Working with JSON Files in Python0%

Working with JSON Files in Python

Intermediate8 min read•Updated: 2026-10-01

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 Type	JSON Equivalent	Notes
`dict`	`object`	JSON keys must always be strings enclosed in double quotes
`list`, `tuple`	`array`	Tuples are serialized to JSON arrays
`str`	`string`	Must use double quotes `""` in JSON
`int`, `float`	`number`	Same numeric representation
`True` / `False`	`true` / `false`	Lowercase in JSON
`None`	`null`	Lowercase `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()`

1import json
2 
3user_profile = {
4    "user_id": 1042,
5    "username": "coder_dev",
6    "is_active": True,
7    "roles": ["admin", "developer"],
8    "preferences": {
9        "theme": "dark",
10        "notifications": False
11    },
12    "metadata": None
13}
14 
15# Serialize with pretty formatting (indent=4) and sorted keys
16json_string = json.dumps(user_profile, indent=4, sort_keys=True)
17print(json_string)

File Serialization with `json.dump()`

1import json
2 
3app_config = {
4    "app_name": "CloudSync Pro",
5    "version": "2.4.1",
6    "timeout_seconds": 30,
7    "debug_mode": False
8}
9 
10# Write directly into a file
11with open("config.json", mode="w", encoding="utf-8") as f:
12    json.dump(app_config, f, indent=4)
13 
14print("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()`

1import json
2 
3with open("config.json", mode="r", encoding="utf-8") as f:
4    config = json.load(f)
5 
6# The result is a standard Python dictionary
7print(f"App: {config['app_name']}")
8print(f"Debug enabled: {config['debug_mode']}")
9print(f"Timeout: {config.get('timeout_seconds')}s")

Parsing Strings with `json.loads()`

1import json
2 
3raw_api_response = '{"status": 200, "message": "Success", "items_count": 3}'
4 
5data = json.loads(raw_api_response)
6print(data["message"])  # Output: Success
7print(type(data))       # Output: <class 'dict'>

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

1
indent: An integer (typically 2 or 4) specifying whitespace indentation for readable "pretty printing". If None, output is compact single-line JSON.
2
sort_keys=True: Sorts dictionary keys alphabetically, useful for consistent caching or version control diffs.
3
separators=(item_separator, key_separator): Defaults to (', ', ': '). Setting separators=(',', ':') eliminates whitespace for minified network payloads.
4
ensure_ascii=False: Preserves non-ASCII characters (such as accented characters or emojis) instead of escaping them as \uXXXX.

1import json
2 
3data = {"name": "Sita", "city": "Bengaluru", "emoji": "🚀"}
4 
5# Minified JSON output with preserved Unicode
6minified = json.dumps(data, separators=(',', ':'), ensure_ascii=False)
7print(minified)
8# 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:

1import json
2from datetime import datetime, date
3 
4data = {
5    "event": "System Maintenance",
6    "timestamp": datetime.now(),
7    "unique_tags": {"network", "cloud", "security"}  # Sets are not natively JSON serializable
8}
9 
10def custom_serializer(obj):
11    if isinstance(obj, (datetime, date)):
12        return obj.isoformat()
13    if isinstance(obj, set):
14        return list(obj)
15    raise TypeError(f"Type {type(obj)} not serializable")
16 
17json_output = json.dumps(data, default=custom_serializer, indent=2)
18print(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:

1import json
2 
3bad_json_string = "{'invalid': 'single quotes not allowed in JSON'}"
4 
5try:
6    result = json.loads(bad_json_string)
7except json.JSONDecodeError as err:
8    print(f"Failed to decode JSON: {err.msg} at line {err.lineno}, column {err.colno}")

⚠️ Common Intermediate Mistakes & Gotchas

1. Confusing `json.dump()` with `json.dumps()`

json.dump(obj, file): Serializes object directly to an open file stream.
json.dumps(obj): Serializes object to a Python string (in memory).

Using dumps() with a file parameter causes a TypeError.

2. Trying to Serialize Non-JSON-Compatible Types

Standard JSON does not support Python datetime, set, or custom class instances directly. Convert them to ISO strings, lists, or dictionaries first, or provide a custom default serializer.

💻 Try It Yourself: JSON Configuration Manager

Scenario

Build a robust configuration manager that stores server settings in a config.json file. If the file exists, load the settings; if it is missing, generate default settings and write them formatted with clean indentation.

Starter Code

1import json
2import os
3 
4CONFIG_FILE = "app_config.json"
5DEFAULT_CONFIG = {
6    "app_name": "MSK Analytics Portal",
7    "version": "1.2.0",
8    "debug_mode": True,
9    "port": 8080,
10    "database": {
11        "host": "localhost",
12        "name": "analytics_db"
13    }
14}
15 
16# TODO: Implement load_or_create_config(filepath, defaults)

Complete Solution

1import json
2import os
3 
4CONFIG_FILE = "app_config.json"
5DEFAULT_CONFIG = {
6    "app_name": "MSK Analytics Portal",
7    "version": "1.2.0",
8    "debug_mode": True,
9    "port": 8080,
10    "database": {
11        "host": "localhost",
12        "name": "analytics_db"
13    }
14}
15 
16def load_or_create_config(filepath, defaults):
17    if not os.path.exists(filepath):
18        print(f"Config not found. Creating default configuration at '{filepath}'...")
19        with open(filepath, "w", encoding="utf-8") as f:
20            json.dump(defaults, f, indent=4)
21        return defaults
22    
23    print(f"Loading existing configuration from '{filepath}'...")
24    with open(filepath, "r", encoding="utf-8") as f:
25        return json.load(f)
26 
27# Test config manager
28config = load_or_create_config(CONFIG_FILE, DEFAULT_CONFIG)
29print(f"Connected to: {config['app_name']} on port {config['port']}")

Expected Output

1Config not found. Creating default configuration at 'app_config.json'...
2Connected to: MSK Analytics Portal on port 8080

Interactive Quiz• Knowledge Check

Practice Quiz

Question 1

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

Question 2

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

Question 3

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

Question 4

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

Question 5

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

🚀 What's Next?

In the next lesson, we will continue your intermediate Python journey with File Exceptions and Error Handling (4: File Handling Advanced).

👉 Continue to Next Lesson: File Exceptions and Error Handling →

Next Lesson

File Exceptions and Error Handling

Continue learning with hands-on practice, examples, and exercises in the upcoming topic.

Related Lessons

Previous Lesson	Next Lesson
Reading & Writing CSV Files	File Exceptions and Error Handling

Practice Quiz

Test your understanding of this lesson with 5 questions. Each question has one correct answer.

Previous Next

PreviousPrevNext

MSK Institute • Shikohabad

Loading Page Content...

Preparing courses, live labs, and learning resources.सामग्री लोड हो रही है, कृपया प्रतीक्षा करें...

Connecting serverPlease wait...

💻 Practical Labs🚀 Free Demo📜 Verified Certificates

File Exceptions and Error Handling

Working with JSON Files in Python

Intermediate8 min read•Updated: 2026-10-01

Study Materials Cheatsheet

Working with JSON Files in Python

1. JSON vs. Python Data Types

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

Python Type	JSON Equivalent	Notes
`dict`	`object`	JSON keys must always be strings enclosed in double quotes
`list`, `tuple`	`array`	Tuples are serialized to JSON arrays
`str`	`string`	Must use double quotes `""` in JSON
`int`, `float`	`number`	Same numeric representation
`True` / `False`	`true` / `false`	Lowercase in JSON
`None`	`null`	Lowercase `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()`

1import json
2 
3user_profile = {
4    "user_id": 1042,
5    "username": "coder_dev",
6    "is_active": True,
7    "roles": ["admin", "developer"],
8    "preferences": {
9        "theme": "dark",
10        "notifications": False
11    },
12    "metadata": None
13}
14 
15# Serialize with pretty formatting (indent=4) and sorted keys
16json_string = json.dumps(user_profile, indent=4, sort_keys=True)
17print(json_string)

File Serialization with `json.dump()`

1import json
2 
3app_config = {
4    "app_name": "CloudSync Pro",
5    "version": "2.4.1",
6    "timeout_seconds": 30,
7    "debug_mode": False
8}
9 
10# Write directly into a file
11with open("config.json", mode="w", encoding="utf-8") as f:
12    json.dump(app_config, f, indent=4)
13 
14print("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()`

1import json
2 
3with open("config.json", mode="r", encoding="utf-8") as f:
4    config = json.load(f)
5 
6# The result is a standard Python dictionary
7print(f"App: {config['app_name']}")
8print(f"Debug enabled: {config['debug_mode']}")
9print(f"Timeout: {config.get('timeout_seconds')}s")

Parsing Strings with `json.loads()`

1import json
2 
3raw_api_response = '{"status": 200, "message": "Success", "items_count": 3}'
4 
5data = json.loads(raw_api_response)
6print(data["message"])  # Output: Success
7print(type(data))       # Output: <class 'dict'>

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

1
indent: An integer (typically 2 or 4) specifying whitespace indentation for readable "pretty printing". If None, output is compact single-line JSON.
2
sort_keys=True: Sorts dictionary keys alphabetically, useful for consistent caching or version control diffs.
3
separators=(item_separator, key_separator): Defaults to (', ', ': '). Setting separators=(',', ':') eliminates whitespace for minified network payloads.
4
ensure_ascii=False: Preserves non-ASCII characters (such as accented characters or emojis) instead of escaping them as \uXXXX.

1import json
2 
3data = {"name": "Sita", "city": "Bengaluru", "emoji": "🚀"}
4 
5# Minified JSON output with preserved Unicode
6minified = json.dumps(data, separators=(',', ':'), ensure_ascii=False)
7print(minified)
8# 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:

1import json
2from datetime import datetime, date
3 
4data = {
5    "event": "System Maintenance",
6    "timestamp": datetime.now(),
7    "unique_tags": {"network", "cloud", "security"}  # Sets are not natively JSON serializable
8}
9 
10def custom_serializer(obj):
11    if isinstance(obj, (datetime, date)):
12        return obj.isoformat()
13    if isinstance(obj, set):
14        return list(obj)
15    raise TypeError(f"Type {type(obj)} not serializable")
16 
17json_output = json.dumps(data, default=custom_serializer, indent=2)
18print(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:

1import json
2 
3bad_json_string = "{'invalid': 'single quotes not allowed in JSON'}"
4 
5try:
6    result = json.loads(bad_json_string)
7except json.JSONDecodeError as err:
8    print(f"Failed to decode JSON: {err.msg} at line {err.lineno}, column {err.colno}")

⚠️ Common Intermediate Mistakes & Gotchas

1. Confusing `json.dump()` with `json.dumps()`

json.dump(obj, file): Serializes object directly to an open file stream.
json.dumps(obj): Serializes object to a Python string (in memory).

Using dumps() with a file parameter causes a TypeError.

2. Trying to Serialize Non-JSON-Compatible Types

Standard JSON does not support Python datetime, set, or custom class instances directly. Convert them to ISO strings, lists, or dictionaries first, or provide a custom default serializer.

💻 Try It Yourself: JSON Configuration Manager

Scenario

Starter Code

1import json
2import os
3 
4CONFIG_FILE = "app_config.json"
5DEFAULT_CONFIG = {
6    "app_name": "MSK Analytics Portal",
7    "version": "1.2.0",
8    "debug_mode": True,
9    "port": 8080,
10    "database": {
11        "host": "localhost",
12        "name": "analytics_db"
13    }
14}
15 
16# TODO: Implement load_or_create_config(filepath, defaults)

Complete Solution

1import json
2import os
3 
4CONFIG_FILE = "app_config.json"
5DEFAULT_CONFIG = {
6    "app_name": "MSK Analytics Portal",
7    "version": "1.2.0",
8    "debug_mode": True,
9    "port": 8080,
10    "database": {
11        "host": "localhost",
12        "name": "analytics_db"
13    }
14}
15 
16def load_or_create_config(filepath, defaults):
17    if not os.path.exists(filepath):
18        print(f"Config not found. Creating default configuration at '{filepath}'...")
19        with open(filepath, "w", encoding="utf-8") as f:
20            json.dump(defaults, f, indent=4)
21        return defaults
22    
23    print(f"Loading existing configuration from '{filepath}'...")
24    with open(filepath, "r", encoding="utf-8") as f:
25        return json.load(f)
26 
27# Test config manager
28config = load_or_create_config(CONFIG_FILE, DEFAULT_CONFIG)
29print(f"Connected to: {config['app_name']} on port {config['port']}")

Expected Output

1Config not found. Creating default configuration at 'app_config.json'...
2Connected to: MSK Analytics Portal on port 8080

Interactive Quiz• Knowledge Check

Practice Quiz

Question 1

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

Question 2

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

Question 3

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

Question 4

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

Question 5

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

🚀 What's Next?

In the next lesson, we will continue your intermediate Python journey with File Exceptions and Error Handling (4: File Handling Advanced).

👉 Continue to Next Lesson: File Exceptions and Error Handling →

Next Lesson

File Exceptions and Error Handling

Continue learning with hands-on practice, examples, and exercises in the upcoming topic.

Related Lessons

Previous Lesson	Next Lesson
Reading & Writing CSV Files	File Exceptions and Error Handling

Practice Quiz

Test your understanding of this lesson with 5 questions. Each question has one correct answer.

Previous Next

Working with JSON Files in Python

1. JSON vs. Python Data Types

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

String Serialization with json.dumps()

File Serialization with json.dump()

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

Reading from a File with json.load()

Parsing Strings with json.loads()

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

5. Handling Non-Serializable Types

6. Error Handling with JSONDecodeError

⚠️ Common Intermediate Mistakes & Gotchas

1. Confusing json.dump() with json.dumps()

2. Trying to Serialize Non-JSON-Compatible Types

💻 Try It Yourself: JSON Configuration Manager

Scenario

Starter Code

Complete Solution

Expected Output

Practice Quiz

🚀 What's Next?

File Exceptions and Error Handling

Related Lessons

Practice Quiz

Loading Page Content...

Working with JSON Files in Python

1. JSON vs. Python Data Types

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

String Serialization with json.dumps()

File Serialization with json.dump()

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

Reading from a File with json.load()

Parsing Strings with json.loads()

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

5. Handling Non-Serializable Types

6. Error Handling with JSONDecodeError

⚠️ Common Intermediate Mistakes & Gotchas

1. Confusing json.dump() with json.dumps()

2. Trying to Serialize Non-JSON-Compatible Types

💻 Try It Yourself: JSON Configuration Manager

Scenario

Starter Code

Complete Solution

Expected Output

Practice Quiz

🚀 What's Next?

File Exceptions and Error Handling

Related Lessons

Practice Quiz

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

String Serialization with `json.dumps()`

File Serialization with `json.dump()`

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

Reading from a File with `json.load()`

Parsing Strings with `json.loads()`

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

6. Error Handling with `JSONDecodeError`

1. Confusing `json.dump()` with `json.dumps()`

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

String Serialization with `json.dumps()`

File Serialization with `json.dump()`

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

Reading from a File with `json.load()`

Parsing Strings with `json.loads()`

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

6. Error Handling with `JSONDecodeError`

1. Confusing `json.dump()` with `json.dumps()`