Add Json Library in Python

Python JSON library is part of the Python standard library, installing it in Python doesn't require installing any other packages. It is a quick and easy process, allowing you to seamlessly work with common data formats. In this article, we will see how to add and use JSON library in Python.

Add and Use JSON Library In Python

Below are step-by-step procedures by which we can add and use JSON library in Python:

Step 1: Understanding Installation Options

Python comes with an in-built JSON library in version 3.5. This means there is no need to install any additional packages for the basic JSON functionality. However,if you're using the old version, i.e., the version below 3.5, you can opt for alternative JSON libraries like SimpleJSON.

Step 2: Importing the Library

It is the same process to import the library for usage in your code, regardless of the version of Python you are using or how you installed it. Just start your script with the line that follows.

import json

Step 3: Using the JSON Library

In this example, a dictionary named "data" is created with keys "name," "age," and "skills." The code converts the dictionary into a JSON string using `json.dumps()`, prints the resulting string, then performs the reverse process using `json.loads()` to convert the JSON string back into a Python dictionary, finally printing the value associated with the key "name" from the reconstructed dictionary.

# create a dictionary
data = {"name": "GFG", "age": 1, "skills": [
    "writing", "coding", "answering questions"]}
# convert the dict in to the json string
json_string = json.dumps(data)
# print the json string
print(json_string)
# json string to python conversion
new_data = json.loads(json_string)
print(new_data["name"])

Output:

{"name": "GFG", "age": 1, "skills": ["writing", "coding", "answering questions"]}
GFG

The json library offers more than just basic functionality. You can explore more advanced features like specifying custom encoding, controlling sorting of dictionary keys, and handling errors, as documented in the official Python documentation.