Python JSON Parser Example

This beginner-friendly example shows how to parse JSON in Python and turn it into normal Python data.

You will learn:

how to import the json module
how to parse a JSON string with json.loads()
how JSON becomes Python data types
how to read values from the parsed result safely

If you want the shortest working example first, start here:

import json

json_text = '{"name": "Alice", "age": 25, "skills": ["Python", "SQL"]}'

data = json.loads(json_text)

print(data)
print(data["name"])
print(data["skills"][0])

Note: Use json.loads() for a JSON string. Use json.load() when reading JSON from a file.

What this example shows

In this page, the script will show you how to:

import Python’s built-in json module
parse JSON text with json.loads()
understand what Python data type you get back
access values from dictionaries, lists, and nested data

This is a common pattern when working with:

API responses
configuration files
saved app data
practice projects that use structured data

Example input JSON

Here is a small JSON string. It includes:

a string
a number
a boolean
a list
a nested object

json_text = """
{
    "name": "Alice",
    "age": 25,
    "active": true,
    "skills": ["Python", "SQL"],
    "address": {
        "city": "London"
    }
}
"""

A few important things to notice:

JSON uses double quotes around keys and string values.
true in JSON is lowercase.
This is still just text until Python parses it.

Parse JSON with `json.loads()`

Use json.loads() when your JSON is stored in a string.

import json

json_text = """
{
    "name": "Alice",
    "age": 25,
    "active": true,
    "skills": ["Python", "SQL"],
    "address": {
        "city": "London"
    }
}
"""

data = json.loads(json_text)

print(data)
print(type(data))

What this does

The key line is:

data = json.loads(json_text)

This converts the JSON text into Python data.

In this example, the top-level JSON value is an object, so the result becomes a Python dictionary.

Expected output:

{'name': 'Alice', 'age': 25, 'active': True, 'skills': ['Python', 'SQL'], 'address': {'city': 'London'}}
<class 'dict'>

If the JSON started with [ and ended with ], the result would usually be a Python list instead.

For a deeper explanation of this function, see json.loads() explained.

Read values from parsed JSON

Once the JSON is parsed, you can use normal Python indexing to read values.

import json

json_text = """
{
    "name": "Alice",
    "age": 25,
    "active": true,
    "skills": ["Python", "SQL"],
    "address": {
        "city": "London"
    }
}
"""

data = json.loads(json_text)

print(data["name"])
print(data["skills"][0])
print(data["address"]["city"])

Expected output:

Alice
Python
London

How each line works

data["name"] gets a top-level value from the dictionary
data["skills"][0] gets the first item from the skills list
data["address"]["city"] gets a nested value step by step

If you try to access a key that does not exist, Python raises a KeyError. See how to fix KeyError when accessing dictionary values.

Safer access with `get()`

If you are not sure a key exists, get() can be safer than direct indexing.

import json

json_text = '{"name": "Alice"}'
data = json.loads(json_text)

print(data.get("name"))
print(data.get("email"))
print(data.get("email", "Not provided"))

Expected output:

Alice
None
Not provided

This helps avoid errors when some fields may be missing.

JSON types and Python types

When Python parses JSON, the data types change like this:

JSON object → Python dict
JSON array → Python list
JSON string → Python str
JSON number → Python int or float
JSON true / false → Python True / False
JSON null → Python None

Example:

import json

json_text = """
{
    "title": "Book",
    "price": 19.99,
    "in_stock": true,
    "tags": ["fiction", "popular"],
    "discount": null
}
"""

data = json.loads(json_text)

print(type(data))
print(type(data["title"]))
print(type(data["price"]))
print(type(data["in_stock"]))
print(type(data["tags"]))
print(data["discount"])

Expected output:

<class 'dict'>
<class 'str'>
<class 'float'>
<class 'bool'>
<class 'list'>
None

Parse JSON from a file

Use json.load() when the JSON is in a file.

import json

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

print(data)

`load()` vs `loads()`

json.load(file) reads JSON from a file object
json.loads(text) reads JSON from a string

That is the main difference.

If you want a full guide, see json.load() explained and how to parse JSON in Python.

Common errors beginners make

Here are some common problems when parsing JSON.

1. Using single quotes inside JSON text

This is invalid JSON:

json_text = "{'name': 'Alice'}"

JSON requires double quotes:

json_text = '{"name": "Alice"}'

If your JSON syntax is wrong, Python may raise a decoding error. See how to fix JSONDecodeError for invalid JSON.

2. Confusing `json.load()` and `json.loads()`

This is a common mix-up:

load = file
loads = string

A simple memory trick:

load = load from file
loads = load from string

3. Trying to access a missing key

This causes an error:

import json

data = json.loads('{"name": "Alice"}')
print(data["email"])

Use get() if the key may not exist:

print(data.get("email"))

4. Forgetting that a parsed array is a list

If the JSON starts as an array:

import json

data = json.loads('["Python", "SQL", "Git"]')
print(type(data))
print(data[0])

Expected output:

<class 'list'>
Python

You cannot use a string key like data["name"] on a list.

When to use this pattern

This simple parsing pattern is useful when you are:

reading API responses
loading app settings from JSON
working with saved data files
practicing how structured text becomes Python objects

If you plan to use JSON from web requests, you may also like how to handle API responses in Python.

FAQ

What is the difference between `json.load()` and `json.loads()`?

json.load() reads JSON from a file object. json.loads() reads JSON from a string.

Does parsed JSON always become a dictionary?

No. A JSON object becomes a dict, but a JSON array becomes a list.

Why does my JSON string fail to parse?

It may use invalid JSON syntax, such as single quotes, missing commas, or trailing commas.

How do I get a nested value from parsed JSON?

Use normal Python indexing step by step, such as data['user']['name'].