Learning

JSON File Operations

json.dumps() — Python → JSON String

python

import json

data = {
    'name': 'Alice',
    'age': 30,
    'active': True,
    'scores': [85, 90, 78],
    'address': None
}

# Convert to JSON string
json_str = json.dumps(data)
print(json_str)
# {"name": "Alice", "age": 30, "active": true, "scores": [85, 90, 78], "address": null}

# Note the translations:
# Python True  → JSON true
# Python False → JSON false
# Python None  → JSON null

# Pretty print (indentation)
pretty = json.dumps(data, indent=2)
print(pretty)
# {
#   "name": "Alice",
#   "age": 30,
#   ...
# }

# Sort keys
sorted_json = json.dumps(data, sort_keys=True, indent=2)

json.loads() — JSON String → Python

python

json_str = '{"name": "Bob", "age": 25}'

# Parse string to dict
data = json.loads(json_str)
print(type(data))  # <class 'dict'>
print(data['name']) # 'Bob'

json.dump() — Python → JSON File

python

data = {'users': [{'id': 1, 'name': 'Alice'}]}

with open('data.json', 'w') as f:
    json.dump(data, f, indent=2)
    # File now contains formatted JSON

json.load() — JSON File → Python

python

with open('data.json', 'r') as f:
    data = json.load(f)
    
print(data['users'][0]['name'])  # 'Alice'

Handling Non-Serializable Types

python

from datetime import datetime

# This will FAIL!
# data = {'time': datetime.now()}
# json.dumps(data)  # TypeError: Object of type datetime is not JSON serializable

# Solution 1: Custom encoder
class DateTimeEncoder(json.JSONEncoder):
    def default(self, obj):
        if isinstance(obj, datetime):
            return obj.isoformat()
        return super().default(obj)

json_str = json.dumps({'time': datetime.now()}, cls=DateTimeEncoder)

# Solution 2: Default function
def custom_serializer(obj):
    if isinstance(obj, datetime):
        return obj.isoformat()
    raise TypeError(f'Type {type(obj)} not serializable')

json_str = json.dumps({'time': datetime.now()}, default=custom_serializer)

Type Mapping Table

| Python | JSON | |--------|------| | dict | object {} | | list, tuple | array [] | | str | string "" | | int, float | number | | True / False | true / false | | None | null |

Note: Tuples become JSON arrays. When loading back, they become lists!

Key Rules

•Use dump()/load() for files, dumps()/loads() for strings — the 's' stands for string
•Python's True/False/None become JSON's true/false/null — remember this when parsing!
•Tuples are converted to JSON arrays and come back as lists — convert manually if needed
•Always use indent=2 for readable JSON files, omit it for compact network payloads
•datetime, set, and custom class objects are NOT JSON serializable — use custom encoder or default function

Your Task

Create a function `save_config(filepath, config_dict)` that writes a dictionary to a JSON file with indentation. Create a function `load_config(filepath)` that reads the JSON file and returns the dict. Wrap load_config in a try/except to handle FileNotFoundError and json.JSONDecodeError gracefully, returning an empty dict on failure.

Learning

JSON File Operations

json.dumps() — Python → JSON String

python

import json

data = {
    'name': 'Alice',
    'age': 30,
    'active': True,
    'scores': [85, 90, 78],
    'address': None
}

# Convert to JSON string
json_str = json.dumps(data)
print(json_str)
# {"name": "Alice", "age": 30, "active": true, "scores": [85, 90, 78], "address": null}

# Note the translations:
# Python True  → JSON true
# Python False → JSON false
# Python None  → JSON null

# Pretty print (indentation)
pretty = json.dumps(data, indent=2)
print(pretty)
# {
#   "name": "Alice",
#   "age": 30,
#   ...
# }

# Sort keys
sorted_json = json.dumps(data, sort_keys=True, indent=2)

json.loads() — JSON String → Python

python

json_str = '{"name": "Bob", "age": 25}'

# Parse string to dict
data = json.loads(json_str)
print(type(data))  # <class 'dict'>
print(data['name']) # 'Bob'

json.dump() — Python → JSON File

python

data = {'users': [{'id': 1, 'name': 'Alice'}]}

with open('data.json', 'w') as f:
    json.dump(data, f, indent=2)
    # File now contains formatted JSON

json.load() — JSON File → Python

python

with open('data.json', 'r') as f:
    data = json.load(f)
    
print(data['users'][0]['name'])  # 'Alice'

Handling Non-Serializable Types

python

from datetime import datetime

# This will FAIL!
# data = {'time': datetime.now()}
# json.dumps(data)  # TypeError: Object of type datetime is not JSON serializable

# Solution 1: Custom encoder
class DateTimeEncoder(json.JSONEncoder):
    def default(self, obj):
        if isinstance(obj, datetime):
            return obj.isoformat()
        return super().default(obj)

json_str = json.dumps({'time': datetime.now()}, cls=DateTimeEncoder)

# Solution 2: Default function
def custom_serializer(obj):
    if isinstance(obj, datetime):
        return obj.isoformat()
    raise TypeError(f'Type {type(obj)} not serializable')

json_str = json.dumps({'time': datetime.now()}, default=custom_serializer)

Type Mapping Table

| Python | JSON | |--------|------| | dict | object {} | | list, tuple | array [] | | str | string "" | | int, float | number | | True / False | true / false | | None | null |

Note: Tuples become JSON arrays. When loading back, they become lists!

Key Rules

•Use dump()/load() for files, dumps()/loads() for strings — the 's' stands for string
•Python's True/False/None become JSON's true/false/null — remember this when parsing!
•Tuples are converted to JSON arrays and come back as lists — convert manually if needed
•Always use indent=2 for readable JSON files, omit it for compact network payloads
•datetime, set, and custom class objects are NOT JSON serializable — use custom encoder or default function

Your Task