Working with JSON Files0%
File Exceptions and Error Handling

Working with JSON Files

Beginner12 min read•Updated: Jul 11, 2026
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Working with JSON Files in Python

JSON (JavaScript Object Notation) is the standard data interchange format for modern web APIs, configuration files, cloud services, and NoSQL databases. Python provides native support for encoding and decoding JSON via its built-in json module.

1. JSON vs. Python Data Types

JSON data maps cleanly to Python's primitive data structures. The standard conversion table is:

Python TypeJSON EquivalentNotes
dictobjectJSON keys must always be strings enclosed in double quotes
list, tuplearrayTuples are serialized to JSON arrays
strstringMust use double quotes "" in JSON
int, floatnumberSame numeric representation
True / Falsetrue / falseLowercase in JSON
NonenullLowercase null in JSON

2. Serialization: dump() vs. dumps()

Serialization (or "encoding / marshalling") converts an in-memory Python object into a JSON-formatted representation.

  • json.dumps(obj): Serializes Python object into a JSON string (s stands for string).
  • json.dump(obj, file): Serializes Python object directly into a file-like stream.

String Serialization with json.dumps()

Python
import json
 
user_profile = {
"user_id": 1042,
"username": "coder_dev",
"is_active": True,
"roles": ["admin", "developer"],
"preferences": {
"theme": "dark",
"notifications": False
},
"metadata": None
}
 
# Serialize with pretty formatting (indent=4) and sorted keys
json_string = json.dumps(user_profile, indent=4, sort_keys=True)
print(json_string)

File Serialization with json.dump()

Python
import json
 
app_config = {
"app_name": "CloudSync Pro",
"version": "2.4.1",
"timeout_seconds": 30,
"debug_mode": False
}
 
# Write directly into a file
with open("config.json", mode="w", encoding="utf-8") as f:
json.dump(app_config, f, indent=4)
 
print("Configuration written to config.json.")

3. Deserialization: load() vs. loads()

Deserialization (or "decoding / unmarshalling") parses JSON data into native Python data structures (dict, list, etc.).

  • json.loads(str): Decodes a JSON string into a Python object.
  • json.load(file): Reads and decodes JSON directly from a file stream.

Reading from a File with json.load()

Python
import json
 
with open("config.json", mode="r", encoding="utf-8") as f:
config = json.load(f)
 
# The result is a standard Python dictionary
print(f"App: {config['app_name']}")
print(f"Debug enabled: {config['debug_mode']}")
print(f"Timeout: {config.get('timeout_seconds')}s")

Parsing Strings with json.loads()

Python
import json
 
raw_api_response = '{"status": 200, "message": "Success", "items_count": 3}'
 
data = json.loads(raw_api_response)
print(data["message"]) # Output: Success
print(type(data)) # Output: <class 'dict'>

4. Useful Parameters for json.dump / json.dumps

  1. 1
    indent: An integer (typically 2 or 4) specifying whitespace indentation for readable "pretty printing". If None, output is compact single-line JSON.
  2. 2
    sort_keys=True: Sorts dictionary keys alphabetically, useful for consistent caching or version control diffs.
  3. 3
    separators=(item_separator, key_separator): Defaults to (', ', ': '). Setting separators=(',', ':') eliminates whitespace for minified network payloads.
  4. 4
    ensure_ascii=False: Preserves non-ASCII characters (such as accented characters or emojis) instead of escaping them as \uXXXX.
Python
import json
 
data = {"name": "Sita", "city": "Bengaluru", "emoji": "🚀"}
 
# Minified JSON output with preserved Unicode
minified = json.dumps(data, separators=(',', ':'), ensure_ascii=False)
print(minified)
# Output: {"name":"Sita","city":"Bengaluru","emoji":"🚀"}

5. Handling Non-Serializable Types

By default, Python raises a TypeError: Object of type ... is not JSON serializable when trying to serialize types like datetime, Decimal, sets, or custom class instances.

To solve this, provide a custom converter via the default parameter:

Python
import json
from datetime import datetime, date
 
data = {
"event": "System Maintenance",
"timestamp": datetime.now(),
"unique_tags": {"network", "cloud", "security"} # Sets are not natively JSON serializable
}
 
def custom_serializer(obj):
if isinstance(obj, (datetime, date)):
return obj.isoformat()
if isinstance(obj, set):
return list(obj)
raise TypeError(f"Type {type(obj)} not serializable")
 
json_output = json.dumps(data, default=custom_serializer, indent=2)
print(json_output)

6. Error Handling with JSONDecodeError

Malformatted JSON raises json.decoder.JSONDecodeError upon parsing. Always safeguard file and network operations with targeted error handling:

Python
import json
 
bad_json_string = "{'invalid': 'single quotes not allowed in JSON'}"
 
try:
result = json.loads(bad_json_string)
except json.JSONDecodeError as err:
print(f"Failed to decode JSON: {err.msg} at line {err.lineno}, column {err.colno}")

Multiple Choice Questions

1. What is the difference between json.dump() and json.dumps() in Python?

A. json.dump() writes directly to a file-like stream, whereas json.dumps() returns a formatted JSON string B. json.dump() reads from a database, while json.dumps() parses local text C. json.dumps() is deprecated in Python 3 and replaced by json.dump() D. json.dump() works only with dictionaries, while json.dumps() works only with lists Answer: A Explanation: The trailing s in dumps() stands for "string". json.dump() requires a writable file stream as its second argument, while json.dumps() outputs a string in memory.

2. When converting a Python tuple to JSON, what does it become?

A. A JSON object B. A JSON array C. A JSON tuple D. A comma-separated string Answer: B Explanation: Both Python lists and tuples serialize to JSON arrays [...] because JSON lacks a distinct tuple primitive.

3. Which argument can be passed to json.dumps() to format the output with clean 4-space indentation?

A. spacing=4 B. tab_size=4 C. indent=4 D. pretty_print=True Answer: C Explanation: The indent keyword argument specifies indentation whitespace, transforming compact JSON into human-readable multi-line formatted JSON.

4. What exception is raised when calling json.loads() on an invalid JSON string?

A. json.JSONDecodeError B. SyntaxError C. ValueError D. KeyError Answer: A Explanation: When parsing invalid JSON syntax (e.g. single quotes or unclosed braces), the json module raises json.decoder.JSONDecodeError (which inherits from ValueError).

5. Why does Python's json module raise a TypeError when attempting to serialize a set directly?

A. Sets are immutable in Python B. JSON has no native unordered distinct collection (set) representation C. Sets require special binary encodings D. Set elements cannot be cast to strings Answer: B Explanation: Standard JSON specification only supports objects, arrays, strings, numbers, booleans, and null. Sets have no direct representation, so Python requires explicit conversion (e.g. via list(my_set)).

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