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.

Frequently asked questions

What function parses JSON in Python?

json.loads(string) parses a JSON string. json.load(file_object) reads from a file. Both are in Python's built-in json module — no third-party library needed. For better performance, orjson and ujson are drop-in alternatives.

What Python type does a JSON object become?

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

What does JSON null become in Python?

JSON null becomes Python None. Check with if value is None rather than if not value, since 0, "", and [] are also falsy but semantically different from None.

How do I handle JSONDecodeError in Python?

Wrap json.loads() in try/except json.JSONDecodeError as e. The exception provides e.msg, e.lineno, and e.colno for precise error reporting. json.JSONDecodeError is a subclass of ValueError.

What is the difference between json.loads and json.load?

json.loads() (with "s") takes a string. json.load() takes a file object and reads from it directly. Use json.load(f) when reading from files — don't read the file to a string just to pass it to json.loads().

Can Python json.loads parse a list?

Yes. json.loads() parses any valid JSON including arrays, primitives, and null at the top level. A JSON array like '[1, 2, 3]' returns a Python list [1, 2, 3]. An array of objects returns a list of dicts.