Introduction to Python Dictionaries

One of the very common data structures in Python is dictionaries. These structures allow you to store data in the form of keys and values. To put it simply, dictionaries are like lists, providing the ability to store collections of items, but with the distinction that each item has a unique key associated with it that can be used to access the value.

Using a dictionary is usually simpler when you want to store data related to specific characteristics. For example, if we want to store information about a person including their name, age, and job, using a dictionary instead of a list will help clarify the links between keys and values, making data access easier.

Dictionaries in Python are mutable, meaning items can be added, removed, or modified. The same flexibility applies to their ability to add, delete, or change entries. This capability allows them to store datasets that need changes dynamically.

In coding with dictionaries, you must remember that keys should be immutable, like strings and numbers, but values can be of any type.

Sample Dictionary Code in Python

dictionary = {"name": "Ali", "age": 25, "job": "engineer"}
print(dictionary["name"])  # Output: Ali
dictionary["age"] = 26  # Change age to 26
print(dictionary["age"])  # Output: 26
dictionary["location"] = "Tehran"
print(dictionary)  # Output: {"name": "Ali", "age": 26, "job": "engineer", "location": "Tehran"}
    

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