 1, 'c': 2, 'd': 3, 'e': 4}

Code 3: Encoding using iterencode package

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# Other Method of Encoding
json.JSONEncoder().encode({"foo": ["bar"]})
'{"foo": ["bar"]}'
  
# Using iterencode(object) to encode a given object.
for i in json.JSONEncoder().iterencode(bigobject):
    mysocket.write(i)

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Code 4: Encoding and Decoding using dumps() and loads()

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# To encode and decode operations
import json
var = {'age':31, 'height'= 6}
x = json.dumps(var)
y = json.loads(var)
print(x)
print(y)
  
# when performing from a file in disk
with open("any_file.json", "r") as readit:
    x = json.load(readit)
print(x)

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Real World Example :
Let us take a real life example on the implementation of the JSON in python. A good source for practice purpose is JSON_placeholder, it provides great API requests package which we will be using in our example. To get started, follow these simple steps. Open Python IDE or CLI and create a new script file, name it sample.py.

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import requests
import json
  
# Now we have to request our JSON data through
# the API package
res = requests.get("https://jsonplaceholder.typicode.com / todos")
var = json.loads(res.text)
  
# To view your Json data, type var and hit enter
var
  
# Now our Goal is to find the User who have 
# maximum completed their task !!
# i.e we would count the True value of a 
# User in completed key.
# {
    # "userId": 1,
    # "id": 1,
    # "title": "Hey",
    # "completed": false,  # we will count
                           # this for a user.
# }
  
# Note that there are multiple users with 
# unique id, and their task have respective
# Boolean Values.
  
def find(todo):
    check = todo["completed"]
    max_var = todo["userId"] in users
    return check and max_var
  
# To find the values.
  
Value = list(filter(find, todos))
  
# To write these value to your disk
  
with open("sample.json", "w") as data:
    Value = list(filter(keep, todos))
    json.dump(Value, data, indent = 2)

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