Dictionaries
Dictionaries in Python
Dictionaries are unordered collections of key-value pairs. They provide a flexible way to store and retrieve data based on unique keys.
Creating Dictionaries
Python
my_dict = {"name": "Alice", "age": 30, "city": "New York"}
Accessing Values
Python
name = my_dict["name"] # Output: "Alice"
Modifying Values
Python
my_dict["age"] = 31
Adding New Key-Value Pairs
Python
my_dict["country"] = "USA"
Deleting Key-Value Pairs
Python
del my_dict["city"]
Checking for Keys
Python
if "age" in my_dict:
print("age key exists")
Iterating Over Dictionaries
Python
for key, value in my_dict.items():
print(key, value)
Common Dictionary Methods
- keys(): Returns a view of the dictionary's keys.
- values(): Returns a view of the dictionary's values.
- items(): Returns a view of the dictionary's key-value pairs as tuples.
- get(key, default=None): Returns the value for a key, or a default value if the key doesn't exist.
- pop(key, default=None): Removes a key-value pair and returns the value.
- update(other_dict): Updates the dictionary with the contents of another dictionary.
Example
Python
person = {"name": "John", "age": 35}
person["occupation"] = "Engineer"
print(person.get("address", "Unknown")) # Output: "Unknown"
person.pop("age")
print(person) # Output: {'name': 'John', 'occupation': 'Engineer'}
Dictionaries are a powerful data structure in Python, allowing you to store and retrieve data efficiently based on key-value pairs.
Uses of Dictionaries in Python
Dictionaries are versatile data structures in Python with numerous applications. Here are some common use cases:
1. Storing Key-Value Pairs
- Storing configuration settings:
Python
config = {
"host": "example.com",
"port": 8080,
"username": "user"
}
- Creating lookup tables:
Python
phonebook = {
"Alice": "123-456-7890",
"Bob": "987-654-3210"
}
- Storing data from APIs or databases:
Python
data = {
"name": "John Doe",
"age": 30,
"city": "New York"
}
2. Counting Occurrences
- Counting word frequencies:
Python
text = "This is a sample text. This is another sentence."
word_count = {}
for word in text.split():
word_count[word] = word_count.get(word, 0) + 1
print(word_count)
3. Implementing Caching
- Storing frequently accessed data:
Python
cache = {}
def expensive_function(x):
if x in cache:
return cache[x]
result = # Calculate the result
cache[x] = result
return result
4. Creating Graphs and Trees
- Representing nodes and their connections:
Python
graph = {
"A": ["B", "C"],
"B": ["D", "E"],
"C": ["F"]
}
5. Customizing Data Structures
- Creating custom data types:
Python
class Person:
def __init__(self, name, age):
self.name = name
self.age = age
people = {
"Alice": Person("Alice", 30),
"Bob": Person("Bob", 25)
}
These are just a few examples of how dictionaries can be used in Python. Their flexibility and efficiency make them a valuable tool for a wide range of applications.