Navigate and extract data from nested JSON structures
Use .get() to safely access dict keys
Flatten, filter, and transform JSON data with list comprehensions
Handle missing keys and type mismatches gracefully
📊 JSON Parser Playground
Click a query to extract data from the simulated JSON response below. See the Python code and result side by side.
JSON and Python
JSON (JavaScript Object Notation) maps directly to Python types: objects become dicts, arrays become lists, strings become str, numbers become int/float, true/false become True/False, null becomes None. Once parsed, you work with ordinary Python data structures.
Safe Navigation
data.get("key") — returns None if key missing (no KeyError). data.get("key", default) returns default instead of None.
For deeply nested access, chain .get(): data.get("user", {}).get("address", {}).get("city") — each level falls back to {} if missing, so the next .get() doesn't crash.
Transforming JSON Data
Real API responses are messy — nested structures, inconsistent keys, mixed types. The standard workflow: fetch → parse → validate → transform → use. Extract only what you need into clean Python objects or dataclasses.
Quick Check
1. What does data.get("key", "default") return if "key" is not in data?
Raises KeyError
Returns None
Returns "default"
Returns an empty dict
2. Given data = [{"name": "Alice", "score": 90}, {"name": "Bob", "score": 75}], what does [u["name"] for u in data if u["score"] >= 80] return?
["Alice", "Bob"]
["Alice"]
["Bob"]
[]
3. A JSON object {} becomes what Python type after json.loads()?
list
dict
set
tuple
4. What is the safest way to access deeply nested JSON without risking a crash from a missing key?
Use data["a"]["b"]["c"] — Python handles missing keys automatically