> ## Documentation Index
> Fetch the complete documentation index at: https://mintlify.com/Chalarangelo/30-seconds-of-code/llms.txt
> Use this file to discover all available pages before exploring further.

# Python Dictionary Operations

> Utilities for transforming, mapping, and converting Python dictionaries

# Python Dictionary Operations

Dictionaries are fundamental data structures in Python. These utilities help you transform, map, and convert dictionary data efficiently.

## Convert Between Lists and Dictionaries

### Dictionary to List

Convert a dictionary to a list of tuples:

```python theme={null}
def dict_to_list(d):
  return list(d.items())

d = {'one': 1, 'three': 3, 'five': 5, 'two': 2, 'four': 4}
dict_to_list(d)
# [('one', 1), ('three', 3), ('five', 5), ('two', 2), ('four', 4)]
```

### List to Dictionary

Combine two lists into a dictionary:

```python theme={null}
def to_dictionary(keys, values):
  return dict(zip(keys, values))

to_dictionary(['a', 'b'], [1, 2]) # {'a': 1, 'b': 2}
```

### Map List to Dictionary

Apply a function to create key-value pairs:

```python theme={null}
def map_dictionary(itr, fn):
  return dict(zip(itr, map(fn, itr)))

map_dictionary([1, 2, 3], lambda x: x * x) # {1: 1, 2: 4, 3: 9}
```

## Transform Dictionary Values

Apply a function to all values in a dictionary:

```python theme={null}
def map_values(obj, fn):
  return dict((k, fn(v)) for k, v in obj.items())

users = {
  'fred': { 'user': 'fred', 'age': 40 },
  'pebbles': { 'user': 'pebbles', 'age': 1 }
}
map_values(users, lambda u : u['age']) # {'fred': 40, 'pebbles': 1}
```

## Sort Dictionary List

Sort a list of dictionaries using multiple keys:

```python theme={null}
friends =  [
  {"name": "John", "surname": "Doe", "age": 26},
  {"name": "Jane", "surname": "Doe", "age": 28},
  {"name": "Adam", "surname": "Smith", "age": 30},
  {"name": "Michael", "surname": "Jones", "age": 28}
]

print(
  sorted(
    friends,
    key=lambda friend:
    (friend["age"], friend["surname"], friend["name"])
  )
)
# [
#   {'name': 'John', 'surname': 'Doe', 'age': 26},
#   {'name': 'Jane', 'surname': 'Doe', 'age': 28},
#   {'name': 'Michael', 'surname': 'Jones', 'age': 28},
#   {'name': 'Adam', 'surname': 'Smith', 'age': 30}
# ]
```

## Practical Use Cases

### Extract Specific Fields

Extract ages from user objects:

```python theme={null}
users = {
  'alice': {'name': 'Alice', 'age': 30},
  'bob': {'name': 'Bob', 'age': 25}
}
ages = map_values(users, lambda u: u['age'])
# {'alice': 30, 'bob': 25}
```

### Create Lookup Tables

Build a lookup table from lists:

```python theme={null}
ids = ['user1', 'user2', 'user3']
names = ['Alice', 'Bob', 'Charlie']
lookup = to_dictionary(ids, names)
# {'user1': 'Alice', 'user2': 'Bob', 'user3': 'Charlie'}
```

### Transform API Responses

Convert API data structures:

```python theme={null}
api_data = {'key1': 'value1', 'key2': 'value2'}
list_format = dict_to_list(api_data)
# [('key1', 'value1'), ('key2', 'value2')]
```

### Multi-level Sorting

Sort complex data structures:

```python theme={null}
employees = [
  {'dept': 'Sales', 'name': 'John', 'salary': 50000},
  {'dept': 'Sales', 'name': 'Jane', 'salary': 60000},
  {'dept': 'IT', 'name': 'Bob', 'salary': 55000}
]

sorted_employees = sorted(
  employees,
  key=lambda e: (e['dept'], -e['salary'], e['name'])
)
# First by department, then by salary (descending), then by name
```

## Next Steps

<CardGroup cols={2}>
  <Card title="Lists" icon="list" href="/python/lists/overview">
    Learn about list operations
  </Card>

  <Card title="Strings" icon="text" href="/python/strings/overview">
    Explore string manipulation utilities
  </Card>
</CardGroup>