script principal

Arte da alma1
 

Seja feliz por favor!

quinta-feira, 17 de novembro de 2022

TUDO HACKER 23 programation total ensino the best hacker

 

< Working With JSON Data in Python - GeeksforGeeks
Skip to content
Related Articles

Related Articles

Working With JSON Data in Python

Improve Article
Save Article
  • Difficulty Level : Easy
  • Last Updated : 03 Jun, 2022
Improve Article
Save Article

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 the 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:  

Python3




# 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)

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  
Python3



# 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))
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 it easy to write data to files. See the following table given 
below.  
Python objectJSON object
dictobject
list, tuplearray
strstring
int, long, floatnumbers
Truetrue
Falsefalse
Nonenull
Example: Serialization  
Consider the given example of a Python object.
Python3



var = {
      "Subjects": {
                  "Maths":85,
                  "Physics":90
                   }
      }
Using Python’s context manager, create a file named Sample.json and open it with write mode. 
Python3



with open("Sample.json", "w") as p:
     json.dump(var, p)
Here,
 the dump() takes two arguments first, the data object to be serialized,
 and second the object to which it will be written(Byte format). 
Deserializing JSON:
Deserialization
 is the opposite of Serialization, i.e. conversion of JSON objects into 
their respective Python objects. The load() method is used for it. If 
you have used JSON data from another program or obtained it as a string 
format of JSON, then it can easily be deserialized with load(), which is
 usually used to load from a string, otherwise, the root object is in a 
list or dict. 
Python3



with open("Sample.json", "r") as read_it:
     data = json.load(read_it)
Example: Deserialization 
Python3



json_var ="""
{
    "Country": {
        "name": "INDIA",
        "Languages_spoken": [
            {
                "names": ["Hindi", "English", "Bengali", "Telugu"]
            }
        ]
    }
}
"""
var = json.loads(json_var)
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 has 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) 
Example 1: Encoding using demjson package. 
Python3



# storing marks of 3 subjects
var = [{"Math": 50, "physics":60, "Chemistry":70}]
print(demjson.encode(var))
Output: 
[{"Chemistry":70, "Math":50, "physics":60}]
Decoding: The decode() function is used to convert the JSON object into python-format type. 
Syntax:
demjson.decode(self, obj)
Example 2: Decoding using demjson package 
Python3



var = '{"a":0, "b":1, "c":2, "d":3, "e":4}'
text = demjson.decode(var)
Output: 
{'a': 0, 'b': 1, 'c': 2, 'd': 3, 'e': 4}
Example 3: Encoding using iterencode package  
Python3



# 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)
Example 4: Encoding and Decoding using dumps() and loads().
Python3



# To encode and decode operations
import json
var = {'age':31, 'height':6}
x = json.dumps(var)
y = json.loads(x)
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)
Command-Line Usage
The JSON library can also be used from the command-line, to validate and pretty-print your JSON.
$ echo "{ \"name\": \"Monty\", \"age\": 45 }"
Searching through JSON with JMESPath
JMESPath
 is a query language for JSON. It allows you to easily obtain the data 
you need from a JSON document. If you ever worked with JSON before, you 
probably know that it’s easy to get a nested value. For example, 
doc[“person”][“age”] will get you the nested value for age in a 
document.
First, install jmespath : 
$ pip3 install jmespath
Real-World Example: 
Let us take a real-life example of the implementation of the JSON in python. A good source for practice purposes is JSON_placeholder,
 it provides a 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. 
Python3



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)
To know more, Click Here

My Personal Notes
arrow_drop_up
Previous
Python JSON
Next

Read, Write and Parse JSON using Python
Related Articles
1.
How to use cURL to Get JSON Data and Decode JSON Data in PHP ?
2.
Working with JSON Data in Java
3.
Python - Difference Between json.load() and json.loads()
4.
Python - Difference between json.dump() and json.dumps()
5.
JSON | modify an array value of a JSON object
6.
How to parse JSON object using JSON.stringify() in JavaScript ?
7.
Working with JSON Files in R Programming
8.
How to Parse Data From JSON into Python?
9.
Convert JSON data Into a Custom Python Object
10.
Serializing JSON data in Python
Article Contributed By :
https://media.geeksforgeeks.org/auth/avatar.png
kartikeya shukla 1
@kartikeya shukla 1
Vote for difficulty
Current difficulty :
Easy





Improved By :
Article Tags :
Practice Tags :
Report Issue
We use cookies to ensure you have the best browsing experience on our website. By using our site, you
acknowledge that you have read and understood our
Cookie Policy &
        Privacy Policy

Lightbox

Start Your Coding Journey Now!





Working With JSON Data in Python - GeeksforGeeks
Skip to content




Related Articles



Related Articles
Working With JSON Data in Python
Improve Article

Save Article

  • Difficulty Level :
Easy
  • Last Updated :
03 Jun, 2022
Improve Article

Save Article

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 the 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:  
Python3



# 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)
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  
Python3



# 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))
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 it easy to write data to files. See the following table given 
below.  
Python objectJSON object
dictobject
list, tuplearray
strstring
int, long, floatnumbers
Truetrue
Falsefalse
Nonenull
Example: Serialization  
Consider the given example of a Python object.
Python3



var = {
      "Subjects": {
                  "Maths":85,
                  "Physics":90
                   }
      }
Using Python’s context manager, create a file named Sample.json and open it with write mode. 
Python3



with open("Sample.json", "w") as p:
     json.dump(var, p)
Here,
 the dump() takes two arguments first, the data object to be serialized,
 and second the object to which it will be written(Byte format). 
Deserializing JSON:
Deserialization
 is the opposite of Serialization, i.e. conversion of JSON objects into 
their respective Python objects. The load() method is used for it. If 
you have used JSON data from another program or obtained it as a string 
format of JSON, then it can easily be deserialized with load(), which is
 usually used to load from a string, otherwise, the root object is in a 
list or dict. 
Python3



with open("Sample.json", "r") as read_it:
     data = json.load(read_it)
Example: Deserialization 
Python3



json_var ="""
{
    "Country": {
        "name": "INDIA",
        "Languages_spoken": [
            {
                "names": ["Hindi", "English", "Bengali", "Telugu"]
            }
        ]
    }
}
"""
var = json.loads(json_var)
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 has 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) 
Example 1: Encoding using demjson package. 
Python3



# storing marks of 3 subjects
var = [{"Math": 50, "physics":60, "Chemistry":70}]
print(demjson.encode(var))
Output: 
[{"Chemistry":70, "Math":50, "physics":60}]
Decoding: The decode() function is used to convert the JSON object into python-format type. 
Syntax:
demjson.decode(self, obj)
Example 2: Decoding using demjson package 
Python3



var = '{"a":0, "b":1, "c":2, "d":3, "e":4}'
text = demjson.decode(var)
Output: 
{'a': 0, 'b': 1, 'c': 2, 'd': 3, 'e': 4}
Example 3: Encoding using iterencode package  
Python3



# 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)
Example 4: Encoding and Decoding using dumps() and loads().
Python3



# To encode and decode operations
import json
var = {'age':31, 'height':6}
x = json.dumps(var)
y = json.loads(x)
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)
Command-Line Usage
The JSON library can also be used from the command-line, to validate and pretty-print your JSON.
$ echo "{ \"name\": \"Monty\", \"age\": 45 }"
Searching through JSON with JMESPath
JMESPath
 is a query language for JSON. It allows you to easily obtain the data 
you need from a JSON document. If you ever worked with JSON before, you 
probably know that it’s easy to get a nested value. For example, 
doc[“person”][“age”] will get you the nested value for age in a 
document.
First, install jmespath : 
$ pip3 install jmespath
Real-World Example: 
Let us take a real-life example of the implementation of the JSON in python. A good source for practice purposes is JSON_placeholder,
 it provides a 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. 
Python3



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)
To know more, Click Here

My Personal Notes
arrow_drop_up
Previous
Python JSON
Next

Read, Write and Parse JSON using Python
Related Articles
1.
How to use cURL to Get JSON Data and Decode JSON Data in PHP ?
2.
Working with JSON Data in Java
3.
Python - Difference Between json.load() and json.loads()
4.
Python - Difference between json.dump() and json.dumps()
5.
JSON | modify an array value of a JSON object
6.
How to parse JSON object using JSON.stringify() in JavaScript ?
7.
Working with JSON Files in R Programming
8.
How to Parse Data From JSON into Python?
9.
Convert JSON data Into a Custom Python Object
10.
Serializing JSON data in Python
Article Contributed By :
https://media.geeksforgeeks.org/auth/avatar.png
kartikeya shukla 1
@kartikeya shukla 1
Vote for difficulty
Current difficulty :
Easy





Improved By :
Article Tags :
Practice Tags :
Report Issue
We use cookies to ensure you have the best browsing experience on our website. By using our site, you
acknowledge that you have read and understood our
Cookie Policy &
        Privacy Policy

Lightbox

Start Your Coding Journey Now!



  
  
  
  /htm>











-





Sem comentários:
  


































        

      









Subscrever:
Mensagens (Atom)







Crie aqui o seu horóscopo gratuito==




Minha moradia!



            Aqui, acredite no seu acontecer!    Universo minha moradia!    Que bela natureza!  Olhar sem igual.  Amor no começar!  Apenas am...













    

  • 

    

    




    

    Da dor ao sorriso.
    

      Entre a dor e o sorriso é preciso aprender a escolher, viver ou morrer! As fadas são bonitas na infância a adolescência mostra os nossos p...
    

    

    

    • 

  • 

    

    




    

    Viver ou morrer.
    

     Não entenda o entender, flor é semente do chegado viver, assim acontece a quem nasceu para escrever. Criar a personagem no morrer ou viver,...
    

    

    

    • 

  • 

    

    




    

    Fé paz amor a porta do paraíso.
    

      Encontra-me no teu chegar sem obstáculos de me poder entregar, há porta do paraíso um dia todos queremos bater temos de trabalhar para em ...
    

    

    

    •