In this article, you will learn the total concept about JSON in python, working process, convert JSON to Python and Python to JSON with examples, pros and cons of JSON file, function in python and more.
Key points of this article –
- # What is JSON in python?
- # Working process JSON in python
- # Convert from JSON to python
- # Convert from python to JSON
- # Advantage of JSON in python
- # Limitations of JSON in python
What is JSON in python?
JSON in python is a syntax of stranded format storing and exchangeable data. JSON referred to text, written to JavaScript Object Notation
JSON (JavaScript Object Notation) is a popular data frame that compares XML to HTML format. It is easy to learn, works with the same dictionaries in python with few differences.
Basically, it works to transmit and receive data from server and web applications. Also working areas are string data from APIs and files configuration.
JSON is independent with other languages and more comfort in python. It always separates from other languages and belongs to a separate library in python that is called JavaScript Object Notation.
When you want to declare a JSON in your python then you input json data.
Example of JSON in python –
>> import json
Working process of JSON in python
In this article, you know that JSON is a file format for storing data. Here I will share how to create a new dataset and show it in JSON format.
Don’t forget-
Follow this to complete these processes step by step.
Step 1: – Installation & importing JSON library in python – json always separate library. Here you need to install this file under your python. After finishing installation then you need to import.
This syntax is –
pip install jsonlib;
pip install demjson
Import json;
Step 2: – Loading JSON format dataset – Loading imported data to used below syntax, write here file name which file you load here –
New_json = json.load( neson )
Step 3: – Checking perform operation of this file – Despite the slight difference, JSON and dictionaries work in the same format. It’s a working area view dataset, using loops, change of values that make different keys to new keys.
Step 4: – Return JSON from Python format – When we load the dataset, it converts to python format. Complete all over these then it is ready to main JSON file.
Complete this section need this syntax below-
New_json_output = json.dump(Njson)
How to Convert from JSON to Python Directory
You have a JSON string then you can convert it using JSON.loads() methods into a python directory. See this example below for a clear concept of converting the area of JSON to Python Directory.
Example of
Import json
#some JSON
a = ‘{“Name” “Md.Anirban”, “age”24, “city”:”Kushtia”}’
#convert a
b = json.loads(a)
# the result is x Python dictionary
print(b[“age”])
Output for this –
24
Most important python objects and its equivalents into JSON string showing below –
| JSON | Python |
| object | dict |
| array | list |
| string | str |
| number(real) | float |
| number(int) | int |
| true | True |
| false | False |
| null | None |
How to Convert from Python Directory to JSON
Sometimes we need to create a string with JSON format
If you have a python string then you can convert it to JSON format by using JSON.dump() methods.
// Note – json dump always follow two arguments like –
- Dictionary- including number of dictionary
- Indent – units of indentation number
Json dump also allows other parameters that work formatting and sorting. For clear understanding see this example below.
Example of python to json parse –
import json
# a Python object (dict):
a= {
“Name”: “Md.Anirban”,
“age”: 24,
“city”: “Kushtia”
}
# convert into JSON
b= json.dumps(a)
# the result is a JSON string
print(b)
Output of this –
Advantage of JSON in python
- JSON is Super fast languages
- Using this to make server pursuing
- Get schema support
- More features are able tools for sharing data.
- Most readable language
- Always contain sustain lower character that helps to reduce data transfer time
- So easier to purse and more
Limitations of JSON in python
Every language has some disadvantages, similar to JSON in python languages. Here include some limitations of using JSON in python.
- Some tools have limitation long time used
- JSON isn’t robust data structure like XML
- JSON can not be well suitable to combine other systems information.
- It is not fully secure platform
- Limitation of terms of support data type.
I strongly believe that you really enjoy this article, it must be helpful. Here I explain everything about JSON in python. You learned how to work with JSON format and the process of it. It helps you create, store and transmit data servers and your python applications.
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