How to Parse JSON in Python

Parse a JSON string with json.loads()

json.loads() takes a JSON string and returns a Python object. The "s" stands for "string".

import json

json_string = '{"name": "Alice", "age": 30, "active": true}'
data = json.loads(json_string)

print(data["name"])    # Alice
print(data["age"])     # 30
print(data["active"])  # True
print(type(data))      # <class 'dict'>

JSON to Python type mapping

When you parse JSON, Python maps each JSON type to the closest Python equivalent:

Read JSON from a file with json.load()

json.load() reads directly from a file object — no need to read the file content manually first.

import json

# Read a JSON file
with open("data.json", "r", encoding="utf-8") as f:
    data = json.load(f)

print(data)         # Python dict/list
print(type(data))   # <class 'dict'>

Always specify encoding="utf-8" to handle international characters correctly on all platforms.

Access nested JSON data

After parsing, use dictionary indexing and list indexing to access nested values.

import json

json_string = """
{
  "user": {
    "name": "Alice",
    "address": {
      "city": "New York",
      "zip": "10001"
    },
    "scores": [95, 87, 92]
  }
}
"""

data = json.loads(json_string)

# Access nested object
city = data["user"]["address"]["city"]
print(city)  # New York

# Access array element
first_score = data["user"]["scores"][0]
print(first_score)  # 95

# Safe access with .get()
country = data["user"]["address"].get("country", "USA")
print(country)  # USA (default value)

Parse a JSON array

If the top-level JSON value is an array, json.loads() returns a Python list.

import json

json_string = '[{"id": 1, "name": "Alice"}, {"id": 2, "name": "Bob"}]'
users = json.loads(json_string)

for user in users:
    print(user["id"], user["name"])

# Output:
# 1 Alice
# 2 Bob

Handle JSON parse errors

json.loads() raises json.JSONDecodeError when the input is invalid JSON. Always wrap it in a try/except block in production code.

import json

def safe_parse(json_string):
    try:
        return json.loads(json_string)
    except json.JSONDecodeError as e:
        print(f"Invalid JSON: {e.msg} at line {e.lineno}, col {e.colno}")
        return None

# Valid JSON
data = safe_parse('{"name": "Alice"}')
print(data)  # {'name': 'Alice'}

# Invalid JSON (trailing comma)
data = safe_parse('{"name": "Alice",}')
print(data)  # Invalid JSON: Expecting property name... → None

json.JSONDecodeError provides .msg, .lineno, and .colno for precise error reporting.

Parse JSON from an API response

When using the requests library, call .json() on the response object — it calls json.loads() internally.

import requests

response = requests.get("https://api.example.com/users/1")
response.raise_for_status()  # Raise error for 4xx/5xx

user = response.json()       # Returns a Python dict
print(user["name"])

Convert JSON to a custom Python class

Use the object_hook parameter to map JSON objects to custom classes automatically during parsing.

import json
from dataclasses import dataclass

@dataclass
class User:
    name: str
    age: int

def user_hook(d):
    if "name" in d and "age" in d:
        return User(name=d["name"], age=d["age"])
    return d

json_string = '{"name": "Alice", "age": 30}'
user = json.loads(json_string, object_hook=user_hook)
print(user)        # User(name='Alice', age=30)
print(user.name)   # Alice

Common mistakes to avoid

• Single quotes — JSON requires double quotes. Python dicts use single quotes, but json.loads("{'key': 'val'}") will raise an error.
• Trailing commas — {"a": 1,} is invalid JSON even though Python dicts allow it in source code.
• Using eval() — Never use eval() to parse JSON. It's a security vulnerability. Always use json.loads().
• Confusing json.loads() and json.load() —loads() takes a string, load() takes a file object.

Convert Python dict back to JSON

Use json.dumps() to serialize a Python object back to a JSON string, andjson.dump() to write to a file.

import json

data = {"name": "Alice", "age": 30, "active": True}

# To string
json_string = json.dumps(data, indent=2)
print(json_string)
# {
#   "name": "Alice",
#   "age": 30,
#   "active": true
# }

# To file
with open("output.json", "w", encoding="utf-8") as f:
    json.dump(data, f, indent=2)

Validate and format JSON online

Before parsing in Python, use the JSON Formatter to validate and inspect your JSON. For schema validation, try the JSON Schema Validator.