Python JSON Module: A Complete Tutorial for Beginners

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Python JSON Module: A Complete Tutorial for Beginners

JSON (JavaScript Object Notation) is the most common format for data exchange on the web. It's lightweight, easy to read, and supported across many platforms. In Python, the json module provides an easy way to encode and decode JSON data.

In this article, you’ll learn:

What JSON is and how it relates to Python
How to convert Python objects to JSON (dump, dumps)
How to convert JSON back to Python objects (load, loads)
Reading and writing JSON files
Custom encoding and decoding
Common use cases and pitfalls

What is JSON?

JSON is a text-based format for representing structured data. It’s widely used for APIs, configuration files, and data storage.

JSON Example:

{
  "name": "Alice",
  "age": 30,
  "is_active": true,
  "skills": ["Python", "Django"]
}

JSON maps naturally to Python data types:

JSON	Python
Object	`dict`
Array	`list`
String	`str`
Number	`int`, `float`
Boolean	`bool`
Null	`None`

Importing the `json` Module

import json

Encoding Python Objects to JSON

Use json.dumps() to convert a Python object to a JSON string.

person = {
    "name": "Alice",
    "age": 30,
    "is_active": True
}

json_string = json.dumps(person)
print(json_string)

Output:

{"name": "Alice", "age": 30, "is_active": true}

Pretty-printed JSON:

print(json.dumps(person, indent=4))

Decoding JSON to Python Objects

Use json.loads() to parse a JSON string into a Python object.

data = '{"name": "Alice", "age": 30, "is_active": true}'
python_obj = json.loads(data)
print(python_obj["name"])

Reading & Writing JSON to Files

✅ Writing to a File (`json.dump()`)

person = {"name": "Bob", "age": 25}

with open("data.json", "w") as f:
    json.dump(person, f, indent=2)

✅ Reading from a File (`json.load()`)

with open("data.json", "r") as f:
    person = json.load(f)
    print(person["age"])

Real-World Example: Saving App Settings

settings = {
    "theme": "dark",
    "notifications": True,
    "volume": 75
}

# Save settings to file
with open("settings.json", "w") as f:
    json.dump(settings, f)

# Later, read them back
with open("settings.json", "r") as f:
    loaded = json.load(f)
    print(loaded["theme"])  # Output: dark

Custom Encoding: Non-Serializable Objects

JSON doesn't support all Python types like datetime, set, or custom classes.

Example: Handling `datetime` objects

import json
from datetime import datetime

def custom_encoder(obj):
    if isinstance(obj, datetime):
        return obj.isoformat()
    raise TypeError("Type not serializable")

data = {"created_at": datetime.now()}

json_string = json.dumps(data, default=custom_encoder)
print(json_string)

Convert Between JSON and Python Types

Python	JSON
`dict`	Object
`list`, `tuple`	Array
`str`	String
`int`, `float`	Number
`True`	`true`
`False`	`false`
`None`	`null`

Common Pitfalls

Mistake	Fix
❌ Serializing unsupported types (`set`, `datetime`)	Use `default=` parameter
❌ Not closing file when writing JSON	Use `with` context manager
❌ Confusing `dump` and `dumps`	`dump()` = to file, `dumps()` = to string
❌ Parsing invalid JSON	Validate or sanitize data before using `loads()`

Tips for Working with JSON

✅ Use indent=2 or indent=4 in dump()/dumps() for pretty-printing
✅ Always wrap file operations in with blocks
✅ Use json.loads() with error handling (try/except) for untrusted data
✅ Use default= in json.dumps() to serialize custom objects
✅ Prefer json.load()/json.dump() for working directly with files

Summary Table

Function	Description
`json.dumps(obj)`	Convert Python object → JSON string
`json.dump(obj, file)`	Write Python object → JSON file
`json.loads(string)`	Convert JSON string → Python object
`json.load(file)`	Read JSON file → Python object

Conclusion

The json module is essential for anyone working with web APIs, configurations, or data exchange in Python. By mastering its features, you can write cleaner, safer, and more interoperable code.

Whether you're building a web app, saving user settings, or working with APIs, the json module is your go-to solution for data serialization in Python.

Tips and Tricks

What is pass in Python?

Python | Pass Statement

The pass statement is used as a placeholder for future code. It represents a null operation in Python. It is generally used for the purpose of filling up empty blocks of code which may execute during runtime but has yet to be written.

def myfunction():
    pass

How can you generate random numbers?

Python | Generate random numbers

Python provides a module called random using which we can generate random numbers. e.g: print(random.random())

We have to import a random module and call the random() method as shown below:

 import random

 print(random.random())

The random() method generates float values lying between 0 and 1 randomly.

To generate customized random numbers between specified ranges, we can use the randrange() method
Syntax: randrange(beginning, end, step)

import random

print(random.randrange(5,100,2))

What is lambda in Python?

Python | Lambda function

A lambda function is a small anonymous function. This function can have any number of parameters but, can have just one statement.

Syntex:
lambda arguments : expression

a = lambda x,y : x+y

print(a(5, 6))

It also provides a nice way to write closures. With that power, you can do things like this.

def adder(x):
    return lambda y: x + y

add5 = adder(5)

add5(1)    #6

As you can see from the snippet of Python, the function adder takes in an argument x and returns an anonymous function, or lambda, that takes another argument y. That anonymous function allows you to create functions from functions. This is a simple example, but it should convey the power lambdas and closures have.

What is swapcase() function in the Python?

Python | swapcase() Function

It is a string's function that converts all uppercase characters into lowercase and vice versa. It automatically ignores all the non-alphabetic characters.

string = "IT IS IN LOWERCASE."  

print(string.swapcase())

How to remove whitespaces from a string in Python?

Python | strip() Function | Remove whitespaces from a string

To remove the whitespaces and trailing spaces from the string, Python provides a strip([str]) built-in function. This function returns a copy of the string after removing whitespaces if present. Otherwise returns the original string.

string = "  Python " 
 
print(string.strip())

What is the usage of enumerate() function in Python?

Python | enumerate() Function

The enumerate() function is used to iterate through the sequence and retrieve the index position and its corresponding value at the same time.

lst = ["A","B","C"] 
 
print (list(enumerate(lst)))

#[(0, 'A'), (1, 'B'), (2, 'C')]

Can you explain the filter(), map(), and reduce() functions?

Python | filter(), map(), and reduce() Functions

filter() function accepts two arguments, a function and an iterable, where each element of the iterable is filtered through the function to test if the item is accepted or not.
```
>>> set(filter(lambda x:x>4, range(7)))

# {5, 6}
```
map() function calls the specified function for each item of an iterable and returns a list of result
```
>>> set(map(lambda x:x**3, range(7)))

# {0, 1, 64, 8, 216, 27, 125}
```
reduce() function reduces a sequence pair-wise, repeatedly until we arrive at a single value..
```
>>> reduce(lambda x,y:y-x, [1,2,3,4,5])

# 3
```
Let’s understand this:

2-1=1
3-1=2
4-2=2
5-2=3

Hence, 3.

What is a namedtuple?

Python | namedtuple

A namedtuple will let us access a tuple’s elements using a name/label. We use the function namedtuple() for this, and import it from collections.

>>> from collections import namedtuple

#format
>>> result=namedtuple('result','Physics Chemistry Maths') 

#declaring the tuple
>>> Chris=result(Physics=86,Chemistry=92,Maths=80) 

>>> Chris.Chemistry
# 92

Write a code to add the values of same keys in two different dictionaries and return a new dictionary.

We can use the Counter method from the collections module

from collections import Counter

dict1 = {'a': 5, 'b': 3, 'c': 2}
dict2 = {'a': 2, 'b': 4, 'c': 3}

new_dict = Counter(dict1) + Counter(dict2)


print(new_dict)
# Print: Counter({'a': 7, 'b': 7, 'c': 5})

Python In-place swapping of two numbers

Python | In-place swapping of two numbers

>>> a, b = 10, 20
>>> print(a, b)
10 20

>>> a, b = b, a
>>> print(a, b)
20 10

Reversing a String in Python

Python | Reversing a String

>>> x = 'PythonWorld'
>>> print(x[: : -1])
dlroWnohtyP

Python join all items of a list to convert into a single string

Python | Join all items of a list to convert into a single string

>>> x = ["Python", "Online", "Training"]
>>> print(" ".join(x))
Python Online Training

python return multiple values from functions

Python | Return multiple values from functions

>>> def A():
	return 2, 3, 4

>>> a, b, c = A()

>>> print(a, b, c)
2 3 4

Python Print String N times

Python | Print String N times

>>> s = 'Python'
>>> n = 5

>>> print(s * n)
PythonPythonPythonPythonPython

Python check the memory usage of an object

Python | Check the memory usage of an object

>>> import sys
>>> x = 100

>>> print(sys.getsizeof(x))
28

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Python JSON Module: A Complete Tutorial for Beginners

Python JSON Module: A Complete Tutorial for Beginners

What is JSON?

JSON Example:

Importing the json Module

Encoding Python Objects to JSON

Output:

Pretty-printed JSON:

Decoding JSON to Python Objects

Reading & Writing JSON to Files

✅ Writing to a File (json.dump())

✅ Reading from a File (json.load())

Real-World Example: Saving App Settings

Custom Encoding: Non-Serializable Objects

Example: Handling datetime objects

Convert Between JSON and Python Types

Common Pitfalls

Tips for Working with JSON

Summary Table

Conclusion

Tips and Tricks

Python | Pass Statement

Python | Generate random numbers

Python | Lambda function

Python | swapcase() Function

Python | strip() Function | Remove whitespaces from a string

Python | enumerate() Function

Python | filter(), map(), and reduce() Functions

Python | namedtuple

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Importing the `json` Module

✅ Writing to a File (`json.dump()`)

✅ Reading from a File (`json.load()`)

Example: Handling `datetime` objects