Nested dictionaries provide a way to organize hierarchical data in Python. This structure consists of dictionaries within dictionaries, creating a multi-level data model similar to tree structures.

Creating a Nested Dictionary

data = {
    'employee_a': {'name': 'Alice', 'department': 'Engineering', 'salary': 75000},
    'employee_b': {'name': 'Bob', 'department': 'Marketing', 'salary': 65000}
}

This structure holds employee records where each employee has multiple attributes stored as an inner dicsionary.

Accessing Values in Nested Dictionaries

Direct Access with Multiple Indices

Chain the key lookups to reach deep values:

data = {
    'employee_a': {'name': 'Alice', 'department': 'Engineering'},
    'employee_b': {'name': 'Bob', 'department': 'Marketing'}
}

dept = data['employee_a']['department']
print(dept)  # Engineering

Safe Access with get() Method

Avoid KeyError exceptions when keys might not exist:

data = {
    'employee_a': {'name': 'Alice', 'department': 'Engineering'}
}

# Retrieve nested value with fallback
email = data.get('employee_c', {}).get('email', 'Not Available')
print(email)  # Not Available

# Alternative using try-except
try:
    result = data['employee_a']['title']
except KeyError:
    result = 'No title'

Modifying Nested Dictionaries

Updating Existing Values

data = {
    'employee_a': {'name': 'Alice', 'salary': 75000},
    'employee_b': {'name': 'Bob', 'salary': 65000}
}

data['employee_a']['salary'] = 80000
data['employee_b']['department'] = 'Sales'

Adding New Entries

data = {
    'employee_a': {'name': 'Alice'},
    'employee_b': {'name': 'Bob'}
}

data['employee_c'] = {'name': 'Charlie', 'department': 'HR', 'salary': 60000}
data['employee_a']['level'] = 'Senior'

Removing Data from Nested Dictionaries

Deleting Specific Keys

data = {
    'employee_a': {'name': 'Alice', 'age': 30, 'city': 'NYC'},
    'employee_b': {'name': 'Bob', 'age': 25}
}

del data['employee_a']['city']
print(data['employee_a'])  # {'name': 'Alice', 'age': 30}

Removing Entire Entries

data = {
    'employee_a': {'name': 'Alice'},
    'employee_b': {'name': 'Bob'}
}

del data['employee_a']

Clearing All Data

data = {
    'employee_a': {'name': 'Alice'},
    'employee_b': {'name': 'Bob'}
}

data.clear()

Iterating Through Nested Dictionaries

Using Nested Loops

data = {
    'employee_a': {'name': 'Alice', 'department': 'Engineering'},
    'employee_b': {'name': 'Bob', 'department': 'Marketing'}
}

for emp_id, details in data.items():
    print(f"Employee ID: {emp_id}")
    for attribute, value in details.items():
        print(f"  {attribute}: {value}")

Iterating Keys and Values Separately

data = {
    'employee_a': {'name': 'Alice', 'department': 'Engineering'},
    'employee_b': {'name': 'Bob', 'department': 'Marketing'}
}

# Iterate over top-level keys
for emp_id in data.keys():
    print(f"ID: {emp_id}")

# Iterate over inner dictionary values
for details in data.values():
    print(details.get('name'))

Flattening Nested Dictionaries

data = {
    'employee_a': {'name': 'Alice', 'department': 'Engineering'},
    'employee_b': {'name': 'Bob', 'department': 'Marketing'}
}

flattened = {
    f"{emp_id}_{attr}": value
    for emp_id, details in data.items()
    for attr, value in details.items()
}
# {'employee_a_name': 'Alice', 'employee_a_department': 'Engineering', ...}

Recursive Access Helper Function

For deeply nested structures, a helper function simplifies access:

def get_nested(data, path, default=None):
    """Access nested dictionary values using a path list."""
    current = data
    for key in path:
        if isinstance(current, dict) and key in current:
            current = current[key]
        else:
            return default
    return current

data = {
    'company': {
        'department': {
            'team': {'lead': 'Alice'}
        }
    }
}

lead = get_nested(data, ['company', 'department', 'team', 'lead'])
print(lead)  # Alice

Practical Use Cases

Configuration Management

config = {
    'development': {
        'database': {'host': 'localhost', 'port': 5432},
        'cache': {'enabled': True, 'ttl': 3600}
    },
    'production': {
        'database': {'host': 'prod-db.example.com', 'port': 5432},
        'cache': {'enabled': True, 'ttl': 7200}
    }
}

env = 'development'
db_host = config[env]['database']['host']

Tree-Style Data Structures

filesystem = {
    '/': {
        'home': {
            'user': {
                'documents': {'report.pdf': {'size': 1024}},
                'images': {}
            }
        }
    }
}